METHODS FOR EVALUATING TUMOR CELL SPHEROIDS USING 3D MICROFLUIDIC CELL CULTURE DEVICE

RELATED APPLICATIONS

This application claims the benefit of U.S. provisional application No. 62/480,192, filed March 31, 2017, the entire contents of which is incorporated by reference herein.

FEDERALLY SPONSORED RESEARCH

This invention was made with government support under K08 CA138918-01A1 and R01 CA190394-01 awarded by the National Institutes of Health. The government has certain rights in the invention.

BACKGROUND

Existing patient-derived cancer models, including circulating tumor cells (CTCs), organoid cultures, and patient-derived xenografts (PDXs) can guide precision cancer therapy, but take weeks to months to generate and lack the native tumor immune microenvironment. Current approaches to study anti-tumor immune responses in patients are also limited by remote measurements in whole blood or plasma, or static assessment of biopsies.

Recently there has been developed a 3D microfluidic device for the short-term culture of murine- and patient-derived organotypic tumor spheroids. Cultured tumor spheroids are believed by some to more closely resemble the native immune microenvironment.

It would be desirable to be able to assess the effects of single drugs and combinations of drugs on tumor cells in the tumor micro-environment. It would be particularly helpful if there were a way to evaluate simultaneously the effects of a combination of immune blockade and anticancer compounds ex vivo. To date, efforts to evaluate tumor cells have been confounded by (i) the tumor cells changing when removed from the body, (ii) the absence of an intact immune system communicating with the tumor microenvironment when the tumor cells are removed from the body, (iii) the inability to distinguish the effects of tumor removal and culturing from the effects of a drug applied in vitro, and (iv) the complexity of measuring at a molecular level immune based markers and other markers which might predict whether a drug might work in vivo based on experiments conducted in vitro. To date, there is no simple assay for evaluating in in a high throughput manner the effects of drugs on human cancer cells in a native tumor microenvironment. SUMMARY

It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid contains sufficient immune components to be predictive of a drug's activity when administered in vivo. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid contains sufficient immune components such that combinations of immune blockade compounds and anti-cancer drugs can be assessed, the results being predictive of administering the drugs in vivo. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid can be evaluated optically and reproducibly, to establish the effects of drugs on the tumor cells within the spheroids, while distinguishing the effects on tumor cells resulting from the act of culturing the tumor cells. It has been discovered, surprisingly, that such techniques for evaluating tumor spheroids can be utilized in a high throughput method for determining the relative amounts of live and dead cells in an environment mimicking that occurring in vivo.

In one aspect, the invention involves a novel approach for evaluating ex vivo response to Immune Checkpoint Blockade (ICB) using murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS) cultured in a 3 -dimensional microfluidic system. Spheroids isolated from fresh mouse and human tumor samples retain autologous lymphoid and myeloid cell populations, including antigen-experienced tumor infiltrating CD4 and CD8 T lymphocytes, and respond to ICB in short-term ex vivo culture. Tumor killing was recapitulated ex vivo using MDOTS derived from the anti-PD-1 sensitive MC38 syngeneic mouse cancer model, whereas relative resistance to anti-PD-1 therapy was preserved in the CT26 and B 16F10 syngeneic models. Systematic cytokine/chemokine profiling following PD-1 blockade in PDOTS from patients with melanoma and other tumors identified significant induction of the

immunoattractants CCL19 and CXCL13, which was confirmed in vivo and correlated with evidence of intratumoral immune cell infiltration. Resistance to anti-PDl treatment in MDOTS and PDOTS also tracked with coinduction of immune suppressive chemokines. Ex vivo profiling revealed a combination therapy as a novel therapeutic strategy to enhance sensitivity to PD-1 blockade in this setting, which effectively predicted tumor response in vivo. These findings demonstrate feasibility of ex vivo profiling of PD- 1 blockade, and offer a novel functional approach to facilitate precision immunooncology and develop novel therapeutic combinations.

According to one aspect of the invention, a method for evaluating tumor cell spheroids in a three-dimensional microfluidic device is provided. The method involves:

obtaining tumor spheroids from an enzyme treated tumor sample,

suspending a first aliquot of the tumor spheroids in biocompatible gel;

suspending a second aliquot of the tumor spheroids in biocompatible gel;

placing the first aliquot of the tumor spheroids in biocompatible gel in a first three- dimensional device,

contacting the first aliquot with a first fluorophore dye selective for dead cells, the first fluorophore dye emitting fluorescence at a first wavelength when bound to a dead cell,

contacting the first aliquot with a second fluorophore dye selective for live cells, the second fluorophore dye emitting fluorescence at a second wavelength different from the first wavelength when bound to a live cell,

measuring total fluorescence emitted by each of the first and second fluorophore dyes in the first aliquot,

culturing the second aliquot in a second three-dimensional device,

contacting the second aliquot with the first fluorophore dye,

contacting the second aliquot with the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye,

measuring total fluorescence emitted by each of the first and second fluorophore dyes in the second aliquot,

wherein an increase or decrease in the ratio of live cells to dead cells in each of the aliquots may be assessed. In one embodiment, the total fluorescence emitted by each of the first and second fluorophore dyes is measured using a camera, preferably at a resolution of at least 2X, at least 3X, at least 4X or more, from directly above or below each three-dimensional device, and preferably wherein the three-dimensional devices are placed on a moveable stage permitting the camera to capture the total fluorescence in each aliquot.

In some embodiments, the dead cell fluorescence and the live cell fluorescence can be added together to yield a live and dead cell total. The amount of dead cells may be expressed as a percentage of the dead cell fluorescence to the total fluorescence. The amount of live cells can be expressed as a percentage of the live cell fluorescence to the total. In some embodiments, the dead cell fluorescence and the live cell fluorescence can be expressed as a ratio, that is, dead cells/live cells or live cells/dead cells. In this manner, changes to the number of dead cells to live cells can be tracked over time, wherein an initial ratio is established prior to culturing and changes to the ratio are determined over time.

In some embodiments, there are multiple aliquots of tumor spheroids, for example three, or four, or five, or six or more than six, and the contacting of the third, fourth, fifth, sixth or more than sixth such aliquots with the first fluorophore dye and second fluorophore dye is carried out, for example, two days, three days, four days, five days, and more than five days, respectively, after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye. The timing of testing aliquots may be separated by any time period , such as one day, less than a day, two days or three or more days. In one embodiment, an aliquot is tested six days after placing the spheroids in the gel.

In any of the embodiments, the second (or any subsequent) aliquot is contacted with at least one test compound during the culturing of the second aliquot and wherein said culturing of the second aliquot in the presence of the test compound occurs for at least 24 hours, at least two days, at least three days, at least four days, at least five days, or at least 6 days or more.

In any of the foregoing embodiments, the second aliquot can be contacted with at least two test compounds during the culturing of the second aliquot and wherein said culturing of the second aliquot in the presence of the test compounds occurs for at least 24 hours, at least two days, at least three days, at least four days, at least five days, or at least 6 days, and preferably wherein at least one of the test compounds is an immune checkpoint inhibitor.

The number of spheroids can be any number of spheroids convenient and available to the researcher, but in the system described below, the number of spheroids in the first and the second aliquots each contain between about 15 and 30 spheroids, preferably between about 20 and 25 spheroids.

In some embodiments, the first three-dimensional device can be a first three-dimensional microfluidic device and the second three-dimensional device can be a second three-dimensional microfluidic device. In some embodiments, the culturing of the first aliquot in the first three- dimensional microfluidic device, is for less than 6 hours, less than 3 hours, less than 2 hours and even less than 1 hour prior to contacting the first aliquot with the first and second fluorophore dyes. In particular, it may be desirable to contact the first aliquot with the dyes prior to culturing the spheroids at all, that is essentially upon introducing the spheroids into the three dimensional device.

In any of the foregoing embodiments, the enzyme can be collagenase.

In any of the foregoing embodiments, the first fluorophore dye can be propidium iodide, DRAQ7, 7-AAD, eBioscience Fixable Viability Dye eFluor® 455UV, eBioscience Fixable Viability Dye eFluor® 450, eBioscience Fixable Viability Dye eFluor® 506, eBioscience Fixable Viability Dye eFluor® 520, eBioscience Fixable Viability Dye eFluor® 660, eBioscience Fixable Viability Dye eFluor® 780, BioLegend Zombie Aqua™, BioLegend Zombie NIR™, BioLegend Zombie Red™, BioLegend Zombie Violet™, BioLegend Zombie UV™, or BioLegend Zombie Yellow™, and/or the second fluorophore dye can be acridine orange, nuclear green LCS l (abl38904), DRAQ5 (abl08410), CyTRAK Orange, NUCLEAR-ID Red DNA stain (ENZ-52406), SiR700-DNA, calcein AM, calcein violet AM, calcein blue AM, Vybrant® DyeCycle™ Violet, Vybrant® DyeCycle™ Green, Vybrant® DyeCycle™ Orange, or Vybrant® DyeCycle™ Ruby.

In any of the foregoing embodiments, the tumor spheroids can be obtained by

mincing a primary tumor sample in a medium supplemented with serum; treating the minced primary tumor sample with an enzyme; and harvesting tumor spheroids from the enzyme treated sample. In some embodiments, the minced primary tumor sample is treated with the enzyme in an amount and/or for a time sufficient to yield a partial digestion of the minced primary tumor sample, and preferably wherein the treatment is for between 10 minutes and 60 minutes, and more preferably between 15 minutes and 45 minutes at a temperature of 25 °C to 39 °C .

In any of the foregoing embodiments, the biocompatible gel can be collagen, BD

Matrigel™ Matrix Basement Membrane, or fibrin hydrogel. In any of the foregoing embodiments, the tumor sample can be derived from a murine model. In some embodiments, the murine model is a syngeneic model selected from the group consisting of Bladder MBT-2, Breast 4T1, EMT6, Colon, Colon26, CT-26, MC38, Fibrosarcoma WEHI-164, Kidney Renca, Leukemia C 1498, L1210, Liver H22, KLN205, LL/2, LewisLung, Lymphoma A20 S, E.G7-OVA, EL4, Mastocytoma P815, Melanoma B 16-BL6, B 16-F10, S91, Myeloma MPC-11, Neuroblastoma Neuro-2a, Ovarian: ID8, Pancreatic Pan02, Plasmacytoma J558, and Prostate RM-1.

In any of the foregoing embodiments, the tumor sample can be a human tumor sample.

In any of the foregoing embodiments, the tumor sample can be a patient derived xenograft (PDX).

In any of the foregoing embodiments, the three-dimensional device can include one or more fluid channels flanked by one or more gel cage regions, wherein the one or more gel cage regions comprises the biocompatible gel in which the tumor spheroids are embedded, and wherein the device recapitulates in vivo tumor microenvironment. In any of the foregoing embodiments, the three-dimensional device can include: a substrate comprised of an optically transparent material and further comprising i) one or more fluid channels; ii) one or more fluid channel inlets; iii) one or more fluid channel outlets; iv) one or more gel cage regions; and v) a plurality of posts; wherein all or a portion of each gel cage region is flanked by all or a portion of one or more fluid channels, thereby creating one or more gel cage region-fluid channel interface regions; each gel cage region comprises at least one row of posts which forms the gel cage region; and the one or more gel cage region has a height of less than 500 μιη.

In any of the foregoing embodiments, the test compound can be a small molecule, a nucleic acid molecule, an RNAi compound, an aptamer, a protein or a peptide, an antibody or antigen-binding antibody fragment, a ligand or receptor-binding protein, a gene therapy vector, or a combination thereof. In any of the foregoing embodiments, the first test compound can be a chemotherapeutic compound, an immunomodulatory compound, or radiation. In any of the foregoing embodiments, the first test compound can be an alkylating compound, an

antimetabolite, an anthracycline, a proteasome inhibitor, or an mTOR inhibitor. In any of the foregoing embodiments, the first test compound can be an immune modulator. BRIEF DESCRIPTION OF THE DRAWINGS

The skilled artisan will understand that the figures, described herein, are for illustration purposes only. It is to be understood that, in some instances, various aspects of the invention may be shown exaggerated or enlarged to facilitate an understanding of the invention. In the drawings, like reference characters generally refer to like features, functionally similar and/or structurally similar elements throughout the various figures. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the teachings. The drawings are not intended to limit the scope of the present teachings in any way.

The features and advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings.

When describing embodiments in reference to the drawings, direction references ("above," "below," "top," "bottom," "left," "right," "horizontal," "vertical," etc.) may be used. Such references are intended merely as an aid to the reader viewing the drawings in a normal orientation. These directional references are not intended to describe a preferred or only orientation of an embodied device. A device may be embodied in other orientations.

As is apparent from the detailed description, the examples depicted in the figures and further described for the purpose of illustration throughout the application describe non-limiting embodiments, and in some cases may simplify certain processes or omit features or steps for the purpose of clearer illustration.

FIG. 1 A is a schematic for preparation and analysis of MDOTS/PDOTS (S2 fraction) from murine or patient-derived tumor specimens.

FIG. IB depicts MC38 allograft immune profiling by flow cytometry comparing bulk tumor (n=5) to S I, S2, S3 (n=6) spheroid fractions (Kruskal-Wallis with Dunn's multiple comparisons test, a=0.05; ns=not significant).

FIG. 1C depicts immune profiling of PDOTS (S2; n=40) (upper panel = % live cells, lower panel = %CD45+ cells) with indicated patient/tumor characteristics, grouped by tumor type and ranked by %CD8+ T cells.

FIG. ID depicts immune cell correlation of S2/S3 fractions (CD45, n=14; CD3, n=15; CD4/CD8, n=13; CD4+CD45RO+, n=9; CD8+CD45RO+, n=8; activated = CD38+ and/or CD69+, n=6), R2 significant for all comparisons. FIG. IE depicts PD-1, CTLA-4, TIM-3 expression on CD4 and CD8 T cell populations in S2/S3 fractions (n=6), R2 significant for all comparisons.

FIG. 2A depicts phase-contrast imaging (4x) of MC38 MDOTS in 3D microfluidic culture.

FIG. 2B is a cytokine heatmap from cultured MC38 MDOTS expressed as log-2 fold change relative to Day 1.

FIG. 2C is a cytokine heatmap from cultured B 16F10 MDOTS expressed as log-2 fold change relative to Day 1.

FIG. 2D illustrates MC38 allograft tumor volume following isotype control IgG (n=10) or rat-anti-mouse anti-PD-1 antibody (n=10) treatment.

FIG. 2E illustrates Day 22 MC38 tumor volumes (unpaired 2-sided t-test, p<0.05).

FIG. 2F is a schematic of MDOTS Live/Dead Imaging workflow.

FIG. 2G illustrates Live (AO = green)/dead (PI = red) quantification of MC38 MDOTS Day 0 (immediately after loading), Day 3, and Day 6 following IgG control or indicated anti-PD- 1 antibody doses; n=4, biological replicates, **p<0.01, ****p<0.0001, Kruskal-Wallis Dunnett's with multiple comparisons test).

FIG. 2H illustrates Live/dead analysis of MC38 spheroids lacking immune cells + anti- PD 1 (n=4, biological replicates).

FIG. 21 illustrates Live/dead analysis of CT26 MDOTS + anti-PDl (n=3, biological replicates, ****p<0.0001).

FIG. 2J illustrates Live/dead analysis of B 16F10 MDOTS + anti-PDl (n=3, biological replicates).

FIG. 2K depicts deconvolution fluorescence microscopy of MC38 and B 16F10 MDOTS Day 6 + anti-PDl (representative images shown).

FIG. 3 A is a cytokine heatmap that illustrates day 3 + anti-PD-1 (n=28) expressed as log2 fold-change (L2FC) relative to untreated control.

FIG. 3B is a cytokine heatmap that illustrates day 3 + anti-CTLA-4 (n=24) expressed as log2 fold-change (L2FC) relative to untreated control.

FIG. 3C is a cytokine heatmap that illustrates day 3 + anti-PD-1 + anti-CTLA-4 (n=24) expressed as log2 fold-change (L2FC) relative to untreated control. FIG. 3D depicts absolute CCL19/CXCL13 levels following single checkpoint blockade (2-sided, paired, t-test, a= 0.05).

FIG. 3E depicts absolute CCL19/CXCL13 levels following single checkpoint blockade (2-sided, paired, t-test, a= 0.05).

FIG. 3F depicts absolute CCL19/CXCL13 levels following dual checkpoint blockade (2- sided, paired, t-test, a= 0.05).

FIG. 3G is a heatmap that illustrates CCL19/CXCL13 mRNA levels from melanoma biopsy samples on anti-PDl treatment relative to pre-PD-1 (L2FC) by qRT-PCR (n=12).

FIG. 3H is a heatmap that illustrates CCL19/CXCL13 mRNA levels from melanoma biopsy samples on anti-PDl treatment relative to pre-PD-1 (L2FC) by RNA-seq (n=17 from 10 patients).

FIG. 31 depicts absolute expression (RPKM) for CCL19 and CXCL13 in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB) or no clinical benefit (NCB) from checkpoint blockade.

FIG. 3J depicts absolute expression (RPKM) for CCR7 and CXCR5, the respective receptors for CCL19 and CXCL13, in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB) or no clinical benefit (NCB) from checkpoint blockade.

FIG. 3K is a heat map that illustrates immune signatures (GSEA) in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients).

FIG. 3L depicts a Kaplan-Meier survival curve by CCL19/CXCL13 expression (high vs. low).

FIG. 3M depicts a Kaplan-Meier survival curve by four-way sorting using cutaneous melanoma (SKCM) TCGA data20 (logrank Mantel-Cox test).

FIG. 3N illustrates immune signatures (GSEA) in melanoma biopsy specimens (pre- and on-treatment) in clusters of patients with varying expression of CCL19 and CXCL13 in cutaneous melanoma (SKCM) TCGA.

FIG. 30 is a heatmap that illustrates an unsupervised hierarchical clustering of Day 3 PDOTS anti-PDl induced cytokines, expressed as row normalized (L2FC; n=14), annotated by response to anti-PD-1 therapy and timing of sample collection. FIG. 4A depicts a scheme of impact of ΤΒΚΙ/ΙΚΚε inhibition on cytokine production from tumor cells and T cells.

FIG. 4B depicts the chemical structure of Compound 1 with IC ₅₀ towards ΤΒΚΙ/ΙΚΚε, and EC ₅₀ in HCT116 cells.

FIG. 4C depicts cytokine heatmaps for CT26 spheroids (lacking immune cells) on Day 1,

3, and 6 + Compound 1 (n=3, biological replicates) expressed as log2 fold-change (L2FC) relative to vehicle control.

FIG. 4D is a dose-response curve for Compound 1 on IL-2 in human CD4 (n=3) and CD8 (n=5) T cells.

FIG. 4E is a dose-response curve for Compound 1 on IFNy in human CD4 (n=3) and

CD8 (n=5) T cells.

FIG. 4F depicts cytokine heatmaps for CT26 MDOTS treated with IgG+Cmpdl (1 μΜ), aPD-1 (10 μg/mL), or aPD-l+Cmpdl (1 μΜ) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG with vehicle control. 2-sided Welch's 2-sample t-test with unequal variance (a=0.05).

FIG. 4G is a chart that depicts live (AO = green)/dead (PI = red) quantification of CT26 MDOTS after 6 days treated with IgG-DMSO, Cmpdl (1 μΜ), aPD-1, and aPD-l+ Cmpdl (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 4H depicts imaging results corresponding to live (AO = green )/dead (PI = red) quantification of CT26 MDOTS after 6 days treated with IgG-DMSO, Cmpdl (1 μΜ), aPD-1, and aPD-l+ Cmpdl (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 41 depicts CT26 allograft tumor volume over time following IgG+vehicle,

IgG+Cmpdl , aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, **p<.01, 1-way ANOVA with Tukey' s multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan- Meier analysis for entire group and pairwise comparisons).

FIG. 4J depicts CT26 allograft percent change in tumor volume following IgG+vehicle, IgG+Cmpdl , aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n= 10 per group, **p<0.01, 1-way

ANOVA with Tukey' s multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 4K depicts CT26 allograft percent survival following IgG+vehicle, IgG+Cmpdl , aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan- Meier analysis for entire group and pairwise comparisons).

FIG. 5A depicts common gating for viable CD45+ cells in immune cell profiling by multi-color flow cytometry experiments.

FIG. 5B depicts gating hierarchy for T cell lineage and phenotypic marker in immune cell profiling by multi-color flow cytometry experiments.

FIG. 5C depicts myeloid cell gating hierarchy in immune cell profiling by multi-color flow cytometry experiments.

FIG. 5D depicts gating for NK lineage and Tregs in immune cell profiling by multi-color flow cytometry experiments.

FIG. 6A depicts immune cell sub-populations in MC38 tumors and/or spheroids from immune cell profiling of MDOTS. Immune cell sub-populations from MC38 (a) bulk tumor (n=5) to S I, S2, S3 (n=6) were evaluated by flow cytometry, as in Fig. lb (Kruskal-Wallis test with Dunn's multiple comparisons test, a=0.05; *p<0.05; ns=not significant).

FIG. 6B depicts a Pearson correlation matrix using composite of 21 cell surface markers in MC38 tumor, S I, S2, and S3 spheroids.

FIG. 6C depicts immune cell sub-populations in B 16F10 tumors and/or spheroids from immune cell profiling of MDOTS. Immune cell sub-populations from B 16F10 (a) bulk tumor (n=5) to S I (n=4), S2 (n=5), and S3 (n=4) evaluated by flow cytometry (Kruskal-Wallis test with Dunn's multiple comparisons test, a=0.05; *p<0.05; ns=not significant).

FIG. 6D depicts CD45+ cells (%live cells) in MC38 (n=6), B 16F10 (n=5), and CT26 (n=5) MDOTS (S2). Kruskal-Wallis test with Dunn's multiple comparisons test, a=0.05;

*p<0.05.

FIG. 6E depicts immune sub-populations (%CD45+ cells) in MC38 (n=6), B 16F10 (n=5), and CT26 (n=5) MDOTS (S2). 2-way ANOVA with Tukey's multiple comparisons test, a=0.05; *p<0.05, ***p<0.001, ****p<0.0001).

FIG. 6F depicts surface expression of T cell exhaustion markers (PD-1, CTLA-4, TIM-3) on CD4 and CD8 populations in PDOTS (n=40) from immune cell profiling of PDOTS.

FIG. 6G depicts surface expression of PD-L1 and PD-L2 on myeloid sub-populations, including granulocytic myeloid-derived suppressor cells (gMDSCs), monocytes, tumor- associated macrophages (TAMs), monocytic myeloid-derived suppressor cells (mMDSCs), and plasmacytoid dendritic cells (pDCs).

FIG. 6H depicts immune cell sub-populations of PDOTS fractions (S I, S2, S3) evaluated by flow cytometry, for CD45+ (n=8), CD3+ (n=8), CD4+ (n=7), CD8+ (n=7), CD 14+ (n=7), and CD 15+ (n=6). Kruskal-Wallis test with Dunn's multiple comparisons test, a=0.05; ns=not significant.

FIG. 61 depicts antigen-experienced sub-population (CD45RO+), effector memory (CD45RO+CCR7-) subtype, and surface expression of T cell exhaustion markers (PD-1, CTLA- 4, TEVI-3) on CD4 populations in PDOTS fractions (n>3; Kruskal-Wallis test with Dunn's multiple comparisons test, a=0.05; ns=not significant).

FIG. 6J depicts antigen-experienced sub-population (CD45RO+), effector memory (CD45RO+CCR7-) subtype, and surface expression of T cell exhaustion markers (PD-1, CTLA- 4, TEVI-3) on CD8 populations in PDOTS fractions (n>3; Kruskal-Wallis test with Dunn's multiple comparisons test, a=0.05; ns=not significant).

FIG. 7 A depicts immunofluorescence staining of MC38 MDOTS.

FIG. 7B depicts immunofluorescence staining of NSCLC PDOTS.

FIG. 7C depicts immunofluorescence staining of NSCLC PDOTS.

FIG. 7D depicts immunofluorescence staining for MC38 MDOTS stained for CD45+ immune cells (purple) and CD8+ T cells (yellow) with calcein (green) staining live cells and Hoechst (blue) staining all cell nuclei at Day 7 after treatment with IgG (10 μg/mL) or anti-PD-1 (10 μg/mL) (scale bar = 20 μιη).

FIG. 7E is a chart that depicts live/dead analysis of MC38 MDOTS + anti-PD-1 performed by independent lab (n=3, biological replicates).

FIG. 7F is a chart that depicts live/dead analysis of CT26 MDOTS performed on Day 6 following treatment with isotype IgG control (10 μg/mL) or anti-PD-1 (10 μg/mL) + anti-CD8 (10 μg/mL) (n=6, biological replicates; 2-way ANOVA with Tukey's multiple comparisons test; ****p<0.0001, ns = not significant).

FIG. 7G depicts a comparison of intratumoral and inter-tumoral heterogeneity evaluating CD8+ T cell counts (IF, performed on Day 4) and live/dead analysis (AO/PI staining) of CT26 MDOTS (Day 5). FIG. 8A depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to aPD-1 grouped by Thl and IFN-γ effector cytokines, (n=28; 2-sided, paired, t-test, a= 0.05).

FIG. 8B depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to aPD- 1 grouped by granulocyte chemoattractants, (n=28; 2-sided, paired, t-test, a= 0.05).

FIG. 8C depicts absolute cytokine levels (pg/mL) obtained by bead-based cytokine profiling of PDOTS under control conditions or in response to aPD- 1 grouped by IPRES immune suppressive cytokines, (n=28; 2-sided, paired, t-test, a= 0.05).

FIG. 8D illustrates a comparison of PDOTS cytokine profiles after 3 days in standard growth conditions with and without isotype control IgG antibody (50 μg/mL) (n=2), performed using PDOTS derived from sample MGH-16 (melanoma).

FIG. 8E depicts CCL19 and CXCL13 levels (pg/mL) relative to the number of spheroids per device in control and treatment (aPD-1) conditions (R2 = Pearson correlation coefficient).

FIG. 8F depicts results of biological replicates for MGH-16 PDOTS in response to PD-1 blockade (n=3, L2FC relative to untreated control on Day 3).

FIG. 8G depicts CCL19 and CXCL13 levels (pg/mL) from biological replicates for MGH-16 PDOTS in response to PD-1 blockade (n=3, L2FC relative to untreated control on Day 3).

FIG. 8H depicts the correlation between CCL19 and CXCL13 upregulation (log2 fold- change relative to untreated control) in response to aPD-1, aCTLA-4, or aPD-1 + aCTLA-4 (R2 = Pearson correlation coefficient).

FIG. 81 illustrates the effect of culture in the microfluidic device on cytokine profile following aPD-1 treatment. Equal volumes of PDOTS from patient MGH-16 (in collagen hydrogels) were loaded for microfluidic device (or into a single well of a 96-well plate in equal volumes of culture media. Media was collected on Day 3 (control and aPD-1) for cytokine profiling. Induction of cytokines represented as fold-change relative to the untreated control.

FIG. 9A is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with aPD-1, aCTLA-4, or aPD-1 + aCTLA-4 in DFCI-25 (melanoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 9B is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo micro fluidic culture with aPD-1, aCTLA-4, or aPD-1 + aCTLA-4 in MGH-12 (melanoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 9C is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with aPD-1, aCTLA-4, or aPD-1 + aCTLA-4 in DFCI-16 (thyroid carcinoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 9D is a heatmap demonstrating log(2) fold-change (relative to untreated control, ranked highest to lowest) in cytokine profiles using conditioned media obtained at indicated time points of ex vivo microfluidic culture with aPD-1, aCTLA-4, or aPD-1 + aCTLA-4 in DFCI-19 (pancreatic adenocarcinoma PDOTS). Arrows denote effector cytokines (e.g. IFN-γ, IL-2) associated with immune-mediated cytolysis.

FIG. 10A depicts RNA-seq showing select cytokines, cytokine receptors, cytotoxic T cell (CTL) associated genes, and IPRES transcripts (L2FC relative to pre-treatment control in 10 sets of patient samples).

FIG. 10B depicts RNA-seq absolute expression (RPKM) for cytotoxic T cell effector associated genes (IFNG, IFNGR1, granzyme A, granzyme B) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients) from checkpoint blockade.

FIG. IOC depicts RNA-seq absolute expression (RPKM) for select IPRES genes in melanoma biopsy specimens (pre- and on-treatment) from patients with established clinical benefit (CB, n=10 samples from 4 patients) or no clinical benefit (NCB, n=17 samples from 6 patients) from checkpoint blockade.

FIG. 10D depicts pre-treatment expression of CCL19 and CXCL13 in responders (n=15) and non-responders (n=13) to PD-1 blockade. Expression data is represented as transcripts per million (TPM) with error bars indicating standard deviation (ns = not significant; unpaired, 2- sided, Mann-Whitney test, a=0.05).

FIG. 10E depicts pre-treatment expression of CCL19 and CXCL13 in patients who experienced clinical benefit (CB, n=14) , no clinical benefit (NCB, n=22), and no clinical benefit, but long-term survival (NCB+LTS, n=5) from ipilimumab (aCTLA-4). Expression data is represented as transcripts per million (TPM) with error bars indicating standard deviation (ns = not significant; Kruskal-Wallis with Dunn's multiple comparisons test, a=0.05).

FIG. 10F is a heatmap demonstrating log(2) fold change (on-aPD-l/pre-aPD-1) in expression of indicated cytokines.

FIG. 10G is a heatmap demonstrating log(2) fold change of plasma cytokines using matched plasma samples (on-treatment/pre-treatment) for responders (R; n=7) and non- responders (NR; n=4) to anti-PD-1 therapy.

FIG. 10H depicts four-way Kaplan-Meier survival curves by CCL19/CXCL13 expression (high-high, high-low, low-high, and low-low) using urothelial bladder carcinoma (BLCA), head & neck squamous cell carcinoma (HNSC), and breast carcinoma (BRCA) TCGA data (pairwise analysis using log-rank Mantel-Cox test, *p<0.05).

FIG. 11A depicts H&E imaging (lOx objective) of tumor-associated tertiary lymphoid structure (TA-TLS), higher magnification (40x objective), and quantitation of TA-TLS identified in 52 H&E slides.

FIG. 1 IB depicts PDOTS divided into CCL19/CXCL13-high (n=14) and

CCL19/CXCL13-low (n=14) by median L2FC (Mann- Whitney test, ****p<0.0001).

FIG. l lC depicts median immune cell composition (CD45+, CD4+, CD8+, CD14+, CD15+) between PDOTS with distinct ex vivo expression of CCL19/CXCL13 (high vs. low).

FIG. 11D depicts median immune cell composition (CD4+PD1+ and CD8+PD-1+) in CCL19/CXCL13 high vs. low PDOTS.

FIG. 1 IE depicts relative expression of CCL19 and CXCL13 by qRT-PCR in cancer- associated fibroblasts (CD45-CD90+), cancer-associated endothelial cells (CD31+CD144+), CD45- (cancer cells, etc.) and CD45+ immune cells following 4-way cell sorting (n=2, technical replicates from MGH-16). FIG. 11F depicts immunohistochemical staining of CCL19, CXCL13, aSMA (cancer- associated fibroblasts), and CD31 (endothelial cells) in melanoma specimen (pt 422, on- treatment; 40x magnification, scale bar 400 μιη).

FIG. 12A depicts mean cytokine changes from PDOTS following ex vivo PD-1 blockade in patients with clinical benefit (n=5; PR/SD) and without clinical benefit (n=9; MR/PD) from PD-1 blockade (*p<0.05).

FIG. 12B depicts four-way Kaplan-Meier survival curves by CX3CL1/CCL20 expression (high-high, high-low, low-high, and low-low) using melanoma TCGA data (pairwise analysis using log-rank Mantel-Cox test, a=0.05, ns = not significant).

FIG. 12C depicts composite IPRES6 score (sum of L2FC for CCL2, CCL7, CCL8,

CCL13, IL-10) in response to ex vivo PD-1 blockade in PDOTS samples from patients with clinical benefit (PR/SD) and without clinical benefit (MR/PD) from PD-1 blockade.

FIG. 12D depicts heatmaps of Day 3 PDOTS anti-PDl induced cytokines for samples DFCI-13, -16, -18, and -21 (serial sampling from same patient with metastatic papillary thyroid cancer), expressed as L2FC relative to untreated control.

FIG. 12E is a chart that depicts serial immune profiling of samples DFCI-13, -16, -18, - 21, and -22 from the same patient undergoing indicated treatments.

FIG. 12F is a heatmap of relative anti-PDl induced cytokine changes from MC38 and B 16F10 MDOTS (L2FC relative to isotype control; n=3, biological replicates).

FIG. 12G is a chart that depicts absolute cytokine levels in CT26 MDOTS over time

(n=3, biological replicates).

FIG. 12H depicts Live/Dead analysis at Day 6 in CT26 MDOTS treated with anti-CCL2 + anti-PD-1 at Days 1, 3, and 6 (L2FC relative to isotype control; n=3, biological replicates).

FIG. 121 is a heatmap of relative cytokine changes in CT26 MDOTS treated with anti- CCL2 + anti-PD-1 at Days 1, 3, and 6 (L2FC relative to isotype control; n=3, biological replicates).

FIG. 13A is a scheme that depicts chemical synthesis of Compound 1.

FIG. 13B is a chart that depicts IC ₅₀ values for indicated enzymes treated with Compound

1.

FIG. 13C depicts an IC ₅₀ curve for TBK1.

FIG. 13D depicts an IC ₅₀ curve for ΙΚΚε (IKBKE). FIG. 13E is a chart that depicts effect of Compound 1 on viability of CT26 spheroids lacking immune cells (n=3, biological replicates).

FIG. 13F illustrates fold-change in IL-2 levels produced by Jurkat cells with increasing doses of Compound 1.

FIG. 13G depicts change in tumor volume following re-implantation of CT26 and EMT-6 cells into the flanks of mice previously treated with anti-PD-Ll+ Compound 1.

FIG. 14A is a cytokine heatmap for MC38 MDOTS treated with IgG+Cmpdl (1 μΜ), aPD-1 (10 μg/mL), or aPD-l+Cmpdl (1 μΜ) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG (10 μg/mL) with vehicle control (DMSO 0.1%). 2-sided Welch's 2-sample t-test with unequal variance (a=0.05).

FIG. 14B is a cytokine heatmap for B 16F10 MDOTS treated with IgG+Cmpdl (1 μΜ), aPD-1 (10 μg/mL), or aPD-l+Cmpdl (1 μΜ) from the mean of n=3 biological replicates, plotted as L2FC relative to isotype control IgG (10 μg/mL) with vehicle control (DMSO 0.1%). 2-sided Welch's 2-sample t-test with unequal variance (a=0.05).

FIG. 14C is a chart that depicts live (AO = green)/dead (PI = red) quantification of MC38

MDOTS after 5 days treated with IgG-DMSO, Cmpdl (1 μΜ), aPD-1, and aPD-l+ Cmpdl (*p<0.05, Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 14D depicts MC38 allograft tumor volume waterfall plot following IgG+vehicle, IgG+Cmpdl , aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n= 10 per group, *p<0.05, **p<0.01, 1- way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14E depicts percent survival following IgG+vehicle, IgG+Cmpdl, aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, *p<0.05, **p<0.01, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14F is a chart that depicts live (AO = green )/dead (PI = red) quantification of B 16F10 MDOTS after 6 days treated with IgG-DMSO, Cmpdl (1 μΜ), aPD-1, and aPD-l+ Cmpdl (a=0.05, ns = not significant. Kruskal-Wallis ANOVA with multiple comparisons; n=3).

FIG. 14G depicts quantification of small lung metastases in B 16F10 tail vein injection model following IgG+vehicle, IgG+Cmpdl , aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, 1-way ANOVA with Tukey's multiple comparison's test, ns = not significant). FIG. 14H depicts quantification of medium lung metastases in B 16F10 tail vein injection model following IgG+vehicle, IgG+Cmpdl , aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, 1-way ANOVA with Tukey' s multiple comparison's test, ns = not significant).

FIG. 141 depicts MB49 allograft tumor volume waterfall plot following IgG+vehicle, IgG+Cmpdl, aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, *p<0.05, 1-way ANOVA with Tukey' s multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan- Meier analysis for entire group and pairwise comparisons).

FIG. 14J depicts MB49 allograft tumor volume waterfall plot as a bar chart following IgG+vehicle, IgG+Cmpdl, aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, *p<0.05, 1- way ANOVA with Tukey' s multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 14K depicts percent survival following IgG+vehicle, IgG+Cmpdl, aPD-Ll+vehicle, and aPD-Ll+Cmpdl (n=10 per group, *p<0.05, 1-way ANOVA with Tukey's multiple comparison's test for tumor volume, log-rank Mantel-Cox test for Kaplan-Meier analysis for entire group and pairwise comparisons).

FIG. 15 depicts a table summary of Pilot RNA Extraction, QC, and Quantitation (left), and a representation bioanalyzer trac showing fully intact total RNA from MDOTS (right).

DETAILED DESCRIPTION Among other aspects, the disclosure provides methods for evaluating tumor cell spheroids in a three-dimensional microfluidic device by monitoring a ratio of live cells to dead cells. In some aspects, the methods include steps of exposing separate aliquots of a tumor spheroid sample to different conditions, such as the inclusion or exclusion of a test compound. As such, in some embodiments, the effects of a test compound can be evaluated by monitoring its effects on the ratio of live cells to dead cells. It has been discovered, surprisingly, that the tumor microenvironment of a cultured tumor spheroid can be evaluated optically and

reproducibly, to establish the effects of drugs on the tumor cells within the spheroids, while distinguishing the effects on tumor cells resulting from the act of culturing the tumor cells.

As used herein, the term "tumor" refers to a neoplasm, i.e., an abnormal growth of cells or tissue and is understood to include benign, i.e., non-cancerous growths, and malignant; i.e., cancerous growths including primary or metastatic cancerous growths. Examples of neoplasms include, but are not limited to, mesothelioma, lung cancer (e.g., small-cell lung cancer, non-small cell lung cancer), skin cancer (e.g., melanoma), stomach cancer, liver cancer, colorectal cancer, breast cancer, pancreatic cancer, prostate cancer, blood cancer, bone cancer, bone marrow cancer, and other cancers.

The term "tumor spheroid," or "tumor cell spheroid" as used herein, refers to an aggregation of tumor cells constituting a small mass, or lump of tumor cells. In some

embodiments, tumor spheroids are less than about 3 cm, less than about 2 cm, less than about 1 cm, less than about 5 mm, less than about 2.5 mm, less than about 1 mm, less than about 100 μιη, less than about 50 μιη, less than about 25 μιη, less than about 10 μιη, or less than about 5 μιη in diameter. In some embodiments, the tumor spheroids have a diameter of 10 μιη to 500 μιη. In some embodiments, the tumor spheroids have a diameter of 40 μιη to 100 μιη. In some embodiments, the tumor spheroids have a diameter of 40 μιη to 70 μιη.

The term "primary tumor sample" as used herein refers to a sample comprising tumor material obtained from a subject having cancer. The term encompasses tumor tissue samples, for example, tissue obtained by surgical resection and tissue obtained by biopsy, such as for example, a core biopsy or a fine needle biopsy. The term also encompasses patient derived xenograft (PDX). Patient derived xenografts are created when cancerous tissue from a patient's primary tumor is implanted directly into an immunodeficient mouse (see, for example, Morton CL, Houghton PJ (2007). "Establishment of human tumor xenografts in immunodeficient mice". Nature Protocols 2 (2): 247-50; Siolas D, Hannon GJ (September 2013). "Patient-derived tumor xenografts: transforming clinical samples into mouse models". Cancer Research 73 (17): 5315— 9). PDX mirrors patients' histopathological and genetic profiles. It has improved predictive power as preclinical cancer models, and enables the true individualized therapy and discovery of predictive biomarkers.

In some embodiments, the subject is a human. In some embodiments, the subject is a non-human mammal or a non-human vertebrate. In some embodiments, the subject is laboratory animal, a mouse, a rat, a rodent, a farm animal, a pig, a cattle, a horse, a goat, a sheep, a companion animal, a dog a cat, or a guinea pig.

In some embodiments, a tumor sample as used herein is derived from a subject known to have resistance or sensitivity to a particular therapeutic treatment. For example, in some embodiments, methods provided herein can identify novel combination therapies and/or novel single therapies that overcome resistance to a specified treatment, e.g., PD-1 inhibition in the treatment of cancer. In some embodiments, where PD-1 combination therapies are to be evaluated, tumor samples may be derived from one or more subjects having the same or varied levels of sensitivity to PD-1 inhibition therapy. In some embodiments, the tumor sample is derived from a B 16F10 murine model. B 16F10 is a murine model that is minimally sensitive to PD-1 blockade. In some embodiments, the tumor sample is derived from an MC38 murine model. MC38 is a murine model that is highly sensitive to PD-1 blockade relative to B 16F10. In some embodiments, the tumor sample is derived from a CT26 murine model. CT26 is a murine model that is of an intermediate sensitivity relative to B 16F10 and MC38 models. In some embodiments, methods provided herein comprises steps of evaluating a combination of two or more of tumor samples derived from B 16F10, MC38, or CT26 models.

Tumor cell spheroids can be prepared by any method known in the art. Exemplary methods for preparing tumor cell spheroids are described in WO 2016/112172, the disclosure of which is incorporated herein by reference.

In some embodiments, the primary tumor sample is collected in a serum-supplemented medium, for example but not limited to, RPMI medium supplemented with 10% fetal bovine serum. The sample is then minced, i.e., cut or chopped into tiny pieces. In some embodiments, the sample is minced on ice. In some embodiments, the minced primary tumor sample comprises tumor pieces in the size of about 3 mm, 2.5 mm, 2.0 mm, 1.5 mm, 1.0 mm, 0.5, or 0.25 mm.

In some embodiments, the primary tumor sample is not frozen and thawed.

In some embodiments, minced primary tumor sample is frozen in a medium

supplemented with serum and thawed prior to treating with the composition comprising the enzyme. In some embodiments, the minced primary tumor sample is frozen for at least 6 hours 12 hours, 24 hours, 2 days, 1 week or one month. In some embodiments, the minced primary tumor sample is frozen at -80 °C. In some embodiments, the minced primary tumor sample is frozen in liquid nitrogen. In some embodiments, the minced primary tumor sample is frozen in a medium supplemented with serum. In some embodiments, the minced primary tumor sample is frozen in a mixture containing serum and solvent such as Dimethyl sulfoxide (DMSO). In some embodiments, the minced primary tumor sample is frozen in a mixture containing fetal bovine serum and Dimethyl sulfoxide (DMSO). In some embodiments, the frozen minced primary tumor sample is thawed, i.e., defrosted, before treating the sample with a composition comprising an enzyme. In some embodiments, the minced primary tumor sample is thawed in a water bath kept at about 37 °C (e.g., 35 °C, 36 °C, 37 °C, 38 °C, or 39 °C). In some embodiments, the minced primary tumor sample is thawed at room temperature.

The minced primary tumor sample is treated with an enzyme mix to digest the tumor samples. In some embodiments, the composition comprising an enzyme includes collagenase. In some embodiments, the composition comprising an enzyme includes a serum-supplemented culture medium, insulin, one or more corticosteroids, one or more antibiotics, collagenase and optionally one or more growth factors. Serum- supplemented culture media, corticosteroids, antibiotics, and growth factors are well-known in the art. In some embodiments, the composition comprising an enzyme comprises DMEM or RPMI, fetal bovine serum, insulin, epidermal growth factor, hydrocortisone, Penicillin and/or Streptomycin, and collagenase. In some embodiments, the composition comprising an enzyme comprises further comprises a buffering agent such as 4-(2-hydroxyethyl)-l-piperazineethanesulfonic acid (HEPES).

"Treating the minced primary tumor sample with a composition comprising an enzyme" comprises incubating the minced tumor samples with the enzyme composition for at least 1 hour. In some embodiments, the minced tumor samples are incubated with the enzyme mix for at least 2 hours, at least 4 hours, at least 6 hours, at least 8 hours, at least 10 hours, at least 12 hours, at least 15 hours or at least 24 hours. In some embodiments, the minced primary tumor sample is incubated with the enzyme mix at 25 °C, 26 °C, 27 °C, 28 °C, 29 °C, 30 °C, 31 °C, 32 °C, 33 °C, 34 °C, 35 °C, 36 °C, 37 °C, 38 °C, or 39 °C. In some embodiments, the minced primary tumor sample is incubated with the enzyme mix at 37 °C.

In some embodiments, the minced primary tumor sample is treated with the composition comprising the enzyme in an amount or for a time sufficient yield a partial digestion of the minced primary tumor sample. In some embodiments, the minced primary tumor sample is treated with the composition comprising the enzyme for 30 minutes to 15 hours at a temperature of 25 °C to 39 °C.

Collecting tumor spheroids from the enzyme mix treated sample comprises centrifuging and washing the sample at least twice followed by isolating the digested tumor spheroids of the desired size. In some embodiments, the enzyme mix treated sample is centrifuged and washed using phosphate buffered saline (PBS) at least twice. Tumor spheroids of the desired size are collected using sieves. In some embodiments, the tumor spheroids having a diameter of 10 μιη, 50 μηι, 100 μιη, 200 μιη, 300 μιη, 400 μιη, 450 μιη, and 500 μιη are collected from the enzyme mix treated sample with the use of a sieve. In some embodiments, the tumor spheroids having a diameter of 40 μιη to 100 μιη are collected from the enzyme mix treated sample with the use of a sieve. In some embodiments, the tumor spheroids having a diameter of 40 μιη, 50 μιη, 60 μιη and 70 μιη are collected from the enzyme mix treated sample with the use of a sieve.

The tumor spheroids having a desired diameter are collected by sieving the enzyme mix treated sample through cell strainers. In some embodiments, the tumor spheroids having a diameter of 10 μιη to 500 μιη are collected by sieving the enzyme mix treated sample via 500 μηι and 10 μιη cell strainers to yield tumor spheroids having a diameter of 10 μιη to 500 μιη. In some embodiments, the tumor spheroids having a diameter of 40 μιη to 100 μιη are collected by sieving the enzyme mix treated sample via 100 μιη and 40 μιη cell strainers to yield tumor spheroids having a diameter of 10 μιη to 500 μιη. The tumor spheroids of the desired diameter are collected and suspended in a biocompatible gel. Examples of biocompatible gel include collagen, BD Matrigel™ Matrix Basement Membrane, or fibrin hydrogel (e.g., fibrin hydrogel generated from thrombin treatment of fibrinogen).

In some embodiments, the collected tumor spheroids are not frozen and then thawed before suspending in the biocompatible gel. In some embodiments, the collected tumor spheroids are introduced into the three-dimensional cell culture device within less than 2 hours, less than 1 hour, less than 30 minutes, less than 20 minutes, less than 10 minutes, or less after collection.

In some embodiments, the collected tumor spheroids are frozen in a freezing medium and then thawed before suspending in the biocompatible gel. In some embodiments, the collected tumor spheroids are frozen for at least 6 hours 12 hours, 24 hours, 2 days, 1 week or one month. In some embodiments, the collected tumor spheroids are frozen at -80 °C. In some

embodiments, the collected tumor spheroids are frozen in liquid nitrogen. In some embodiments, the collected tumor spheroids are frozen at -80 °C overnight, and then transferred to liquid nitrogen for storage. In some embodiments, the collected tumor spheroids are frozen in a medium supplemented with serum. In some embodiments, the collected tumor spheroids are frozen in a mixture containing culture medium such as DMEM or RPMI, fetal bovine serum and solvent such as Dimethyl sulfoxide (DMSO). The frozen spheroids are thawed, for example overnight at 4 °C, and then suspended in the biocompatible gel.

The tumor spheroids are cultured, i.e., grown, in a three dimensional (3D) microfluidic device. In some embodiments, the tumor spheroids are cultured with endothelial cells, such as human umbilical vein endothelial cells (HUVECs). In some embodiments, the tumor spheroids are cultured without endothelial cells. In some embodiments, the tumor spheroids are cultured with or without endothelial cells for at least 1 day, at least 2 days, at least 4 days, at least 6 days, at least 1 week, or at least 2 weeks.

3D microfluidic devices are known in the art and include, for example, but not limited to, the devices described in US 2013/0143230, EP2741083, US 2014/0057311, US 8748180, and WO 2016/112172, the disclosures of which are incorporated by reference herein.

In some embodiments, a 3D microfluidic device refers to a device that comprises one or more fluid channels flanked by one or more gel cage regions, wherein the one or more gel cage regions comprises the biocompatible gel in which the tumor spheroids are embedded, and wherein the device recapitulates, i.e., mimics, the in vivo tumor microenvironment. In order to facilitate visualization, the microfluidic device is typically comprised of a substrate that is transparent to light, referred to herein as "an optically transparent material". As will be appreciated by those of skill in the art, suitable optically transparent materials include polymers, plastic, and glass. Examples of suitable polymers are polydimethylsiloxane (PDMS),

poly(methyl methacrylate) (PMMA), polystyrene (PS), SU-8, and cyclic olefin copolymer

(COC). In some embodiments, all or a portion of the device is made of a biocompatible material, e.g., the material is compatible with, or not toxic or injurious to, living material (e.g., cells, tissue).

The fluid channel can be used to contain a (one or more) fluid (e.g., cell culture media), cells such as endothelial cells, cellular material, tissue, fluorophore dyes, and/or compounds (e.g., drugs) to be assessed, while the gel cage regions may be used to contain a gel (e.g., biologically relevant gel, such as collagen, Matrigel™, or fibrin hydrogel (e.g., fibrin hydrogel generated from thrombin treatment of fibrinogen)). In some embodiments, the 3D microfluidic device comprises the device described in US 2014/0057311, the disclosure of which is incorporated by reference herein. In particular, paragraphs [0056] to [0107] which describe the regions, channels, chambers, posts, and arrangement of posts, and paragraphs [0127] to [0130] which describe the methods of making the device are incorporated by reference herein.

In some embodiments, the method for identifying a compound for treating cancer, comprises culturing a first and second aliquot of tumor cell spheroids in a three-dimensional microfluidic device as described herein in the presence and absence of one or more test compounds, detecting a change in the ratio of live cells to dead cells in the aliquots of tumor cell spheroids.

In some embodiments, the change in the ratio of live cells to dead cells in the aliquots of tumor cell spheroids is monitored by measuring the total fluorescence emitted by each of the first and second fluorophore dyes. Accordingly, in some embodiments, the dead cell fluorescence and the live cell fluorescence can be added together to yield a live and dead cell total. In some embodiments, the amount of dead cells may be expressed as a percentage of the dead cell fluorescence to the total fluorescence. In some embodiments, the amount of live cells can be expressed as a percentage of the live cell fluorescence to the total. In some embodiments, the dead cell fluorescence and the live cell fluorescence can be expressed as a ratio. For example, in some embodiments, the ratio is expressed as dead cells/live cells or live cells/dead cells. In this manner, expressing as a ratio provides a standardized method of evaluating tumor cell spheroids.

In some embodiments, proliferation and/or dispersion of the tumor cell spheroids are also assessed.

In some embodiments, the method for identifying a compound or combination of compounds for treating cancer, comprises obtaining tumor spheroids from an enzyme treated tumor sample, suspending a first aliquot of the tumor spheroids in biocompatible gel, and suspending a second aliquot of the tumor spheroids in biocompatible gel. In some embodiments, the method further comprises placing the first aliquot of the tumor spheroids in biocompatible gel in a first three-dimensional device, and contacting the first aliquot with a first fluorophore dye selective for dead cells and a second fluorophore dye selective for live cells, where the first fluorophore dye emits fluorescence at a first wavelength when bound to a dead cell and the second fluorophore dye emits fluorescence at a second wavelength different from the first wavelength when bound to a live cell. In some embodiments, the method further comprises measuring total fluorescence emitted by each of the first and second fluorophore dyes in the first aliquot. In some embodiments, the method further comprises culturing the second aliquot in a second three-dimensional device, contacting the second aliquot with the first fluorophore dye and the second fluorophore dye, wherein the contacting of the second aliquot with the first fluorophore dye and second fluorophore dye is carried out at least 24 hours after the contacting of the first aliquot with the first fluorophore dye and second fluorophore dye. In some embodiments, the method further comprises measuring total fluorescence emitted by each of the first and second fluorophore dyes in the second aliquot, wherein an increase or decrease in the ratio of live cells to dead cells in each of the aliquots may be assessed.

"Culturing patient-derived tumor cell spheroids in the presence of the test compound" comprises introducing the test compound into the one or more fluid channels of the device described herein, wherein the one or more gel cage regions of the device comprises a gel in which the tumor spheroids are embedded; and culturing the tumor spheroids under suitable culture conditions. Suitable conditions include growing the tumor cell spheroids under standard cell culture conditions (e.g. at 37 °C in a humidified atmosphere of >80% relative humidity air and 5 to 10% C0 ₂ ).

In some embodiments, techniques provided herein relate to evaluating the effects of one or more therapeutic treatments in a tumor cell spheroid culture. In some embodiments, changes in the tumor cell spheroid culture are evaluated using one or more luminescent probes (e.g., one or more fluorescent dyes). For example, in some embodiments, methods described herein comprise steps of contacting a tumor cell spheroid culture with a first fluorophore dye and a second fluorophore dye that each selectively bind to a cell type that is different from the other, and where the fluorophore dyes emit fluorescence at different wavelengths when bound to the respective cell types. In some embodiments, the first fluorophore dye is selective for dead cells and the second fluorophore dye is selective for live cells. In some embodiments, the first fluorophore dye is selective for live cells and the second fluorophore dye is selective for dead cells.

In some embodiments, one or more fluorophore dye (e.g., one or more of a first fluorophore dye, one or more of a second fluorophore dye) is introduced into the one or more fluid channels of the cell culture device. The techniques provided in the present disclosure are envisioned to be compatible with any suitable fluorophore dye (e.g., fluorophore-containing dyes, stains, fluorescent labels, etc.). Suitable fluorophore dyes are known in the art and can be selected by a practitioner in view of a desired application of the techniques described herein. For example, in some embodiments, the one or more fluorophore dyes utilized in the techniques described herein can be compatible with staining under fixed or non-fixed conditions.

Fluorophore dyes that can be used for the detection of dead cells in non-fixed conditions include, by way of example and not limitation, DNA-dependent stains such as propidium iodide, DRAQ7, and 7-AAD. Fluorophore dyes that can be used for the detection of dead cells in either fixed or non-fixed conditions include, by way of example and not limitation, dyes listed in Table 1.

Table 1. Examples of dyes to stain for dead cells

The techniques provided in the present disclosure are envisioned to be compatible with any suitable fluorophore dye selective for live cells known in the art. Fluorophore dyes that can be used for the detection of live or fixed cells include, by way of example and not limitation, DNA-dependent stains such as acridine orange, nuclear green LCS 1 (abl38904), DRAQ5 (ab 108410), CyTRAK Orange, NUCLEAR-ID Red DNA stain (ENZ-52406), and SiR700-DNA Examples of non-DNA-dependent fluorophore dyes that stain for live cells are known in the art and include, by way of example and not limitation, calcein AM, calcein violet AM, and calcein blue AM. Fluorophore dyes that can be used for the detection of live or fixed cells include, by way of example and not limitation, dyes shown in Table 2. Table 2. Examples of dyes to stain for live cells

Additionally, two-color cell viability assays are available and may be used with the techniques described herein. Examples of live/dead cytotoxicity kits include, by way of example and not limitation, kits shown in Table 3.

Table 3. Examples of kits containing dyes to stain for both live/dead cells

resazurin/SYTOX™ Green C12-resazurin Red (Live) 1,000 assays

Changes in the tumor cell spheroid culture which predict or demonstrate a reduction in proliferation and/or dispersion of the tumor cell spheroids in the presence or absence of the test compound can be detected using known methods in the art, such as, chemical or physical methods, or a combination thereof.

As described herein, a tumor cell spheroid sample is evaluated by analyzing the relative amounts of live cells and dead cells in separate aliquots of the sample. In some embodiments, the relative amounts of live cells and dead cells in an aliquot is determined by fluorescence measurement. For example, in some embodiments, fluorescence measurement comprises total fluorescence acquisition of the emissions detected from a first fluorophore dye that selectively binds dead cells and a second fluorophore dye that selectively binds live cells. Based on such measurements, the relative emission levels can be parsed out to provide the amount of live cells relative to the amount of dead cells in the aliquot.

In some embodiments, the relative amounts or ratio of live cells to dead cells in an aliquot can be expressed as a percentage of the total fluorescence, such that:

[(% live cells)+(% dead cells)=100%]

In some embodiments, the relative levels of live cells and dead cells in a first aliquot is compared to a similar measurement obtained for a second aliquot that has been treated with a test compound. An increase in (% dead cells) in the presence of the test compound compared to the first aliquot is indicative that the test compound is effective for inducing cell death. In some embodiments, the percentage of dead cells in the presence of an effective test compound is increased relative to the absence of the test compound by about 5%, by about 10%, by about 15%, by about 20%, by about 25%, by about 30%, by about 35%, by about 40%, by about 50%, by about 60%, by about 70%, by about 80%, by about 90%, or greater.

In some embodiments, a change in the tumor cell spheroid culture can further be detected visually, e.g., using confocal microscopy imaging. The images obtained can be analyzed as described in Aref et al. Integr Biol (Camb). 2013 Feb;5(2):381-9, the disclosure of which is incorporated by reference in its entirety. In particular, the paragraphs on pages 387-388 relating to image acquisition and analysis (normalized dispersion, Δ/Δ0, and normalized cell number (N/NO)) are incorporated by reference in their entirety.

In some embodiments, the change in the tumor cell spheroid culture is a clustering of immune cells around one or more tumor cell spheroids in the culture. In some embodiments, the change in the tumor cell spheroid culture is a decrease in size and/or number of cells of one or more tumor cell spheroids in the culture.

In some embodiments, the change in the tumor cell culture is further detected chemically. For example, in some embodiments, the change in the tumor cell spheroid culture is determined by detection of the presence of a biological molecule secreted into the culture supernatant. In some embodiments, the biological molecule is a protein, carbohydrate, lipid, nucleic acid, metabolite, or a combination thereof. In some embodiments, the biological molecule is a chemokine or a cytokine. In some embodiments, the biological molecule is known to be associated with activation of the immune system or otherwise an enhancement of the immune response.

In some embodiments, the detected biological molecule(s) involves single cell sequencing of T cell receptors on tumor spheroid associated CD4 and CD8 T cells that become activated in the device.

In some embodiments, a sample of tumor cell spheroid culture supernatant may be obtained from the 3D culture device. In some embodiments, a secreted biological molecule or a profile of secreted biological molecules, e.g., a cytokine profile or chemokine profile, may be detected in the tumor cell spheroid culture supernatant.

Methods for detecting secreted biological molecules are known in the art. Exemplary assays and cytokines are disclosed, for example, in WO 2016/112172, the disclosure of which is incorporated herein by reference.

In some embodiments, a sample of tumor cell spheroid is analyzed by nucleic acid content. For example, it is possible to analyze extracellular nucleic acids, e.g., nucleic acids present in a culture medium of a tumor cell spheroid sample using methods known in the art.

Alternatively, nucleic acids can be isolated from cells in a cultured sample using methods known in the art. In some embodiments, such analysis can be used to assess gene expression, e.g., to evaluate the expression of genes associated with cytotoxicity, such as cytokines and cytokine receptors. In some embodiments, DNA and/or RNA (e.g., mRNA, rRNA, tRNA, etc.) from a sample may be analyzed. In some embodiments, RNA content of a sample is analyzed using RNA-seq.

In some embodiments, the test compound inhibits epithelial-mesenchymal transition (EMT). In some embodiments, the test compound is a small molecule compound. In some embodiments, the methods described herein are used to screen a library of test compounds, for example, a library of chemical compounds. In some embodiments, the test compound comprises a nucleic acid molecule, for example, a DNA molecule, an RNA molecule, or a DNA/RNA hybrid molecule, single- stranded, or double-stranded. In some embodiments, the test compound comprises an RNAi compound, for example, an antisense-RNA, an siRNA, an shRNA, a snoRNA, a microRNA (miRNA), or a small temporal RNA (stRNA). In some embodiments, the test compound comprises an aptamer. In some embodiments, the test compound comprises a protein or peptide. In some embodiments, the test compound comprises an antibody or an antigen-binding antibody fragment, e.g., a F(ab')2 fragment, a Fab fragment, a Fab' fragment, or an scFv fragment. In some embodiments, the antibody is a single domain antibody. In some embodiments, the compound comprises a ligand- or receptor-binding protein. In some embodiments, the compound comprises a gene therapy vector.

In some embodiments, more primary tumor cell spheroids are cultured in the presence of more than one compound, e.g., a first test compound and a second test compound, optionally a third test compound, fourth compound, etc.

In some embodiments, a test compound is an anti-cancer compound. In some

embodiments a test compound is a chemotherapeutic compound, an immunomodulatory compound, or radiation.

Exemplary chemotherapeutic compounds include asparaginase, busulfan, carboplatin, cisplatin, daunorubicin, doxorubicin, fluorouracil, gemcitabine, hydroxyurea, methotrexate, paclitaxel, rituximab, vinblastine, vincristine, etc. In some embodiments, a test compound is a vinca alkaloid, e.g., vinblastine, vincristine, vindesine, vinorelbine. In some embodiments, a test compound is an alkylating compound, e.g., cyclophosphamide, decarbazine, melphalan, ifosfamide, temozolomide. In some embodiments, a test compound is an antimetabolite, e.g., folic acid antagonists, pyrimidine analogs, purine analogs or adenosine deaminase inhibitor, e.g., fludarabine. In some embodiments, a test compound is an mTOR inhibitor. In some embodiments, a test compound is a proteasome inhibitor, e.g., aclacinomycin A, gliotoxin or bortezomib.

In some embodiments, a test compound is a small molecule inhibitor, e.g., a TBK1 inhibitor, a MEK inhibitor, a FAK inhibitor, a BRD/BET inhibitor, a CDK 4/6 inhibitor, an HDAC inhibitor, a DNMT inhibitor (or hypomethylating compound), a MET inhibitor, an EGFR inhibitor, or a BRAF inhibitor. In some embodiments, a test compound is a kinase inhibitor, e.g., a TBK1 inhibitor, a MEK inhibitor, a FAK inhibitor, or a CDK 4/6 inhibitor. For example, TBK-1 inhibitors are known in the art, e.g., Yu, T., et al. "TBK1 inhibitors: a review of patent literature (2011 - 2014)" Exp. Opin. On Ther. Patents 25(12); Hasan, M., et al. J. Immunol. 195(10):4573-77; and US20150344473, the contents of each of which are incorporated herein by reference.

Exemplary immunomodulatory compounds include immune activating compounds or inhibitors of an immune checkpoint protein selected from the group consisting of: CTLA-4, PD- 1, PD-L1, TIM3, LAG3, B7-H3 (CD276), B7-H4, 4-1BB (CD137 ), OX40, ICOS, CD27, CD28, PD-L2, CD80, CD86, B7RP1, HVEM, BTLA, CD137L, OX40L, CD70, CD40, CD40L, GAL9, A2aR, and VISTA. In some embodiments, the immune checkpoint inhibitor is a peptide, antibody, interfering RNA, or small molecule. In some embodiments, the immune checkpoint inhibitor, e.g., inhibitor, is a monoclonal antibody, or an Ig fusion protein. In some

embodiments, the immune checkpoint inhibitor is an antibody or an antigen binding fragment thereof. In some embodiments, the immune checkpoint inhibitor is an anti-PD-1 antibody.

In some embodiments, the immune checkpoint inhibitor inhibits PD1. In humans, programmed cell death protein 1 (PD-1) is encoded by the PDCD1 gene. PDCD1 has also been designated as CD279 (cluster of differentiation 279). This gene encodes a cell surface membrane protein of the immunoglobulin superfamily. PD-1 is a 288 amino acid cell surface protein molecule. PD-1 has two ligands, PDLl and PD-L2, which are members of the B7 family. PD-1 is expressed on the surface of activated T cells, B cells, and macrophages. PD-1 is expressed in pro-B cells and is thought to play a role in their differentiation. See T. Shinohara 5 et al., Genomics 23 (3): 704-6 (1995). PD-1 is a member of the extended CD28/CTLA-4 family of T cell regulators. (Y. Ishida et al., "EMBO J. 11 (11): 3887-95, (1992)). PD-1 may negatively regulate immune responses. PD1 limits autoimmunity and the activity of T cells in peripheral tissues at the time of an inflammatory response to infection. An immune checkpoint inhibitor that inhibits PD-1, or a PD-1 antagonist, as used herein is a molecule that binds to PD-1 and inhibits or prevents PD-1 activation. Without wishing to be bound by theory, it is believed that such molecules block the interaction of PD-1 with its ligand(s) PD-L1 and/or PD-L2.

PD-1 activity may be interfered with by antibodies that bind selectively to and block the activity of PD-1. The activity of PD-1 can also be inhibited or blocked by molecules other than antibodies that bind PD-1. Such molecules can be small molecules or can be peptide mimetics of PD-L1 and PD-L2 that bind PD-1 but do not activate PD-1. Molecules that antagonize PD-1 activity include those described in U.S. Publications 20130280265, 20130237580, 20130230514, 20130109843, 20130108651, 20130017199, and 20120251537, 2011/0271358, EP 2170959B 1, the entire disclosures of which are incorporated herein by reference. See also M. A. Curran, et al., Proc. Natl. Acad. Sci. USA 107, 4275 (2010); S. L. Topalian, et al., New Engl. J. Med. 366, 2443 (2012); J. R. Brahmer, et al., New Engl. J. Med. 366, 2455 (2012); and D.E. Dolan et al., Cancer Control 21, 3 (2014). Herein, PD-1 antagonists include: nivolumab, also known as BMS- 936558 (Bristol-Meyers Squibb, and also known as MDX-1106 or ONO-4538), a fully human IgG4 monoclonal antibody against PD-1; pidilizumab, also known as CT-011 (CureTech), a humanized IgGl monoclonal antibody that binds PD-1; MK-3475 (Merck, and also known as SCH 900475), an anti-PD-1 antibody; and pembrolizumab (Merck, also known as MK-3475, lambrolizumab, or Keytruda), a humanized IgG4-kappa monoclonal antibody with activity against PD-1. Compounds that interfere bind to the DNA or mRNA encoding PD-1 also can act as PD-1 inhibitors. Examples include a small inhibitory anti-PD-1 RNAi, an anti-PD-1 antisense RNA, or a dominant negative protein. PD-L2 fusion protein AMP-224 (codeveloped by Glaxo Smith Kline and Amplimmune) is believed to bind to and block PD-1.

In some embodiments, the immune checkpoint inhibitor inhibits PD-L1. In humans, programmed death-ligand 1 (PD-L1), also known as B7 homolog 1 (B7-H1) or cluster of differentiation 274 (CD274), is a 40kDa type 1 transmembrane protein that is encoded by the CD274 gene. Foreign antigens normally induce an immune response triggering proliferation of antigen-specific T cells, such as antigen- specific CD8+ T cells. PD-L1 is an immune checkpoint inhibitor that may block or lower such an immune response. PD-L1 may play a major role in suppressing the immune system during events such as pregnancy, tissue allografts, autoimmune disease, and other disease states, such as hepatitis and cancer. The PD-L1 ligand binds to its receptor, PD-1, found on activated T cells, B cells, and myeloid cells, thereby modulating activation or inhibition. In addition to PD-1, PD-L1 also has an affinity for the costimulatory molecule CD80 (B7-1). Upon IFN-γ stimulation, PDL1 is expressed on T cells, natural killer (NK) cells, macrophages, myeloid dendritic cells (DCs), B cells, epithelial cells, and vascular endothelial cells.

PD-L1 activity may be blocked by molecules that selectively bind to and block the activity of PD-L1. Anti-PD-Ll antibodies block interactions between PD-L1 and both PD-1 and B7-1 (also known as CD80). Block means inhibit or prevent the transmission of an inhibitory signal mediated via PD-L1. PD-L1 antagonists include, for example: BMS-30 936559, also known as MDX-1105 (Bristol-Meyers Squibb), a fully human, high affinity, immunoglobulin (Ig) G4 monoclonal antibody to PD-L1; MPDL3280A, also known as RG7446 or atezolizumab (Genentech/Roche), an engineered human monoclonal antibody targeting PDL1;

MSB0010718C, also known as avelumab (Merck), a fully human IgGl monoclonal antibody that binds to PD-L1; and MEDI473 (AstraZeneca/Medlmmune), a human immunoglobulin (Ig) G1K monoclonal antibody that blocks PD-L1 binding to its 5 receptors. Compounds that bind to the DNA or mRNA encoding PD-L1 also can act as PD-L1 inhibitors, e.g., small inhibitory anti- PDL1 RNAi, small inhibitory anti-PD-Ll RNA, anti-PD-Ll antisense RNA, or dominant negative PD-L1 protein. Antagonists of or compounds that antagonize PD-L1, e.g., anti-PD-Ll antibodies and PD-L1 antagonists, may include, but are not limited to those previously mentioned and any of those that are disclosed in Stewart et al., 2015, 3(9): 1052-62; Herbst et al., 2014, Nature 515:563-567; Brahmer et al., N Engl J Med 2012; 366:2455-2465; US8168179; US20150320859; and/or US20130309250, all incorporated herein by reference.

In some embodiments, the immune checkpoint inhibitor inhibits CTLA-4. CTLA-4 (also known as CTLA-4 or cluster of differentiation 152 (CD 152)), is a transmembrane glycoprotein that, in humans, is encoded by the CTLA-4 gene. CTLA-5 4 is a member of the immunoglobulin superfamily, which is expressed on the surface of helper T cells and is present in regulatory T cells, where it may be important for immune function. CTLA-4, like the homologous CD28, binds to B7 molecules, particularly CD80/B7-1 and CD86/B7-2 on antigen-presenting cells (APCs), thereby sending an inhibitory signal to T cells. CTLA-4 functions as an immune checkpoint that inhibits the immune system and is important for maintenance of immune tolerance. CTLA-4 activity may be blocked by molecules that bind selectively to and block the activity of CTLA-4 or that bind selectively to its counter-receptors, e.g., CD80, CD86, etc. and block activity of CTLA-4. Blocking means inhibit or prevent the transmission of an inhibitory signal via CTLA-4. CTLA-4 antagonists include, for example, inhibitory antibodies directed to CD80, CD86, and/or CTLA-4; small molecule inhibitors of CD80, CD86, and CTLA-4;

antisense molecules directed against CD80, CD86, and/or CTLA-4; adnectins directed against CD80, CD86, and/or CTLA-4; and RNAi inhibitors (both single and double stranded) of CD80, CD86, and/or CTLA-4.

Suitable CTLA-4 antagonists and/or anti-CTLA-4 antibodies include humanized anti- CTLA-4 antibodies, such as MDX-010/ipilimumab (Bristol-Meyers Squibb), tremelimumab/CP- 675,206 (Pfizer; AstraZeneca), and antibodies that are disclosed in PCT Publication No. WO 2001/014424, PCT Publication No. WO 2004/035607, U.S. Publication No. 2005/0201994, European Patent No. EP 1212422 B l, U.S. Pat. Nos. 5,811,097, 5,855,887, 6,051,227,

6,984,720, 7,034,121, 8,475,790, U.S. Publication Nos. 2002/0039581 and/or 2002/086014, the entire disclosures of which are incorporated herein by reference. Other anti-CTLA-4 antibodies and/or CTLA-4 antagonists that can be used in a method of the present disclosure include, for example, those disclosed in Hurwitz et al., Proc. Natl. Acad. Sci. USA, 95(17): 10067-10071 (1998); Camacho et al., J. Clin. Oncology, 22(145): Abstract No. 2505 (2004) (antibody

CP9675206); Mokyr et al., Cancer Res., 58:5301-5304 (1998), and Lipson and Drake, Clin Cancer Res; 17(22) November 15, 2011; US8318916; and/or EP1212422B 1, all of which are herein incorporated by reference, in their entireties.

In some embodiments, the immune checkpoint inhibitor inhibits VISTA. V-domain Ig suppressor of T cell activation (VISTA), (also known as PD-H1, PD-1 homolog, or Diesl), is a negative regulator of T cell function. VISTA is a 309 aa type I transmembrane protein that is composed of seven exons, it has one Ig-V like domain, and its sequence is similar to the Ig-V domains of members of CD28 and B7 families. VISTA is highly expressed in the tumor microenvironment (TME) and on hematopoietic cells. It is also expressed on macrophages, dendritic cells, neutrophils, natural killer cells, and naive and activated T cells. Its expression is highly regulated on myeloid antigen-presenting cells (APCs) and T cells, while lower levels are found on CD4+ T cells, CD8+ T cells, and Treg cells. VISTA shows some sequence homology to the PD-1 ligand, PD-L1, however the two immune checkpoint inhibitors are structurally different and have different signaling pathways. VISTA blockade has been shown to enhance antitumor immune responses in mice, while in humans, blockade of the related PD-1 pathway has shown great potential in clinical immunotherapy trials. VISTA is a negative checkpoint regulator that suppresses T-cell activation and its blockade may be an efficacious

immunotherapeutic strategy for human cancer. VISTA (Wang et al., 2011. JEM. 208(3):577-92.; Lines et al., 2014. Cancer Res. 74(7): 1924-32.; Kondo et al. 2015. J. of Immuno.V194.;

WO2011120013; US20140105912; US20140220012; US20130177557, US20130177557, incorporated by reference herein, in their entireties).

VISTA activity may be blocked by molecules that selectively bind to and block the activity of VISTA. Molecules or compounds that are VISTA antagonists include peptides that bind VISTA, antisense molecules directed against VISTA, single- or doublestranded RNAi molecules targeted to degrade or inhibit VISTA, small molecule inhibitors of VISTA, anti- VISTA antibodies, inhibitory antibodies directed to VISTA, and humanized antibodies that selectively bind and inhibit VISTA. Antagonists of or compounds that antagonize VISTA, e.g., anti- VISTA antibodies and VISTA antagonists, are not limited to, but may include any of those that are disclosed in Liu et al. 2015. PNAS. 112(21):6682-6687; Wang et al., 2011. JEM.

208(3):577-92; Lines et al., 2014. Cancer Res. 74(7): 1924-32; Kondo et al. 2015. J. of

Immuno.V194; WO2015097536, EP2552947, WO2011120013, US20140056892, US8236304, WO2014039983, US20140105912, US20140220012, US20130177557; WO2015191881;

US20140341920; CN105246507; and/or US20130177557, all of which are incorporated by reference herein, in their entireties.

In some embodiments, the immune checkpoint inhibitor inhibits TIM-3. In some embodiments, the immune checkpoint inhibitor inhibits LAG- 3.

In some embodiments, a combination of test compounds are tested in the cell culture. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a CTLA-4 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD1 inhibitor and a TIM-3 inhibitor. In some embodiments, the

combination of immune checkpoint inhibitors includes a PD1 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-Ll inhibitor and a CTLA-4 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-Ll inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PD-L1 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor and a LAG-3 inhibitor. In some

embodiments, the combination of immune checkpoint inhibitors includes a TIM-3 inhibitor and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PDl inhibitor , a CTLA-4 inhibitor, and a TIM-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PDl inhibitor, a CTLA-4 inhibitor , and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a PDl inhibitor, a TIM-3 inhibitor, and a LAG-3 inhibitor. In some embodiments, the combination of immune checkpoint inhibitors includes a CTLA-4 inhibitor, a TIM-3 inhibitor , and a LAG-3 inhibitor.

In some embodiments, the combination of test compounds includes an immune checkpoint inhibitor and a small molecule compound. In some embodiments, the combination of test compounds includes an immune checkpoint inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a PD-1 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a PD-L1 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a CTLA-4 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a VISTA inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a TIM-3 inhibitor and a TBK-1 inhibitor. In some embodiments, the combination of test compounds includes a LAG-3 inhibitor and a TBK-1 inhibitor.

In some embodiments, an immune activating compound is a CD28 antagonist, e.g., an anti-CD28 antibody. An antibody, or immunoglobulin, is a glycoprotein containing two identical light chains (L chains), each containing approximately 200 amino acids, and two identical heavy chains (H chains), which generally are at least twice as long as the L chains. The paratope of the antibody is specific for a particular epitope of an antigen, and their spacial complementarity (binding) "tags" the microbe for further action or neutralize its actions directly. The antibody communicates with other components of the immune response via its crystallizable fragment (Fc) region, which includes a conserved glycosylation site. There are five Fc regions, resulting in the five different antibody isotypes: IgA, IgD, IgE, IgG, and IgM. IgD functions as an antigen receptor on B cells that have not been exposed to antigens, and activates basophils and mast cells, resulting in the production of antimicrobial factors. IgG, expressed in four forms, provides the majority of antibody-based immunity against invading pathogens. IgM is expressed on the surface of B cells as a monomer, and in a secreted form as a pentamer. It eliminates pathogens during the early phases of humoral (B cell-mediated) immunity before there 5 are sufficient levels of IgG. IgG is often used in immunotherapy.

The term antibody is used in the broadest sense and specifically includes, for example, single monoclonal antibodies, antibody compositions with polyepitopic specificity, single chain antibodies, and antigen-binding fragments of antibodies. An antibody may include an

immunoglobulin constant domain from any immunoglobulin, such as IgGl, IgG2, IgG3, or IgG4 subtypes, IgA (including IgAl and IgA2), IgE, IgD or IgM.

A fluorescence light source provides an excitation wavelength to excite a fluorophore. A fluorescent light source can be used in connection with a photosensitive detector capable of detecting total fluorescence emitted by the excited fluorophore to generate an image. A fluorescence microscope can be configured to include a fluorescence light source and a photosensitive detector. Fluorescence microscopes are available in the art and are commercially available. A skilled artisan would be able to select a microscope with appropriate capabilities for the desired imaging and/or analysis.

Fluorescence microscopes are available in upright or inverted configurations, either of which are suitable for use with the provided methods. In an upright microscope configuration, the objective and photosensitive detector, e.g., camera, is disposed above the stage, pointing down. Exemplary upright fluorescent microscopes include, but are not limited to, Nikon Eclipse 80i Fluorescent Microscope. In an inverted microscope configuration, the light source is disposed above the stage pointing down, and the objective is disposed below the stage pointing up.

In some embodiments, a fluorescence microscope is an epifluorescence microscope, in which light of the appropriate excitation wavelength is passed through the objective lens onto the sample to be examined. In some such embodiments, fluorescence is emitted from the sample through the same objective lens through which the light initially passed, and is then detected via a photosensitive detector, e.g., a camera. In some instances, a dichroic beam splitter may be used to filter the emitted fluorescence by permitting fluorescence of a particular wavelength to pass through, while reflecting the remaining fluorescence, to increase the signal-to-noise ratio. In some embodiments, a fluorescence microscope is a confocal microscope. Confocal microscopes can be used, for example, to generate three dimensional structures from a series of optical section images. In some embodiments, a fluorescence microscope is a total internal reflection fluorescence microscope.

In some embodiments, the fluorescence microscope is configured to permit measurement of emission of fluorescence from two or more distinct fluorophore dyes at distinct wavelengths. For example, in some embodiments, the fluorescence microscope contains a filter arrangement that allows separation of the fluorescence emitted by the two or more distinct fluorophore dyes.

In some embodiments, the microscope is configured to permit measurement of multiple capture images of the same microfluidic device by moving the stage on which the microfluidic device is disposed. In some embodiments, the stage is a motorized stage. Motorized stages are known in the art and are commercially available. In some embodiments, the stage is configured to move one dimensionally, e.g., to move in the x-axis. In some embodiments, the stage is configured to move two dimensionally, e.g., to move in the x- and y-axes. In some

embodiments, the stage is configured not to move in three dimensions, e.g., to not move in the z- axis. In some such embodiments, the focal plane of the tumor cell spheroids in the three- dimensional microfluidic device remains the same throughout the fluorescence detection.

In some embodiments, a three dimensional analysis of the tumor cell spheroids is performed. For example, in some embodiments, the stage is configured to move in three dimensions, e.g., moves in x-, y-, and z-axes. In such embodiments, images of multiple sections (e.g., focal planes) can be obtained to generate a Z stack using microscopes, photosensitive detectors, and software available in the art. For example, commercially available ProScan controller and TTL Breakout Box (Prior Scientific, Rockland, MA) can be used to control a CCD camera for Z-stack image acquisition.

The overall resolution of the fluorescence emission detection depends on the

magnification of the objective lens through which the detectable signal passes, and/or the magnification of the photosensitive detection device, e.g., camera. In some embodiments, the magnification of the objective lens is at least 2X, at least 3X, at least 4X, at least 10X, at least 40X, at least 100X, or more. In some embodiments, the magnification of the photosensitive detection device, e.g., camera, is OX. In some embodiments, the magnification of the photosensitive detection device, e.g., camera, is at least 2X, at least 3X, at least 4X, at least 10X, or more. In some embodiments, the overall resolution of the fluorescence detection is at least 2X, at least 3X, at least 4X, at least 10X, at least 40X, at least 100X, at least 400X, at least 1000X, or more. In some embodiments, the resolution at which the fluorescence is detected is such that the entire field of the three dimensional device containing the tumor cell spheroids can be imaged without adjusting the focal plane.

Images of the fluorescence emitted by the fluorophore dyes are detected and/or captured using a photosensitive detector. Photosensitive detectors capable of detecting total fluorescence are known in the art and commercially available. In some embodiments, a photosensitive detector is a camera or a photodiode. In some embodiments, the camera is a CCD camera. Exemplary cameras include, but are not limited to CoolSNAP CCD Camera (Roper Scientific). In some embodiments, the photodiode is an avalanche photodiode.

Images can be acquired by the photosensitive detector and analyzed, e.g., using commercially available software. Exemplary image capture and analysis software includes, but is not limited to NIS-Elements AR software package (Nikon). In some embodiments, multiple images of a microfluidic device are captured by the detector and stitched together. Images may be deconvoluted using available programs such as AutoQuant (Media Cybernetics).

The present invention is further illustrated by the following Examples, which in no way should be construed as further limiting. The entire contents of all of the references (including literature references, issued patents, published patent applications, and co pending patent applications) cited throughout this application are hereby expressly incorporated by reference.

EXAMPLES

Example 1. Materials and methods for ex vivo profiling

Patient Samples.

A cohort of patients (Tables S l-1 and S l-2) treated at Massachusetts General Hospital and Dana-Farber Cancer Institute was assembled for PDOTS profiling and culture between August 2015 and August 2016. Informed consent was obtained from all subjects. Tumor samples were collected and analyzed according to Dana-Farber/Harvard Cancer Center IRB- approved protocols. These studies were conducted according to the Declaration of Helsinki and approved by the MGH and DFCI IRBs. De-identified archival matched plasma and tissue samples from the MGH Melanoma Tissue Bank were obtained from patients pre- or on-treatment with anti-PD-1 therapy as indicated. Mutational analysis performed on clinically validated next- generation sequencing (NGS) platforms at MGH and DFCI. Clinical benefit (CB) to PD-1 was defined as absence of disease, decrease in tumor volume (radiographic or clinical), or stable disease, whereas patients with no clinical benefit (NCB) included patients with mixed response, progression on treatment, and primary non-responders.

(cutaneous)

MGH-19 24/F Adreno-cortical II N/A

carcinoma

DFCI-01 73/F Melanoma III Not tested

(cutaneous)

DFCI-02 (#) 81/M Melanoma IV CDKN2A (Q50*)

(cutaneous)

DFCI-04 72/F Mesothelioma IV 9p del, polysomy

22

DFCI-06 42/F Merkel cell IV BRCA2 (F439V) carcinoma

DFCI-07 58/M NSCLC/lung IV KRAS/ LKB1 adeno-carcinoma

DFCI-09 45/M Pancreatic IIB KRAS ^G12D , TP53 adenocarcinoma

DFCI-10 ( ^A ) 55/M Thyroid cancer IV TP53, MSH2,

(Hurthle cell) PTEN

DFCI-12 58/F Head/neck IV Unknown

squamous cell

carcinoma

DFCI-13 (*) 76/M Thyroid cancer IV Unknown

(papillary)

DFCI-15 75/F Thyroid cancer IV

(papillary)

DFCI-16 (*) 76/M Thyroid cancer IV Unknown

(papillary)

DFCI-17 (#) 81/M Melanoma IV CDKN2A (Q50*)

(cutaneous)

DFCI-18 (*) 76/M Thyroid cancer IV Unknown

(papillary)

DFCI-19 67/M Pancreatic IIA Unknown

adenocarcinoma

DFCI-20 51/M Thyroid cancer IV None identified

(papillary)

DFCI-21 (*) 76/M Thyroid cancer IV Unknown

(papillary)

DFCI-22 (*) 76/M Thyroid cancer IV Unknown

(papillary)

DFCI-24 79/M Small cell lung IV Unknown

cancer

DFCI-25 68/M Melanoma IV NRAS ^Q61 ,

(cutaneous) CDKN2A (Q50*)

DFCI-27 72/M Melanoma IV BRAF ^WT

(cutaneous)

DFCI-29 ( ^A ) 55/M Thyroid cancer IV TP53, MSH2,

(Hurthle cell) PTEN

DFCI-30 52/M Merkel cell IV Unknown

carcinoma

DFCI-31 67/M Merkel cell IV Unknown carcinoma

DFCI-32 89/M Merkel cell Illb Unknown carcinoma

DFCI-33 49/M Thyroid cancer IV Unknown

(differentiated)

(*)DFCI-13, 16, 18, 21, 22 represent serial pleural effusion samples from same patient.

(**) MGH-04 and MGH-07 are serial biopsies from the same patient.

(#) DFCI-02 and -17 are samples from same patient.

( ^Λ ) DFCI-10 and DFCI-29 are samples from the same patient.

(□) MGH-12 and MGH-14 are serial samples from a patient with a brain metastasis requiring resection and subsequent re -resection.

pleurectom

everolimus DFCI-30 carboplatin- Response Alive; on etoposide,

None Lymph node ocPD

radiation -1 treatment (recurrence)

DFCI-31 carboplatin- Subcutaneo Stable Alive; on

None ocPD-1

etoposide us Disease treatment

DFCI-32 N/A Alive; on

None None Primary Radiation

treatment

DFCI-33 Radioactive Pleural N/A Alive; on

None lenvatinib

iodine effusion treatment

(*)DFCI-13, 16, 18, 21, 22 represent serial pleural effusion samples from same patient.

(**) MGH-04 and MGH-07 are serial biopsies from the same patient.

(#) DFCI-02 and -17 are samples from same patient.

( ^Λ ) DFCI-10 and DFCI-29 are samples from the same patient.

(□) MGH-12 and MGH-14 are serial samples from a patient with a brain metastasis requiring resection and subsequent re -resection.

AE = adverse event.

irAE = immune -related adverse event.

MR = mixed response.

PD = progressive disease

Syngeneic Murine Models.

All animal experiments were performed in compliance with established ethical regulations and were approved by the Dana-Farber Animal Care and Use Committee. MC38 murine colon adenocarcinoma cells were generously provided by Dr. Gordon Freeman (DFCI) received under an MTA from Dr. Jeffrey Schlom of NCI (Bethesda, MD). B 16F10 melanoma cells, CT26 colon carcinoma cells, and EMT6 breast mammary carcinoma cells were obtained from ATCC. Cells were expanded, tested free for mycoplasma and mouse pathogens. Thawed cells were cultured for up to three passages in DMEM (MC38, B 16F10) or RPMI 1640 (CT26) supplemented with 10% heat-inactivated FBS at 37 °C in a humidified incubator maintained at 5% C0 ₂ . Cell counts were performed prior to implantation by both hemocytometer & Invitrogen Countess Cell Counter. MC38 colon carcinoma cells, CT26 colon carcinoma cells, and B 16F10 melanoma cells (5 x 10 ⁵ cells/mouse in 100 μί), re-suspended in sterile PBS (Ca ⁺ , Mg ⁺ free), were injected into 8 week old female C57BL/6 albino mice or Balb/c (Jackson) and tumors were collected 2-3 weeks post- implantation or on reaching 2000 mm in size (or if there were any humane reason, including decreased BW >15% for 1 week or moribund) and MDOTS were prepared as described below. Implantation of CT26 colon carcinoma cells was performed using BALB/c mice in identical fashion. For in vivo treatment studies, mice were randomized (using the deterministic method) and then injected with 10 mg/kg isotype control IgG (clone 2A3, BioXCell) or rat- anti-mouse PD-1 (clone RMPl-14, BioXCell) every 3 days x 8 doses and tumor volume was measured as shown. Investigators were not blinded to treatment groups. Tumor volume (TV) was monitored on a weekly basis after the initial tumor volume is about 100mm . TV was measured twice weekly during the exponential tumor growth phase, and body weight was monitored on a weekly basis after implantation.

Spheroid Preparation and Microfluidic Culture.

Fresh tumor specimens (murine and human patients) were received in media (DMEM) on ice and minced in a 10 cm dish (on ice) using sterile forceps and scalpel. Minced tumor was resuspended in DMEM (4.5 mM glucose, 100 mM sodium pyruvate, 1: 100 penicillin- streptomycin) (Corning CellGro, Manassas, VA) +10% FBS (Gemini Bio-Products, West Sacramento, CA), 100 U/mL collagenase type IV (Life Technologies, Carlsbad, CA), and 15 mM HEPES (Life Technologies, Carlsbad, CA), except for CT26 tumors that were prepared in RPMI. Samples were pelleted and resuspended in 10-20 mL media. Red blood cells were removed from visibly bloody samples using RBC Lysis Buffer (Boston Bio-Products, Ashland, MA). Samples were pelleted and then resuspended in fresh DMEM +10% FBS and strained over 100 μιη filter and 40 μιη filters to generate S I (>100 μη), S2 (40-100 μιη), and S3 (<40 μη) spheroid fractions, which were subsequently maintained in ultra low-attachment tissue culture plates. S2 fractions were used for ex vivo culture. An aliquot of the S2 fraction was pelleted and resuspended in type I rat tail collagen (Corning, Corning, NY) at a concentration of 2.5 mg/mL following addition of 1 Ox PBS with phenol red with pH adjusted using NaOH (pH 7.0-7.5 confirmed using PANPEHA Whatman paper (Sigma-Aldrich, St. Louis, MO)). The spheroid- collagen mixture was then injected into the center gel region of the 3D microfluidic culture device. Collagen hydrogels containing PDOTS/MDOTS were hydrated with media with or without indicated therapeutic monoclonal antibodies after 30 minutes at 37 °C. MDOTS were treated with isotype control IgG (10 μg/mL, clone 2A3) or anti-PD-1 (0.1, 1.0, 10 μg/mL, clone RMPl-14). Monoclonal rat-anti-mouse-CCL2 (5 μg/mL, clone 123616, R&D Systems) was used for CCL2 neutralization in MDOTS. PDOTS were treated with anti-PD-1 (pembrolizumab, 250 μg/mL), anti-CTLA-4 (ipilimumab, 50 μg/mL), or combination (250 μg/mL pembrolizumab + 50 μg/mL ipilimumab). Doses were selected (1: 100 dilutions of stock concentrations used clinically) to correspond to reported peak plasma concentrations of each drug following administration of 10 mg/kg (FDA CDER application). In select experiments, PDOTS were treated with InVivoMAb human IgG isotype control (BioXCell). For spheroid cultures lacking immune cells, MC38 or CT26 cells (1 x 10 ⁶ ) were seeded in low attachment conditions for 24 hours and were filtered (as above). The S2 fraction was pelleted and resuspended in collagen (as above) prior to microfluidic culture.

Flow Cytometric Immune Profiling of Murine Tumors and MOOTS.

Tumors from MC38 and B 16F10 syngeneic murine models were procured as described above. Cells were incubated for 20 minutes in the dark at room temperature using the Zombie NIR Fixable Viability Kit (Biolegend, 423105) at a dilution of 1 :500 in PBS . FcR were blocked by incubation with the anti-mouse CD16/CD32 clone 2.4G2 blocking Ab (Fisher Scientific) for 15 minutes at 4 °C at a 1: 100 dilution in flow cytometry staining buffer (PBS + 5% FBS). Cell surface staining was performed by incubation for 20 minutes at 4 °C using the following Abs diluted in flow cytometry staining buffer (total staining volume of 100 uL): Lymphocyte Staining Panel - CD45 AF488 (BioLegend 103122), CD25 PE (BioLegend 101904), CD19 PE- Dazzle (115554), CD49b PE-Cy7 (BioLegend, 108922), CD3 BV421 (BioLegend , 100228), CD8 BV510 (BioLegend 100752), CD4 BV786 (Fisher Scientific # BDB563331); Myeloid Staining Panel - F4/80 AF488 (BioLegend # 123120), MHCII PE (BioLegend # 107608), CDl lc BV421 (BioLegend # 117330), Ly6G BV510 (BioLegend # 127633), CDl lb BV650

(BioLegend # 101239), Ly6C BV711 (BioLegend # 128037), CD45 BV786 (Fisher Scientific # BDB564225), CD19 APC-Cy7 (BioLegend # 115530), and CD49b APC-Cy7 (BioLegend # 108920) were included with the myeloid staining panel to be used as a dump channel along with the dead cells as determined by the Zombie NIR viability stain. After cell surface staining, cells were fixed by incubating in 200 μΐ _^ IC Fixation Buffer (eBioscience # 00-8222-49) for 10 minutes at room temperature. Cells were washed and resuspended in flow cytometry staining buffer and read the following day on a BD LSR Fortessa flow cytometer. Data were analyzed using FlowJo software version 10.0.8.

Flow Cytometric Immune Profiling of PDOTS and Human Tumor Samples.

Cells were incubated with Live/Dead Fixable Yellow Dead Cell Stain Kit (Life

Technologies, Carlsbad, CA) for 8 minutes in the dark at room temperature or Live/Dead Fixable Zombie NIRTM (Biolegend, San Diego, CA) for 5 minutes in the dark at room temperature in FACS buffer (PBS +2% FBS) at a ratio of 250 μΐ. L/D IX dilution per 100 mg of original sample weight. Surface marker and intracellular staining were performed according to the manufacturer's protocol (eBioscience, San Diego, CA). FcR were blocked prior to surface antibody staining using Human FcR Blocking Reagent (Miltenyi, San Diego, CA). Cells were fixed in 1% PBS +2% FBS and washed prior to analysis on a BD LSRFortessa with FACSDiva software (BD Biosciences, San Jose, CA). Data were analyzed using FlowJo (Ashland, OR) software version 10.0.8. Cell viability was determined by negative live/dead staining.

Antibodies were specific for the following human markers: CD3 (HIT3a; UCHT1), CD8 (RPA- T8), CD14 (M5E2; MphiP9), CD45 (HI30), CD56 (B 159), CCR7 (150503), EpCAM (EBA-1), HLA-DR (G46-6), PD-1 (EH12.1), and IgGl isotype control (MOPC-21) from BD Biosciences (San Jose, CA); CD3 (UCHT1), CD4 (RPA-T4), CD14 (M5E2), CD15 (W6D3), CD16 (3G8), CD19 (HIB 19), CD25 (BC96), CD33 (WM53), CD38 (HIT2), CD40L (24-31), CD45 (HI30), CD45RA (HI100), CD45RO (UCHL1), CD56 (HCD56; 5.1H11), CD66b (G10F5), CD69 (FN50), CD123 (6H6), CD163 (GHJ761), CTLA-4 (L3D10), CXCR5 (J252D4), EpCAM (9C4), Ki-67 (Ki-67), PD-1 (EH12.2H7), PD-Ll (29E.2A3), PD-L2 (24F.10C12), TIM-3 (F38-2E2), IgG2a isotype control (MOPC-173), IgG2b isotype control (MPC-11), and IgGl isotype control (MOPC-21) from BioLegend (San Diego, CA); Pan-cytokeratin (Cl l) and PD-Ll (E1L3N) from Cell Signaling Technologies (Danvers, MA); CD45 (2D1), FOXP3 (236A/E7), and IL-10 (236A/E7) from Affymetrix/eBioscience (San Diego, CA). Four-way flow sorting of immune cells (CD45+), tumor cells (CD45-CD31-CD90-), cancer-associated fibroblasts (CD45-CD31- CD90+), and endothelial cells (CD45-CD31+CD144+) was conducted on a BD Aria II SORP with gates set using single stain controls and manual compensation using the following antibodies: CD31-APC (Biolegend, 303115), CD45-BV711 Biolegend, 304050), CD90-PE/Cy7 (Biolegend, 328123), and CD144-PE (Biolegend, 348505). Cells were sorted into cold PBS and stored on ice before mRNA extraction using established techniques.

Microfluidic Device Design and Fabrication.

Microfluidic device design and fabrication was performed according to methods known in the art (e.g., Aref, A. R. et al., Integr. Biol. (Camb.) (2013), the content of which is incorporated herein by reference in entirety), with modifications of device dimensions to accommodate larger volumes of media. MDOTS were also evaluated using DAX-1 3D cell culture chip (AIM Biotech, Singapore), for select studies.

Live/Dead Staining.

Dual labeling was performed by loading microfluidic device with Nexcelom ViaStain™

AO/PI Staining Solution (Nexcelom, CS2-0106). Following incubation with the dyes (20 minutes at room temperature in the dark), images were captured on a Nikon Eclipse 80i fluorescence microscope equipped with Z-stack (Prior) and CoolSNAP CCD camera (Roper Scientific). Image capture and analysis was performed using NIS-Elements AR software package. Image deconvolution was done using AutoQuant Module. Whole device images were achieved by stitching in multiple captures. Live and dead cell quantitation was performed by measuring total cell area of each dye. Three different laboratories verified immune-mediated cell death of MC38 MDOTS following PD-1 blockade. To inhibit CD8+ T cell cytotoxicity, CT26 MDOTS were treated with 10 μg/mL anti-CD8a Ab (clone 53-6.72, BioXCell). Intertumoral and intratumoral heterogeneity experiments were performed using CT26 allografts as described above. MDOTS were prepared using separate pieces of a larger tumor alongside MDOTS prepared from a smaller allograft. MDOTS were processed, treated, and profiled as described above. Immunofluorescence for CD8+ T cells was performed as described below. Immunofluorescence and Time-Lapse Imaging.

For immunofluorescence studies, PDOTS and MDOTS were washed with PBS and blocked with FcR blocking reagent (PDOTS - Miltenyi, Cambridge, MA, MDOTS - BioLegend, San Diego, CA) for 30 minutes at room temperature. Directly conjugated antibodies for PDOTS were CD326 EpCAM-PE (clone 9C4), CD45-AlexaFluor-488 (HI30), CD8a-AlexaFluor488 (RPA-T8); for MDOTS - CD45-AlexaFluor488 or 647 (30-F11), CD8a-PE (53-6.7)

(BioLegend, San Diego, CA). Antibodies were diluted 1:50 in 10 ug/mL solution of Hoechst 33342 (Thermo Fisher Scientific, Waltham, MA) in PBS and loaded into microfluidic devices for 1-hour incubation at room temp in the dark. Spheroids were washed twice with PBS with 0.1% Tween20 followed by PBS. For viability assessment, microfluidic devices were loaded with 1: 1000 solution of calcein AM (Thermo Fisher Scientific, Waltham, MA) in PBS. Images were captured on a Nikon Eclipse 80i fluorescence microscope equipped with Z-stack (Prior) and CoolSNAP CCD camera (Roper Scientific). Image capture and analysis was performed using NIS-Elements AR software package. Brightfield time-lapse images were captured with a lOx NA 0.3 objective and cooled CCD camera (Orca R2, Hamamatsu) in a humidified, temperature-controlled chamber. Illumination was with a CoolLED pe-100 white light LED. Time lapse imaging of several fields of view over time was controlled by NISElements software of a Prior motorized stage along with the LED and camera.

Cytokine Profiling.

Two multiplex assays were performed utilizing a bead-based immunoassay approach, the Bio-Plex Pro™ Human Cytokine 40-plex Assay (Cat# 171 AK99MR2) and Bio-Plex Pro™ Mouse Cytokine Panel 1, 23-plex (Cat# M60009RDPD) on a Bio-plex 200 system (Cat# 171000201). MDOT/PDOT conditioned media concentration levels [pg/mL] of each protein were derived from 5-parameter curve fitting models. Fold changes relative to the MDOT/PDOT control were calculated and plotted as log2FC. Lower and upper limits of quantitation

(LLOQ/ULOQ) were imputed from standard curves for cytokines above or below detection. Conditioned media from PDOTS were assayed neat and plasma was diluted 1:4.

Tertiary Lymphoid Structure Evaluation.

Fifty-two sections stained with hematoxylin & eosin (H&E) of melanoma pre- and on- therapy with anti-PD-1 were evaluated independently by two dermatopathologists for the presence of tertiary lymphoid structures (TLS) at the periphery of these tumors. These are characterized by prominent lymphocytic infiltrate, sometimes with germinal center formation and with associated high endothelial venules, as shown in FIG. 10A. RNA-seq.

Freshly isolated patient tumor samples (from patients consented to DF/HCC protocol 11- 181) were snap frozen in liquid nitrogen and RNA was collected using the Qiagen RNeasy Mini kit. RNA libraries were prepared from 250 ng RNA per sample using standard Illumina protocols. RNA sequencing was performed at the Broad Institute (Illumina HiSeq2000) and the Wistar Institute (Illumina NextSeq 500). RNA samples were ribo-zero treated and then subjected to library prep using Epicentre's ScriptSeq Complete Gold kit. Quality check was done on the Bioanalyzer using the High Sensitivity DNA kit and quantification was carried out using KAPA Quantification kit. Raw RNA-Seq data (BAM files) read counts were summarized by featureCounts with parameters that only paired-ended, not chimeric and well mapped

(mapping quality >/= 20) reads are counted. Then normalization was applied to eliminate bias from sequencing depths and gene lengths by edgeR, thus RPKMs (Reads Per Kilobase of transcript per Million mapped reads).

Quantitative Real-Time PCR.

Analysis of expression levels of CCL19 and CXCL13 by quantitative reverse

transcription polymerase chain reaction (qRT-PCR) was performed using tissue samples obtained from patients with metastatic melanoma. Samples were selected from patients treated with anti-PD-1 therapy with available tissue pre- and on-treatment. All patients provided written consent to DF/HCC protocol 11-181 (Melanoma Tissue and Blood Collection). Tissue samples were snap frozen in liquid nitrogen and processed to yield RNA, which was stored at -80 °C after extraction. Normal lymph node tissue was used as a positive control for expression of CCL19 and CXCL13. Primers were designed for CXCL13 (Fwd: 5 '-GAGGC AGATGGAACTTGAGC- 3' (SEQ ID NO: 1), Rev: 5 '-CTGGGGATCTTCGAATGCTA-3 ' (SEQ ID NO: 2)) and CCL19 (Fwd: 5 '-CC AACTCTGAGTGGCACCAA-3 ' (SEQ ID NO: 3), Rev: 5'- TGAACACTACAGCAGGCACC-3 ' (SEQ ID NO: 4)), Total RNA was extracted via the QIAGEN RNeasy Mini Kit after being ground with the QIAGEN TissueRuptor. The extraction process was automated via the QIAGEN QIAcube. RNA was stored in 1.5 mL RNAse-free EP tubes and then quantified using the QIAGEN Qubit. cDNA was reverse-transcribed from RNA using the Invitrogen Superscript VILO kit run on an Applied Biosystems 2720 Thermo Cycler and then stored in 1.5 mL tubes in a -40 °C freezer until later use. For qPCR the samples were run in triplicate on a Roche LightCycler 96 using Bio-Rad's SsoAdvanced Universal SYBR Green Supermix in a total volume of 20 per well, β-tubulin (Fwd: 5'- CGC AGAAGAGGAGGAGGATT-3 ' (SEQ ID NO: 5), Rev: 5'-

GAGGAAAGGGGC AGTTGAGT-3 ' (SEQ ID NO: 6)) were employed to normalize the expression of target genes. Four runs were performed. RT-PCR was performed in triplicate and values averaged. Effect of PD-1 blockade depicted as log2 fold change in CCL19 or CXCL13 expression (normalized to β-tubulin) from on-treatment samples relative to pre-treatment samples. For analysis of CCL19/CXCL13 expression in sorted cell populations (FIG. 10H), qRT-PCR was performed according to methods known in the art (e.g., Zhu, Z. et al. Cancer Discov. (2014), the content of which is incorporated herein by reference in entirety) using the following primers: and CXCL13 (Fwd: 5 '-CTCTGCTTCTC ATGCTGCTG-3 ' (SEQ ID NO: 7), Rev: 5-TGAGGGTCCACAC ACAC AAT-3 ' (SEQ ID NO: 8)) and CCL19 (Fwd: 5'- ATCCCTGGGTACATCGTGAG-3 ' (SEQ ID NO: 9), Rev: 5'- GCTTCATCTTGGCTGAGGTC-3 ' (SEQ ID NO: 10)), using 36B4 (Fwd: 5'- CAGATTGGCTACCC AACTGTT-3 ' (SEQ ID NO: 11), Rev: 5'-

GGAAGGTGTAATCCGTCTCC AC-3 ' (SEQ ID NO: 12)) to normalize gene expression.

Immunohistochemistry.

Immunohistochemistry staining was performed on 4 μιη formalin-fixed paraffin- embedded sections. All procedures were done on the automated Ventana Discovery Ultra staining system. Sections were first deparaffinized using EZ prep solution and antigen retrieval was achieved using Cell Conditioning solution 1. Sections were blocked with Discovery

Inhibitor (all from Ventana). Sections were incubated with primary antibodies for 16 minutes for population markers and 12 hours for CXCL13 and CCL19, then washed and incubated with OmniMap anti-Mouse or anti-Rabbit conjugated with horseradish peroxidase (HRP) (Ventana, cat# 760-4310 and 760-4311) for an additional 16 minutes. Discovery Purple or OmiMAP DAB chromogen kits (cat# 760-229 or 760-159) was then applied to generate a color reaction. Slides were then counterstained with hematoxylin II followed by bluing reagent (Ventana, cat# 790- 2208 and cat# 760-2037). Primary antibodies used for staining were: anti-CCL19 (RD Systems, cat# MAB361-100; 1:200) and anti-CXCL13 (Abeam, cat# abl l2521; 1: 150), CD31 (Cell Marque, cat# 131M-94; 1:500); aSMA (Abeam, cat# ab5694; 1:400).

Source Data.

Data for differential CCL19 and CXCL13 gene expression analysis were obtained from published reports (e.g., Hugo, W. et al. Cell (2016), Chen, P. L. et al. Cancer Discov. (2016), Van Allen, E. M. et al. Science (2015), Cancer Genome Atlas, N. Cell (2015), the contents of each of which are incorporated herein by reference in entirety). For data from Hugo et al. and Van Allen et al., transcriptome sequencing data were aligned using TopHat and normalized gene expression, presented as transcripts per million (TPM), was quantified using DESeq2 (e.g., see Kim, D. et al. Genome Biol. (2013), and Love, M.I. et al. Genome Biol. (2014), the contents of each of which are incorporated herein by reference in entirety) (Table S3). NanoString source data (Chen et al.) for PD-1 responders (n=4) and non-responders (n=8) were compared (on-PD- 1/pre-PD-l) and expressed as log-2 fold change. For TCGA analysis, raw RNA-Seq data (BAM files) of TCGA SKCM samples was downloaded from Genomic Data Commons and read counts were summarized (featureCounts) and normalized using edgeR, to generate RPKMs. CCL19 and CXCL13, samples were separated into two groups by kmeans clustering of RPKM values: high group and low group, value of center of each group was used to label high or low. The survival curves were constructed according to Kaplan-Meier method on these two groups (high; n=206 and low; n=257) and survival was compared between groups using the logrank (Mantel- Cox) test (a=0.05). Four-way grouping was performed using median cutoff to define high and low expression. Single sample GSEA (ssGSEA) was performed using immune cell signatures according to methods known in the art (e.g., Bindea, G. et al. Immunity (2013), the content of which is incorporated herein by reference in entirety).

Synthesis of Compound 1, 5-(4-((4-(4-(oxetan-3-yl)piperazin-l-yl)phenyl)amino)-l,3,5- triazin-2- yl)-2-((tetrahydro-2H-pyran-4-yl)oxy)benzonitrile.

Step 1. To a solution of 2,4-dichloro-l,3,5-triazine (9.5 g, 63 mmol) in N,N- dimethylformamide (150 mL) at 0 °C (flushed with argon balloon) was added a solution of 4-(4- (oxetan-3-yl)piperazin-l-yl)aniline (14.1 g, 60.2 mmol) in N,N-dimethylformamide (100 mL) over 5 minutes via cannula and stirred in an ice-bath for 1 hour. A solution of 40%

Methanol/CH ₂ Cl ₂ (200 mL) was added to the reaction mixture and stirred at room temperature. After 1 hour, the solid formed were filtered and washed twice with diethyl ether. Solids were collected to provide the first lot of product. To the filtrate, diethyl ether (200 mL) was added and stirred overnight at room temperature. The solids were separated by filtration to provide a second lot of product. Both lots were combined to provide a total yield of 20 g (91%) of 4- chloro-N-(4-(4-(oxetan-3-yl)piperazin-l-yl)phenyl)-l,3,5-tri azin-2-amine which was used without purification. LCMS-ESf (m/z): calculated for Ci ₆ Hi ₉ ClN ₆ 0: 346.1; found: 347.1 (M+H). Step 2. To a mixture of 4-chloro-N-(4-(4-(oxetan-3-yl)piperazin- l-yl)phenyl)- l,3,5- triazin-2- amine (4.6 g, 13.2 mmol), 2-fluoro-5-(4,4,5,5-tetramethyl-l,3,2-dioxaborolan-2- yl)benzonitrile (3.5 g, 14.5 mmol), Pd(dppf)Ci ₂ CH ₂ Ci ₂ (1.2 g, 1.6 mmol) and potassium carbonate (3.6 g, 26.4 mmol) under argon was added a mixture of de-gassed solvents (1,2- dimethoxyethane (53 mL)/water (27 mL)) and sonicated until all solids went into solution (~5 minutes). The mixture was stirred under argon at 100 °C in a heating block for 1 hour. After cooling to room temperature, water (200 mL) was poured into the reaction mixture and the solids were filtered off and washed with diethyl ether (100 mL). The resulting dark brown solids were suspended in Acetonitrile (20 mL) and stirred at reflux (~2 minutes) and then stirred at room temperature for 2 hours. To this suspension di-ethyl ether (20 mL) was added and the mixture was stirred at room temperature overnight. Solids were taken by filtration to yield crude dark brown product. In 1 g batches, the crude product was suspended in Dichloromethane (150 mL) in a separatory funnel. To the suspension Trifluoroacetic acid was added until all solids had gone into solution. Water was added (150 mL) and mixture was shaken vigorously until black precipitates appeared. The black solids were filtered off. To the filtrate, a saturated aqueous solution of NaHC0 ₃ was added slowly to fully neutralize the mixture. No solids precipitated during this process. The organic phase was dried over MgS0 ₄ and evaporated under reduced pressure to yield a bright yellow material (Total yield 3.1 g, 55% yield). LCMS-ESr ^1" (m/z): calculated for C ₂ H ₂₂ FN ₇ 0: 431.1 ; found: 432.2 (M+H).

Step 3. To a solution of Tetrahydro-2H-pyran-4-ol (4.7 mL, 49 mmol) in THF (200 mL) at 0 °C, Potassium t-butoxide (3.8 g, 51 mmol) was added and the reaction mixture was allowed to warm to room temperature. After 30 minutes, solid 2-fluoro-5-[4-([4-[4-(oxetan-3- yl)piperazin- l-yl]phenyl]amino)- l,3,5-triazin-2-yl]benzonitrile (10 g, 23.2 mmol) was added and stirred overnight at 60 °C. The reaction mixture was then cooled to 0 °C with a water/ice bath and slowly diluted with water (1.2 L) over 30 minutes and stirred at room temperature for 45 minutes. The solids formed were filtered and dried to give 5-(4-((4-(4-(oxetan-3-yl)piperazin- l- yl)phenyl)amino)- l,3,5-triazin-2-yl)-2-((tetrahydro-2H-pyran-4-yl)oxy)benzoni trile as a yellow solid (10.6 g, 90% yield) LCMS-ESF (m/z): calculated for C ₂₈ H ₃ iN ₇ 0 ₃ : 513.3; found: 514.5 (M+H) 1H NMR (400 MHz, DMSO-d6) δ 10.23 (d, J = 19.4 Hz, 1H), 8.80 (s, 1H), 8.74 - 8.50 (m, 2H), 7.68 (br, 2H), 7.60 (d, J = 9.0 Hz, 1H), 7.11 (br, 2H), 4.99 (m, 1H), 4.91 - 4.74 (m, 4H), 4.52 (m, 1H), 3.91 (m, 2H), 3.59 (ddd, J = 11.6, 8.5, 3.0 Hz, 2H), 3.80 - 3.30 (m, 4H), 3.30 - 2.90 (m, 4H), 2.09 (m, 2H), 1.87 - 1.64 (m, 2H).

In vitro characterization of Compound 1.

Biochemical single point inhibition and IC ₅₀ concentrations for TBK1, ΙΚΚε (IKBKE), and off-target kinases were determined at ThermoFisher Scientific using SelectScreen Kinase Profiling Services (Madison, WI, USA) (Tables S4A and S4B-1-7). To determine cellular potency, the human colorectal cancer carcinoma cell line HCT116 (ATCC, Manassas, VA) was maintained in T175 flasks in complete RPMI medium; RPMI 1640 supplemented with 10% FBS, IX Penicillin- Streptomycin solution and IX MEM (non-essential amino acids). HCT116 cells were grown to 90-95% confluency in T175 flasks containing complete RPMI medium and transfected in bulk using Lipofectamine 2000 (Invitrogen, Carlsbad, CA) with 70 μg of ISG54- luciferase reporter plasmid (Elim Biopharmaceuticals Inc., Hayward, CA). The reporter plasmid contains a luciferase gene expression cassette under the transcriptional regulation of the promoter of the human interferon stimulated gene 54 (ISG54). Transfection of the cells was allowed to take place for 6 hours, after which the cells were harvested by treatment with 0.25% trypsin EDTA (Corning Inc., Corning, NY). Trypsinized cells were added to 384-well poly-d-lysine treated black clear bottom tissue culture assay plates (Greiner Bio-One GmbH, Kremsmiinster, Austria) at a density of 20,000 cells/well in 80 of complete RPMI medium and incubated overnight. After 16-18 hours post-transfection, the assay plates were washed with PBS (Corning Inc., Corning, NY), followed by addition of 80 μΕΛνεΙΙ of serum-free RPMI 1640 medium containing IX Penicillin-Streptomycin solution, IX MEM and 350 nL of DMSO or titrations of Compound 1. Compound 1 titrations were generated by 1.5-fold dilution steps in two

overlapping serial dilution series to generate a 40-point compound dose range. After incubation at 37 °C for 1 hour, the cells were stimulated with Poly(LC) (InvivoGen, San Diego, CA) at a final concentration of 15 μg/mL in Optimem media (Life Technologies, Rockville, MD). The assay plates were incubated for 5 hours at 37 °C, followed by addition of One-Glo luciferase firefly reagent (Promega, Madison, WI) at 1 : 1 volume/well and luminescence was measured in an EnVision Multilabel Plate Reader (PerkinElmer, Santa Clara, CA). The EC 50 values were calculated from the fit of the dose-response curves to a four-parameter equation. All EC ₅₀ values represent geometric mean values of a minimum of four determinations. lnterleukin-2 and interferon gamma analysis.

Freshly isolated human CD4+ and CD8+ T cells were obtained from AllCells (Alameda, CA, USA). Cells were spun down and resuspended in serum free Xvivol5 media (Lonza Walkersville, Inc., Chicago, IL, USA) supplemented with 5 ng/niL IL-17 and incubated overnight at 37 °C. Cells were plated on anti-CD3 coated plates (5 μg/mL OKT3, eBioscience, Dallas, TX, USA, overnight) with 2 μg/mL anti-CD28 (eBioscience, Dallas, TX, USA). Cells are treated in replicate plates with a dose-titration of Compound 1 for 24 hours for IL-2 and 96 hours for IFNy. IL-2 and IFNy in the supernatant were measured using single- or multi-plex immunoassay (Mesoscale Discovery, Rockville, MD, USA). Jurkat T cell leukemia cells (clone E61 obtained from ATCC) plated on anti-CD3 coated plates were treated with a dose titration of Compound 1 for 24 hours. IL-2 in the supernatant was measured as described above.

In vivo Compound 1 combination treatments.

Combination studies were performed by vivoPharm (Hummelstown, PA, USA). All procedures used in the performance of these studies were carried out in accordance with vivoPharm' s Standard Operating Procedures, with particular reference to US_SOPvP_EF0314 "General Procedures for Efficacy Studies." CT26 colon carcinoma cells (1 x 10 ⁶ cells/mouse in 100 μί, passage 2-3) were re-suspended in serum-free DMEM and implanted in the upper right flank of 11-12 week old female Balb/c mice (Charles River Laboratories). Mice were randomized into four groups of 10 using a matched pair distribution method based on tumor size for CT26. Treatment was initiated 12 days post-inoculation with mean tumor volume at start of dosing of 125.85 mm . Vehicle or Compound 1 (40 mg/kg) was administered by oral gavage daily for 26 days and isotype control or a reverse chimera anti-PD-Ll cloned from literature reports (e.g., Deng, R. et al. MAbs (2016), the content of which is incorporated herein by reference in entirety) and placed into a mouse IgGl framework (10 mg/kg) was administered every 5 days for a total of six doses. Investigators were not blinded to treatment groups. Mice bearing CT26 tumors with exceptional responses to combination therapy with aPD-Ll and Compound 1 were re-implanted with CT26 cells (lxlO ⁶ , lower left flank) and EMT6 cells (0.5xl0 ⁶ , upper left flank) to evaluate development of immunologic memory. MB49 and MC38 in vivo combination studies performed under identical conditions in B6 mice. B 16F10 tail vein injection studies were performed in accordance with methods known in the art (e.g., Zhang, J. et al. Cell Rep. (2016), the content of which is incorporated herein by reference in entirety). After tail vein injection (1 x 10 ⁵ cells in 100 μί), mice were treated with Vehicle or 40 mg/kg

Compound 1 daily for 13 days + anti-PD-Ll (10 mg/kg) or isotype control on Days 0, 5, and 10. Mice were sacrified on Day 13 and lung metastases were quantified (small <1 mm, medium >1 mm and <3 mm, large > 3mm). No large lung metastases were detected.

Statistical Methods and Data Analysis.

All graphs depict mean + s.d. unless otherwise indicated. Graphs were generated and statistical analysis performed using GraphPad/Prism (v7.0) and R statistical package. Pearson correlation matrix using 21 cell surface markers for MDOTS were calculated with R across tumors and different sized spheroids. Unsupervised hierarchical clustering was performed using GenePattern. Example 2. Ex Vivo Profiling of PD-1 Blockade Using Organotypic Tumor Spheroids

Existing patient-derived cancer models, including circulating tumor cells (CTCs), organoid cultures, and patient-derived xenografts (PDXs) can guide precision cancer therapy, but take weeks to months to generate and lack the native tumor immune microenvironment. Current approaches to study anti-tumor immune responses in patients are also limited by remote measurements in whole blood or plasma, or static assessment of biopsies. To overcome these challenges and model immune checkpoint blockade (ICB) ex vivo, a 3D microfluidic device was adapted to the short-term culture of murine- and patient-derived organotypic tumor spheroids (MDOTS/PDOTS). Following limited collagenase digestion of fresh tumor specimens, multicellular organotypic spheroids with autologous immune cells were isolated.

MDOTS/PDOTS were analyzed by flow cytometry (FIG. 5) or loaded in collagen into the central channel of the device for exposure to anti-PD-1 or anti-CTLA-4 antibodies (FIG. 1A).

Using the MC38 and B 16F10 immune competent syngeneic murine tumor models, lymphoid and myeloid immune cell composition of bulk tumor was compared with different spheroid populations (S I >100 μιη; S2 40-100 μιη; and S3 <40 μιη). Flow cytometric analysis revealed similar populations across all immune cell fractions examined (FIG. IB, FIGs. 6A-6C, Tables S2-1 through S2-4). MDOTS (S2) from B 16F10 demonstrated fewer CD45+ cells than MC38 and another model, CT26 (Extended Data Fig. 2d), although immune sub-populations were relatively consistent across MC38, B 16F10, and CT26 models (FIG. 6E). Since S2 MDOTS were optimally sized for culture in the microfluidic device, this fraction was utilized for subsequent studies.

A large panel of PDOTS (n=40) was immunophenotyped by flow cytometry, enriching for cancers responsive to PD-1 blockade (e.g., melanoma, Merkel cell carcinoma) (FIG. 1C, Tables 1A and IB). A range of lymphoid (CD19+ B cells, CD4+ and CD8+ T cells) and myeloid (CD15+ granulocytic, CD14+ monocytic lineages, CD123+ dendritic cells) populations were consistently detected in PDOTS (FIG. 1C). Variable surface expression of exhaustion markers (PD-1, CTLA-4, TEVI-3) was detected on CD4+ and CD8+ T cells (FIG. 6F) and PD-1 ligands (PD-L1 and PD-L2) on myeloid populations, including dendritic cells, myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs) (FIG. 6G). A strong correlation of T-cell profiles was confirmed between PDOTS (S2) and S3 fractions, including antigen-experienced (CD45RO+) (FIG. ID) and exhausted CD4 and CD8 T cells (FIG. IE), and overall conservation of immunophenotype regardless of spheroid size (FIGs. 6H-6J). These data demonstrate that PDOTS retain autologous immune cells, including key tumor-infiltrating T lymphocyte populations.

3D microfluidic culture of MDOTS and PDOTS resulted in growth and expansion over time (FIG. 2A) as well as cytokine elaboration in conditioned medium (FIGs. 2B-2C).

Tumor/immune cell intermixture in spheroids was further demonstrated by immunofluorescence microscopy (FIGs. 7A-7C). Dynamic cellular interactions were observed by live imaging, and survival of CD45+ immune cells ex vivo in the device was confirmed (FIG. 7D). Thus, short- term culture and cytokine profiling of PDOTS/MDOTS is feasible using this 3D microfluidic device.

MDOTS were exposed to ex vivo PD-1 blockade, starting with MC38 allografts that respond to anti-PD-1 treatment in vivo (FIGs. 2D-2E). MC38 MDOTS were treated with anti- PD-1 antibody (or isotype control) for 3 days or 6 days in the device (FIG. 2F). Dual labeling de-convolution fluorescence microscopy using acridine orange (AO, live cells) and propidium iodide (PI, dead cells) demonstrated >90% viability of MDOTS at the time of spheroid loading (Day 0) and over time in culture with control (FIG. 2G). Treatment with anti-PD-1 resulted in dose- and time-dependent killing of MC38 MDOTS (FIG. 2G, FIG. 2K, FIG. 7E), in contrast to cell line-derived MC38 spheroids lacking autologous immune/stromal cells (FIG. 2H). Modest killing was evident in the intermediately sensitive CT26 model (FIG. 21), whereas MDOTS derived from the PD-1 resistant B 16F10 model exhibited little cell death despite identical treatment (FIGs. 2J-2K). Anti-PDl induced killing of CT26 MDOTS required CD8+ T cells (FIG. 7F), which varied between tumors of different size, but not between distinct regions from a single tumor (FIG. 7G). These data demonstrate the ability to recapitulate sensitivity and resistance to PD-1 blockade ex vivo using well-defined mouse models.

Responses to PD-1 blockade in PDOTS were evaluated. To perform systematic assessment of ex vivo ICB in PDOTS, acute cytokine production was used as a quantitative measure of early immune activation rather than ex vivo killing, which was more robust in MDOTS. Day 3 cytokine release from PDOTS (n=28) + PD-1 blockade was analyzed, and upregulation of CCL19 and CXCL13 was observed in the majority of samples (23/28) (FIG. 3A, FIG. 3D, FIGs. 8A-8C). CCL19/CXCL13 induction was not observed with isotype IgG control (FIG. 8D), and was comparatively minimal following CTLA-4 blockade (FIG. 4B, FIG. 4E). CCL19/CXCL13 generation was also preserved across a range of spheroid numbers (FIG. 8E) with little intra-assay variability (FIGs. 8F-8G). CCL19 correlated with CXCL13 across PDOTS samples, and required the microfluidic device for robust induction (FIGs. 8H-8I).

CCL19/CXCL13 upregulation was also evident following dual PD-1 + CTLA-4 blockade (FIG. 3C, FIG. 3F), and accompanied by induction of additional effector cytokines (e.g., IFN-γ, IL-2, and TNF-a) in select samples (FIG. 9).

In consonance with PDOTS profiling results, CCL19/CXCL13 mRNA expression increased in patients treated with PD-1 blockade (FIGs. 3G-3H, Tables S4A and Tables S4B-1 through S4B-7). Although fold induction of CCL19/CXCL13 did not clearly correlate with response (FIG. 10A), higher absolute levels of CCL19 and CXCL13, and their receptors (CCR7 and CXCR5), was evident in banked samples from melanoma patients with clinical benefit (CB) from checkpoint blockade (FIGs. 3I-3J, FIGs. lOB-lOC). Pretreatment CCL19/CXCL13 mRNA expression levels alone failed to correlate with responsiveness to PD-1 or CTLA-4 blockade in melanoma RNAseq datasets (FIGs. 10D-10E). NanoString data from matched formalin-fixed and paraffin-embedded tissue or banked plasma was also insufficient to detect correlation with response (FIGs. 10F-10G). As PD-1 blockade promotes immune cell infiltration in vivo, gene set enrichment analysis (GSEA) was performed using published immune signatures, which revealed enrichment of diverse immune cell populations in patients with CB to checkpoint blockade (FIG. 3K). To evaluate the clinical significance of CCL19/CXCL13, Cancer Genome Atlas melanoma (SKCM) data were analyzed. Improved patient survival was evident in melanoma specimens with higher expression of CCL19/CXCL13 (FIGs. 3L-3M; p<0.001). Evaluation of TCGA data for other cancers (e.g., bladder cancer, head and neck, and breast) revealed similar a pattern (FIG. 10H). Immune GSEA using melanoma TCGA data confirmed enrichment of diverse immune cell gene sets in melanoma patients with high levels of both CCL19 and CXCL13 (FIG. 3N), consistent with their established roles as chemoattractants.

CCL19/CXCL13 coordinate humoral and cell-mediated adaptive immunity in lymph nodes and tertiary lymphoid structures (TLS), and cancer-associated TLS have been associated with improved prognosis. Histologic review of melanoma biopsy specimens pre- and on- anti- PD1 only identified rare TLS (FIG. 11A) likely due to limited sampling by core biopsy.

Expression of CCL19 in the melanoma TME has been linked to cancer-associated fibroblasts (CAFs), and CXCL13 to CD8+ exhausted T cells. CCL19 is also strongly expressed in lymph node high endothelial venules. It was noted that strongest induction of CCL19/CXCL13 by anti- PD1 was independent of the number of total CD45+ cells or other immune subpopulations in PDOTS (FIGs. 11B-11D). Therefore, CD45+ and CD45- cell populations from a sample (MGH- 16) marked by robust anti-PDl induced secretion of CCL19 and CXCL13 were sorted, to determine the cellular source of CCL19 and CXCL13 in PDOTS. Indeed, stromal populations including CD90+CD45- cancer-associated fibroblasts, CD31+CD144+ endothelial cells, and tumor cells (CD45-) expressed CCL19 in particular, while CXCL13 was also detected in CD45+ cells (FIG. HE). Immunohistochemical staining confirmed expression of CCL19 and CXCL13 in stromal elements including cancer-associated fibroblasts (aSMA) and endothelial cells (CD31) (FIG. 11F).

To better understand the relationship between anti-PDl induced PDOTS cytokine profiles and clinical benefit to ICB, unsupervised hierarchical clustering of cytokine profiles from patients specifically treated with anti-PD-1 therapy was performed. PDOTS from patients with mixed response or progression on anti-PD-1 therapy elaborated multiple immune suppressive cytokines/chemokines (e.g., CCL2) in addition to CCL19/CXCL13 (FIG. 30). Induction of significantly higher levels of CCL20 and CX3CL1 in patients with no clinical benefit (NCB) to PD-1 blockade (FIG. 12A) was noted, consistent with their lack of association with survival (FIG. 12B) and previous association of CX3CL1 induction with anti-PD-Ll resistance. Several of these immune suppressive cytokines/chemokines induced in PDOTS were also components of an innate PD-1 resistance (IPRES) gene expression signature (FIG. 12B), which correlated with nonresponse but missed statistical significance (p=0.08, FIG. 12C). Serial PDOTS profiling from an individual patient revealed that induction of multiple granulocytic and monocytic chemoattractants predicted infiltration of these respective myeloid populations following disease progression on anti-PD-1 therapy in vivo (FIGs. 12D-12E). These data highlight the potential of this assay to identify cytokines changes associated with ineffective anti-tumor immune responses despite CCL19/CXCL13 induction following ICB.

Higher levels of immune suppressive cytokines were also induced in anti-PDl -resistant B 16F10 MDOTS relative to MC38 MDOTS (FIG. 12F), as well as the intermediately resistant CT26 MDOTS model, which elaborated particularly high levels of CCL2 (FIG. 12G). Because of its partial sensitivity to anti-PDl, CT26 model was used to determine whether MDOTS profiling could identify novel combination therapies that overcome resistance. However, neutralization of CCL2 alone failed to enhance PD-1 mediated killing of CT26 MDOTS (FIG. 12H-12I), suggesting the need for alternative strategies that more broadly inhibit immune suppressive signaling within the TME and reactivate T cells.

It was noted that the homologous innate immune signaling kinases TBK1 and ΙΚΚε not only promote autocrine/paracrine cytokine signaling, but also restrain T cell activation, suggesting that a dual impact of ΤΒΚΙ/ΙΚΚε inhibition on the TME could enhance anti-tumor activity of PD-1 blockade (FIG. 4A). A novel potent/selective ΤΒΚΙ/ΙΚΚε inhibitor Compound 1 (Cmpdl) was synthesized (FIG. 4B, FIGs. 13A-D, Tables S5-1 and S5-2), which lacks JAK inhibitory activity, in contrast to the multitargeted inhibitor momelotinib (CYT387). Cmpdl effectively blocked immune suppressive cytokine elaboration by CT26 cell line spheroids, without cytotoxic effects (FIG. 4C, FIG. 13E), and enhanced secretion of IL-2 and IFN-γ from purified CD4+ and CD8+ T cells (FIGs. 4D-4E) and IL-2 from Jurkat cells (FIG. 13F).

Decreased levels of CCL4, CCL3, and IL-Ιβ with concomitant induction of cytokines involved in activated innate immune responses (e.g., G-CSF) were observed in CT26 MDOTS treated with Cmpdl + anti-PD-1 (FIG. 4F). Ex vivo combination treatment enhanced killing of CT26 MDOTS (FIGs. 4G-4H), which predicted in vivo response with greater tumour control and longer survival than mice treated with Cmpdl or anti-PD-Ll alone (FIGs. 4I-4K).

Reimplantation of CT26 into mice with exceptional responses to combination therapy showed no growth, suggesting immunologic memory for CT26 tumors (FIG. 13F).

Combination treatment in the PD-1 sensitive MC38 MDOTS model enhanced ex vivo killing and in vivo survival, although neither of these reached significance compared to single- agent PD-1/PD-L1 (FIGs. 14A-14D). The intrinsically resistant B 16F 10 model could not be sensitized with Cmpdl treatment (FIGs. 14E-14H), possibly due to the relative paucity of immune cells in B 16F10 MDOTS compared to CT26 and MC38 MDOTS. Indeed,

downregulation of several immune suppressive chemokines (e.g., CCL2, CCL5) in B 16F10

MDOTS was observed, but without concomitant induction of G-CSF and related innate immune response cytokines (FIGs. 14A-14B). However, enhanced response to combination treatment with Cmpdl was confirmed in vivo using a fourth partially anti-PDl sensitive syngeneic model (MB49 bladder carcinoma), further validating its activity. Importantly, MDOTS responses in three models (CT26, MC38, and B 16F10) effectively recapitulated the in vivo response (or lack thereof) to PD-1 blockade +/- ΤΒΚΙ/ΙΚΚε inhibition, highlighting the potential of ex vivo screening in MDOTS to develop combination immunotherapies more generally.

Example 3. Transcriptomic analysis of MDOTS/PDOTS following ex vivo treatment

RNA is collected from a subset of the MDOTs within the device after the supernatants have been collected and cDNA libraries for RNA sequencing is generated to evaluate global transcriptome changes associated with treatment regimen on single samples per drug treatment. These types of data may be generated from a variety of clinical specimens. The RNA Advance tissue RNA isolation method (Beckman Coulter) is utilized, which is a bead wash based separation technique, which facilitates elution volumes amenable to sample input for RNA-Seq library preparation. Automated library preparation can be performed using as little as 10 ng of good quality RNA. The RNA Access method from Illumina is utilized, which enriches for the coding region of the genome. Libraries are sequenced on the NextSeq500 platform, as 75 bp Single End to generate approximately 20 million reads per sample. With appropriate adaptors, 24 samples are multiplexed on each NextSeq500 run. The concentration [ng/ul], yield [ng] and quality of RNA (high RIN# by bioanalyzer) derived from the MDOTS are more than sufficient to ensure good quality libraries for subsequent sequencing (FIG. 15).

The STAR RNA sequencing alignment tool (Spliced Transcripts Alignment to a

Reference) [STAR_2.5.0a]) is utilized to align the data to the genome (RefSeq gene annotations). DeSeq2 is utilized to perform differential expression analysis (+2-fold, P value<0.05). Overlaps between differentially expressed genes and the annotated Immunological gene sets in the

Molecular Signature Database or MSigDB (FDR q-value<0.05) are computed. CIBERSORT (Newman AM et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015 May;12(5):453-7.) is utilized to provide an estimation of the abundances of member cell types in a mixed cell population, including more than 20 immune subsets, using the transcriptomic data generated.

The additional information garnered from whole transcriptome analysis provides a deeper understanding of the biological response to PD- 1 immune blockage on its own and in

combination with other immune blockade compounds or a MEK inhibitor. This knowledge complements secretion profiling to identify novel mechanisms of both response and resistance. Moreover, computational methods to evaluate the "immunone" including GSEA and

CIBERSORT, permit inference of changes in immune cell populations using established gene signatures. Tables with Supportive Data for Example 2:

Table S2-1

SI 5 0.558 0.549 0.708 0.802 0.860

SI 6 0.461 0.470 0.554 0.691 0.834

S2 1 0.749 0.788 0.603 0.635 0.455

S2 2 0.948 0.936 0.865 0.816 0.367

S2 3 0.881 0.883 0.696 0.634 0.230

S2 4 0.680 0.651 0.836 0.925 0.825

S2 5 0.308 0.310 0.540 0.713 0.925

S2 6 0.183 0.226 0.383 0.590 0.884

S3 1 0.740 0.776 0.569 0.636 0.459

S3 2 0.827 0.856 0.664 0.688 0.407

S3 3 0.790 0.817 0.548 0.510 0.165

S3 4 0.685 0.675 0.792 0.839 0.768

S3 5 0.300 0.278 0.518 0.567 0.793

S3 6 0.226 0.246 0.430 0.499 0.766

Table S2-2

S3 3 0.921 0.764 0.888 0.642 0.428 0.437

S3 4 0.663 0.605 0.580 0.959 0.958 0.889

S3 5 0.283 0.178 0.166 0.720 0.911 0.867

S3 6 0.261 0.112 0.101 0.665 0.845 0.794

Table S2-3

1.000 2.000 3.000 4.000 5.000 6.000

Tumor 1 0.740 0.827 0.790 0.685 0.300 0.226

Tumor 2 0.776 0.856 0.817 0.675 0.278 0.246

Tumor 4 0.569 0.664 0.548 0.792 0.518 0.430

Tumor 5 0.636 0.688 0.510 0.839 0.567 0.499

Tumor 6 0.459 0.407 0.165 0.768 0.793 0.766

SI 1 0.908 0.937 0.921 0.663 0.283 0.261

SI 2 0.685 0.808 0.764 0.605 0.178 0.112

SI 3 0.776 0.844 0.888 0.580 0.166 0.101

SI 4 0.767 0.808 0.642 0.959 0.720 0.665

SI 5 0.654 0.649 0.428 0.958 0.911 0.845

SI 6 0.666 0.634 0.437 0.889 0.867 0.794

S2 1 0.984 0.945 0.893 0.779 0.485 0.510

S2 2 0.835 0.920 0.816 0.741 0.327 0.298

S2 3 0.901 0.890 0.976 0.625 0.243 0.201

S2 4 0.707 0.717 0.517 0.970 0.792 0.747

S2 5 0.529 0.481 0.217 0.862 0.894 0.929

S2 6 0.493 0.443 0.139 0.782 0.836 0.920

S3 1 1.000 0.960 0.913 0.746 0.426 0.440

S3 2 0.960 1.000 0.874 0.763 0.387 0.394

S3 3 0.913 0.874 1.000 0.550 0.181 0.146

S3 4 0.746 0.763 0.550 1.000 0.849 0.812

S3 5 0.426 0.387 0.181 0.849 1.000 0.955

S3 6 0.440 0.394 0.146 0.812 0.955 1.000

Table S3

Pt38 R 9077.47447 44808.3318 Pt38 R 292.4756557 24.68183797

Pt4 R 158.462804 383.601214 Pt4 R 2.601765411 0.107674982

Pt5 R 0.8957807 94.056973 Pt5 R 0.038933398 0.069888488

Pt6 R 1.44330175 90.2063594 Pt6 R 0.020724471 0.022144073

Pt8 R 617.842921 243.736198 Pt8 R 12.63014518 0.085181314

Pt9 R 1131.85131 641.694215 Pt9 R 35.53789234 0.344448618

Ptl NR 2340.48615 479.579124 Ptl NR 99.54999655 0.348730135

PtlO NR 2.70089632 2584.08255 PtlO NR 0.098714409 1.614630139

Ptl2 NR 292.02708 93.1555918 Ptl2 NR 8.617132617 0.046994022

Ptl6 NR 14.8144533 421.153742 Ptl4 NR 9.131829845 0.112841472

Ptl4 NR 221.968265 160.438202 Ptl6 NR 0.360470362 0.17519376

Pt20 NR 3001.54512 6437.79678 Pt20 NR 49.36256271 1.810023107

Pt22 NR 1426.52919 960.941811 Pt22 NR 21.09294252 0.242911252

Pt23 NR 15.1942229 2322.92855 Pt23 NR 0.229044285 0.598647058

Pt25 NR 944.629262 879.267764 Pt25 NR 11.4526496 0.182246738

Pt29 NR 420.240506 1498.70041 Pt29 NR 11.97953537 0.73038345

Pt31 NR 39.9689397 296.01996 Pt31 NR 0.909356479 0.115140091

Pt32 NR 4.86573555 259.830278 Pt32 NR 0.18150561 0.165701082

Pt7 NR 217.069727 429.20605 Pt7 NR 4.459248487 0.150737839

15 responders

13 non-resonders

Table S4A. Melanoma Patient Samples - Patient Treatment Details

1

42-S4 post-CTLA-4 (214 days); post-BRAFi/MEKi (102 days); on-PD- 1 (38 days)

42-S5 post-CTLA-4 (250 days); post-BRAFi/MEKi (138 days); post- PD-1 (74 days)

62-S6 pre-CTLA-4; pre-PD-1 NCB (stable disease— > disease

62-S7 post-CTLA-4 (235 days); on-PD- 1 (3 days) progression)

62-S8 post-CTLA-4 (277 days); on-PD- 1 (45 days)

272-S 1 pre-CTLA-4 CB (near complete response,

272-S2 post-CTLA-4 (47 days); pre-PD-1 PD-1 stopped due to irAE,

272-S3 post-CTLA-4 (437 days); post-PD-1 (346 days) eventual progression off therapy)

422-S 1 pre-PD-1, pre-CTLA-4 CB (excellent response after ipi-

422-S2 on-PD- 1, on-CTLA-4 nivo— > nivo)

51-S 1 pre-PD-Ll CB (stable disease with a single

51-S2 post-PD-Ll (224 days) escape lesion)

98-S 1 post-PD-1 (83 days); pre-CTLA-4 CB (mixed response— >

98-S2 post-PD-1 (109 days); post-CTLA-4 (25 days) response)

98-S3 post-PD-1 (182 days); post-CTLA-4 (98 days)

Table S4B-1

8 2 7 5 5 9 2 5

VEGFA 3.5339226 4.8352526 1.2942845 0.8670554 1.6518651 1.2393400 1.5851421 2.8943662

6 9 9 9 5 8 8

VEGFC 6.1275426 8.3234783 0.8157491 2.3208504 1.8504199 1.4714798 1.248408 2.3378798

6 1 7 3 5

CCR7 0.4388903 0.9061339 0.4213949 3.5517162 0.9712967 4.5111978 0.1138050 0.4290472

9 7 8 1 9 7 4

CXCR5 0.0694288 0.1391269 0.1833183 0.3911629 0.2012098 0.6038444 0.1 0.0414771

4 6 4 5 2 4 7

AXL 32.503153 60.063585 2.9185948 8.5506901 6.3051904 4.6324774 2.5648347 3.6162262

5 7 3 3 2 3 3 1

GZMA 2.5155048 9.7614830 3.1628008 53.720088 30.132477 28.575523 1.5375052 13.882791

8 3 5 4 9 8

GZMB 3.1300029 3.0973556 0.7346123 33.048311 4.4346990 8.6421007 3.4719104 10.526737

3 4 4 2 5 3 2

IFNGR1 51.451865 56.805094 54.126570 61.463800 58.820999 82.210607 43.636380 28.251941

5 7 8 2 7 5 6 3

TNF 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

IL2 0.1345724 0.1797779 0.1 0.1 0.1 0.1672027 0.1 0.1

9 4 4

IFNG 0.2667062 0.2375319 0.1 3.0052527 0.7214051 2.0987111 0.3803658 1.0622119

7 7 4 6 5 1 5

0.1 Below quantification

Table S4B-2

CCL8 3.97261692 2.5061445 2.3229953 2.9329615 34.176518 59.250610 7.98116 4.12935

8 7 3 2 7 673 83

CCLl 3 2.57546133 5.9095417 1.0844684 3.6412366 67.662574 58.352470 5.93524 8.85494

4 1 5 9 222 803

IL10 1.9128064 1.5099751 6.1537277 0.3460126 5.8799046 2.4895965 0.16767 0.64954

1 9 1 9 663 159

VEGFA 2.44542296 1.5991809 1.0830365 0.2985924 2.5732817 0.9207440 0.72348 1.68157

8 8 1 3 9 459 005

VEGFC 0.99412394 1.7657199 1.0099629 0.6069254 3.9945039 0.9011043 1.56860 1.77229

5 4 1 3 848 407

CCR7 0.21397451 0.8706652 0.8804039 0.5225367 0.9133338 0.5371007 0.20257 0.09809

3 3 2 569 159

CXCR5 0.0372339 0.1442907 0.1702221 0.0909271 0.4414724 0.0934614 0.1 0.1

3 2 1

AXL 3.15217802 5.9937903 5.5922516 2.6999677 10.096701 3.8971181 4.64898 4.82579

3 6 1 1 024 31

GZMA 5.26766769 14.812260 18.795847 3.4512941 118.36424 42.569851 8.66651 5.88984

2 5 8 2 7 831 997

GZMB 3.6058497 22.405901 21.316618 3.6437254 109.39022 31.834899 1.03001 2.13752

6 5 8 5 9 359 208

IFNGR 81.0920132 110.98998 60.150012 79.943328 95.051625 75.067716 0.1 35.6153 1 1 6 8 3 856

TNF 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

IL2 0.14433941 0.1 0.8248450 0.1 0.1 0.3623085 0.1 0.1

5 9

IFNG 0.66748061 0.4619026 3.1605018 0.1164301 7.8010793 4.3083087 0.56421 0.32784

8 3 4 8 2 667 729

0.1 Below quantification

Table S4B-3

IL10 0.2284 10.917 12.167 3.6530 2.5668 2.0336 2.3790 1.4334 0.2647 0.5514 2.3265 0994 5298 5798 185 4581 7129 281 0819 9124 5316 6264

VEGF 1.2154 1.5902 1.8999 4.3628 1.4161 0.5181 0.9738 0.7125 2.6930 6.8442 0.7615 A 9229 7526 1979 9443 8926 3138 5307 9811 6142 4133 4607

VEGF 0.9496 1.6618 2.8688 1.7314 1.9682 2.4611 6.2059 0.7044 0.8551 1.0115 5.7539 C 7388 3682 9762 75 5775 5994 211 8349 934 3397 4032

CCR7 0.3219 8.2797 12.785 4.4486 5.8463 95.563 5.9694 8.1505 0.1371 0.0587 4.2646 412 4664 4505 3917 1976 4831 5609 0896 0131 8489 5798

CXCR 0.5201 1.0994 2.2136 0.7986 0.3759 48.118 0.3045 1.7523 0.0198 0.0170 0.9276 5 9769 2208 2828 8685 6741 0912 7195 7544 8094 4869 2141

AXL 2.4522 56.652 74.840 13.302 10.912 19.143 2.5444 29.894 0.4802 0.5294 144.03 467 2478 5834 7932 7259 2302 2739 754 0963 5552 8705

GZM 3.5899 80.806 125.25 46.316 41.801 37.834 10.117 40.963 1.7925 1.8787 27.175 A 9916 4715 7307 0997 2 5867 4052 4229 5175 8039 4305

GZM 7.6167 17.166 16.400 3.8232 10.157 4.1352 8.2944 14.847 2.4492 3.1559 18.753 B 7215 4256 9527 8583 8792 438 4931 8181 8242 2022 749

IFNG 11.873 57.056 61.182 37.312 44.674 85.673 184.21 47.254 22.869 32.495 124.27 Rl 3792 3904 6911 7656 7933 7313 3974 564 9314 3981 9512

TNF 0.1 1.2625 1.5847 0.6940 1.3675 2.6171 0.3316 0.4518 0.1182 0.0405 0.7320

8841 6345 7351 8178 4127 9142 3519 1037 4803 6497

IL2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1

IFNG 0.2049 10.296 11.652 2.8320 2.8885 1.7466 0.1231 4.9071 0.0509 0.0436 10.096 5433 9456 9517 9437 0742 2482 5714 7196 142 6094 2879

0.1 Below

quantification

Table S4B-4

IL2 1.34 1.00 1.00 1.67 1.00 0.69 5.71 1.00 3.62

IFNG 0.89 30.05 7.21 20.99 2.79 0.69 4.73 67.00 37.00

Table S4B-5

Table S4B-6

CXCR5 1.00 1.09 0.13 1.72 -1.27 1.95 2.19 2.28 0.04

AXL 0.89 1.55 1.11 0.67 0.50 0.93 0.83 1.90 0.53

GZMA 1.96 4.09 3.25 3.18 3.17 1.49 1.84 5.10 3.62

GZMB -0.02 5.49 2.59 3.56 1.60 2.64 2.56 4.91 3.13

IFNGR1 0.14 0.18 0.12 0.60 -0.63 0.45 -0.43 0.25 -0.09

TNF 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

IL2 0.42 0.00 0.00 0.74 0.00 -0.53 2.51 0.00 1.86

IFNG -0.17 4.91 2.85 4.39 1.48 -0.53 2.24 6.07 5.21

Table S4B-7

Table S5-1. Project SSBK10488_30712; provides data for Cmpdl (1000 μΜ).

Table S5-2.

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While several inventive embodiments have been described and illustrated herein, those of ordinary skill in the art will readily envision a variety of other means and/or structures for performing the function and/or obtaining the results and/or one or more of the advantages described herein, and each of such variations and/or modifications is deemed to be within the scope of the inventive embodiments described herein. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the inventive teachings is/are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific inventive embodiments described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, inventive embodiments may be practiced otherwise than as specifically described and claimed. Inventive embodiments of the present disclosure are directed to each individual feature, system, article, material, kit, and/or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and/or methods, if such features, systems, articles, materials, kits, and/or methods are not mutually inconsistent, is included within the inventive scope of the present disclosure.

All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms.

All references, patents, and patent applications disclosed herein are incorporated by reference with respect to the subject matter for which each is cited, which in some cases may encompass the entirety of the document.

The indefinite articles "a" and "an," as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean "at least one." The phrase "and/or," as used herein in the specification and in the claims, should be understood to mean "either or both" of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with "and/or" should be construed in the same fashion, i.e., "one or more" of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the "and/or" clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to "A and/or B", when used in conjunction with open-ended language such as "comprising" can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc.

As used herein in the specification and in the claims, "or" should be understood to have the same meaning as "and/or" as defined above. For example, when separating items in a list, "or" or "and/or" shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as "only one of or "exactly one of," or, when used in the claims, "consisting of," will refer to the inclusion of exactly one element of a number or list of elements. In general, the term "or" as used herein shall only be interpreted as indicating exclusive alternatives (i.e. "one or the other but not both") when preceded by terms of exclusivity, such as "either," "one of," "only one of," or "exactly one of." "Consisting essentially of," when used in the claims, shall have its ordinary meaning as used in the field of patent law.

As used herein in the specification and in the claims, the phrase "at least one," in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase "at least one" refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, "at least one of A and B" (or, equivalently, "at least one of A or B," or, equivalently "at least one of A and/or B") can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc.

It should also be understood that, unless clearly indicated to the contrary, in any methods claimed herein that include more than one step or act, the order of the steps or acts of the method is not necessarily limited to the order in which the steps or acts of the method are recited.

In the claims, as well as in the specification above, all transitional phrases such as "comprising," "including," "carrying," "having," "containing," "involving," "holding,"

"composed of," and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases "consisting of and "consisting essentially of shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. It should be appreciated that embodiments described in this document using an open-ended transitional phrase (e.g.,

"comprising") are also contemplated, in alternative embodiments, as "consisting of and

"consisting essentially of the feature described by the open-ended transitional phrase. For example, if the disclosure describes "a composition comprising A and B," the disclosure also contemplates the alternative embodiments "a composition consisting of A and B" and "a composition consisting essentially of A and B."