INHIBITORS AND RELATED METHODS

FIELD OF THE INVENTION

The present invention belongs to the field of personalized medicine. More specifically, the invention relates to biomarkers, namely NOCIVA and optionally ARPP19, for use in a predicting response to treatment with tyrosine kinase inhibitors in subjects with haematological cancer, such as CML, ALL or AML. Use of said biomarkers for related purposes is also envisaged. Moreover, said biomarkers not only facilitate disease management of subjects with haematological cancers but could also be employed in clinical trials of drug candidates.

BACKGROUND OF THE INVENTION

Chronic myeloid leukaemia (CML), also known as chronic myelogenous leukaemia, accounts for about 15-25% of all adult leukaemias. CML is associated with a chromosomal translocation called the Philadelphia chromosome, and it is characterized by the increased and unregulated growth of myeloid cells in the bone marrow and the accumulation of these cells in the blood. The translocation is also found in acute lymphoid leukemia (ALL), as well as in rare cases of acute myeloid leukemias (AML).

Targeted drugs called tyrosine-kinase inhibitors (TKIs) have revolutionized the treatment of CML and led to dramatically improved long-term survival rates. In summary, the first-generation TKI imatinib, which is extremely safe and potentially quite cheap, has been reported to lead to long-term optimal response in approximately 60% of patients. Second generation TKIs dasatinib and nilotinib are licensed for first-line therapy based on data from phase III clinical trials (DASISION and ENESTnd). These trials suggest that both dasatinib and nilotinib are superior drugs when compared with standard dose imatinib (Saglio et al. NEJM, 2010, 362: 2251-2259; Kantarjian et al. NEJM, 2010, 362: 2260-2270). In individual patients, the survival advantage may largely depend on a particular TKI.

Acute myeloid leukaemia (AML) is the most common acute leukaemia affecting adults. Incidence of AML is 2 to 3 new cases per 100 000 inhabitants per year. AML is a heterogeneous clonal haematological malignancy that disrupts normal hematopoiesis and it is one of the most aggressively progressive cancer types. First curative therapies for AML were developed in the 1970s-80s and before this, patients with AML had a dismal prognosis of only three months. In the 2010s, 50% of the patients with AML under age 60-65 can obtain a full remission.

Advances in understanding the genetic diversity of AML have enabled identification of prognostic subgroups within AML cases. Classification of AML subtypes is also clinically relevant in order to optimize treatment strategies and to reduce treatment related mortality and relapse risk. Patients in good progno sis risk category are treated with chemotherapy, which allows up to 70% of the patients to go to full remission. Alternatively, treatment for those intermediate and poor prognosis patients for which it is suitable, is allogeneic stem cell trans plantation, which remains as a dangerous procedure with many possible complications with mortality of 30%. Side effects related to transplantation can also be short-term, lasting from weeks to months, or long-term that can last years or a lifetime.

Tyrosine kinases play a critical role also in AML. Indeed, TKls show an interesting clinical potential at least in certain subsets of AML patients. For example, imatinib shows interesting clinical activity in a subset of patients with c- kit-positive AML (Kindler et al. Blood, 2004, 103: 3644-3654), while dasatinib show clinical potential in a rare subtype of AML, namely BCR-ABL-positive AML (Xiaoyan Shao et al. Medicine, 2018, 97: 44).

Protein Phosphatase 2A (PP2A) is a trimeric (A-B-C subunits) tumor suppressor complex. In cancer cells, the tumor suppressor activity of PP2A is inhibited. However, the PP2A complex proteins are mutated with rather low frequency in all cancer types. Instead, the most prevalent mode of PP2A inhibition in cancer seems to be the overexpression of PP2A inhibitor proteins, such as cancerous inhibitor of PP2A (C1P2A or K1AA1524). C1P2A overexpression associates with poor patient prognosis in more than dozen human solid cancer types (Khanna and Pimanda, Int J Cancer, 2016, 138: 525-532). In CML, a high C1P2A protein level is a predictor of subsequent progression to blast crisis (Lucas et al. Blood, 2011, 117: 6660-6668). On the other hand, the clinical relevance of C1P2A in AML is unclear as no correlation between C1P2A mRNA levels and clinical outcome has been seen (Lucas et al., Blood Advances, 2018, 2: 964-968).

NOC1VA is a novel variant of C1P2A. At mRNA level, the variant comprises exons 1-13 of C1P2A fused C-terminally to a part of the intron between exons 13 and 14 in K1AA1524 gene. NOC1VA transcript thus formed is a unique and previously unknown sequence, wherein the intronic sequence is in a coding frame with a preceding C1P2A mRNA sequence, and after 40 nucleotides, corresponding to 13 amino acids, is followed by classical stop codon (translation termination) TAA. Thus, the NOC1VA gene product codes for a truncated C1P2A protein with 13 new amino acids (NNKNTQEAFQVTS) at the C-terminal end. Importantly, this 13 aa peptide sequence does not match with any known protein sequence in the human proteome based on a Blast homology search. No previous identification of disease relevance of NOC1VA has been reported.

ARPP19 (cAMP-regulated phosphoprotein 19), also known as ARPP- 19, a member of the alpha-endosulfine (ENSA) family, is ubiquitously expressed mitotic PP2A inhibitor that promotes the G2/M transition and the mitotic state. ARPP19 requires phosphorylation of a conserved serine residue (Ser-62) by the Greatwall kinase (mammalian Greatwall orthologue is MAST -like kinase) in order to bind PP2A and subsequently inhibit PP2A activity towards a physiological CDK1 substrate. W02011/066660 discloses ARPP19 as a member of a leukaemia stem cell signature comprising the expression profile of 80 genes. However, ARPP19 is not disclosed, nor suggested, as a predictive biomarker of response to TK1 treatment.

There is an identified need in the art for the development of sensitive, specific and non-invasive means and methods assessing or predicting drug efficacy in the treatment of subjects with haematological cancers. The present invention addresses this emerging but unmet medical need by providing biomarker-based methods for use in selecting the optimal TK1 on the basis of biological markers of treatment response. Consequently, patients with a high risk of drug resistance can potentially be identified at diagnosis and treated accordingly.

Ideal biomarkers would not only facilitate disease management of patients with haematological cancers but could also be employed in clinical trials of drug candidates.

BRIEF DESCRIPTION OF THE INVENTION

An object of the present invention is to provide means and methods for predicting a response of a particular patient to TKls. The invention is defined by the appended claims.

In one aspect, the invention provides an in vitro method of predicting whether a subject with haematological cancer is likely to have a positive response to a treatment with a first generation tyrosine kinase inhibitor (TK1), the method comprising: (a) determining a level of N0C1VA expression in a sample obtained from the subject;

(b) comparing the determined expression level to a relevant control, preferably to that of an apparently healthy subject, and

(c) predicting whether the subject is likely to have a positive response to the TK1 on the basis of the comparison.

In some embodiments of the method, low expression level of NOC1VA as compared to the control indicates that the subject is likely to have a positive response to the first generation TK1. On the other hand, in some other embodiments, high expression level of NOC1VA as compared to a control indicates that the subject is not likely to have a positive response to the first generation TK1.

In some further embodiments of the method, the method further comprises predicting whether a subject with haematological cancer is likely to have a positive response to a treatment with a second generation TK1, the method comprising:

(d) determining a level of ARPP19 expression in a sample obtained from the subject;

(e) comparing the determined expression level to a relevant control, preferably to that of an apparently healthy subject, and

(f) predicting whether the subject is likely to have a positive response to the TK1 on the basis of the comparison.

In some yet further embodiments of the invention, low expression level of ARPP19 as compared to the control indicates that the subject is likely to have a positive response to the second generation TK1. On the other hand, in some still further embodiments, high expression level of ARPP19 as compared to the control indicates that the subject is not likely to have a positive response to the second generation TK1.

Consequently, treatment with a second or third generation TK1 is recommended for the subject with high NOC1VA expression. For the subject with low NOC1VA expression, treatment with a first generation TK1 is recommended. Alternatively or additionally, treatment with a third or further generation TK1, and/or enhanced monitoring for disease progression is recommended for the subject with high NOC1VA and high ARPP19 expression. For the subject with high NOC1VA and low ARPP19 expression, treatment with a second generation TK1 is recommended. Also provided are methods for selecting or recommending or assigning a treatment to a subject with haematological cancer, or for assessing the efficacy of a TKI in the treatment of haematological cancer, based on determinations of NOCIVA or NOCIVA and ARPP19 expression levels in a sample obtained from the subject.

In a further aspect, the invention provides a kit for use in the methods set forth herein. The kit comprises one or more reagents specific for NOCIVA, or one or more reagents specific for NOCIVA and ARPP19. Also provided is use of said kit for carrying out the methods set forth herein.

Other objectives, aspects, embodiments, details and advantages of the present invention will become apparent from the following figures, detailed description, examples, and dependent claims.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following the invention will be described in greater detail by means of preferred embodiments with reference to the attached drawings.

Figure 1A. Kaplan-Meier survival curve for event free survival (EFS) by NOCIVA gene expression in imatinib treated chronic myeloid leukaemia (CML) patient cohort (n=20). Median serves as cut-off value. Higher NOCIVA expression is associated with significantly shorter EFS in imatinib treated CML patients (p=0.004 by log-rank test).

Figure IB. Kaplan-Meier survival curve for time to complete molecular response (CMR) by NOCIVA gene expression in imatinib treated CML patient cohort (n=20). Patients with high diagnostic NOCIVA expression had significantly inferior time to CMR (p=0.04 by log-rank test).

Figure 1C. Imatinib treated CML patients with low NOCIVA expression had a higher rate of early molecular response (EMR), although this did not reach statistical significance (p>0.05).

Figure ID. Kaplan-Meier survival curve for EFS by NOCIVA gene expression in second-generation tyrosine kinase inhibitor (2G TKI) treated CML patient cohort (n=14). Median serves as cut-off value. No significant difference in the EFS times of the groups could be detected in this cohort (p=0.43 by log-rank test).

Figure IE. Kaplan-Meier survival curve for CMR by NOCIVA gene expression in 2G TKI treated CML patient cohort (n=14). No significant difference in the CMR times of the groups could be detected in this cohort (p=0.12 by log- rank test).

Figure IF. 2G TKI treated CML patients with high NOCIVA expression had a slightly higher rate of EMR, but this did not reach any statistical significance (p>0.05).

Figure 2A. Pearson’s correlation for RNA-seq based ARPP19 mRNA expression and responses of patient-derived AML cells (n=39) against indicated drugs in MCM (mononuclear cell medium). Negative values indicate significant (P < 0.05) resistance to indicated drug in samples with high ARPP19 mRNA expression.

Figure 2B. ARPP19 protein expression across indicated AML human cell lines. Based on results MOLM-14 and Kasumil are considered as low ARPP19 expressing cell lines whereas HL-60 and KG1 are considered as high ARPP19 expressing cell lines.

Figure 2C. Validation of resistance to 2nd generation tyrosine kinase inhibitor (2G TKI) Dasatinib in high ARPP19 expressing AML cell lines (HL-60 and KG1) in MCM medium. Other tested drugs did not show exclusive correlation between drug response and ARPP19 protein levels.

Figure 2D. High ARPP19 expressing AML cell lines (HL-60 and KG1) show resistance to 2G TKI drug, Dasatinib, in MCM medium.

Figure 3A. Imatinib treated CML patients (n=20) did not show any correlation in response to therapy and diagnostic ARPP19 mRNA expression status. Shown is median with 95% confidence interval (Cl). ARPP19 high (n=5) vs. ARPP19 low (n=15), p=0.74 by Mann-Whitney test.

Figure 3B. 2G TKI treated CML patients that had diagnostic low ARPP19 mRNA expression (n=9) had significantly longer event free survival in 2G TKI treated CML patient cohort (n=14), when comparing to diagnostic high ARPP19 mRNA expressing patients (n=5). Shown is median with 95% confidence interval (Cl). ARPP19 high vs. ARPP19 low, p=0.04 by Mann-Whitney test.

Figure 4A. A schematic presentation of the present method of predicting response to treatment and/or selecting or recommending an effective treatment to subjects with haematological cancer.

Figure 4B. A schematic presentation of an embodiment of the present method of predicting response to treatment and/or selecting or recommending an effective treatment to subjects with haematological cancer.

Figure 5A. NOCIVA expression in 158 CML patients stratified by whether the patient subsequently progressed to blast crisis. RQ = relative quantification.

Figure 5B. NOCIVA expression in 158 CML patients stratified by TKI (imatinib, n=80; dasatinib, n=78) and whether the patient subsequently progressed to blast crisis. Imatinib-treated patients who subsequently progressed to blast crisis had significantly higher expression of NOCIVA at diagnosis than those patients who did not progress (p=0.04). RQ = relative quantification.

Figure 6A. Freedom from progression (FFP) i.e. the number of patients who progressed to blast crisis over time for 158 CML patients with low or high NOCIVA expression.

Figure 6B. FFP for imatinib-treated (n=80) CML patients with low or high NOCIVA expression.

Figure 6C. FFP for dasatinib-treated (n=78) CML patients with low or high NOCIVA expression.

Figure 7A. FFP for 158 CML patients stratified into quartiles based on NOCIVA expression. Quartile 1 had the lowest NOCIVA expression and quartile 4 had the highest NOCIVA expression. A trend not reaching statistical significance is shown that patients with high NOCIVA expression (4th quartile) at diagnosis had inferior FFP.

Figure 7B. FFP for imatinib-treated (n=80) CML patients stratified into quartiles based on NOCIVA expression. A significantly inferior FFP (p=0.04) is shown for patients with high NOCIVA expression at diagnosis (4th quartile). FFP is expressed as percent survival.

Figure 7C. FFP for Dasatinib-treated (n=78) CML patients stratified into quartiles based on NOCIVA expression. No statistically significant impact on FFP is shown in any of the quartiles.

Figure 8A. FFP for 158 CML patients stratified into quartiles based on C1P2A expression. Quartile 1 had the lowest C1P2A expression and quartile 4 had the highest C1P2A expression. No statistically significant impact on FFP is shown in any of the quartiles.

Figure 8B. FFP for imatinib-treated (n=80) CML patients stratified into quartiles based on C1P2A expression. No statistically significant impact on FFP is shown in any of the quartiles.

Figure 8C. FFP for dasatinib-treated (n=78) CML patients stratified into quartiles based on C1P2A expression. No statistically significant impact on FFP is shown in any of the quartiles. DETAILED DESCRIPTION OF THE INVENTION

The methods provided herein are based, at least in part, on the surprising discovery that the expression level of NOCIVA or NOCIVA and ARPP19 can be used to predict whether a subject with a myeloid disease is likely or unlikely to respond to a specific type or class of tyrosine kinase inhibitors (TKIs). Accordingly, the determined expression level of NOCIVA or NOCIVA and ARPP19 can accurately determine, discriminate between and/or stratify which type or class of TKIs should be selected or recommended for the treatment of a haematological cancer and/or administered to subject for the treatment of a haematological cancer.

As used herein, the term "or" has the meaning of both "and"' and "or" (i.e. "and/or"). Furthermore, the meaning of a singular noun includes that of a plural noun and thus a singular term, unless otherwise specified, may also carry the meaning of its plural form. In other words, the term "a" or "an" may mean one or more.

As used herein, the term "subject" refers to an animal, preferably to a mammal, more preferably to a human. The term includes, but is not limited to, mammalian animals such as domestic animals such as livestock, pets and sporting animals. Examples of such animals include without limitation carnivores such as cats and dogs and ungulates such as horses. Thus, the present invention may be applied in both human and veterinary medicine. Herein, the terms "subject", "patient" and "individual" are interchangeable.

As used herein, the term "apparently healthy" refers to a subject or a pool of subjects who show no signs of a haematological cancer or its subtype in question, and thus are believed not to be affected by said cancer or its subtype in question and/or who are predicted not to develop said cancer or its subtype in question.

As used herein, the term "haematological cancer" refers to a malignancy affecting blood, bone marrow or lymph nodes. Haematological cancers are referred to as leukaemia, lymphoma and myeloma depending on the type of cell affected. Lymphoma is a group of blood cancers that develop from lymphocytes. Multiple myeloma, also known as plasma cell myeloma, is a cancer of plasma cells.

As used herein, the term "leukaemia" refers to a cancer which starts in blood-forming tissue, usually the bone marrow, and affects white blood cells. Leukaemia can be classified by the type of white cell affected (myeloid or lym- phatic). Non-limiting examples of leukaemias include acute myeloid leukaemia (AML), chronic myeloid leukaemia (CML), acute lymphoid leukaemia (ALL), acute promyelocytic leukaemia (APL), and subgroups thereof. In some embodiments, AML and CML may be called collectively as "myeloid disorders".

As used herein, the term "tyrosine kinase inhibitor" (TKI) refers to a pharmaceutical drug that inhibits tyrosine kinases, which are enzymes that are responsible for the activation of many proteins by signal transduction cascades. Tyrosine kinases activate their target proteins by adding a phosphate group to the protein, a step that TKIs inhibit.

As used herein, the term "BCR-ABL1 TKI" refers to a class of TKIs that selectively inhibit a constitutively active BCR-ABL1 tyrosine kinase that has been implicated in the pathogenesis of CML, ALL and a subset of AML cases. The term encompasses all current and future BCR-ABL1 TKIs irrespective of the generation thereof.

As used herein, the term "first-generation BCR-ABL1 TKI" (1G TKI) refers to the original BCR-ABL1 TKI imatinib.

Mechanisms of imatinib resistance are classically divided into two types. BCR-ABLl-independent mechanisms involve mainly increased drug efflux/decreased uptake and activation of alternative onco-pathways. BCR-ABL1- dependent mechanisms, in turn, are mainly due to point mutations of BCR-ABL1 that alter inhibitor binding or conformational changes. Minor reasons for BCR- ABLl-dependent resistance involve gene amplification or hyperexpression.

As used herein, the term "second-generation BCR-ABL1 TKI" (2G TKI) refers to BCR-ABL1 TKIs developed with the aim to override the BCR-ABL1- dependent resistance by loosening conformational and binding requirements without loosing specificity. 2G TKIs solve almost the entirety of BCR-ABL1 mutations except for T351I. Generally, 2G TKIs show decreased resistance and intolerance as compare to imatinib. Currently available clinically approved 2G TKIs include nilotinib, dasatinib, and bosutinib. However, the term 2G TKI is not limited to the TKIs listed herein.

The T351I mutation frustrates the action of 2G TKIs through two potent mechanisms: break of a H-b and strong stabilization of the active DFG-in conformation. Notably, the T351I mutation prevents conformational changes of the Bcr-Abll protein from active to inactive form, therefore conferring resistance to several DFG-out inhibitors. This obstacle is overcome by third-generation TKIs.

As used herein, the term "third-generation BCR-ABL1 TKI" (3G TKI) refers to BCR-ABL1 TKIs developed with the aim to override the T351I- dependent resistance. To date the only approved 3G TKI is ponatinib. However, the term 3G TKI is not limited to ponatinib.

Further BCR-ABL1 TKIs developed since the advent of 2G TKIs but which have not yet entered common clinical practice for neither CML nor ALL include, but may not be limited to, bafetinib, rebastinib, tozasertib, danusertib, HG-7-85-01, GNF-2 and -5, and 1,3,4-thiadiazole derivatives. Further molecules are likely to enter the clinics in the near future to overcome persistent resistances.

As used herein, the terms "treatment" and "treating", and the like, refer to the administration of a TKI to a subject in need thereof for purposes which may include ameliorating, lessening, inhibiting, or curing a haematological cancer, such as CML or AML. Amounts and regimens for the administration of TKI may be determined readily by those with ordinary skill in the clinical art of treating haematological cancers. Generally, the dosage of the TKI treatment will vary depending on considerations such as: age, gender and general health of the patient to be treated; kind of concurrent treatment, if any; frequency of treatment and nature of the effect desired; duration of the symptoms; and other variables to be adjusted by the individual physician. A desired dose can be administered in one or more applications to obtain the desired results, using any appropriate route of administration. In addition, TKI treatment may be used alone or in combination i.e. administered simultaneously, separately or sequentially with other pharmaceutical drugs or treatment modalities.

As used herein, the term "effective amount" refers to an amount of pharmaceutical drug, such as TKI, by which harmful effects of the haematological cancer are, at a minimum, ameliorated.

As used herein, the term "likely to respond" refers to an above-average likelihood, chance or probability that a subject will have a positive response to treatment. In other words, a subject having a positive response to treatment can be regarded as a subject who is sensitive to said treatment.

As used herein, the term "not likely to respond" refers to an above- average likelihood, chance or probability that a subject will not have a significant positive response to treatment. In other words, a subject not having a significant positive response to treatment can be regarded as a subject who is resistant to said treatment.

As used herein, the term "resistant" with respect to a treatment refers to lack of significant reduction in the severity a subject’s disease, or lack of significant amelioration of one or more symptoms of the disease despite the treatment. Drug resistance may manifest itself as an increased relapse risk.

As used herein, the term "relapse" refers to a recurrence of a past medical condition or the signs and symptoms thereof after a period of improvement.

As used herein, the term "positive response" with respect to a treatment refers to at least a partial significant reduction in the severity, and amelioration of one or more symptoms of a subject’s disease, or significantly slowed or halted disease progression, in a way that the prognosis of a subject is significantly improved as a result of the selected treatment. "Prolonged overall survival", "prolonged progression-free survival", "prolonged event-free survival", "early molecular response", "faster complete cytogenetic response", "faster major molecular response" and "faster complete molecular response" when compared to the median outcome of the disease for example, are non-limiting examples of a positive response. Further examples of a positive response include remission and a curative response.

As used herein, the term "overall survival" (OS) refers to the length of time from either the date of diagnosis or the start of treatment for a disease that patients diagnosed with the disease are still alive.

As used herein, the term "progression-free survival" (PFS) refers to the length of time during and after the treatment of a disease that a patient lives with the disease but it does not get worse. In CML and AML, the term "progression" refers to disease progression from chronic phase to blast crisis, which is usually fatal.

As used herein, the term "event free survival" (EFS) refers to the length of time after primary treatment that the patient remains free of certain complications or events that the treatment was intended to prevent or delay. Herein, "events" were defined by the first occurrence of any of the following: death from any cause during treatment, progression to the accelerated phase or blast crisis, or loss of a cytogenetic response.

As used herein, the term "early molecular response" (EMR) refers to a BCR-ABL1/ABL1 ratio of <10% following 3 months of treatment. Patients who achieved an EMR have a superior overall survival and a reduced risk of disease progression.

As used herein, the term "time to complete cytogenetic response (CCR)" refers to the length of time required for achieving 0% Ph+ metaphases by conventional cytogenetics or BCR-ABL1/ABL1 ratio of 1%.

As used herein, the term "time to major molecular response (MMR)" refers to the length of time required for achieving a BCR-ABL1/ABL ratio of 0.1% or less. This may also be described as a 3 log reduction from baseline/ diagnosis.

As used herein, the term "time to complete molecular response (CMR)" refers to the length of time required for achieving no detectable BCR-ABL1 transcripts in two consecutive samples with good quality control values.

As used herein, the term "remission" refers to the disappearance of the signs and symptoms of a disease. A remission can be temporary or permanent.

As used herein, the term "freedom from progression (FFP)" refers to the number (expressed typically as percentage) of patients progressing to blast crisis over time. FFP is herein, e.g. in figures 6-8, indicated as percentage of patients not in blast crisis, which percentage is initially 100% and may diminish over time as some or all patients progress to blast crisis.

As used herein, the term "NOCIVA" refers to a variant of cancerous inhibitor of PP2A (CIP2A or KIAA1524). At mRNA level, the variant comprises exons 1-13 of CIP2A fused C-terminally to a part of the intron between exons 13 and 14 in KIAA1524 gene. NOCIVA transcript thus formed is a unique and previously unknown sequence, wherein the intronic sequence is in a coding frame with a preceding CIP2A mRNA sequence, and after 40 nucleotides, corresponding to 13 amino acids, is followed by classical stop codon (translation termination) TAA. Thus, the NOCIVA gene product codes for a truncated CIP2A protein with 13 new amino acids (NNKNTQEAFQVTS; SEQ ID NO: 3) at the C-terminal end. Importantly, this 13 aa peptide sequence does not match with any known protein sequence in the human proteome based on a Blast homology search. The nucleic acid sequence set forth in SEQ ID NO: 1 represents the complementary DNA (cDNA) sequence of NOCIVA mRNA, while the amino acid sequence of NOCIVA polypeptide is set forth in SEQ ID NO: 2. SEQ ID NO: 3 corresponds to amino acids 546-558 of SEQ ID NO: 2.

As used herein, the term "ARPP19" (cAMP-regulated phosphoprotein 19, also known as ARPP-19) refers to a protein phosphatase inhibitor that specifically inhibits PP2A during mitosis.

As used herein, the term "high expression" refers to an expression level of a biomarker that is higher in a sample under analysis than in a relevant control sample, or exceeds a control value. High expression level can be determined qualitatively and/or quantitatively according to standard methods known in the art. In some embodiments, the term "high expression" refers to a statistically significantly higher level or amount of the biomarker as compared with that of a relevant control.

As used herein, the term "low expression" refers to an expression level of a biomarker that is lower in a sample under analysis than in a relevant control sample, or is below a control value. Low expression level can be determined qualitatively and/or quantitatively according to standard methods known in the art. In some embodiments, the term "low expression" refers to a statistically significantly lower level or amount of the biomarker as compared with that of a relevant control.

In some embodiments, the term "relevant control" refers to a mean expression level of a biomarker in question in a sample obtained from apparently healthy subjects. In some other embodiments, the term "relevant control" refers to a mean expression level of a biomarker in question in subjects with the haematological cancer in question. Accordingly, the term "relevant control" may refer not only to a control sample but also to a control value obtained from a control sample.

As used herein, the term "sample" refers to a biological or clinical sample obtained from a subject. Preferred sample types include bone marrow samples obtained e.g. by a biopsy or aspiration, and blood samples, such as whole blood, serum, plasma, fractionated or non-fractionated peripheral blood mononuclear cells (PBMCs) or any purified blood cell type.

In the studies leading to the present invention, clinical samples obtained from newly diagnosed chronic phase CML patients were analysed for the mRNA expression level of NOC1VA, or C1P2A, or NOC1VA and ARPP19. Based on the results, the patients were stratified into high or low expressing groups. Correlation analyses were then carried out to study the relationship between the expression level (high or low) and the clinical outcome after treatment with either imatinib, dasatinib or nilotinib. According to the results, low expression level of NOC1VA indicates that the subject is likely to respond to a first generation TK1, whereas high expression level of NOC1VA indicates that the subject is not likely to respond to a first generation TK1. On the other hand, low expression level of ARPP19 indicates that the subject is likely to respond to a second generation TK1, whereas high expression level of ARPP19 indicates that the subject is not likely to respond to a second generation TK1. Thus, subjects with high NOC1VA expression should be assigned to or recommended or selected a treatment with a second or third generation TKIs, and subjects with low NOC1VA expression should be assigned to or recommended or selected a treatment with first generation TKIs. Typically, as indicated by the results of the studies herein, a treatment with 2G TKIs is sufficient for subjects with high NOC1VA expression.

Notably, subjects with high ARPP19 expression are at high relapse risk and should be assigned to or recommended or selected a treatment with third- or further generation TKIs, subjected to investigational protocols and/or monitored carefully for disease progression. Thus, subjects with high NOC1VA and high ARPP19 expression should be assigned to or recommended or selected a treatment with third or further generation TKIs, and/or enhanced monitoring for disease progression. Subjects with high NOC1VA and low ARPP19 expression should be assigned to or recommended or selected a treatment with second generation TKIs.

The results set forth above may be used to formulate a prognostic scheme described in Figure 4A, wherein subjects with low expression level of NOC1VA are likely to respond to a 1G TK1 (imatinib) whereas subjects with high expression level of NOC1VA are likely not to respond to a 1G TK1 (imatinib) but are likely to respond to a 2G or 3G TK1, preferably to a 2G TK1.

In some aspects of the invention, the patients are analysed also for ARPP19 in order to distinguish subjects who are likely to respond to a 2G TK1 from those subjects who are not (Figure 4B). In accordance with the present results, low expression level of ARPP19 indicates that the subject is likely to respond to a 2G TK1, whereas high expression level of ARPP19 indicates that the subject is not likely to respond to a 2G TK1 and should therefore be assigned to treatment with more potent TKIs or investigational protocols and/or be monitored carefully for disease progression. Thus, in some embodiments, it may be enough to carry out the NOC1VA assay or test without the ARPP19 assay or test, or vice versa, as readily understood by those skilled in the art. In some other embodiments, both the NOC1VA and ARPP19 assay or test are to be carried out.

In the studies leading to the present invention, a high NOC1VA gene expression level was shown to be associated with an inferior FFP for 1G TK1 treated patients but not with 2G TK1 treated patients, whereas C1P2A gene expression level (determined as mRNA expression) showed no statistical significance or association with FFP regardless of the type of TK1 (1G or 2G) treatment received. Accordingly, NOC1VA surpasses the performance of C1P2A in all aspects of the invention including methods of predicting the response to treatment with a TKI, treatment selection or recommendation, or assigning treatment, or treatment efficiency assessment.

Accordingly, in one aspect the present invention provides an in vitro method of predicting response to a TKI in a subject with haematological cancer, based on the determination of the expression level of NOCIVA in a sample obtained from said subject as set forth above. In a further aspect, the present invention provides an in vitro method of predicting response to a TKI in a subject with haematological cancer, based on the determination of the expression level of NOCIVA and ARPP19 in a sample obtained from said subject as set forth above. Thus, NOCIVA or NOCIVA and ARPP19 determinations may provide substantial help in clinical decision making in choosing appropriate treatment procedures. In other words, NOCIVA or NOCIVA and ARPP19 determination may be used for stratifying subjects for different treatment modalities.

In a related aspect, the present invention provides an in vitro method for assessing the efficacy of a TKI in the treatment of a subject with haematological cancer, based on the determination of the expression level of NOCIVA in a sample obtained from said subject as set forth above. In a further related aspect, the present invention provides an in vitro method for assessing the efficacy of a TKI in the treatment of a subject with haematological cancer, based on the determination of the expression level of NOCIVA and ARPP19 in a sample obtained from said subject as set forth above.

In another related aspect, the present invention also provides an in vitro method of selecting or recommending a type or a class of TKIs for the treatment of a haematological cancer in a subject in need thereof, based on the determination of the expression level of NOCIVA or optionally NOCIVA and ARPP19 in a sample obtained from said subject. In accordance with the present invention, a 1G TKI (imatinib) should be selected for or recommended to those subjects whose NOCIVA expression level is low. On the other hand, a 2G or 3G TKI should be selected for or recommended to those subjects whose NOCIVA expression level is high. A 2G TKI should be selected for or recommended to those subjects whose NOCIVA expression level is high but ARPP19 expression is low. Third or further generation TKI should be selected for or recommended to those subjects with high expression levels of both NOCIVA and ARPP19.

In some embodiments, the present methods for response to treatment predictions, treatment efficacy assessments, assigning treatments, and treatment selections or recommendations may be used in combination with any known methods and assays for the same or related purpose.

In a further aspect, the present invention provides an in vitro method for monitoring treatment response predictions, treatment efficacy assessments, assigning treatments, and treatment selections or recommendations in a subject with haematological cancer, based on the determination of the expression level of NOCIVA or optionally NOCIVA and ARPP19 in a sample obtained from said subject. Such a monitoring method involves analysing one or more serial samples obtained from the subject at different time points. The number and interval of the serial samples may vary as desired. The difference between the obtained determination results serves as an indicator of the course of the haematological cancer.

In some implementations, the present methods for response to treatment predictions, treatment efficacy assessments, and treatment selections or recommendations may further include therapeutic intervention. Once a subject is identified to exhibit a given probable response to treatment, he/she may be subjected to the treatment that is predicted to be effective. Thus, in some embodiments, the present invention provides a method for treating haematological cancer in a subject in need thereof or assigning the subject to a treatment by determining whether the subject will respond to a certain TKI based on the expression level of NOCIVA or optionally NOCIVA and ARPP19 as set forth above, and then administering to said subject an effective amount of a TKI that is predicted to be effective. In the method, a sample obtained from the subject prior to treatment is contacted with one or more reagents that specifically detect NOCIVA or optionally NOCIVA and ARPP19, and determining whether or not the expression of NOCIVA or optionally NOCIVA and ARPP19 is increased or decreased in said sample by comparing said expression with a relevant control. If or in case the expression level of NOCIVA is low, the subject should be assigned to 1G TKI (imatinib) treatment. If or in case the expression level of NOCIVA is high, the subject is unlikely to respond to imatinib, and should be assigned to a treatment with 2G or 3G TKI. In a further embodiment, the subject is further tested for ARPP19 expression. If or in case the expression level of NOCIVA is high and of ARPP19 is low, the subject should be assigned to a treatment with 2G TKI, such as nilotinib or dasatinib. However, if or in case the expression level of both NOCIVA and ARPP19 is high, the subject is unlikely to respond to 2G TKI, and should therefore be assigned to a treatment with more potent TKIs or even investigational protocols. Alternatively or in addition, subjects with high expression levels of both NOC1VA and ARPP19 should be monitored for disease progression more frequently than usual.

The present invention provides advantages not only for individual patient care but also for better selection and stratification of patients for clinical trials. For example, cancer patients grouped on the basis of their NOC1VA or NOC1VA and ARPP19 expression levels could be employed in clinical studies with the aim of developing efficient new personalized therapeutic tools such as new medical procedures or drugs.

Determining the expression level of NOC1VA or NOC1VA and ARPP19 may be carried out by any available or future means suitable for this purpose. Said determination may be executed at different molecular levels, preferably at mRNA, cDNA, or protein level as is well known in the art. The present invention is not limited to any determination technique. Thus, in different embodiments, different means or combinations thereof for analysing a clinical sample for the expression of NOC1VA or NOC1VA and ARPP19 may be used. For the sake of simplicity, in the following description of suitable detection techniques, the term "biomarker" is used to refer to NOC1VA or NOC1VA and ARPP19.

Applicable methods for use in determining expression level of a biomarker at nucleic acid level include but are not limited to microarrays, which are a collection of nucleic acid, e.g. DNA, spots attached to a solid surface. Each DNA spot contains an oligonucleotide of a specific DNA sequence, known as a probe or capture probe. These can consist of a short section of a gene or other oligonucleotide such as DNA or LNA element that are used to hybridize target cDNA, mRNA or cRNA (also called anti-sense RNA) in a sample under high- stringency conditions. Probe-target hybridization can be detected and/or quantified e.g. by detection of fluorophore-, silver-, or chemiluminescence-labeled target nucleic acids to determine their relative abundance in the sample. In some array types a recognition element (transducer) capable of converting a surface- bound probe-target nucleic acid interaction into a quantifiable signal may be incorporated. Among the several different types of transducers available, especially those based on electrochemical or optical detection are popular in the art. Similarly to other nucleic acid analysis methods, both types of sensors can either be run as label-free or label-using and also divided to heterogeneous and homogeneous assay formats based on the requirement for washing.

One suitable application is the NanoString's nCounter technology, which is a variation on the DNA microarray. It uses molecular "barcodes" and microscopic imaging to detect and count up to several hundred unique transcripts in one hybridization reaction. Each color-coded barcode is attached to a single target-specific probe corresponding to a gene of interest. In some embodiments the use of an array based technology such as the NanoString is beneficial in order to detect biomarker expression.

In accordance with the above, the expression of a biomarker at nucleic acid level may be determined using any suitable method with or without nucleic acid amplification. For example, biomarker mRNA may be first converted into its complementary cDNA with the aid of a reverse transcriptase, followed by DNA amplification, e.g. by reverse transcriptase PCR (RT-PCR) including but not limited to quantitative PCR (qPCR), also known as real-time PCR. The presence, absence or concentration of the expressed biomarker mRNA polynucleotide or an amplification product thereof may be assessed according to methods available in the art, for example by using a biomarker-specific capture or detection probe. Further potential methods suitable for determining the expression of a biomarker at nucleic acid level, with or without a reverse transcription step and/or a nucleic acid amplification step depending on the method selected, include but are not limited to RNase protection assays, molecular beacon-based oligonucleotide hybridization assays, melting curve analysis combined with oligonucleotide probes and/or intercalating labels, gel electrophoresis analysis, Southern blotting, microarrays such as DNA microarrays and RNA microarrays, direct probing, and signal accumulation assays.

The detection of hybridization complexes can be carried out by any suitable method available in the art. Hybridization complexes may in some assay methods be physically separated from unhybridized nucleic acids (e.g. by employing one or more wash steps to wash away excess target mRNA/cDNA, the probe, or both), and detectable labels bound to the complexes are then detected. More often, however, homogeneous detection is employed where no physical separation of hybridized and unhybridized molecules is required. In nucleic acid amplification assays, homogeneous detection may be performed as a separate step after amplification, i.e. using homogeneous end-point detection. The accumulation of the amplicon can also be homogeneously monitored during the amplification assay by use of qPCR type of methods. The various homogeneous detection methods can further be classified into probe-using and non-probe-using formats. Detectable labels refer to radioactive, fluorescent, biological or enzymatic tags or labels of standard use in the art. A detectable label can be conjugated to either the oligonucleotide probe or the target polynucleotide. As is evident to those skilled in the art, the choice of a particular detectable label dictates the manner in which it is bound to the probe or the target sequence, as well as the technique to be used for detection. Although the present invention is not specifically dependent on the use of a label for the detection of a particular nucleic acid sequence, such a label might be beneficial, by increasing the sensitivity or specificity of the detection and simplifying the multiplexing of the assays. Further-more, a detectable label may better enable automation.

Intercalating dyes (e.g. SYBR Green) can be used to detect the amplification of the DNA fragment of interest during a nucleic acid amplification reaction such as PCR. Intercalation occurs when ligands of an appropriate size and chemical nature position between the planar base pairs of DNA. These ligands are mostly polycyclic, aromatic, and planar, and therefore often make suitable nucleic acid stains. The intensity of fluorescence increases respectively during the amplification and it can be measured in real-time without the need of separate oligo-nucleotide probes.

As appreciated by those skilled in the art, a variety of controls and additives may be employed to improve accuracy of hybridization assays. For instance, samples may be hybridized to an irrelevant probe and/or treated with RNAse A prior to hybridization, to assess false hybridization or prevent unspecific or unwanted effects.

In some embodiments, determining the expression of a biomarker is performed by sequencing techniques. Numerous methods suitable for this purpose have been described in the art and include, but are not limited to, traditional Sanger sequencing and next-generation sequencing (NGS) techniques. The pre-sent embodiments are not limited to any branded technique.

A representative commercial platform suitable for use in accordance with some embodiments of the invention, wherein the presence or quantity of a biomarker, if any, is detected by sequencing, is Illumina’s sequencing by synthesis (SBS) technology, particularly TruSeq® technology. Applying TruSeq® technology requires that two oligonucleotide probes, which hybridize upstream and downstream of the region of interest, are designed and synthetized. Each probe contains a unique, target specific sequence and a universal adapter sequence. An extension-ligation reaction is used to unite the two probes and create a library of new template molecules with common ends. Adapter-ligated DNA is then subjected to PCR amplification, which adds indexes and sequencing primers to both ends. Sequencing may then be performed by any suitable equipment, such as MiSeq® sequencer, utilizing a reversible terminator-based method enabling detection of single bases as they are incorporated into growing DNA strands.

Non-limiting examples of suitable equipment for sequencing purposes include Illumina® Sequencers, such as MiSeq™, NExtSeq500™, and HiSeq™ (e.g. HiSeq™ 2000 and HiSeq™ 3000), and Life Technologies’ Sequencers, such as Ion Torrent™ Sequencer and Ion Proton™ Sequencer. It should be understood that utilizing any of these equipment requires that appropriate sequencing technique and chemistry be used.

In some embodiments relating to NGS techniques, detection of a biomarker mRNA is possible with deep sequencing such as a one performed with Illumina HiSeq™ 3000 platform, 150 bp reading length and paired-end library.

Further methods suitable for detecting the expression level of a biomarker include, but are not limited to, RNA in situ hybridization technologies such as RNAscope® (Advanced Cell Diagnostics, ACD) and ViewRNA™ (Invitrogen).

Regions especially suitable for determining the expression of NOCIVA at nucleic acid level include the NOCIVA-specific sequence without the poly-A tail (nucleotides 1635-1983 of SEQ ID NO: 1); the sequence encoding the novel NOCIVA peptide (nucleotides 1636-1674 of SEQ ID NO: 1); and the 3’UTR without the poly-A tail (nucleotides 1675-1983 of SEQ ID NO: 1).

Generally, determining the level of a biomarker expression at protein level comprises contacting a sample obtained from a subject in need of said determination with a binding body, such as an antibody, specifically recognizing polypeptide in question (i.e. NOCIVA and/or ARPP19) under conditions wherein the binding body specifically interacts with the biomarker; and detecting said interaction (if any); wherein the presence or degree of said interaction correlates with the presence of the biomarker or the level of the biomarker expression in said sample. Binding bodies alternative to antibodies and fragments thereof suitable for determining biomarker expression at protein level include but are not limited to oligonucleotide or peptide aptamers, receptors and biologically interacting proteins.

Accordingly, in some embodiments of the present invention, expression level of a biomarker may be determined by an immunoassay, which comprises for example the following steps: providing an antibody that specifically binds to the biomarker; contacting a patient sample, preferably comprising permeabilied or disrupted cells, with an anti-biomarker antibody; and detecting the presence of a complex of the antibody bound to the biomarker (if any) in the sample. If desired, the antibody can be fixed to a solid support to facilitate washing and subsequent detection of the complex, prior to contacting the antibody with the sample. After incubating the sample with an anti-biomarker antibody, the mixture may be washed and the antibody-biomarker complex formed can be detected. This can be accomplished by e.g. using a detectable antibody, i.e. detectably labelled antibody, or an antibody labelled with an enzyme and incubating the complex with a detection reagent, i.e. substrate of the enzyme. Alternatively, the biomarker can be detected using an indirect assay, wherein, for example, a second, labelled antibody is used to detect the antibody-biomarker complex formed.

In some embodiments, the expression level of a biomarker may be determined using a non-competitive assay format. Non-competitive immunoassays, also known as reagent excess assays, sandwich assays, immunometric assays or two-site assays, generally involve use of two antibodies targeting different epitopes in the antigen, one antibody for antigen capture and the other labelled for detection. A person skilled in the art will be well capable of establishing a binding assay for measuring the level of a biomarker alone or in relation with any relevant control. Accordingly, formation of the antibody- biomarker complex may be determined using any of a number of well-recognized non-competitive immunological binding assays. Useful assays include, for example, enzyme immune assays (E1A) such as enzyme-linked immunosorbent assay (ELISA); fluorescent immuno-sorbent assays (FLA) such as time-resolved immunoflurometric assays (TR-1FMA); chemiluminescence immunoassays (CL1A) and radioimmune assays (R1A).

Depending on the assay type employed, either the first antibody or the second antibody, or both, may be conjugated or otherwise associated with a detectable label selected from the group including, but not limited to, optical agents such as fluorescent labels including a variety of organic and/or inorganic small molecules and a variety of fluorescent proteins and derivatives thereof, phosphorescent labels, chemiluminescent labels, and chromogenic labels; radioactive labels such as radionuclides that emit gamma rays, positrons, beta or alpha particles, or X-rays, and enzymes such as alkaline phosphatase (AP) and (horseradish) hydrogen peroxidase (HRP). Said association can be direct, e.g. through a covalent bond, or indirect, e.g. via a secondary binding agent, a chelator, or a linker. Techniques for conjugating or otherwise associating detectable agents to anti-bodies are well known and antibody labelling kits are commercially avail able from dozens of sources. One or both of the antibodies may also be expressed as fusion proteins with a detectable label or a detection tag by recombinant tech niques.

In some embodiments of non-competitive immunoassays, the detection antibody is detectably labelled. In some other embodiments, the detection antibody is recognized by a further antibody comprising a detectable label. In some still other embodiments, the detection antibody comprises a tag that is recognizable by a further antibody comprising a detectable label. In some still further embodiments, the detection antibody and said further antibodies are la-belled with the same label, e.g. for improving sensitivity. In some other embodiments, the detection antibody and said further antibodies are labelled with different labels.

Immunoassays suitable for carrying out the methods of the present invention include solid-phase immunoassays, such as lateral flow assays and conventional sandwich assays carried out on a solid surface such as glass, plastic, ceramic, metal or a fibrous or porous material such as paper, in the form of e.g. a microtiter plate, a stick, a card, an array, a sensor, a bead, or a microbead. Said solid-phase immunoassay may be either heterogeneous or homogeneous. In heterogeneous assays, any free antigens or antibodies are physically separated from immunocomplexes formed, e.g. by washings, while no such separation is necessary in homogeneous assays including the many forms of biosensors.

Suitable homogeneous immunoassays are not limited to solid-phase assay formats but encompass also homogeneous immunoassays carried out in solution. Such in-solution immunoassays are particularly advantageous because neither immobilization nor washing steps are required, making them simple and easy to perform. Thus, in some embodiments, the immunoassay is liquid-based homogeneous immunoassay.

Further examples of suitable methods for determining the expression level of a biomarker at protein level include conventional Western blot assays, dot blot assays and assay formats based on immunohistochemistry. Moreover, for example flow cytometry, such as fluorescence-activated cell sorting (FACS), may be used for detecting antibody-ARPP19 complexes. Moreover, techniques suitable for determining the expression level of ARPP19 at protein level include MS-based detection methods, such as selected reaction monitoring (SRM), SWATH and mass cytometry from cancer cell samples based on the unique peptide. Also in such embodiments, the method may include comparing the expression level of ARPP19 with that of a control biomarker.

In a further aspect, the present invention provides a kit and use thereof for detecting the expression level of NOC1VA or NOC1VA and ARPP19 in a clinical sample, for any purpose set forth above. Preferably, the kit comprises at least one NOClVA-specific oligonucleotide or at least one NOClVA-specific oligonucleotide and at least one ARPP19-specific oligonucleotide, such as a probe and/or a primer pair. A person skilled in the art can easily determine any further reagents to be included in the kit depending on the desired technique for carrying out determination of the expression level of NOC1VA or NOC1VA and ARPP19.

In some embodiments, an appropriate control reagent or sample or a threshold value may be comprised in the kit. The kit may also comprise a computer readable medium, comprising computer-executable instructions for performing any of the methods of the present disclosure.

It will be obvious to a person skilled in the art that, as technology advances, the inventive concept can be implemented in various ways. The invention and its embodiments are not limited to the examples described above but may vary within the scope of the claims.

EXAMPLE 1. Analysis of CML patient samples

Study cohort

The study cohort included 34 newly diagnosed chronic phase (CP) chronic myeloid leukaemia (CML) patients (one patient was excluded as there was no follow up data) from Liverpool area in United Kingdom. Valid ethical permissions were obtained both for sample collection and for expression profiling described herein. 20 patients received imatinib which is standard first line therapy and 14 received a second generation tyrosine kinase inhibitor (2G TK1) either dasatinib (n=7) or nilotinib (n=7). The average age at diagnosis was 51 years (range 19-75). Patients’ characteristics are shown in Table 1. Table 1.

Materials and methods

mRNA expression levels of N0C1VA and ARPP19 were analysed by real-time quantitative PCR (RQ-PCR) and mRNA expression was calculated using the 2 ^A -ddCt -method. To estimate the degree of overexpression in CML, the expression of each gene was normalized to the expression level in a commercial normal pooled (from 56 males and females) bone marrow control sample (636591, lot 1002008, Clontech Laboratories, Fremont, CA, USA). B-actin and GAPDH were used as calibrators. For the purpose of the analysis, the median NOC1VA or ARPP19 mRNA expression was determined and patients where stratified as high and low expressing groups. Also overexpression (RQ>1) was used for cut off value for analysis.

Primers for each gene specific assay were designed to be located to different exonic sequences to avoid amplification of genomic DNA. Primer concentration in each reaction was 300 nM and probe concentration 200nM. Specificity of qPCR reactions was verified by agarose gel electrophoresis and melting curve analysis. One band of the expected size and a single peak, respectively, were required. Amplification of target cDNAs was performed using KAPA PROBE FAST qPCR Kit (Kapa Biosystems) and 7900 HT Fast Real-Time PCR System (Thermo Fisher) according to the manufacturers’ instructions. Quantitative real-time PCR was executed under the following conditions: 95°C for 10 min followed by 45 cycles of 95°C for 15 s and 60°C for lmin. Relative gene expression data was normalized to expression level of endogenous house-keeping genes Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and beta acting using 2 ^A -AAC(t) method with Thermo Fisher Cloud Real-time qPCR Relative Quantification application. Results were derived from the average of at least two independent experiments and two technical replicates.

Primer and probe sequences for NOC1VA assay were: forward cagtctggactgagaatattattgga (SEQ ID NO: 4), reverse ggcattgtttgctgctatacttt (SEQ ID NO: 5), probe tccactgc (SEQ ID NO: 6). Primer and probe sequences for b-actin assay were: forward tcacccacacrgtgcccatctacgc (SEQ ID NO: 7), reverse cagcggaaccgctcattgccaatgg (SEQ ID NO: 8), probe atgccctcccccatgccatcctgcgt (SEQ ID NO: 9). Primer and probe sequences for GAPDH assay were: forward acccactcctccacctttga (SEQ ID NO: 10), reverse ttgctgtagccaaattcgttgt (SEQ ID NO: 11), probe acgaccactttgtcaagctcatttcctggt (SEQ ID NO: 12). Primer and probe sequences for ARPP19 assay were: forward cagagggagcactatgtctgc (SEQ ID NO: 13), reverse gcttttaattttgcttcttctgct (SEQ ID NO: 14), probe universal probe library (UPL) #68.

Results

NOCIVA

To perform the clinical correlations, the entire CML cohort was split depending on whether patients received 1G TK1 (Imatinib) or 2G TK1 (Dasatinib or Nilotinib). Imatinib treated patients

Figure 1A shows that EFS was significantly shorter in the high NOC1VA cohort (p=0.004) of Imatinib treated CML patients.

"Time to" CMR and EMR were used to assess the depth of a patient’s response, with CMR being the deepest form of response. As shown in Figure IB, patients with high NOC1VA expression had significantly inferior time to CMR (p=0.04). In terms of EMR, the patients with low NOC1VA expression had a higher rate of EMR, although this did not reach statistical significance (Figure 1C).

2G TKI treated patients

Due to superior clinical activity of 2G TKFs, there was only one event in terms of EFS (Figure ID) and with patient that had high NOC1VA expression.

Unlike the results seen for imatinib treated patients, NOC1VA expression levels did not correlate with either time to CMR (Figure IE) or degree of EMR (Figure IF) among 2G TKI treated patients.

Conclusions

In conclusion, high NOC1VA mRNA expression assessed at CML diagnosis is associated with an inferior EFS as well as lower rates of CMR for imatinib treated patients. Critically, not a single patient with high levels of NOC1VA mRNA at diagnosis achieved CMR. Conversely, NOC1VA levels did not correlate significantly with any clinical responses among 2G TKI treated patients.

ARPP19

To perform the clinical correlations, the entire CML cohort was split depending on whether patients received 1G TKI (Imatinib) or 2G TKI (Dasatinib or Nilotinib). Overexpression (RQ>1) was used as cut off value for these analysis.

Imatinib treated patients

There was no significant difference in the ARPP19 low and high cohorts in terms of imatinib treated patients and therapy responses over time. The EFS rates are shown in Figure 3A.

2G TKI treated patients

ARPP19 low cohort had significantly higher EFS time compared to ARPP19 high cohort (p=0.04, Figure 3B). Conclusions

In conclusion, high ARPP19 mRNA expression assessed at CML diagnosis is associated with an inferior EFS rates for 2G TK1 treated patients.

EXAMPLE 2. Analysis of patient-derived AML cells and AML cell lines in vitro

Patient-derived AML cells (n=39) were analysed with respect to RNA- seq based mRNA expression of ARPP19 and responses of against a panel of pharmaceutical drugs in mononuclear cell medium (MCM) (Figure 2A). Among the tested drugs, samples with high ARPP19 mRNA expression were resistant to lenalomide, dasatinib and XAV-939 (P < 0.05; Figure 2A).

Next, human AML cell lines were analysed for ARPP19 protein expression. Based on the results, MOLM-14 and Kasumil were considered as low ARPP19 expressing cell lines, whereas HL-60 and KG1 were considered as high ARPP19 expressing cell lines (Figure 2B).These AML cell lines were then tested for potential resistance to a panel of pharmaceutical drugs (Table 2.). Interestingly, high ARPP19 expressing AML cell lines (HL-60 and KG1) showed resistance to 2G TKI, Dasatinib, in MCM medium (Figures 2C and 2D). Other tested drugs did not show exclusive correlation between the drug response and ARPP19 protein levels.

Table 2.

Conclusions

In conclusion, cells with low ARPP19 mRNA expression respond to 2G TKI, whereas cells with high ARPP19 mRNA expression show resistance to 2G TKI.

EXAMPLE 3. NOCIVA expression analysis of CML patient samples Study cohort

NOCIVA gene expression was assessed in samples from a cohort of 814 patients in a laboratory-based study with no clinical intervention. The study was carried out on diagnostic blood samples obtained in the United Kingdom at original CML diagnosis between August 2008 and March 2013.

The 814 patients were randomly allocated either Imatinib 400mg or Dasatinib lOOmg each once daily. Follow-up was monthly for 3 months, 3- monthly until 12 months, then 6-monthly. Patients were followed until the sooner of 5 years or a change of therapy due to either intolerance or resistance. In this study, a total of 158 patient samples were used. The 158 samples were the first 140 samples in the cohort with material biobanked and 18 patients who progressed to blast crisis. Of the 158 patients, 80 received Imatinib and 78 received Dasatinib.

Materials and methods

Mononuclear cells (MNC) were separated from the samples by density-dependent centrifugation and then cryopreserved. RNA was extracted from the samples using RNeasy mini kit (Qiagen). RNA was stored at -70°C. cDNA was synthesised using standard procedures and stored at -20°C.

NOCIVA gene expression was assayed as mRNA expression level by TaqMan quantitative real-time PCR. Each assay consisted of cDNA, a forward and reverse primer and a 6-FAM dye-labelled probe. The real time PCR amplifications were undertaken using a Step One Real-time PCR system (Applied Biosystems) with the following conditions: 50°C for 2 min, 95°C for 10 min followed by 40 cycles of denaturation at 95°C for 15 secs and annealing/extension at 60°C for 1 min.

Primer and probe sequences for NOCIVA assay were: forward atgccaagacacagtcaaaatg (SEQ ID NO: 15), reverse cctgcttgcataaactggtaatc (SEQ ID NO: 16), probe cagaggcagaggataa (SEQ ID NO: 17). Primer and probe sequences for GAPDH assay were: forward acccactcctccacctttga (SEQ ID NO: 10), reverse ttgctgtagccaaattcgttgt (SEQ ID NO: 11), probe acgaccactttgtcaagctcatttcctggt (SEQ ID NO: 12).

NOCIVA gene expression was calculated using the 2 ^A -ddCt -method to achieve results for relative quantification (RQ) where ddCt is the normalised signal level in a sample relative to the normalised signal level in the calibrator sample. A pool of cDNA from 4 normal (apparently healthy) individuals was used as calibrator and all the samples were normalised to GAPDH as an endogenous control. In Kaplan-Meier plots, p values were determined using the log-rank (Mantel-Cox) test, where significant p values are shown. All analyses were undertaken in R 3.5.0 and GraphPad prism v8.1.

Results

Disease progression

High NOCIVA expression in the CML patient samples was defined as a value above the mean RQ value for all samples. Figure 5A shows that of all patients (n = 158), those patients who progressed to blast crisis had higher levels of NOCIVA at diagnosis, although this did not reach statistical significance. To perform the clinical correlations, the CML cohort of 158 patients was stratified depending on whether patients had received 1G TKI (Imatinib, n=80) or 2G TKI (Dasatinib, n=78) treatment (Figure 5B).

Imatinib treated patients

Imatinib-treated patients who subsequently progressed to blast crisis had significantly higher expression of NOCIVA at diagnosis than those Imatinib- treated patients who did not progress (p=0.04).

2G TKI treated patients

Dasatinib-treated patients who subsequently progressed to blast crisis did not have a significant difference in NOCIVA expression at diagnosis to those Dasatinib-treated patients who did not progress.

Conclusions

In conclusion, high NOCIVA expression at CML diagnosis is associated with disease progression for Imatinib-treated patients. Accordingly, low expression level of NOCIVA indicates that the subject is likely to respond to a first generation TKI, whereas high expression level of NOC1VA indicates that the subject is not likely to respond to a first generation TKI.

Freedom from progression

Figure 6A-C shows freedom from progression (FFP) i.e. the number (percentage) of patients who progressed to blast crisis over time. Figure 6A shows FFP for all patients (n = 158) showing either low or high NOC1VA expression. There was a trend for patients with high NOC1VA expression at diagnosis to have an inferior FFP, although this did not reach statistical significance. To perform the clinical correlations, the CML cohort was stratified depending on whether patients had received 1G TK1 (Imatinib, n=80) or 2G TK1 (Dasatinib, n=78) treatment. Imatinib treated patients

The trend for patients with high NOC1VA expression at diagnosis to have an inferior FFP was observed for the Imatinib-treated patients (Figure 6B). The trend, however, did not reach statistical significance. 2G TKI treated patients

The trend for patients with high NOC1VA expression at diagnosis to have an inferior FFP was not observed for the Dasatinib-treated patients (Figure 6C). Conclusions

In conclusion, high NOC1VA expression at CML diagnosis shows a trend (although not statistically significant) towards being associated with an inferior FFP for Imatinib-treated patients but not for Dasatinib-treated patients.

Freedom from progression in patients stratified based on NOCIVA expression

CML patients were stratified into quartiles based on diagnostic NOCIVA expression. Quartile 1 had the lowest NOCIVA expression and quartile 4 had the highest NOCIVA expression (Figure 7A-C). The results for all patients in the study is shown in Figure 7 A, where there is a trend indicating that patients with high NOCIVA expression (4 ^th quartile) at diagnosis had inferior FFP. The trend, however, does not reach statistical significance. The patients were further stratified depending on whether they had received 1G TK1 (Imatinib) or 2G TK1 (Dasatinib) treatment.

Imatinib treated patients

As shown in Figure 7B, Imatinib-treated patients with high NOCIVA expression at diagnosis (4 ^th quartile) had a significantly inferior FFP (p=0.04) as compared to other quartiles. Number of patients in Imatinib-treated quartiles was Ql, n=20; Q2, n= 20; Q3, n=19; Q4, n=21.

2G TKI treated patients

As shown in Figure 7C, there is no statistically significant impact on FFP in Dasatinib-treated patients in any of the quartiles of NOCIVA expression at diagnosis. Number of patients in Dasatinib-treated quartiles was Ql, n=19; Q2, n= 20; Q3, n=20; Q4, n=19.

Conclusions

In conclusion, high NOCIVA expression (4 ^th quartile) at CML diagnosis is associated with an inferior FFP for Imatinib-treated patients but not for Dasatinib-treated patients. Accordingly, low expression level of NOCIVA indicates that the subject is likely to respond to a first generation TKI, whereas high expression level of NOCIVA indicates that the subject is not likely to respond to a first generation TKI.

EXAMPLE 4. CIP2A gene expression analysis of CML patient samples

C1P2A gene expression was assessed in the same 158 samples as in Example 3 hereinabove. As stated in Example 3, the 158 samples were the first 140 samples in the cohort of 814 patients with material biobanked and 18 patients who progressed to blast crisis. Of the 158 patients, 80 received Imatinib and 78 received Dasatinib treatment.

Materials and methods

C1P2A gene expression was assayed as mRNA expression level by TaqMan quantitative real-time PCR using the same methods as in Example 3. Primers and probe for CIP2A assay were TaqMan predesigned forward and reverse primers and probe for CIP2A gene KIAA1524 (Fisher Scientific).

Freedom from progression in patients stratified based on CIP2A expression

Figure 8A-C shows Kaplan-Meier curves for freedom from progression (FFP) for CML patients stratified into quartiles based on diagnostic CIP2A expression. Quartile 1 had the lowest C1P2A expression and quartile 4 had the highest C1P2A expression. Figure 8A shows FFP for all patients (n = 158). There was no trend or statistical significance for patients with high C1P2A (4 ^th quartile) expression at diagnosis to have an inferior FFP. To perform the clinical correlations, the CML cohort was further stratified depending on whether patients had received 1G TK1 (Imatinib, n=80) or 2G TK1 (Dasatinib, n=78) treatment.

Imatinib treated patients

As shown in Figure 8B, Imatinib-treated patients with high C1P2A expression at diagnosis (4 ^th quartile) did not have a significantly inferior FFP.

2G TKI treated patients

As shown in Figure 8C, there is no statistically significant impact on FFP in Dasatinib-treated patients with high C1P2A expression (4 ^th quartile) at diagnosis.

Conclusions

In conclusion, high C1P2A gene expression (4 ^th quartile) at CML diagnosis is not associated with an inferior FFP for Imatinib-treated patients or Dasatinib-treated patients. This is different from NOC1VA expression, where high NOC1VA expression (4th quartile) at CML diagnosis is associated with an inferior FFP for Imatinib-treated patients but not for Dasatinib-treated patients (Example 3; Figure 7A-C). Thus, NOC1VA gene expression has an improved value as compared to C1P2A in predicting response to treatment with a 1 ^st generation TKI.