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Title:
GUT COMMENSAL BACTERIA FOR TREATMENT OF HUMAN COLORECTAL CANCER
Document Type and Number:
WIPO Patent Application WO/2019/149859
Kind Code:
A1
Abstract:
The invention relates to the use of a bacterium, or a plurality of kinds of bacteria, in treatment or prevention of cancer, particularly as an slow-release parenteral administration form. Combinations with chemotherapy agents or checkpoint inhibitor agents are provided.

Inventors:
IEZZI GIANDOMENICA (CH)
CREMONESI ELEONORA (CH)
EPPENBERGER-CASTORI SERENELLA (CH)
SPAGNOLI GIULIO (CH)
Application Number:
PCT/EP2019/052447
Publication Date:
August 08, 2019
Filing Date:
January 31, 2019
Export Citation:
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Assignee:
UNIV BASEL (CH)
International Classes:
A61K35/741; A61K35/742; A61K35/744; A61P35/00
Domestic Patent References:
WO2012142605A12012-10-18
WO2013053836A12013-04-18
WO2016063263A22016-04-28
WO2016196605A12016-12-08
WO2017085520A12017-05-26
WO2017085518A12017-05-26
Foreign References:
EP3012270A12016-04-27
Other References:
THEOFILOS POUTAHIDIS: "Gut Microbiota and the Paradox of Cancer Immunotherapy", FRONT IMMUNOL, vol. 5, no. 157, 7 April 2014 (2014-04-07), pages 1 - 5, XP009512851
CHEMICAL ABSTRACTS, Columbus, Ohio, US; abstract no. 477202-00-9
CHEMICAL ABSTRACTS, Columbus, Ohio, US; abstract no. 946414-94-4
CHEMICAL ABSTRACTS, Columbus, Ohio, US; abstract no. 1374853-91-4
CHEMICAL ABSTRACTS, Columbus, Ohio, US; abstract no. 1036730-42-3
CHEMICAL ABSTRACTS, Columbus, Ohio, US; abstract no. 1380723-44-3
CHEMICAL ABSTRACTS, Columbus, Ohio, US; abstract no. 1537032-82-8
Attorney, Agent or Firm:
SCHULZ JUNGHANS PATENTANWÄLTE PARTGMBB (Berlin, DE)
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Claims:
Claims

1. A preparation of bacteria for use in a method of treatment or prevention of cancer, wherein said preparation of bacteria comprises bacteria of

a. at least 2, particularly 3, 4, 5, 6, 7, 8, 9, 10, 1 1 or all of the genera comprised in a first consortium genera group consisting of Bacteroides, Alistipes, Odoribacter, Roseburia, Faecalibacterium, Desulfovibrio, Prevotella, Alloprevotella, Phascolarctobacterium, Flavonifractor, Pseudoflavonifractor, Clostridium and Coprococcus',

b. at least 2, particularly 3, 4 or all of the genera comprised in a second consortium genera group consisting of Sediminibacterium, Treponema, Enterococcus, Methylobacterium and Actinomyces.

2. The preparation of bacteria for use in a method of treatment or prevention of cancer according to claim 1 , wherein

a. bacteria of genus Bacteroides are selected from one or several of the species Bacteroides massiliensis, Bacteroides chinchillae, Bacteroides sartorii, Bacteroides ovatus; and/or Bacteroides uniformis;

a. bacteria of genus Alistipes are selected from one or several of the species Alistipes putredinis, Alistipes onderdonkii, Alistipes senegalensis, Alistipes timonensis, Alistipes shaihii and/or Alistipes finegoldii;

b. bacteria of genus Odoribacter are selected from the species Odoribacter splanchnicus;

c. bacteria of genus Roseburia are selected from the species Roseburia inulinovorans and/or Roseburia faecis;

d. bacteria of genus Faecalibacterium are selected from the species Faecalibacterium prausnitzii;

e. bacteria of genus Desulfovibrio are selected from one or several of the species Desulfovibrio piger, Desulfovibrio fairfieldensis, Desulfovibrio desulfuricans subsp. Desulfuricans, Desulfovibrio legallii;

f. bacteria of genus Prevotella are selected from the species Prevotella stercorea; g. bacteria of genus Alloprevotella are selected from the species Alloprevotella rava; h. bacteria of genus Flavonifractor are selected from the species Flavonifractor plautii;

i. bacteria of genus Pseudoflavonifractor are selected from the species Pseudoflavonifractor phocaeensis and/or Pseudoflavonifractor capillosus; j. bacteria of genus Clostridium are selected from one or several of the species Clostridium sphenoides, Clostridium xylanolyticum, Clostridium celerecrescens, Clostridium algidixylanolyticum, Desulfotomaculum guttoideum and/or Merdimonas faecis:

k. bacteria of genus Coprococcus are selected from the species Coprococcus comes;

L. bacteria of genus Sediminibacterium are selected from the species Sediminibacterium ginsengisoli and/or Sediminibacterium salmoneum;

m. bacteria of genus Treponema are selected from the species Treponema medium and/or Treponema vincentii;

n. bacteria of genus Enterococcus are selected from one or several of the species Enterococcus hirae, Enterococcus faecium, Enterococcus faecalis, Enterococcus dispar, Enterococcus durans, and/or Enterococcus villorum ; o. bacteria of genus Methylobacterium are selected from one or several of the species Methylobacterium aminovorans, Methylobacterium extorquens , Methylobacterium lusitanum, Methylobacterium thiocyanatum, Methylobacterium podarium, Methylobacterium populi, Methylobacterium pseudosasae, Methylobacterium rhodesianum Methylobacterium rhodinum, Methylobacterium suomiense, Methylobacterium variabile and/or Methylobacterium zatmanii; and/or

p. bacteria of genus Actinomyces are selected from the species Actinomyces cardiffensis.

3. The preparation of bacteria for use in a method of treatment or prevention of cancer according to claims 1 or 2, wherein the bacteria belong to a strain comprised in Table 16.

4. The preparation of bacteria for use in a method of treatment or prevention of cancer according to any one of the preceding claims, wherein said preparation is administered by parenteral administration, particularly by oral administration, as a gastro-resistant tablet or capsule, as a food product, a yogurt, or dissolved into a beverage, or as suppository.

5. The preparation of bacteria for use in a method of treatment or prevention of cancer according to claim 4, administered as an enteric-coated [pH dependent, slow-release, gastro-resistant] tablet or capsule.

6. The preparation of bacteria for use in a method of treatment or prevention of cancer according to any one of the preceding claims, wherein said cancer is colorectal cancer (CRC).

7. The preparation of bacteria for use in a method of treatment or prevention of cancer according to any one of the preceding claims, wherein the cancer is characterized by absence or significantly low abundance of CD3 positive cells.

8. A pharmaceutical composition for parenteral administration, particularly as a gastroresistant tablet or capsule or as a suppository, for the treatment or prevention of cancer, particularly CRC, said pharmaceutical composition comprising several of the kinds of bacteria as specified in claims 1 to 3, or comprising solely or additionally one or several of the bacteria as specified in any one of Tables 1A, 1 B, 1 C, 2A, 2B, 2C, 3A, 3B and 3C.

9. The pharmaceutical composition for the treatment or prevention of cancer according to claim 8, wherein said pharmaceutical composition is administered prior to surgical resection of the lesion.

10. The pharmaceutical composition for the treatment or prevention of cancer according to claim 8 or 9, wherein the pharmaceutical composition comprises several of the kinds of bacteria as specified in claims 1 to 3, or comprising solely or additionally one or several of the kinds of bacteria specified in any one of Tables 1 A, 1 B, 2A, 2B, 3A and 3B and said pharmaceutical composition is administered concomitant with administration of a chemotherapeutic agent.

1 1. The pharmaceutical composition for the treatment or prevention of cancer according to claim 8 or 9, wherein said pharmaceutical composition comprises several of the kinds of bacteria as specified in claims 1 to 3, or comprising solely or additionally one or several of the kinds of bacteria specified in any one of Tables 1 A, 1 C, 2A, 2C, 3A and 3C and is administered concomitant with administration of a checkpoint inhibitory agent or checkpoint agonist agent.

12. The pharmaceutical composition for the treatment or prevention of cancer according to claim 8, wherein said pharmaceutical composition comprises several of the kinds of bacteria as specified in claims 1 to 3, or comprising solely or additionally one or several of the kinds of bacteria specified in any one of Tables 1 A, 1 B, 2A, 2B, 3A and 3B and is the composition is administered a. prior to surgical resection of the lesion and

b. prior to administration (following resection) of a chemotherapeutic agent.

13. The pharmaceutical composition for the treatment or prevention of cancer according to claim 8, wherein said pharmaceutical composition comprises several of the kinds of bacteria as specified in claims 1 to 3, or comprising solely or additionally one or several of the kinds of bacteria specified in any one of Tables 1 A, 1 C, 2A, 2C, 3A and 3C and the composition is administered

c. prior to surgical resection of the lesion and

d. prior to administration (following resection) of a checkpoint inhibitory agent or checkpoint agonist agent.

14. The pharmaceutical composition for the treatment or prevention of cancer according to any one of claims 10 or 12, wherein said checkpoint inhibitory agent is selected from an inhibitor of CTLA4 interaction with CD80 or CD86, and an inhibitor of the interaction of PD-1 with its ligand PD-L1 , particularly an antibody against any one of CTLA4, CD80, CD86, PD-1 , PD-L1 , more particularly a monoclonal antibody against human CTLA4, PD-1 , or PD-L1 , and/or wherein said checkpoint agonist agent is selected from an agonist antibody or ligand to 4-1 BB and/or 4-1 BBL (CD137L, Uniprot P41273).

Description:
Gut commensal bacteria for treatment of human colorectal cancer

The present invention relates to the use of gut microbiota to elicit chemokine production within colorectal tumour tissues and to promote tumour infiltration by T cell populations of positive prognostic significance.

Description

Colorectal cancer (CRC) is the third most common type of cancer world-wide, and is most frequently observed in developed countries. Treatment options include surgery, radiation therapy, chemotherapy, targeted therapy or a combination thereof. The average 5 year survival rate is between 40% and 65%.

Infiltration of immune cells into the tumour tissue positively influences the clinical outcome of CRC. High densities of tumor infiltrating lymphocytes (TILs) including cytotoxic CD8+ T cells, IFN-g expressing T-helper 1 cells (Th1 ), CXCR5+ follicular T-helper cells (Tfh) and, surprisingly, Foxp3+ regulatory T cells (Tregs) are associated with prolonged patient survival. The chemotactic factors driving these cell populations into CRC tissues remain largely undefined. Expression of defined chemokines, including CXCL9, CXCL10, CXCL16, and CX3CL1 , was reported to correlate with high densities of tumor infiltrating lymphocytes (TILs), and to predict favorable clinical outcome. However, putative responding cell subsets within immune infiltrating cells have not been carefully characterized. Furthermore, chemokine sources and micro-environmental stimuli leading to chemokine production within CRC tissues were not addressed so far.

Based on the above-mentioned state of the art, the objective of the present invention is to provide improved means and methods for cancer treatment by increasing the number of beneficial tumour infiltrating lymphocytes present in the tumour. This objective is attained by the claims of the present specification.

Summary of the invention

A first aspect of the invention relates to the use of bacteria, or a preparation comprising bacteria, selected from a panel as disclosed herein treatment or prevention of cancer, particularly colon cancer.

The bacteria may belong to a genus, or to several genera, selected from Actinomyces, Alloprevotella, Coprococcus, Desulfovibrio, Enterococcus, Escherichia, Faecalibacterium, Lachnoclostridium, Methylobacterium, Odoribacter, Phascolarctobacterium, Prevotella, Pseudoflavonifractor, Roseburia, Seminidibacterium, Shigella, and T reponema. More than one kind of bacteria may be administered. Alternatively, the bacteria belong to a genus, or to several genera, comprised in the group of Bacteroides, Alistipes, Odoribacter, Roseburia, Faecalibacterium, Desulfovibrio, Prevotella, Alloprevotella, Phascolarctobacterium, Flavonifractor, Pseudoflavonifractor, Clostridium and Coprococcus.

Another alternative aspect relates bacteria that belong to a genus, or to several genera, comprised in the group of Sediminibacterium, Treponema, Enterococcus, Methylobacterium and Actinomyces.

The invention further relates to a preparation of bacteria for use in a method of treatment or prevention of cancer, wherein said preparation of bacteria comprises bacteria of at least 2, particularly 3, 4, 5, 6, 7, 8, 9, 10, 11 or all of the genera comprised in a first consortium genera group consisting of Bacteroides, Alistipes, Odoribacter, Roseburia, Faecalibacterium, Desulfovibrio, Prevotella, Alloprevotella, Phascolarctobacterium, Flavonifractor, Pseudoflavonifractor, Clostridium and Coprococcus.

Alternatively, the preparation of bacteria for use in a method of treatment or prevention of cancer comprises at least 2, particularly 3, 4 or all of the genera comprised in a second consortium genera group consisting of Sediminibacterium, Treponema, Enterococcus, Methylobacterium and Actinomyces.

Particular embodiments of these aspects comprise three, four, five or six, or even ten of these genera.

Particular embodiments of these aspects comprise particular species selected from these genera.

Particular embodiments of these aspects comprise particular strains selected from these genera.

Another aspect of the invention relates to a pharmaceutical composition comprising one, several, even up to a dozen or more of the bacterial strains disclosed herein. The pharmaceutical composition can be administered for treatment or prevention of cancer, particularly colon cancer.

Yet another aspect of the invention relates to a combination medicament that comprises a bacterium, or a selection of different bacteria, according to the first aspect of the invention, applied prior to or after surgical resection of the lesion and an active agent selected from a chemotherapeutic agent and a checkpoint inhibitory agent or checkpoint agonist agent.

Terms and definitions

In the context of the present specification, the term checkpoint inhibitory agent or checkpoint inhibitory antibody is meant to encompass an agent, particularly a (non-agonist) antibody (or antibody-like molecule) capable of disrupting the signal cascade leading to T cell inhibition after T cell activation as part of what is known in the art the immune checkpoint mechanism. Non-limiting examples of a checkpoint inhibitory agent or checkpoint inhibitory antibody include antagonist (blocking) antibodies to CTLA-4 (Uniprot P16410), PD-1 (Uniprot

Q151 16), PD-L1 (Uniprot Q9NZQ7), B7H3 (CD276; Uniprot Q5ZPR3), Tim-3, Gal9, VISTA, or Lag3.

In the context of the present specification, the term checkpoint agonist agent or checkpoint agonist antibody is meant to encompass an agent, particularly but not limited to an antibody (or antibody-like molecule) capable of engaging the signal cascade leading to T cell activation as part of what is known in the art the immune checkpoint mechanism. Non-limiting examples of receptors known to stimulate T cell activation include CD122 and CD137 (4- 1 BB; Uniprot Q0701 1 ). The term checkpoint agonist agent or checkpoint agonist antibody encompasses agonist antibodies to CD137 (4-1 BB), CD134 (0X40), CD357 (GITR), CD278 (ICOS), CD27 or CD28.

In the context of the present specification, the term (immune) checkpoint modulatory agent encompasses checkpoint inhibitory agents, checkpoint inhibitory antibodies, checkpoint agonist agents and checkpoint agonist antibodies.

Detailed description

According to a first aspect, the invention provides a bacterium, selected from a panel of bacteria, for use in a method of treatment or prevention of cancer. The bacteria belong to a genus selected from Actinomyces, Alloprevotella, Coprococcus, Desulfovibrio, Enterococcus, Escherichia, Faecalibacterium, Lachnoclostridium, Methylobacterium, Odoribacter, Phascolarctobacterium, Prevotella, Pseudoflavonifractor, Roseburia, Seminidibacterium, Shigella, and Treponema.

Alternatively, the bacteria belong to a genus, or to several genera, comprised in the group of Bacteroides, Alistipes, Odoribacter, Roseburia, Faecalibacterium, Desulfovibrio, Prevotella, Alloprevotella, Phascolarctobacterium, Flavonifractor, Pseudoflavonifractor, Clostridium and Coprococcus.

Another alternative aspect relates bacteria that belong to a genus, or to several genera, comprised in the group of Sediminibacterium, Treponema, Enterococcus, Methylobacterium and Actinomyces.

The invention further relates to a preparation of bacteria for use in a method of treatment or prevention of cancer, wherein said preparation of bacteria comprises bacteria of at least 2, particularly 3, 4, 5, 6, 7, 8, 9, 10, 11 or all of the genera comprised in a first consortium genera group consisting of Bacteroides, Alistipes, Odoribacter, Roseburia, Faecalibacterium, Desulfovibrio, Prevotella, Alloprevotella, Phascolarctobacterium, Flavonifractor, Pseudoflavonifractor, Clostridium and Coprococcus.

In particular embodiments, these bacteria are selected from the following species:

bacteria of genus Bacteroides are selected from one or several of the species Bacteroides massiliensis, Bacteroides chinchillae, Bacteroides sartorii, Bacteroides ovatus; and/or Bacteroides uniformis;

bacteria of genus Alistipes are selected from one or several of the species Alistipes putredinis, Alistipes onderdonkii, Alistipes senegalensis, Alistipes timonensis, Alistipes shaihii and/or Alistipes finegoldii;

bacteria of genus Odoribacter are selected from the species Odoribacter splanchnicus; bacteria of genus Roseburia are selected from the species Roseburia inulinovorans and/or Roseburia faecis;

bacteria of genus Faecalibacterium are selected from the species Faecalibacterium prausnitzii;

bacteria of genus Desulfovibrio are selected from one or several of the species Desulfovibrio piger, Desulfovibrio fairfieldensis, Desulfovibrio desulfuricans subsp. Desulfuricans, Desulfovibrio legallii;

bacteria of genus Prevotella are selected from the species Prevotella stercorea;

bacteria of genus Alloprevotella are selected from the species Alloprevotella rava;

bacteria of genus Flavonifractor are selected from the species Flavonifractor plautii; bacteria of genus Pseudoflavonifractor are selected from the species Pseudoflavonifractor phocaeensis and/or Pseudoflavonifractor capillosus;

bacteria of genus Clostridium are selected from one or several of the species Clostridium sphenoides, Clostridium xylanolyticum, Clostridium celerecrescens, Clostridium algidixylanolyticum, Desulfotomaculum guttoideum and/or Merdimonas faecis:

and/or

bacteria of genus Coprococcus are selected from the species Coprococcus come.;

Alternatively, the preparation of bacteria for use in a method of treatment or prevention of cancer comprises at least 2, particularly 3, 4 or all of the genera comprised in a second consortium genera group consisting of Sediminibacterium, Treponema, Enterococcus, Methylobacterium and Actinomyces.

In particular embodiments, these bacteria are selected from the following species:

bacteria of genus Sediminibacterium are selected from the species Sediminibacterium ginsengisoli and/or Sediminibacterium salmoneum;

bacteria of genus Treponema are selected from the species Treponema medium and/or Treponema vincentii; bacteria of genus Enterococcus are selected from one or several of the species Enterococcus hirae, Enterococcus faecium, Enterococcus faecalis, Enterococcus dispar, Enterococcus durans, and/or Enterococcus villorunr,

bacteria of genus Methylobacterium are selected from one or several of the species Methylobacterium aminovorans, Methylobacterium extorquens , Methylobacterium lusitanum, Methylobacterium thiocyanatum, Methylobacterium podarium, Methylobacterium populi, Methylobacterium pseudosasae, Methylobacterium rhodesianum Methylobacterium rhodinum, Methylobacterium suomiense, Methylobacterium variabile and/or Methylobacterium zatmanii; and/or

bacteria of genus Actinomyces are selected from the species Actinomyces cardiffensis.

In more particular embodiments, the bacteria are selected from strains comprised in Table 16.

When reference is made to“a bacterium”, the skilled person understands that this refers to a plurality (in other words, an effective dose) of bacteria of the same phylum, species or strain, as the context may indicate. Where reference is made to“a bacterium”, this does not exclude the possibility that more than one kind of bacterium is administered. In certain embodiments, the invention provides for the administration of a plurality of kinds of bacteria of the phyla, species or strains identified herein.

In certain embodiments, the bacterium is provided for preventing cancer, particularly colorectal cancer (CRC).

More specifically, the bacteria and combinations and preparations of bacteria provided herein are particularly useful for patients whose tumours are characterized by little or no infiltration of CD3 positive cells. In the study underlying this specification, the cut-off values to score tumors as CD3high or CD3low was 157 cells/mm 2 histologically, but the skilled person will be aware of other criteria to determine patients at particular risk, or patients likely to benefit based on tumour infiltration of CD3 positive cells, based on histological or molecular markers (mRNA expression).

In certain embodiments, the bacterium is provided for delaying the onset of cancer in a subject identified as at risk of developing cancer, particularly CRC. In certain embodiments, the bacterium is provided for reducing the progression cancer, particularly CRC. Treatment of cancer, according to this aspect of the invention, may involve additional medicines, particularly so-called checkpoint modulator (antagonist/blocker or agonist) therapy.

The inventors have analyzed expression of immune cell markers, chemokines, and bacterial 16S ribosomal RNA (16SrRNA) in fresh CRC samples and corresponding tumor-free tissues. They demonstrated that CRC infiltration by distinct T cell subsets is associated with defined chemokine signatures. These chemokines were expressed by tumor cells upon exposure to defined gut bacteria. Abundance of defined bacteria correlated with high chemokine expression, enhanced T cell infiltration, and improved survival.

The inventors' findings reveal the ability of gut microbiota to induce the production of chemotactic factors by CRC cells, thereby recruiting T cell populations of favorable prognostic significance. This knowledge allows the development of innovative treatments aimed at modifying the gut flora to promote CRC infiltration by beneficial immune cells.

In certain embodiments, the bacterium belongs to the family Acidaminococcaceae.

In certain embodiments, the bacterium belongs to the phylum Actinobacteria.

In certain embodiments, the bacterium belongs to the phylum Bacteroidetes.

In certain embodiments, the bacterium belongs to the genus Escherichia.

In certain embodiments, the bacterium belongs to the phylum Firmicutes.

In certain embodiments, the bacterium belongs to the phylum Proteobacteria.

In certain embodiments, the bacterium belongs to the phylum Spirochaetae

In certain embodiments, the bacterium belongs to the family Actinomycetaceae

In certain embodiments, the bacterium belongs to the family Bacteroidaceae.

In certain embodiments, the bacterium belongs to the family Chitinophagaceae.

In certain embodiments, the bacterium belongs to the family Desulfovibrionaceae.

In certain embodiments, the bacterium belongs to the family Enterobacteriaceae.

In certain embodiments, the bacterium belongs to the family Enterococcaceae.

In certain embodiments, the bacterium belongs to the family Lachnospiraceae.

In certain embodiments, the bacterium belongs to the family Methylobacteriaceae.

In certain embodiments, the bacterium belongs to the family Porphyromonadaceae.

In certain embodiments, the bacterium belongs to the family Prevotellaceae.

In certain embodiments, the bacterium belongs to the family Rikenellaceae.

In certain embodiments, the bacterium belongs to the family Ruminococcaceae.

In certain embodiments, the bacterium belongs to the family Spirochaetaceae.

In certain embodiments, the bacterium belongs to the genus Actinomyces.

In certain embodiments, the bacterium belongs to the genus Alloprevotella.

In certain embodiments, the bacterium belongs to the genus Clostridium.

In certain embodiments, the bacterium belongs to the genus Coprococcus.

In certain embodiments, the bacterium belongs to the genus Desulfovibrio.

In certain embodiments, the bacterium belongs to the genus Enterococcus.

In certain embodiments, the bacterium belongs to the genus Faecalibacterium. In certain embodiments, the bacterium belongs to the genus Lachnoclostridium.

In certain embodiments, the bacterium belongs to the genus Methylobacterium.

In certain embodiments, the bacterium belongs to the genus Odoribacter.

In certain embodiments, the bacterium belongs to the genus Phascolarctobacterium.

In certain embodiments, the bacterium belongs to the genus Prevotella.

In certain embodiments, the bacterium belongs to the genus Pseudoflavonifractor.

In certain embodiments, the bacterium belongs to the genus Roseburia.

In certain embodiments, the bacterium belongs to the genus Seminidibacterium.

In certain embodiments, the bacterium belongs to the genus Shigella.

In certain embodiments, the bacterium belongs to the genus Treponema.

In certain embodiments, the bacterium belongs to the genus Phascolarctobacterium.

In certain embodiments, more than one kind of bacterium is employed, and the bacteria are selected from one of the phyla, families and/or genera mentioned in the above list. In certain embodiments, two kinds of bacteria are selected. In certain embodiments, three kinds of bacteria are selected. In certain embodiments, four kinds of bacteria are selected. In certain embodiments, five kinds of bacteria are selected.

In certain embodiments, more than one kind of bacterium is employed, and the bacteria belong to a genus comprised in Table 1 .

In certain embodiments, more than one kind of bacterium is employed, and the bacteria belong to a species comprised in Table 2.

In certain embodiments, the bacteria belong to one of the following bacterial species: Actinomyces cardiffensis, Actinomyces gerencseriae, Actinomyces hyovaginalis, Actinomyces massiliensis, Actinomyces meyeri, Actinomyces odontolyticus, Actinomyces suimastitidis, Actinomyces timonensis, Actinomyces turicensis, Alistipes finegoldii, Alistipes onderdonkii, Alistipes putredinis, Alistipes senegalensis, Alistipes shahii, Alistipes timonensis, Alloprevotella rava, Alloprevotella tannerae, Bacteroides massiliensis, Bacteroides uniformis, Bacteroides fluxus, Bacteroides oleiciplenus, Bacteroides rodentium, Bacteroides stercorirosoris, Clostridium aerotolerans, Clostridium aldenense, Clostridium algidixylanolyticum, Clostridium amygdalinum, Clostridium asparagiforme, Clostridium celerecrescens, Clostridium indolis, Clostridium lavalense, Clostridium methoxybenzovorans, Clostridium saccharolyticum, Clostridium sphenoides, Clostridium xylanolyticum, Coprococcus comes, Desulfotomaculum guttoideum, Desulfovibrio fairfieldensis, Desulfovibrio legallii, Desulfovibrio piger, Enterococcus canintestini, Enterococcus canis, Enterococcus dispar, Enterococcus durans, Enterococcus faecalis, Enterococcus faecium, Enterococcus hirae, Enterococcus lactis, Enterococcus mundtii, Enterococcus olivae, Enterococcus ratti , Enterococcus rivorum, Enterococcus villorum, Enterococcus caccae, Escherichia coli, Escherichia fergusonii, Escherichia marmotae, Escherichia vulneris, Faecalibacterium prausnitzii, Flavonifractor plautii, Methylobacterium aminovorans, Methylobacterium extorquens, Methylobacterium lusitanum, Methylobacterium podarium, Methylobacterium populi, Methylobacterium pseudosasae, Methylobacterium rhodesianum, Methylobacterium suomiense, Methylobacterium thiocyanatum, Methylobacterium zatmanii, Methylobacterium rhodinum, Methylobacterium variabile, Odoribacter splanchnicus, Phascolarctobacterium succinatutens, Prevotella stercorea, Pseudoflavonifractor capillosus, Pseudoflavonifractor phocaeensis, Roseburia faecis, Roseburia inulinivorans, Sediminibacterium ginsengisoli, Sediminibacterium salmoneum, Sediminibacterium goheungense, Shigella boydii, Shigella flexneri 2a, Shigella sonnei, Treponema medium, Treponema vincentii.

In certain embodiments, the bacterium belongs to a strain comprised in Table 3.

The inventors have surprisingly found that CRC samples characterized by high CD3 infiltration and upregulation of certain bacteria genera (Fig.13 upper and lower panel) have a trend towards a better recurrence-free survival.

In certain embodiments, the bacterium is administered by parenteral administration. In certain embodiments, the bacterium is administered by oral administration. In certain embodiments, the bacterium is administered as a gastro-resistant tablet or capsule.

In certain embodiments, the bacterium is administered as a food product, particularly as a milk- based food product, more particularly as a yogurt.

In certain embodiments, the bacterium is administered dispersed into a beverage.

In certain embodiments, the bacterium is administered as a suppository.

In certain embodiments, the cancer is colorectal cancer (CRC).

In an alternative to the first aspect of the invention, the bacterium is provided for use as a method of treatment or prevention of a colorectal condition. In certain embodiments, the colorectal condition is advanced colorectal adenoma.

According to an alternative of this aspect of the invention, a combination medicament is provided. The combination medicament comprises a bacterium, or a selection of different bacteria, according to the first aspect of the invention, applied prior to or after surgical resection of the lesion and an active agent selected from

a chemotherapeutic agent and

a checkpoint inhibitory agent or checkpoint agonist agent.

The combination medicament is provided for the treatment or prevention of cancer, particularly colorectal cancer. In certain embodiments, the chemotherapeutic agent is applied after administration of the bacterium.

In certain embodiments, the combination medicament is provided prior to surgical resection of the lesion.

In certain embodiments, the combination medicament comprises a chemotherapeutic agent and is provided prior to surgical resection of the lesion.

In certain embodiments, the combination medicament comprises a chemotherapeutic agent and is provided prior to and after surgical resection of the lesion.

Surgery is the mainstay curative treatment for colorectal adenomas and non-metastasized colorectal cancer.

For adenomas and early stage CRC (stage I and II) no additional therapies are usually administered. For stage III CRC, chemotherapy is administered after surgery (defined as adjuvant treatment).

In more-advanced cases of rectal cancer, chemotherapy or radiotherapy are administered before surgery to reduce tumour load (neoadjuvant treatment).

For metastatic CRC (stage IV) chemotherapy alone or combined with targeted agents (including growth factor-specific monoclonal antibodies and multikinase inhibitors) is the standard treatment. Since May 2017, administration of anti-PD-1 antibodies (pembrolizumab) has also been approved as second-line therapy. Any of these treatment regimens can be combined with the bacterial treatment according to the present invention, particularly:

Before and after surgery surgery to patients undergoing endoscopical resection of advanced colorectal adenomas;

Before and after surgery to patients with early stage CRCs;

Before neoadjuvant chemotherapy and after surgery to patients with stage III rectal cancers:

Before administration of pembrolizumab in metastatic CRC.

In certain embodiments, the combination medicament is provided for use in a method of treatment or prevention of cancer. In certain embodiments, the cancer is colorectal cancer (CRC)

In certain embodiments, the immune checkpoint inhibitor agent is an inhibitor of interaction of CTLA4 with CD80 or CD86. In certain embodiments, the immune checkpoint inhibitor agent is an inhibitor of interaction of programmed cell death protein 1 (PD-1 ) with its receptor PD-L1. In certain embodiments, the checkpoint inhibitory agent is selected from an antibody against any one of CTLA4, CD80, CD86, PD-1 , PD-L1. In certain embodiments, the checkpoint inhibitory agent is selected from a monoclonal antibody against human CTLA4, PD-1 , or PD- L1 .

In certain embodiments, the immune checkpoint inhibitor agent is ipilimumab (Yervoy; CAS No. 477202-00-9).

In certain embodiments, the immune checkpoint inhibitor agent is selected from the clinically available antibody drugs nivolumab (Bristol-Myers Squibb; CAS No 946414-94-4), pembrolizumab (Merck Inc.; CAS No. 1374853-91-4), pidilizumab (CAS No. 1036730-42-3), atezolizumab (Roche AG; CAS No. 1380723-44-3), and Avelumab (Merck KGaA; CAS No. 1537032-82-8).

In certain embodiments, the immune checkpoint agonist agent is utomilumab (PF- 05082566), a fully human lgG2 monoclonal antibody against 4-1 BB currently undergoing clinical trials.

In certain embodiments, the checkpoint modulatory agent is a polypeptide selected from an antibody, an antibody fragment, and an antibody-like molecule, and the polypeptide is selectively reactive to a checkpoint mediator. In certain embodiments, the checkpoint mediator is selected from CTLA4, PD-1 , CD80, CD86, PD-L1 , and PD-L2, TIM-3, 4-1 BB and 4-1 BBL.

In certain embodiments, the checkpoint agonist agent is selected from an agonist antibody or ligand to 4-1 BB and/or 4-1 BBL (CD137L, Uniprot P41273).

A second aspect of the invention relates to the use of a bacterium, selected from a panel of bacteria, for use in a method of treatment or prevention of cancer without the co-administration of a checkpoint modulator. While many embodiments of this aspect of the invention overlap with those cited above, which do not employ an additional active agent, this aspect provides additional bacteria which may have been implied in co-adjuvant administration of bacteria and checkpoint modulators, but have never been shown to elicit a positive effect in absence of the immune checkpoint modulator (Cl) agents.

This is important as the use of Cl agents is often associated with significant side effects, which in certain patients may limit or proscribe their use.

The kind of bacteria that may be employed as monotherapy includes all bacteria mentioned above and in addition, the bacteria of Table 3A. The term“monotherapy” as used here refers to the concept that only bacteria are employed, and no checkpoint modulators, but the monotherapy includes the possibility that a number of different kinds of bacteria are used, particularly a plurality of 2, 3, 4, 5 6, 7, 8 or more different kinds of bacteria. Certain embodiments of any of the aspects of the invention described herein relate to a medicament for use in a method of treatment or prevention of cancer comprising a bacterium according to the first aspect. In certain embodiments thereof, the cancer is colorectal cancer (CRC).

In certain embodiments of any of the aspects of the invention described herein, the medicament for use in a method of treatment or prevention of cancer is formulated as an enteric-coated tablet or capsuleln certain embodiments, the medicament for use in a method of treatment or prevention of cancer is formulated as a pH sensitive tablet or capsule. In certain embodiments, the medicament for use in a method of treatment or prevention of cancer is formulated as a slow-release tablet or capsule. In certain embodiments, the medicament for use in a method of treatment or prevention of cancer is formulated as a gastro-resistant tablet or capsule. Such capsules and tablets minimize dissolution of the capsule or tablet in the stomach but allow dissolution in the small intestine.

In certain embodiments of any of the aspects of the invention described herein, the medicament for use in a method of treatment or prevention of cancer is formulated as a suppository. In certain other embodiments, the medicament for use in a method of treatment or prevention of cancer is formulated as a food product, particularly as a milk product, or as a yogurt. In certain embodiments, the medicament for use in a method of treatment or prevention of cancer is dispersed into a beverage.

Wherever alternatives for single separable features are laid out herein as“embodiments”, it is to be understood that such alternatives may be combined freely to form discrete embodiments of the invention disclosed herein.

The invention is exemplarily illustrated but not limited to the following items of invention:

Item 1 : A bacterium for use in a method of treatment or prevention of cancer, particularly CRC, wherein said bacterium belongs to a genus selected from Actinomyces, Alloprevotella, Bacteroides, Bariatricus, Clostridium, Coprococcus, Desulfovibrio, Enterococcus, Escherichia, Faecalibacterium, Flavonifractor, Fusicatenibacter, Lachnoclostridium, Methylobacterium, Odoribacter, Phascolarctobacterium, Prevotella, Pseudoflavonifractor, Roseburia, Ruminococcus, Seminidibacterium, Shigella, and Treponema (any of the genera identified in Tables 1A, 1 B and 1 C).

Item 2: A bacterium for use in a method of treatment or prevention of cancer, particularly CRC, wherein said bacterium belongs to a species comprised in Table 2A, 2B, or 2C.

Item 3: A bacterium for use in a method of treatment or prevention of cancer, particularly CRC, wherein said bacterium belongs to a strain comprised in table 3A, 3B or 3C. Item 4: The bacterium for use in a method of treatment or prevention of cancer according to any one of the preceding items, wherein said bacterium is administered by parenteral administration, particularly by oral administration, as a gastro-resistant tablet or capsule, as a food product, a yogurt, or dissolved into a beverage, or as suppository.

Item 5: The bacterium for use in a method of treatment or prevention of cancer according to item 4, administered as an enteric-coated [pH dependent, slow-release, gastro- resistant] tablet or capsule.

Item 6: The bacterium for use in a method of treatment or prevention of cancer according to any one of the preceding items, wherein said cancer is colorectal cancer (CRC).

Item 7: A pharmaceutical composition for parenteral administration, particularly as a gastroresistant tablet or capsule or as a suppository, for the treatment or prevention of cancer, particularly CRC, said pharmaceutical composition comprising one or several of the kinds of bacteria specified in any one of Tables 1A, 1 B, 1 C, 2A, 2B, 2C, 3A, 3B and 3C.

Item 8: The pharmaceutical composition for the treatment or prevention of cancer according to item 7, wherein said pharmaceutical composition is administered prior to surgical resection of the lesion.

Item 9: The pharmaceutical composition for the treatment or prevention of cancer according to item 7 or 8, wherein the pharmaceutical composition comprises one or several of the kinds of bacteria specified in any one of Tables 1A, 1 B, 2A, 2B, 3A and 3B and said pharmaceutical composition is administered concomitant with administration of a chemotherapeutic agent.

Item 10: The pharmaceutical composition for the treatment or prevention of cancer according to item 7 or 8, wherein said pharmaceutical composition comprises one or several of the kinds of bacteria specified in any one of Tables 1 A, 1 C, 2A, 2C, 3A and 3C and is administered concomitant with administration of a checkpoint inhibitory agent or checkpoint agonist agent.

Item 1 1 : The pharmaceutical composition for the treatment or prevention of cancer according to item 7, wherein said pharmaceutical composition comprises one or several of the kinds of bacteria specified in any one of Tables 1A, 1 B, 2A, 2B, 3A and 3B and is administered

a. prior to surgical resection of the lesion and

b. prior to administration (following resection) of a chemotherapeutic agent. Item 12: The pharmaceutical composition for the treatment or prevention of cancer according to item 7, wherein said pharmaceutical composition comprises one or several of the kinds of bacteria specified in any one of Tables 1A, 1 C, 2A, 2C, 3A and 3C and is administered

- prior to surgical resection of the lesion and

prior to administration (following resection) of a checkpoint inhibitory agent or checkpoint agonist agent.

Item 13: The pharmaceutical composition for the treatment or prevention of cancer according to items 10 or 12, wherein said checkpoint inhibitory agent is selected from an inhibitor of CTLA4 interaction with CD80 or CD86, and an inhibitor of the interaction of PD-1 with its ligand PD-L1 , particularly an antibody against any one of CTLA4, CD80, CD86, PD-1 , PD-L1 , more particularly a monoclonal antibody against human CTLA4, PD-1 , or PD-L1 , and/or wherein said checkpoint agonist agent is selected from an agonist antibody or ligand to 4-1 BB and/or 4-1 BBL (CD137L, Uniprot P41273).

The invention is further illustrated by the following examples, tables and figures, from which further embodiments and advantages can be drawn. These examples are meant to illustrate the invention but not to limit its scope.

Identified bacteria

Table 1A - identified bacterial genera associated with T cell recruitment in tumor tissues and improved prognosis

Treponema

Table 1 B - identified bacterial genera (monotherapy or cytostatica therapy combination)

Bacteroides

Table 1 C - identified bacterial genera (monotherapy or checkpoint modulator combination)

Table 2A - identified bacterial species associated with T cell recruitment in tumor tissues and improved prognosis

Table 2C - identified bacterial species (monotherapy or checkpoint modulator combination)

Table 3A - identified bacterial strains associated with T cell recruitment in tumor tissues and improved prognosis

Table 3B - identified bacterial strains (monotherapy or cytostatica therapy combination)

Table 3C - identified bacterial strains (monotherapy or checkpoint modulator combination)

Combinations of the bacteria of Table 3A with other bacteria of tables 1 , 2, 3 and 3A possible, but no combination with Cl agents are claimed.

The invention

Brief description of the figures

Fig. 1 shows that CRC infiltration by T cells is associated with overexpression of defined chemokines. Expression of the genes encoding the indicated immune cell markers and chemokines was analyzed in 62 freshly excised CRC tissues (Table 4) and corresponding tumor-free colonic mucosa samples by qRT-PCR. Upper left panel: Y axis indicates gene expression levels in CRC tissues (bold) and tumor-free colonic mucosa samples (gray) relative to GAPDH. Statistical significance was assessed by Wilcoxon signed rank test ( * p<0.05; *** p<0.0001 ). Lower left panel: Unsupervised hierarchical clustering of the expression of the indicated genes in individual CRC specimens as related to corresponding tumor-free colonic tissues Right panel: Expression of the indicated chemokine (see also Table 5) in tumors as related to corresponding tumor-free colonic tissues, according to their distribution within the different clusters.

Fig. 2 shows that CRC infiltrating T cells express receptors binding overexpressed chemokines. Single cell suspensions obtained from freshly excised clinical CRC specimens were surface stained with fluorochrome labeled antibodies specific for CD8, or CD4, in combination with the indicated chemokine receptors. Intracellular staining for Foxp3 was then performed. For detection of IL-17 producing cells, cell suspensions were stimulated with PMA/lonomycin, and after 4 h cells were fixed, permeabilized and intracellularly stained with antibodies specific for IL-17 and the indicated chemokine receptors. Percentages of positive cells within gated CD8+, CD4+ Foxp3-, CD4+ Foxp3+, CD4+ CXCR5+, and CD4+ IL-17+ cells are shown. Means and standard deviations are indicated by bars. In panel 5 CCR1 1 , CXCR3, CXCR4, and CXCR5 were not tested.

Fig. 3 shows that defined chemokine signatures are associated with CRC infiltration by individual immune cell subsets. Chemokines significantly associated with expression of immune cells markers were assigned a score calculated, as detailed in Table 6. A heat map of score values is shown.

Fig. 4 shows that overexpression of T cell-related chemokine gene signatures is associated with improved prognosis. Upper panel: A transcriptomic data set from 31 1 CRC samples was downloaded from The Cancer Genome Atlas (TCGA, cancergenome.nih.gov). The indicated markers and chemokine genes expression levels were clustered in an unsupervised hierarchical manner using the WardD2 algorithm. Three main clusters were formed including tumors showing homogeneous upregulation (cluster 1 ), heterogeneous upregulation (cluster 2), or downregulation (cluster 3) of markers analyzed. Lower panel (Fig.4 continued): Kaplan- Meier curves showing the probability of overall survival (OS, Y axis) of patients included in the obtained clusters.

Fig. 5 shows that tumor cells express genes encoding T cell recruiting chemokines. Expression of the indicated chemokine genes was evaluated by qRT-PCR in total CRC tissues and corresponding purified tumor cells (n=10), or in the indicated established CRC cell lines. Y axes indicate expression levels of indicated chemokine genes relative to GAPDH. Means are indicated by bars. Statistical significance was assessed by Mann Whitney test ( * p<0.05).

Fig. 6 shows Toll-like receptor (TLR) expression on primary CRC cells. EpCAM + cells sorted from CRC clinical specimens (upper row) and CRC cells from established cell lines (lower row) were surface stained (left column) and intracellularly stained (right column) with antibodies specific for the indicated TLRs. MFI in individual samples or cell lines are shown. Means are indicated by bars. Fig. 7 shows that gut bacteria-derived stimuli induce chemokine gene expression in human CRC cells from established cell lines. CRC cell from the LS180 (upper panel and Fig. 7 continued), Colo205 (middle panel), and HT29 (lower panel) cell lines were treated with (upper panel): control medium (1 ), LPS, 1 pg/ml (2), Poly (l:C), 10 pg/ml (3), Flagellin, 100 ng/ml(4), or FSL-1 , 1 pg/ml(5), or with (Fig.7 continued): control medium (1 ), heat-inactivated (h.i.) Fusobacterium nucleatum (6), h.i. Escherichia Coli (7), or h.i. Bacteroides Fragilis (8) (CRC cell ratio = 30:1 ). After four hours, expression levels of the indicated chemokine genes were analyzed by qRT-PCR, using GAPDH as reference gene (indicated on the Y axis). Cumulative data from three independent experiments are shown. Statistical significance was assessed by two-way ANOVA test ( * =p<0.05).

Fig. 8 shows that gut bacteria-derived stimuli induce chemokine expression in human primary CRC cells. CRC organoids were generated from freshly resected CRC specimens or from first- passage CRC xenografts and characterized by histo-morphological analysis. Upper panels: Representative picture of CRC organoids evaluated by phase-contrast microscopy (upper left), or by histological analysis upon H&E staining (upper right), or following immunofluorescence staining with antibodies specific for B-catenin (left) or Ki67 (right) and DAPI are shown. Magnifications and scale bars are also indicated. Lower panel: Organoids were incubated with control medium (1 ) or stimulated with a mixture of Toll-like receptor (TLR) agonists (2) or bacteria (3), as used in Figure 6. After four hours, expression levels of genes encoding the indicated chemokines were analyzed by qRT-PCR, using GAPDH as reference gene (Y axis). Cumulative data from five experiments (2 performed with fresh specimens-derived and three with xenograft-derived organoids) are shown. Statistical significance was assessed by two- way ANOVA test ( * =p<0.05).

Fig. 9 shows that exposure of tumor cells to gut flora promotes chemokine expression in CRC tissues. Upper panels: NSG mice were inoculated with LS180 cells (10 L 5 cells/mouse) intraperitoneum (i.p., n=17, condition 1 ) or intra cecum (i.c. , n=66, condition 2). Starting from day 10, a randomized group of mice inoculated i.p., (n=7) or i.c. (n=28), were treated with Ampicillin and Vancomycin for three weeks (conditions 1 + and 2+, respectively). On day 31 xenografts were removed and expression levels of the indicated chemokine genes and of 16S were analyzed by qRT-PCR, using GAPDH gene as reference (indicated on the Y axes). Cumulative data from three independent experiments are shown. Statistical significance was assessed by two-way ANOVA test ( * = p<0.05, ** p<0.01 , *** p<0.0001 ). Lower panels: Expression of 16S and chemokine genes in tumor xenografts, generated upon i.p. or i.c. injection of LS180 cells, was assessed by qRT-PCR, and potential correlations were evaluated. Spearman r and corresponding p-values are indicated.

Fig. 10 shows that chemokine expression in tumor xenografts is associated with the presence of defined bacteria. Upper panel: Gut flora composition of CRC i.c. xenografts developed in mice untreated (-) or undergoing antibiotics treatment (+) was analyzed upon 16SrRNA sequencing and correlations with expression of chemokine genes were evaluated. Abundance of individual phyla in the two experimental groups is shown. 1 : Bacteroidetes; 2: Firmicutes; 3: Proteo bacteria; 4: Others. Lower panels: Left: Log2 fold change of specific operational taxonomic units (OTUs) in untreated versus abx-treated mice (see alsoTable 7). Right: Heat map of Spearman r values of correlations found between the indicated chemokines and abundance of defined OTUs (see alsoTable 8).

Fig. 1 1 shows that exposure of tumor cells to gut flora promotes T cell recruitment into CRC. NSG mice were inoculated with LS180 i.p. (n=1 1 ) or i.c. (n=14). On day 29, mice were adoptively transferred with equal numbers (5x10 L 6 cells/mouse) of human CFSE-labelled CRC-derived CD4+ and CD8+ T cells. After 48 hours, extent of human TIL migration into tumors was evaluated by flow cytometry. Cumulative data from two independent experiments performed with TILs derived from two different samples (P312, empty circles and P326, black circles) are shown. Statistical significance was assessed by one-way ANOVA test

( *** p<0.0001 ).

Fig. 12 shows analysis of the gut flora composition of 27 primary CRC samples (right column, 0+) and their corresponding tumor-free colonic tissues (left column, 0) upon 16SrRNA sequencing. Data refer to relative abundance of individual phyla. 1 : Bacteroidetes; 2: Firmicutes; 3: Proteobacteria; 4: Fusobacteria; 5: Actinobacteria; 6: others. Statistical significance was assessed by Wilcoxon test. Significant p values (<0.05) are indicated.

Fig. 13 shows that abundance of defined bacterial families correlates with T cell infiltration and improved clinical outcome in human CRCs. The gut flora composition of 27 primary CRC samples pre-assessed for density of CD3+ infiltrate (CD3high n=14, CD3low n=13) was analyzed by 16SrRNA sequencing. Upper panel: Unsupervised hierarchical clustering of OTU abundances was performed using the hclust algorithm based on the Ward D2 method 1 and 2 indicate clusters identified according to the gut flora composition. 3 and 4 indicate tumors characterized by low and high CD3+ infiltration, respectively. Middle panels (Fig. 13 continued): Kaplan-Meier curves illustrating overall survival (panel 1 ) or recurrence-free survival (panel 2) probability of patients included in clusters 1 and 2 as identified by hierarchical analysis. Statistical significance was assessed by log-rank test. Lower panel (Figure 13 continued): Fold change (log2) of OTUs enriched in CD3high as compared to CD3low tumors are shown (see also Table 9). Differential OTU analysis on normalized abundance counts was performed with DESeq2 software (v1 .12.4). Statistical significance (p<0.05) was assessed using a Wald test.

Fig. 14 shows that abundance of defined bacteria families correlates with expression of individual chemokines and T cell markers. Expression of genes encoding for the indicated markers or chemokines was assessed in 27 CRC samples (see above) and Spearman correlations between all markers were calculated. Correlation matrixes illustrating major correlations found between expression of T cell markers and chemokine genes (upper panel) to each other and (lower panel) versus OTU abundances. Color and diameter of the spots are proportional to the calculated Spearman correlation coefficients as indicated in the blue to red bar. All r and corresponding p values are listed in Tables 10 and 1 1 .

Fig. 15: Correlations between relative abundance of indicated OTU in CRC specimens (n=27)

Examples

Example 1 : Materials and methods

Clinical specimen collection and processing

Clinical specimens were collected from consenting patients undergoing surgical treatment at Basel University Hospital, St. Claraspital in Basel, and Ospedale Civico di Lugano, Switzerland (Swiss cohort, n=62), and at Klinikum Rechts Der Isar, Munich, Germany (German cohort, n=31 ). Use of human samples was approved by local ethical authorities (Ethikkommission Nordwest und Zentralschweiz, Comitato etico cantonale Ticino, and Ethics committee of the Faculty of Medicine of the TUM). Clinical-pathological characteristics of patients included in these cohorts are reported in Table 4. CRC or tumor-free colonic tissue samples were cryopreserved for RNA extraction. In addition, fresh specimens from Swiss cohort tissue samples were enzymatically digested (200 U/ml collagenase IV, Worthington Biochemical Corporation, 400 pg/mL hyaluronidase type l-S, Sigma-Aldrich, and 200 pg/mL DNAse I, Sigma-Aldrich, for 1 hour at 37°C) to obtain single cell suspensions. Samples from the German cohort were assessed for the presence of CD3+ infiltrates by IHC (see the respective sections below). In addition, peripheral blood mononuclear cells (PBMCs) from healthy donors (HDs) or patients (Swiss cohort) were isolated by density gradient (Histopaque-1077, Sigma-Aldrich) centrifugation.

Evaluation of T cell infiltration in CRC samples by immunofluorescence

The presence of CD3+ infiltrates was assessed by immunofluorescence (IF) on 27 CRC samples of the German cohort. Human tissue cryosections (8 pm) from the center of surgically resected tumors, as confirmed by trained pathologists, were stained with a specific anti-CD3 antibody (NeoMarker, 1 :300; RM-9107-S) and a secondary antibody coupled to fluorophore Cy3 (Dianova), and counterstained for nuclei with DAPI, after fixation with 3% PFA. Stained sections were scanned with a Zeiss Axiovert microscope using a 400x magnification with an oil immersion objective. A standardized total area of 1.22 mm2 was analyzed using the MosaiX software function of Zeiss Axiovision. Cells were counted manually from digital images by two independent observers blind to the identity of the samples. To derive optimal cut-off values for intra-tumoral CD3-cell densities, maximally selected log-rank statistics was performed by R Software version 2.13.0 (R Foundation for Statistical Computing, Vienna, Austria). A cut-off with maximum separation for tumor-specific post-operative survival, as well as for recurrence- free survival was determined at 157 cells/mm2. CD3-densities above this value were labelled as“CD3-high” and densities below this value as“CD3-low”.

Real-time reverse transcription PCR assays

Total RNA was extracted from stored CRC tissues or sorted cell populations using Nucleospin RNA kit (Macherey-Nagel) and reverse transcribed using the Moloney Murine Leukemia Virus Reverse Transcriptase (M-MLV RT, Invitrogen). Quantitative Real-Time PCR (qRT-PCR) was performed in the ABI prism™ 7700 sequence detection system, using TaqMan Universal Master Mix, No AmpErase UNG (both from Applied Biosystems) and commercially available primer sequences (Table 12).

Flow cytometry

Cell suspensions from CRC and tumor-free colonic mucosa samples and PBMCs from healthy donors (HDs) or patients with CRC were surface stained with fluorochrome labeled antibodies specific for CD8, or CD4, in combination with the indicated chemokine receptors. Intracellular staining for Foxp3 was then performed. For detection of IL-17 producing cells, cell suspensions were stimulated with PMA/lonomycin, and after 4 hours cells were fixed, permeabilized and intracellularly stained with antibodies specific for IL-17 and the indicated chemokine receptors. Cells were analyzed by FACSCalibur flow cytometer (BD Biosciences).

Primary CRC cells were sorted from tumor cell suspensions by magnetic microbeads conjugated to EpCAM-specific antibodies (MACS® MicroBeads from Miltenyi Biotec). Cell purity was > 97%, as evaluated by flow cytometry. EpCAM-negative fractions were used for expansion of tumor-infiltrating lymphocytes (TILs).

The Cancer Genome Atlas analysis

A data set of deep transcriptome sequencing of 31 1 CRC samples (TCGA colon & rectum adenocarcinoma (COADREAD) gene expression by RNAseq (NluminaHiSeq), was downloaded from the The Cancer Genome Atlas (http://canceraenome.nih.aov/ ' )· Unsupervised hierarchical clustering was performed using the hclust agglomeration algorithm based on the Ward.D2 method, which squares Euclidean distances before inputting them, by means of the Statistical Package Software R (Version 3.4.1 , (2017-06-30) www.r-proiect.org '

Cell lines

LS180, HT29, Colo205, HCT15, DLD1 , HCT1 16, SW480 and SW620 human CRC cell lines were purchased from the European Collection of Cell Cultures, and immediately stored in liquid nitrogen. Cells used for individual experiments were thawed from original cryopreserved aliquots and maintained in culture, for a maximum of 10 passages, in RPMI 1640 (Gibco) or McCoy's 5A medium (Sigma-Aldrich) for HT29, or L15 Medium (Leibovitz, Sigma-Aldrich), for SW480 and SW620, supplemented with 10% fetal bovine serum, 2mM Glutamine and 100pg/ml kanamycin sulphate (both from Gibco). Absence of mycoplasma contamination in cultured cells was verified by PCR testing prior to investigations.

Primary CRC cell isolation and phenotypic characterization

Primary CRC cells were sorted from tumor cell suspensions by magnetic microbeads conjugated to EpCAM-specific antibodies (MACS® MicroBeads from Miltenyi Biotec). Cell purity was > 97%, as evaluated by flow cytometry. Purified EpCAM+ cells were surface or, upon fixation, intracellularly stained with fluorochrome-labeled TLR-specific antibodies and analyzed by FACSCalibur flow cytometer (BD Biosciences). EpCAM-negative fractions were used for TIL expansion (see below).

TIL isolation and expansion

CRC-derived EpCAM- cells were stimulated with 1 pg/ml of phytohaemagglutinin (Sigma Aldrich) and expanded in medium supplemented with 100 lU/ml IL-2 (Roche Applied Science) and 5% of pooled human AB serum for 20 days. CD8+ and CD4+ T cells were then sorted by flow cytometry and expanded as bulk populations.

Organoid generation and characterization

Organoids were generated from single cell suspensions obtained from freshly resected CRC specimens (n=2) or first-passage xenografts (n=3), developed upon s.c. injection of primary CRC cell suspensions in eight-week old NSG mice (NOD.Cg-Prkdcscid N2rgtm1 Wjl/SzJ, Charles River Germany). Briefly, cell suspensions was passed through a 70-pm cell strainer (BD Bioscience), and cell clusters remaining on the top of the mesh were collected and seeded onto Matrigel-coated 12 well plates (Matrigel Growth factor reduced, phenol red free, BD Biosciences) in 1 ml/well DMEM/F12 (GIBCO) culture medium supplemented with 2% GFR Matrigel, Kanamycin (GIBCO), HEPES (GIBCO), Glutamax (GIBCO), N2 Supplement (Invitrogen, #17502-048), B27 (Invitrogen, #17504-044), and N-Acetyl-L-Cysteine (NAC, Sigma A9165-5G), as previously reported (1 ). Half of the medium was changed every 3 days and organoids were passaged and transferred to fresh Matrigel at a 1 :3 ratio according to growth rates.

For histological evaluation, organoids were collected and embedded in OCT. Cryosections were cut (10um), fixed with 4% paraformaldehyde (PFA) for 20 minutes at room temperature and stained for hematoxylin & eosin or immunofluorescence. For immunofluorescence analysis, slides were stained with mouse anti-beta Catenin- (1 :100, Cell Signaling) or rabbit anti-Ki67- (Abeam) specific antibodies, followed by secondary species-specific Alexa Fluor 488-conjugated or 546-conjugated antibodies (Invitrogen). Nuclei were counterstained with DAPI. Slides were examined under an Olympus BX61 fluorescence microscope (Olympus Switzerland) and images were captured with 10x, 20x and 60x magnification using a digital camera and Analysis software (Soft Imaging System GmbH).

TLR agonists

CRC cells or organoids were stimulated with Lipopolysaccharides (LPS, 1 pg/ml from Escherichia coli 01 1 1 :B4, Sigma-Aldrich), polyinosinic-polycytidylic acid (poly(l:C), 10pg/ml, Invivogen), synthetic diacylated lipoprotein (FSL-1 , 1 pg/ml, Invivogen), and purified flagellin from S. Typhimurium (100ng/ml, Invivogen).

Bacteria

All bacteria strains were purchased from American type culture collection (ATCC). Fusobacterium nucleatum (subsp. Nucleatum, ATCC 25586), and Bacteroides fragilis (non- enterotoxigenic strain 9343, ATCC 25285) were cultured overnight under anaerobic conditions in blood agar plates, at 37°. Escherichia coli (Castellani and Chalmers, ATCC 25922) was cultured in Tryptic Soy Agar/Broth (BD). All bacteria were used following heat-inactivation at 90° for 1 hour.

CRC cell stimulation with TLR agonists and bacteria

For tumor cell stimulation the following TLR agonists were used: Lipopolysaccharides (LPS, 1 pg/ml from Escherichia coli 01 1 1 :B4, Sigma-Aldrich), polyinosinic-polycytidylic acid (poly(l:C), 10pg/ml, Invivogen), synthetic diacylated lipoprotein (FSL-1 , 1 pg/ml, Invivogen), and purified flagellin from S. Typhimurium (100ng/ml, Invivogen).

Fusobacterium nucleatum (subsp. Nucleatum, ATCC 25586), and Bacteroides fragilis (non- enterotoxigenic strain 9343, ATCC 25285) were purchased from American type culture collection (ATCC) and cultured overnight under anaerobic conditions in blood agar plates, at 37°. Escherichia coli (Castellani and Chalmers, ATCC 25922) was cultured in Tryptic Soy Agar/Broth (BD). All bacteria were used following heat-inactivation at 90° for 1 hour. CRC cells from established cell lines or from CRC-derived organoids were incubated with TLR agonists or heat-inactivated bacteria (bacteria: tumor cell ratio = 30:1 ) at 37 C. After 4 hours, chemokine expression was assessed by qRT-PCR.

In vivo experiments

In vivo experiments were approved by Basel and Zurich Cantonal Veterinary offices. NSG mice (NOD.Cg-Prkdcscid N2rgtm1 Wjl/SzJ,) initially purchased from Charles River Germany, were bred and maintained in the inventors’ animal facility. Tumor xenografts were generated in eight-week old NSG mice (NOD.Cg-Prkdcscid N2rgtm1 Wjl/SzJ,) upon intra peritoneum (i.p.) and intra cecum (i.c.) injection (17) of LS180 cells (3c10 L 5/ mouse), resuspended in a 1 :1 mixture of PBS and Growth Factor Reduced Matrigel (Corning Costar). For intracecal injection mice were anesthetized with ketamine and xylazine (Streuli Pharma AG) i.p.. Following laparotomy, cecum was exteriorized and tumor cells were injected into cecum wall (30 mI / injection). After injection, gut was returned to the abdominal cavity and incision was closed by atraumatic, resorbable sutures. From day 10, a randomized group of i.c. injected mice was treated with Ampicillin sodium salt (1 g/L, Amresco) and Vancomycin Hydrochloride (0.2 g/L, Bio Basic Canada), administered in drinking water. Tumors were harvested on day 31 and assessed for chemokine gene expression.

To evaluate T cell migration, at day 29 tumor-bearing mice were adoptively transferred with CFSE-labeled CD4+ and CD8+ T cells, previously isolated from primary CRC specimens and expanded in vitro (5x10 6 T cells/subset/mouse). Two days later, frequencies of transferred TILs were evaluated in cell suspensions of digested tumors by flow-cytometry.

16S rRNA gene sequencing and analysis

Bacterial flora was analyzed based on 16S rRNA sequencing. Total RNA was purified from 27 samples of the German cohort, (tumor and tumor-free tissues) and from tumor xenografts, and reverse transcribed. Two-step PCR libraries were created using the primer pair 515F (5 - GTGCCAGCMGCCGCGGTAA-3, SEQ ID NO 03') and 806R (5'-G GACT AC H VGG GTWT CT A AT-3', SEQ ID NO 04), targeting the V4 region of 16S rRNA gene in all bacteria. Libraries were sequenced on the lllumina MiSeq platform using a v2 500 cycles kit resulting in 2x250 bp reads. Demultiplexing and trimming of lllumina adaptor residuals for the produced paired-end reads were performed using the lllumina MiSeq Reporter software (v2.6.2). Quality of reads was checked with FastQC software (vO.1 1 .5). Locus specific primers were trimmed from the sequencing reads with the software cutadapt (v1 9.2.dev0). Paired-end reads were discarded if the adaptor could not be trimmed. Trimmed forward and reverse reads of the paired-end reads were merged considering a minimum overlap of 15 bases using USEARCH software (v8.1 .1861 ). Merged sequences were quality filtered allowing a maximum of one expected error per merged read and also discarding those containing ambiguous bases. Remaining reads were clustered at a similarity level of 97% using the UPARSE algorithm within the USEARCH framework to form operational taxonomic units (OTUs) while discarding singletons and chimeric reads in the process. OTUs were aligned against the reference sequences of the SILVA 16S rRNA database (v128) and taxonomies were predicted considering a minimum confidence threshold of 0.6 using USEARCH. Alpha and beta diversity calculations as well as the rarefaction analysis were performed with the R package phyloseq (v1 .16.2). Community diversity was estimated using observed richness, Chaol and Shannon indices. Differential OTU analysis on normalized abundance counts was performed with DESeq2 software (vl .12.4).

For the identification of bacterial species, sequences identifying individual OTUs of interest (i.e. associated with high density of T cell infiltrates and/or high levels of chemokine expression) were evaluated by BLAST-based search. Species showing the highest genomic identity (>97%) were selected. The inventors focused on OTUs accounting for > 1000 reads (0.0196 relative abundance, considering all samples). Within this group, OTUs/species were selected according to their association with T cell infiltration and/or chemokine expression. Sequences displaying >97% of identity are expected to belong to the same species.

Statistical analysis

Statistical significance of differences in expression levels of immune cell genes between CRC and tumor-free tissues (Figure 1 ) were assessed by Wilcoxon signed rank test ( * p<0.05; *** p<0.0001 ), in expression levels of chemokine genes (Figure 5) by Mann Whitney test ( * p<0.05); in chemokine gene expression (Figures 7-9) and migrations rates (figure 1 1 ) were assessed by two-way ANOVA test ( * = p<0.05, ** p<0.01 , *** p<0.0001 ).

Unsupervised hierarchical clustering of expression levels of immune marker and chemokine genes (Figures 1 and 4) or OTU abundances (Figure 13) was performed using the hclust algoritm based on the Ward D2 method. Statistical significance of differences in survival probability (Figures 4 and 13) was assessed by log-rank test.

Statistical significance of differences in normalized OTU abundance counts between CD3high and CD3low tumors (Table 9) was assessed using a Wald test (p<0.05).

Correlations between expression levels of immune cell markers and/or chemokines genes with each other or with OTU abundance (Figure 14) or relative correlations between OTU abundances (Figure 15) were evaluated by Spearman's rank correlation coefficient. Values <0.05 were considered significant.

Example 2: CRC infiltration bv T cells is associated with overexpression of defined

chemokines.

The inventors analyzed expression of genes encoding immune cell markers, including CD3 for total T cells, CD4 for T-helper cells, CD8 for CTLs, T-bet and IRF-1 for Thl , IL-4, IL-5 and IL- 13 for Th2, IL-17 for Th17, CXCR5 for Tfh, and Foxp3 for Tregs, in 62 CRCand corresponding tumor-free colonic tissues (Table 4) All T cell markers were expressed, except for IL-4 which was undetectable in all samples (data not shown), and IL-5 and IL-13, expressed only in a few samples, thus suggesting that CRC infiltration by Th2 cells in CRC is marginal. IL-17 and Foxp3 gene expression was significantly increased in tumors as compared to control tissues (p<0.0001 ), whereas expression of CD4 and CXCR5 genes was slightly reduced (p<0.05). Expression of all T cell subset markers, except IL-17, significantly correlated with that of CD3 and CD4 (Figure 1 , upper left panel).

Upon normalization of immune cell marker expression in tumor samples versus corresponding tumor-free colonic tissues and unsupervised hierarchical analysis, samples clustered in three main groups: one characterized by overexpression of most T cell markers (cluster 1 ), a second displaying heterogeneous expression (cluster 2), and a third characterized by downregulation of all T cell marker genes (cluster 3 , Figure 1 , lower left panel). Analysis of different clusters revealed a panel of chemokine genes significantly upregulated in highly but not in poorly infiltrated tumors (Figure 1 , right panel). Furthermore, significant correlations between expression of genes encoding individual chemokines and specific immune cell markers were observed (Table 5), suggesting that these chemokines might be involved in T cell recruitment into tumor tissues.

Example 3: TILs express receptors binding overexpressed chemokines

The inventors then analyzed chemokine receptor profiles of CD8+ (panel 1 ), CD4+ (Foxp3-) effector T cells (panel 2), and CD4+ Foxp3+ Tregs (panel 3), in freshly excised CRC specimens (Figure 2). All three subsets in tumors and control tissues were largely positive for CCR5, CXCR3, and CXCR4, whereas lower cell fractions expressed CCR3, CCR6 and CCR10. Considerable fractions of CD4+ T cells and Tregs also expressed CCR4. Furthermore, within CD4+ T cells a small subset of CXCR5+ cells was detectable, confirming tumor infiltration by Tfh. This cell subset, however, did not show significant expression of additional chemokine receptors (panel 4). Chemokine receptor profiles on Th1 and Th17 cells could not be properly assessed, since the stimulation, required for their identification, based on cytokine production capacity, causes down-modulation of most chemokine receptors (data not shown). We could only detect CCR6 on a large majority of Th17 cells (up to 88%), and CCR4 on a smaller fraction (up to 38%) (panel 5) Expression of CCR1 or CCR1 1 was undetectable in all T cell subsets (data not shown).

Example 4: Defined chemokine signatures underlie CRC infiltration bv individual T cell subsets

Chemokines significantly correlating with any T cell marker were assigned scores, calculated according to the following formula: Spearman r value x percentage of corresponding chemokine receptor-positive cells (Table 6). Thus, the inventors identified putative chemokine signatures for each T cell subset (Figure 3). In particular, for CTLs they selected CCL3, CCL4, CCL5, and CCL8 (binding to CCR5), CXCL9 and CXCL10 (binding to CXCR3), and CXCL12 (binding to CXCR4). Th1 -associated chemokine signature mainly included CCR4-ligands CCL17, CCL22, and CXCL12, together with CCL3, CCL5, CXCL9, and CXCL1 1 . CXCL12, CCL17 and CCL22, and to a lower extent CCL5 and CXCL9, also underlay tumor infiltration by Tregs. Infiltration by Tfh was exclusively associated with expression of CXCL13, whereas Th17-associated signature included CCL20 and CCL17, and to a lower extent CCL25, CCL27, and CCL28.

Identified signatures were validated in a larger cohort, including 31 1 CRC samples from The Cancer Genome Atlas (TCGA, cancergenome.nih.gov) (Figure 4). Unsupervised hierarchical analysis identified different clusters. One included samples overexpressing CD8, IRF-1/T- bet, FoxP3, and CXCR5, and all corresponding chemokines (Cluster 1 ); two additional groups showed heterogeneous expression of all markers and chemokines (clusters 2). Finally, a group displayed low expression of all markers and related chemokines (cluster 3) Importantly, samples overexpressing all T cell markers and their chemokine signatures showed improved survival as compared to those from other clusters (Figure 4, continued). Thus, overexpression of the identified chemokines associates with infiltration by beneficial T cell populations and improved prognosis.

Example 5: T cell recruiting chemokines are expressed bv tumor cells

To identify cellular sources of T cell recruiting chemokines, the inventors evaluated their potential production by tumor cells, the major component of CRC microenvironment. Gene expression analysis of chemokines in primary CRC cells, isolated from freshly excised CRC specimens based on EpCAM expression, revealed that tumor cells express most relevant chemokine genes (Figure 5). For some chemokines, including CCL3, CCL4, and CCL20, gene expression levels were significantly higher in purified CRC cells than in total tumor tissues, suggesting that tumor cells are likely major contributors of these chemokines within CRC microenvironment. In contrast, purified tumor cells did not express CCL7, CCL8, CCL1 1 , CCL13, CCL17, and CCL27 genes (data not shown).

Remarkably, in vitro cultured CRC cell lines expressed fewer chemokine genes and to lower extents as compared to primary tumor cells, suggesting that chemokine expression in tumor cells may be stimulated by micro-environmental factors absent in vitro.

Example 6: Chemokine expression is induced in CRC cells bv gut-flora derived stimuli

Translocation of commensal bacteria or derived stimuli across altered epithelia was described in CRC. The inventors hypothesized that chemokine production in tumor cells might be triggered by gut flora-derived microbial stimuli. Indeed, CRC cells from primary tumors and established cell lines express TLRs potentially sensing them (Figure 6). Stimulation of CRC cells from cell lines (Figure 7) and CRC organoids (Figure 8) with TLR agonists induced upregulation of constitutively expressed chemokine genes, including CCL20, CXCL9, and CXCL10, and de novo expression of additional chemokine genes, including CCL3, CCL4, CCL5 and CCL22. In contrast, no CXCL12 expression was observed.

Upregulation of most chemokine genes was also induced upon exposure of CRC cells to bacterial species enriched in CRC tissues, including Fusobacterium nucleatum, Bacteroides fragilis, and Escherichia coli (18-20) (Figure 7 continued and Figure 8). Thus, microbial stimulation appears to be sufficient to partially recapitulate in cell lines chemokine expression profiles of primary CRC.

The inventors further investigated effects of gut commensal bacteria on chemokine expression in vivo. Levels of chemokine expression were evaluated in tumor xenografts generated in NSG mice upon i.p. or i.c. injection of human CRC cells from established cell lines. Strikingly, intra- cecal tumors displayed significantly higher levels of CCL5 (70-fold increase), CCL20 (19-fold increase), CXCL10 (12-fold increase) and CXCL1 1 (3-fold increase), as compared to i.p. xenografts (Figure 9 upper panels), suggesting that chemokine expression is strongly induced by exposure to gut flora. Importantly, antibiotic treatment of tumor bearing mice dramatically reduced tumor-derived chemokine expression in i.c. xenografts (Figure 9, upper panels indicating that commensal bacteria are main chemokine inducers in CRC cells. Indeed, expression levels of CCL20, CXCL10 and CXCL1 1 in xenografts significantly correlated with bacterial loads, as assessed by ribosomal subunit 16S expression (Figure 9, lower panels). Furthermore, gut flora composition analysis revealed a reduction of specific bacteria families within Bacteroidetes and Firmicutes in xenografts from antibiotic-treated as compared to untreated mice (Figure 10, upper and lower left panels and Table 7). Moreover, significant correlations between abundance of Rikenellaceae, Ruminococcace, and Lachnospiracee and expression levels of CCL5, CCL20, and CXCL1 1 were detected (Figure 10, lower right panel and Table 8).

Example 7: Gut microbiota in tumors correlate with extent of T cell infiltration

To assess actual impact of bacteria-induced chemokines on T cell recruitment into tumor tissues, the inventors adoptively transferred CRC-derived CD4+ and CD8+ TILs into tumor bearing NSG mice and evaluated their homing to i.p. or i.c. tumors. Strikingly, TILs migrated into i.c. xenografts to significantly higher extents than in i.p. tumors (Figure 1 1 ), indicating that presence of gut microbiota enhances T cell recruitment into xenografts.

However, only weak to moderate correlations were observed between 16S and IRF-1 (r=0.267; p=0.034), CCL3 ( r=0.457; p=0.0019), and CXCL12 (r=0.348;p=0.005), suggesting that specific bacteria families, rather than total bacterial loads, influence T cell recruitment into CRC tissues. The inventors therefore analyzed gut flora composition of CRC samples previously characterized for abundance of CD3+ infiltrates (Table 4, German cohort, n=27) and corresponding tumor-free tissues. Overall, the majority of detectable bacteria were represented by Bacteroidetes, Proteobacteria, and Firmicutes, Bacteroidetes and Firmicutes were slightly reduced in tumor tissues as compared to corresponding tumor-free tissues, whereas Fusobacteria were significantly increased (p=0.014, Figure 12). Unsupervised hierarchical analysis of operational taxonomic unit (OTU) abundances in tumor tissues, identified two main clusters: cluster 1 including 10/13 samples displaying low CD3 densities (CD3low), and cluster 2 including all 14 tumors displaying high CD3 densities (CD3high) plus 3 CD3low tumors (Figure 13, upper panel). Importantly, samples from cluster 1 displayed a prolonged overall and recurrence-free survival as compared to samples in cluster 2 (Figure 13 continued, panels 1 and 2). Specific bacterial genera, including Alloprevotella, Treponema, and Desulfovibrio, were significantly enriched in CD3high tumors, whereas, Prevotella, Bacteroides, and Fretibacterium, among others, were overrepresented in CD3low tumors (Figure 13 continued and Table 9). Expression of T cells markers and chemokine genes was also assessed in these samples. Consistent with results from previous cohort, CD8, IRF-1 , Foxp3 and CXCR5 were strongly associated with each other and with previously identified chemokine signatures (Figure 14 upper panel and Table 10). Unfortunately, correlations with IL-17 were not evaluable since this cytokine was poorly expressed in these samples. Most importantly, significant correlations between abundance of specific bacteria and expression of individual T cell markers and chemokines genes were observed. In particular, abundance of different families of Firmicutes, mainly including Lachnospiraceae and Ruminococcaceae, significantly correlated with expression of CCR5 and CXCR3 binding chemokines. Abundance of Proteobacteria was also associated with expression of all prognostically favorable T cell markers and most corresponding recruiting chemokines (Figure 14 lower panel and Table 1 1 ). Thus, expression of chemokine genes in human CRC tissues is associated with abundance of specific bacteria.

Example 8: Identification of specific consortia among bacterial species associated with high T cell infiltration and chemokine expression

Upon analysis of relative correlations between abundance of identified OTUs (Figure 15 and Table 14), the inventors observed that they cluster in two main groups. In particular, the inventors identified two bacterial consortia including 15 and 6 OTUs, respectively, corresponding to specific bacterial species, as listed in Table 15. These data suggest a symbiotic gut colonization potential of these bacteria for therapeutic application. Example 9: Discussion

Aim of this study was to elucidate the nature of chemotactic factors promoting infiltration of human CRC by T cell populations associated with favorable prognosis, and to gain insights on cellular sources and stimuli eliciting their production within CRC microenvironment. Based on correlations between expression of T cell markers and chemokines in freshly excised CRC tissues, and on chemokine receptor profiles of tumor infiltrating immune cells, the inventors identified prominent chemokine signatures associated with recruitment of individual immune cell populations into CRC tissues. In particular, expression of CCR3- and CCR5- binding chemokines, including CCL3, CCL4, CCL5, CCL7, CCL8, and CCL13, and of CXCR3 ligands, including CXCL9 and CXCL10, correlated with presence of both CTLs and Th1 cells. This may suggest that these subsets, expressing similar chemokine receptor patterns, may be concomitantly recruited. Indeed, in the sample cohort, a significant positive correlation between expression of CD8 and IRF-1 was detected.

More surprisingly, Th1 - and, to a lower extent, CTL-related signatures also partially overlapped with that associated with Tregs infiltration. Remarkably, both Th1 and Tregs markers were associated with expression of CXCL12, and of CCR4-ligands CCL17 and CCL22. Also, a weak but significant correlation was detected between Tregs infiltration and expression of CCL5 and CXCL9. Although unexpected, these findings are consistent with chemokine receptor profiles displayed by Tregs, largely resembling those of Th1 , and, to lower extents, of CTLs. Thus, within CRC tissues, recruitment of Tregs may parallel that of effector T cells. Accordingly, Foxp3 expression in CRC samples significantly correlated with that of both CD8 and IRF-1 genes.

In contrast, chemokine signatures associated with infiltration by Tfh and Th17 were clearly distinct, the first being exclusively represented by CXCL13, and the second by CCL20 and CCL17, and to lower extents CCL25, CCL27, and CCL28. Unexpectedly, however, in both cohorts analyzed, expression of CXCR5 and CXCL13 clustered with that of CD8, IRF-1 , Foxp3 and correlating chemokines, suggesting that infiltration by Tfh cells may also parallel that of CTLs, Th1 and Tregs. Thus, expression of CXCL13, by primary CRC cells, could be evoked by stimuli also inducing secretion of CTL, Th1 and Tregs recruiting chemokines (see below).

The inventors' work identifies tumor cells as important chemokine sources. CRC cells per se express a spectrum of chemokines relevant for the recruitment of favorable immune cells, including CCL3, CCL4, CCL5, CCL20, and CXCL10, binding receptors expressed by CTLs and Th1 cells. In contrast, genes encoding chemokines involved in recruitment of Tregs, including CCL17 and CCL22, although detected in CRC tissues, were rarely expressed by purified CRC cells, suggesting that they may be mainly produced by other cell types within tumor microenvironment.

Remarkably, CRC cells isolated from different samples displayed heterogeneous chemokine gene expression levels, possibly reflecting distinct molecular characteristics and/or exposure to different microenvironmental conditions. Differential genomic and epigenomic instability may at least partially explain heterogeneity of chemokine gene expression across different samples. Accordingly, different CRC cell lines, although maintained under comparable culture conditions, displayed variable degrees of chemokine production capacity.

Importantly, in vitro cultured cell lines generally display significantly lower chemokine gene expression levels than primary CRC cells, indicating that micro-environmental stimuli also play relevant roles in modulating chemokine gene expression. Previous studies showed that gut commensal bacteria translocated across the neoplastic epithelium may interact with tumor cells and induce direct pro-tumorigenic effects or release of pro-tumorigenic cytokines. However, their ability to modulate chemokine production by tumor cells was not evaluated so far. Strikingly, the inventors found that stimulation by gut commensal bacteria in vitro and in vivo induces in tumor cell lines upregulation or de novo expression of multiple chemokine genes, recapitulating profiles and levels of chemokine gene expression of primary CRC cells. Most interestingly, the inventors demonstrated that tumor cell exposure to gut bacteria ultimately results in higher T cell recruitment into tumor xenografts, revealing a role of gut commensal bacteria in controlling extent of tumor infiltration by beneficial immune cells.

Consistent with in vivo findings, the inventors found that extent of T cell infiltration in primary human CRCs is significantly associated with presence of specific bacteria families and genera. Furthermore, the inventors observed significant correlations between abundance of defined bacteria families and expression levels of specific chemokine genes, indicating that gut commensal bacteria trigger production of immune cell recruiting chemokines within tumor tissues. Importantly, composition of gut flora also predicted improved overall and recurrence- free survival. Notably, the cluster associated to more favorable prognosis also included three samples displaying low T cell infiltration, possibly suggesting that certain bacteria may favor recruitment of immune cells other than T cells, also beneficially impacting on clinical outcome, including neutrophils and NK cells. Although additional studies are warranted to elucidate potential interactions between gut microbiota and other immune cell populations, it is tempting to speculate that gut flora composition in CRC patients may concur with tumor genetic characteristics to determine extent and quality of immune cell infiltration ultimately steering clinical outcome.

In in vitro experiments the inventors found that different species of CRC-associated bacteria, including Escherichia coli and Bacteroides fragilis, may promote, although to different extents, expression of T cell recruiting chemokine genes. Ex-vivo analysis of human samples showed that Firmicutes, and in particular Lachnospiraceae and Ruminococcaceae, although represented in gut flora to lower extents than other phyla, are mostly associated with expression of T cell recruiting chemokines. Furthermore, abundance of Bacteroides and, Proteo bacteria, also correlated with expression of most T cell recruiting chemokines and with tumor infiltration by all T cell subsets predictive of good prognosis. Notably, defined bacteria types were associated with expression of multiple chemokine encoding genes, possibly indicating their capacity to promote simultaneous recruitment of different T cell populations. This is consistent with the clustering of the expression of CD8, Th1 , Foxp3 and CXCR5 observed in clinical samples, characterized by favorable prognosis.

Molecular mechanisms mediating the cross-talk between CRC cells and gut bacteria also remain to be elucidated. Colon epithelial cells are capable of sensing gut microorganism through pattern recognition receptors (PRRs), including TLRs. The inventors' data suggest that bacteria-induced chemokine gene expression may be initiated by TLR triggering on tumor cells. Indeed, the inventors observed TLRs expression on primary CRC cells. Furthermore, stimulation with purified TLR agonists resulted in marked induction of chemokine gene expression in CRC cells. However, further studies are warranted to precisely identify which TLRs, and, possibly, other PRRs, are engaged by individual CRC associated bacterial species.

In conclusion, this study identifies tumor cells as a major chemokine source in CRC and reveals the key role played by gut microbiota in triggering chemokine production ultimately leading to T cell recruitment in tumor tissues and improved prognosis.

Table 7. Fold changes (log2) of OTU abundances in intra-cecal tumor from untreated versus antibiotic-treated mice.

Table 8. Correlations between OTU abundance and chemokine gene expression levels in intra-cecal tumors developed in untreated mice.

* Significant correlation coefficients >0.3 and p-value <0.05 are indicated in bold.

Table 9. Relative OTU abundance in CD3 hi versus CD3 low tumors.

Sequences

SEQ ID NO 01 GCT GCC TCC CGT AGG AGT EUB338 sense probe

SEQ ID NO 02 ACT CCT ACG GGA GGC AGC EUB338 anti-sense probe SEQ ID NO 03 GTGCCAGCMGCCGCGGTAA primer 515F

SEQ ID NO 04 GGACTACHVG G GT WT CTA AT primer 806R

SEQ ID NO 05 TCC TAC GGG AGG CAG CAG T Microsynth primer forward SEQ ID NO 06 GGACTACCAGGGTATCTAATCCTGTT Microsynth primer reverse SEQ ID NO 07 CGTATTACCGCGGCTGCTGGCAC Microsynth Probe