PRODUCTS AND USES THEREOF FOR PREDICTING THE SENSITIVITY OF A SUBJECT TO CANCER IMMUNOTHERAPY AND FOR SELECTING OPTIMIZED THERAPY

Abstract

The present invention relates to a method of predicting, assessing or monitoring the sensitivity of a subject having a cancer to an immunotherapy, preferably to an immunotherapy combining at least two immunotherapeutic agents, and to corresponding kits and uses thereof. The method of predicting, assessing or monitoring the sensitivity of a subject having a tumor to an immunotherapy typically comprises a step of assessing, before any immunotherapeutic treatment step in the subject, the presence of CD4+CD25highCD39high T cells in a tumor sample of the subject, the presence of CD4+CD25highCD39high T cells in the tumor sample of the subject being indicative of sensitivity of the subject to the immunotherapy, and the absence of CD4+CD25highCD39high T cells in the tumor sample of the subject being indicative of resistance of the subject to the immunotherapy.

Claims

1-14. (canceled)

15. An in vitro method of predicting, assessing or monitoring the sensitivity or resistance of a subject having a cancer to an immunotherapy combining at least two immunotherapeutic agents, in particular an anti-PD-1 monoclonal antibody and an anti-CTLA4 antibody, wherein the method comprises a step of determining, before any immunotherapeutic treatment step in the subject, in a tumor sample of the subject, the presence of CD4.sup.+CD25highCD39high T cells, the presence of CD4.sup.+CD25highCD39high T cells in the tumor sample being indicative of sensitivity of the subject to the immunotherapy, and the absence of CD4.sup.+CD25highCD39high T cells in the tumor sample being indicative of resistance of the subject to the immunotherapy.

16. The in vitro method according to claim 15, wherein CD4.sup.+CD25highCD39high T cell further expresses at least one additional marker selected from CD3, CD45, CD127 and Foxp3.

17. The in vitro method according to claim 16, wherein the CD4.sup.+CD25highCD39high T cell is a CD127low T cell.

18. The method according to claim 15, wherein the anti-PD-1 monoclonal antibody is selected from nivolumab and pembrolizumab.

19. The method according to claim 15, wherein the anti-CTLA4 monoclonal antibody is selected from ipilimumab and tremelimumab.

20. The method according to claim 15, wherein the cancer is selected from melanoma, lung, head and neck cancer, renal cancer and bladder cancer.

21. The method according to claim 15, wherein the tumor sample is a fresh tumor sample biopsy or a tumor sample biopsy which has not been frozen.

22. The method according to claim 21, wherein the method comprises a step of dosing via ELISA at least one marker selected from VEGFA, IL6, CXCL8, granzyme, in the supernatant of the fresh tumor sample biopsy after an incubation step of at least one minute.

23. An in vitro method of predicting, assessing or monitoring the sensitivity or resistance of a subject having a cancer to an immunotherapy combining at least two immunotherapeutic agents, in particular an anti-PD-1 monoclonal antibody and an anti-CTLA4 antibody, after one or several treatment steps with the immunotherapy in the subject, wherein the method comprises a step a) of determining, in a tumor sample of the subject, the expression level of CD4.sup.+CD25highCD39high T cells, and a step b) of comparing said CD4.sup.+CD25highCD39high T cells level to a CD4.sup.+CD25highCD39high T cells reference expression level, an expression level of CD4.sup.+CD25highCD39high T cells below the CD4.sup.+CD25highCD39high T cells reference expression level being indicative of sensitivity of the subject to the immunotherapy and an expression level of CD4.sup.+CD25highCD39high T cells above the CD4.sup.+CD25highCD39high T cells reference expression level being indicative of resistance of the subject to the immunotherapy.

24. The in vitro method according to claim 23, wherein the CD4.sup.+CD25highCD39high T cells reference expression level is the level of CD4.sup.+CD25highCD39high T cells in the tumor of the subject before any immunotherapeutic treatment step in the subject.

25. The in vitro method according to claim 23, wherein CD4.sup.+CD25highCD39high T cell further expresses at least one additional marker selected from CD3, CD45, CD127 and Foxp3.

26. The in vitro method according to claim 25, wherein the CD4.sup.+CD25highCD39high T cell is a CD127low T cell.

27. The method according to claim 23, wherein the anti-PD-1 monoclonal antibody is selected from nivolumab and pembrolizumab.

28. The method according to claim 23, wherein the anti-CTLA4 monoclonal antibody is selected from ipilimumab and tremelimumab.

29. The method according to claim 23, wherein the cancer is selected from melanoma, lung, head and neck cancer, renal cancer and bladder cancer.

30. The method according to claim 23, wherein the tumor sample is a fresh tumor sample biopsy or a tumor sample biopsy which has not been frozen.

31. The method according to claim 30, wherein the method comprises a step of dosing via ELISA at least one marker selected from VEGFA, IL6, CXCL8, granzyme, in the supernatant of the fresh tumor sample biopsy after an incubation step of at least one minute.

32. The method according to claim 30, wherein the fresh tumor sample biopsy or tumor sample biopsy which has not been frozen, has been dissociated with both enzymatic and mechanical procedures before being stained and used.

33. A method of selecting an appropriate therapeutic treatment for a subject having a cancer, which method comprises a step of predicting or assessing the sensitivity of a subject having a cancer to an immunotherapy combining at least two immunotherapeutic agents using a method according to claim 15.

34. A method of selecting or disqualifying a subject having a cancer for inclusion in a clinical trial, the clinical trial being for evaluating an immunotherapy combining at least two immunotherapeutic agents, which method comprises a step of predicting or assessing the sensitivity of a subject having a cancer to an immunotherapy combining at least two immunotherapeutic agents using a method according to claim 15.

Description

FIGURES

[0107] FIG. 1. Flow cytometry and scRNA-seq analysis to caracterize CD4+CD25+CD39+ cells Flow cytometry from 7 melanoma samples showed that CD25+CD39+ cell represented 70.9% (16.7) of CD4+ cells, and that CD4+CD25+CD39+ cells were also FoxP3+ in 75.7% (13.4) of cases. These populations expressed significantly more activation molecules such as ICOS, OX40, 42BB, TIGIT or CTLA4 (Mann-Whitney test, p<0.05 for all comparisons but CD4+CD39+ and CD25- or CD25+: p=0.1). On scRNA-seq data: UMAP gene expression clustering from tumor infiltrating lymphocytes (n=3) and violin plot showing log-normalised expression of genes of CD3+CD4+FOXP3+ and CD3+CD4+FOXP3-TILs confirms the significant co-expression of CD4 and Foxp3 gene and genes coding for CD25 and CD39, but also for ICOS, OX40, 41BB (CD137) and CTLA4.

[0108] FIG. 2. NIVIPIT trial design scheme

[0109] FIG. 3. Safety profile of intratumoral and intravenous arms

[0110] Time to Treatment-related grade 3-4 toxicity event-free survival curves (time from randomization to first documentation of treatment-related grade 3-4 toxicity) and incidence at 6 and 12 months (top). Distribution pie charts of treatment related toxicities according to treatment arm (middle). Bar chart showing treatment related grade 3 adverse events according to treatment arm (bottom).

[0111] FIG. 4. Efficacy results: PFS and OS estimations

[0112] Median PFS for the IT arm was 12.2 months [4.4NR].

[0113] Median PFS was not reached for the IV arm nor Median OS for none of the 2 arms. Histograms show the best response rate in the IT and IV arms. Response on injected and non-injected lesions is shown for the IT arm (Waterfall plot).

[0114] FIG. 5. Pharmacokinetic results of Ipilimumab and Nivolumab in the IT and IV arms

[0115] Violin plots showing plasma levels of Ipilimumab (ELISA assay) and Nivolumab (Liquid chromatography-tandem mass spectrometry technology) in the IT (0.3 mg/kg of Ipilimumab and 1 mg/kg of Nivolumab) and IV arm (3 mg/kg of Ipilimumab and 1 mg/kg of Nivolumab). Blood samples were performed with 30 minutes prior and after immunotherapy administration. Nivolumab was administered after Ipilimumab. The non-parametric Mann-Whitney test was used for comparisons. *<0.5 **<0.01 ***<0.001 ****<0.0001

[0116] FIG. 6. Fresh tumor analysis using flow cytometry and secretome titration of responders vs non responders

[0117] a. Box plots showing evolution of intratumoral activated Tregs. A higher proportion is observed at baseline, that decrease under treatment for responders.

[0118] b. Higher Granzyme A and B levels, that further increase after treatment were observed in responder patients secretome, i.e., the supernatant of tumor biopsies (Meso scale Discovery). Nota bene: CD4+/CD39high/CD25high and CD4+/CD25high/CD127low were grouped under the appellation Treg like (samples were analyzed using 2 different panels during the study) (top). Granzyme A & B concentrations in the supernatant of fresh tumor biopsies of first line stage III & IV melanoma at baseline, with or without Durable Clinical Benefit (DCB) from a combination of anti-PD1 & anti-CTLA4 (bottom).

[0119] c. Proportions of CD39+CD25+ cells among CD4+ T-cells at baseline in fresh tumor biopsies of first line stage III & IV melanoma with or without Durable Clinical Benefit (DCB) from a combination of anti-PD1 & anti-CTLA4. Flow cytometry of immune cells performed on fresh biopsy samples shows that at baseline (prior to any treatment), patients having a high proportion of CD4+CD39highCD25high have a significantly higher probability to present a durable clinical benefit (DCB: disease control lasting for more than 6 months).

[0120] FIG. 7. Proportions of CD4+FOXP3+ regulatory T-cells (Tregs) in freshly resected primary tumors of different histology (MM: malignant melanoma: NSCLC: Non Small Cell Lung Cancer: RCC: Renal Cell Cancer: HNSCC: Head & Neck Squamous Cell Carcinoma: EOC: Epithelial Ovarian Cancer: UC: Urothelial Cancer).

[0121] FIG. 8. Proportions of CD25+ (left), CD39+ (middle) and CTLA4+ (right) cells within CD8+, CD4+Foxp3 et CD4+Foxp3+

[0122] FIG. 9. Level of Expression of CD25 and CD39 on CD4+Foxp3 and CD4+Foxp3+ cells A. Level of Expression expressed as mean fluorescent intensity (MFI) of CD25 and CD39 on CD8+, CD4+Foxp3 and CD4+Foxp3+ cells.

[0123] B. CD39 and CD25 are the highest checkpoint expressed in terms of Ratio of Mean Fluorescence Intensity (MFI) between Foxp3+ and Foxp3 cells.

[0124] FIG. 10. Proportions of CD25+, CD39+ and CTLA4+ cells among CD4+Foxp3+ cells in several tumor types

[0125] Respective proportions of CD25+ cells (A), CD39+ cells (B) and CTLA4+ cell among CD4+Foxp3+ cells in several types of tumor. Malignant Mesothelioma (MM), Non-Small Cell Lung Cancer (NSCLC), Renal Cell Carcinoma (RCC), Head and Neck Squamous Cell Carcinoma (HNSCC), Epithelial Ovarian Cancer (EOC) and Urothelial Carcinoma (UC).

[0126] FIG. 11. Soluble factor supernatant dosage of biopsies of NIVIPIT secretome (Quantification Score, QS)

[0127] FIG. 12. Secretome data for biopsies at baseline in NIVIPIT Clinical Trial

[0128] FIG. 13. Highly-specific predictive value of CD4+CD25highCD39high cells

[0129] A ROC curve analysis was done using n=19 patients with CD4+CD25highCD39high frequencies as a predictor of event (death). The resulting AUC of the ROC curve demonstrates a highly-specific and moderately-sensitive predictive value of CD4+CD25highCD39high frequencies.

[0130] B. Kaplan Meier curves of OS in patients with CD4+CD25highCD39high <3.61 (gray) and CD4+CD25highCD39high 3.61 (black). Statistical comparison was done using the Log-Rank test.

[0131] FIG. 14. Highly-specific predictive value of low secretome Granzyme A and Granzyme B

[0132] A. ROC curve analysis was done using n=19 patients with Granzyme A frequencies as a predictor of event (death)

[0133] B. ROC curve analysis was done using n=20 patients with Granzyme B frequencies as a predictor of event (death).

[0134] C. Kaplan Meier curves of OS in patients with Granzyme A high (gray) 16O pg/ml and Granzyme A low 160 pg/ml (black). Statistical comparison was done using the Log-Rank test. 5D. Kaplan Meier curves of OS in patients with Granzyme B high (gray) 11.6 pg/ml and Granzyme B low 11.6 pg/ml (black). Statistical comparison was done using the Log-Rank test.

[0135] Throughout this application, various references describe the state of the art to which this invention pertains. The disclosures of these references are hereby incorporated by reference into the present disclosure.

[0136] Other characteristics and advantages of the invention are given in the following experimental section (with reference to FIGS. 1 to 6), which should be regarded as illustrative and not limiting the scope of the present application.

EXPERIMENTAL PART

Example 1Safety and Efficacy of Intravenous (IV) Nivolumab with Intratumoral (IT) Ipilimumab in Metastatic Melanoma

[0137] Inventors herein below describe the results of the NIVIPIT trial, a randomized multicenter Phase 1b study comparing the intratumoral (IT) administration of Ipilimumab (Ipi), an IgGI anti-CTLA4, to the intravenous (IV) Ipi with intravenous (IV) Nivolumab (nivo) administration, in patients (Pts) with Metastatic Melanoma (MM).

Methods

[0138] This study was approved by the national ethics committee.

[0139] Previously untreated metastatic melanoma patients (n=61) (Table 1 Patient Characteristics) were randomly assigned 1:2, to receive IV Nivo (1 mg/kg) in combination with either IV Ipi (3 mg/kg) (IV arm: n=21) or 10 lower dose IT Ipi (0.3 mg/kg) (IT arm: n=40 every 3 weeks for 4 doses), followed by Nivo 3 mg/kg every 2 weeks for up to 12 months (FIG. 2).

TABLE-US-00001 TABLE 1 Patient Characteristics IT Arm IV Arm N = 40 N = 21 Sex, n (%) Male/Female 26 (65%)/14 (35%) 12 (57%)/9 (43%) Age at randomization Median: years old [range] 55 [22-79] 58 [28-82] Site, n (%) Gustave Roussy, Villejuif 21 (53%) 9 (43%) IC-HCL, Lyon 14 (35%) 9 (43%) Saint-Louis APHP, Paris 4 (10%) 2 (10%) IUCT Oncopole, Toulouse 1 (3%) 1 (5%) BRAF status, n (%) Wild type 21 (53%) 13 (62%) Mutated 19 (47%) 8 (38%) AJCC Stage, n (%) IlIC 0 1 (5%) IIID 6 (15%) 2 (10%) IV 34 (85%) 18 (86%) LDH, n (%) < ULN (upper limit normal) 19 (53%) 10 (53%) > ULN 17 (47%) 9 (47%) missing 4 2 NLR (neutrophil/lymphocyte) Median: [range] 2.4 [1.4-20.5] 3.3 [1.1-6.9]
Flow Cytometry Immune Cells Phenotyping and Analysis from tumor biopsies

[0140] Core biopsy samples from tumors at baseline and prior to cycle 2 (injected and non-injected) were immediately placed into 1 ml of NaCl 0.9% and sent to the laboratory (LRTI-U1015). After a minimum of 30 minutes of incubation, fine-needle biopsies were mechanically dissociated with the bottom of a 2 ml syringe in a wet 70 m filter placed at the top of a 50 ml centrifuge tube. Isolated cells were then washed by centrifugation and the pellet was re-suspended in an appropriate volume of NaCl 0.9% for cell surface staining protocol. Antibodies mix was composed of immune markers CD45, CD3, CD4, CD8 and HLA-ABC, activation markers HLA-DR and CD25, T-Regulator markers CD39 and CTLA-4, Immune checkpoint markers PD-1, OX40 and TIGIT and a co-stimulator marker CD26. CTLA-4 was first stained at +37 C. for 20 min before others surface antibodies were added and incubated at +4 C. for 15 min. Two different panels were used, as CD39, CD26 and CD33 have been added, and CD127 and 41BB have been abandoned after the first 9 patients (for 22 patients). Then, cells were washed twice and acquisition were performed on an 18-colors flow cytometer BD Fortessa X20 (BD Biosciences). Data were processed in FCS 3.0 format and analyzed with KALUZA software version 2.1. From our population of interest, doublets were first excluded based on forward-scatter-Height versus forward-scatter Area plot, and then viable cells were selected. Tumor infiltrating T-lymphocytes were then selected with a CD45+ and CD3+ gate, and then were divided into two sub-populations based on CD4 and CD8 expression.

Plasmatic and Secretome Cytokines Measurement

[0141] To evaluate soluble factors in patient's plasma and/or supernatant of biopsies, a Quickplex SQ120 platform enabling highly sensitive electro-chemo-luminescent detection (Meso Scale Discovery, Rockville, MD) was used following the manufacturer's instructions. The analytes measured were: Interleukins 6 (IL-6), 8 (IL-8): Vascular Endothelial Growth Factor (VEGF); Enzymatic proteins (Granzyme A and B): . Absolute concentrations of soluble analytes (in pg/mL or fg/mL) in patient samples were calculated by use of a four-point-fit calibration curve of the standard dilutions (MSD DISCOVERY WORKBENCH analysis software) and were considered detectable if both runs of each sample had a signal greater than the analyte- and plate-specific lower limit of detection (LLOD).

[0142] The primary objective was to compare grade 3 immune related Adverse Events (irAE) rates at 6 months.

[0143] Secondary objectives were safety and efficacy evaluation of the IT arm and to explore predictive immune biomarkers on blood and tumor samples using flow cytometry and chemokine/cytokines titration.

[0144] Fresh tumor biopsies pre- and on-treatment on both injected and non-injected tumors were analyzed by flow cytometry, and soluble factors from their supernatant (secretome) were titrated with Meso Scale Discovery R multiplex (cf. FIG. 1A).

[0145] Fresh sequential whole blood samples were collected for flow cytometry phenotyping of immune cells, and for measuring systemic exposure to Ipi (PK) using ELISA (cf. FIG. 1B).

Results

[0146] 40 patients were treated in the IT arm and 21 in the IV arm.

[0147] The study met its primary endpoint with lower toxicity rate at 6 months in the IT arm, with 22.6% [12.4:37.6] vs 57.1% [36.5:75.5] of patients presenting grade 3 treatment related Adverse Events (AEs), and no procedure-related grade 3 AEs in the IT arm out of 162 IT injections performed (including deep seated lesions) (cf. FIG. 3).

[0148] Objective response rate (ORR) per RECIST 1.1 were observed in 50% [32.9; 67.1] of the patients in the IT arm vs 65.0% [0.41:0.85] in the IV arm.

[0149] In the IT arm, 65.7% of the injected tumors showed a complete response (CR) or partial response (PR) (cf. FIG. 4).

[0150] Serum Ipi concentrations were much lower in the IT arm (: 10) (cf. FIG. 5).

[0151] Before beginning a second step of treatment with the same immunotherapeutic treatment (i.e., at C2), patients in both arms had significant decreased circulating nave regulatory T cells (Tregs) independently from tumor responses. Presence of intratumoral CD25hi CD39hi activated Tregs that decreased significantly upon IT injection only in responders (including DCB patients), was predictive of the overall tumor response in the IT arm (cf. FIG. 6A). Moreover, both granzyme A and granzyme B concentrations in tumor secretome at baseline were significantly higher in responders (including DCB patients) than non-responders in both arms (cf. FIG. 6B).

Conclusions

[0152] IT Ipi in combination with IV Nivo is not only safe but could reduce grade 3 (gr3) toxicity of the Immune Checkpoint Blockers (ICB) combination. The high response rate in injected lesions was associated with the reduction of intra-tumoral activated Treg and prompts a use of the herein identified new biomarkers (CD4+CD25highCD39high T cells, also herein identified as activated Tregs or CD25hi CD39hi activated Tregs: as well as Granzyme B) in the oligometastatic and neoadjuvant setting to determine the sensitivity or resistance of a subject to immunotherapy, preferably to an immunotherapy combining at least two immunotherapeutic agents, in particular to anti-PD1 and anti-CD4 combined immunotherapy. In addition, direct assessment of cytolytic and regulatory pathways on fresh biopsies represents a novel, simple and rapid strategy to predict treatment efficacy.

Example 2-CD4.SUP.+.CD25highCD39High T Cells Biomarker Identified in Other Cancers

[0153] In order to better define what is the prevalence of the CD4+CD25+CD39+ T-cell population in cancer, inventors prospectively phenotype 35 freshly resected primary tumors.

TABLE-US-00002 TABLE 2 Patient Characteristics MM NSCLC RCC HNSCC EOC UC n % n % n % n % n % n % Total 7 9% 9 12% 12 16% 11 14% 22 29% 12 16% Gender Female 3 43% 4 44% 2 17% 4 36% 22 100% 1 8% Male 3 43% 4 44% 10 83% 7 64% 0 0% 9 75% Missing 1 14% 1 11% 0 0% 0 0% 0 0% 2 17% Age Median 50 68 57 63 55 78 (years) Range 40-63 63-79 33-67 21-89 19-74 47-89 Missing 1 14% 1 11% 4 33% 0 0% 0 0% 2 17% Metastatic N+ 7 100% 5 56% 1 8% 8 73% 11 50% 5 42% Lymph N 0 0% 3 33% 11 92% 2 18% 5 23% 5 42% Nodes Nx 0 0% 0 0% 0 0% 1 9% 6 27% 0 0% Missing 0 0% 1 11% 0 0% 0 0% 0 0% 2 17% Status at Primary 0 0% 8 89% 6 50% 10 91% 22 100% 0 0% surgery Relapsing 7 100% 0 0% 1 8% 1 9% 0 0% 0 0% Missing 0 0% 1 11% 5 42% 0 0% 0 0% 12 100% NLR Low (<2.59) 0 0% 2 22% 3 25% 6 55% 11 50% 0 0% High (2.59) 0 0% 6 67% 5 42% 4 36% 9 41% 0 0% Missing 7 100% 1 11% 4 33% 1 9% 2 9% 12 100% dNLR Low (<1.65) 0 0% 2 22% 4 33% 6 55% 17 77% 0 0% High (1.65) 0 0% 6 67% 4 33% 4 36% 3 14% 0 0% Missing 7 100% 1 11% 4 33% 1 9% 2 9% 12 100% Assays Cyrometry T cells 7 100% 7 78% 12 100% 10 91% 21 95% 12 100% Cytometry ICPs 7 100% 6 67% 7 58% 8 73% 4 18% 0 0% scRNAseq 0 0% 2 22% 0 0% 1 9% 1 5% 0 0%

[0154] First, inventors have identified the proportion of CD4+FOXP3+ regulatory T-cells (Tregs) 5 among the CD3+ cells population in freshly resected primary tumors of different histology (FIG. 7) and the proportion of CD25+, CD39+ and CTLA4+ cells within CD8+, CD4+Foxp3 et CD4+Foxp3+ cells population (FIG. 8). The level of expression of CD25 and CD39 have been measured (FIG. 9A). CD39 and CD25 are the highest checkpoint expressed in terms of Ratio of Mean Fluorescence Intensity (MFI) between Foxp3+ and Foxp3 cells (FIG. 9B) 10

[0155] Inventors have demonstrated the presence of this new biomarker in different types of cancer. They showed that more than 75% of CD4+Foxp3.sup.+ T cells express CD25 (FIG. 10A) and more than 80% of CD4+Foxp3.sup.+ T cells express CD39 (FIG. 10B) in different types of tumor: Malignant Mesothelioma (MM), Non-Small Cell Lung Cancer (NSCLC), Renal Cell Carcinoma (RCC), Head and Neck Squamous Cell Carcinoma (HNSCC), Epithelial Ovarian Cancer (EOC) and Urothelial Carcinoma (UC).

Example 3Secretome Cytokines Measurement

[0156] To evaluate soluble factors in patient's supernatant of biopsies, a Quickplex SQ120 platform enabling highly sensitive electrochemiluminescent detection (Meso Scale Discovery, Rockville, MD) was used following the manufacturer's instructions. The analytes measured were: Interleukins (IL-1B, IL-2RA, IL-6, IL-22), Interferons (IFN-): IFN--inducible protein-10 (IP-10): Tumor Necrosis Factors (TNF-): Vascular Endothelial Growth Factor (VEGF): Immune checkpoint soluble proteins (PD-1, PD-L1): Cytotoxic Granules (Granzyme A and B). Absolute concentrations of soluble analytes (in pg/mL) in patient samples were calculated by use of a four-point-fit calibration curve of the standard dilutions (MSD DISCOVERY WORKBENCH analysis software) and were considered detectable if both runs of each sample had a signal greater than the analyte- and plate-specific lower limit of detection (LLOD) (FIG. 11). Inventors consider that a cytokine/soluble factor is measurable when the Quantification Score (QS) is above 0.5. Best QS were found for IP-10, Granzyme A and B, PD-1, IL-6, IL-1B, IL-2Ra and VEGF in the secretome of biopsies (FIG. 12).

Example 4: Highly-Specific Predictive Value of CD4+CD25highCD39High Cells, Granzyme A and Granzyme B

[0157] An optimal cut-off value was determined using the Youden index, with the objective of maximizing the AUC of the ROC Curve for the CD4+CD25highCD39high at baseline. The optimal cut-off value at baseline is 3.61% CD4+CD25highCD39high with AUC 80.1% (FIG. 13A). The resulting AUC of the ROC curve demonstrates a highly-specific and moderately-sensitive predictive value of CD4+CD25highCD39high frequencies.

[0158] Kaplan Meyeur Survival analysis demonstrates that patients with low CD4+CD25highiCD39high frequencies at baseline are at increased risk of death compared to those with high frequencies (FIG. 13 B).

[0159] An optimal cut-off value was determined using the Youden index, with the objective of maximizing the AUC of the ROC Curve for the Granzyme A (FIG. 14A) and Granzyme B (FIG. 14 B) in the secretome at baseline. The optimal Granzyme A cut-off value is 160 pg/ml with AUC 63%, the optimal Granzyme B cut-off value is 11, 6 g/ml with AUC 71%.

[0160] Kaplan Meyeur Survival analysis demonstrate that patients with low secretome Granzyme A frequencies (FIG. 14 C) and secretome Granzyme B frequencies (FIG. 14 D) at baseline are at increased risk of death compared to those with high frequencies.

REFERENCES

[0161] Ilie, M., Long-Mira, E., Bence, C., Butori, C., Lassalle, S., Bouhlel, L., Fazzalari, L., Zahaf, K., Lalve, S., Washetine, K., et al. (2016). Comparative study of the PD-L1 status between surgically resected specimens and matched biopsies of NSCLC patients reveal major discordances: a potential issue for anti-PD-L1 therapeutic strategies. Ann. Oncol. 27, 147-153. [0162] Kerr, K. M., Tsao, M.-S., Nicholson, A. G., Yatabe, Y., Wistuba, I. I., and Hirsch, F. R. (2015). Programmed Death-Ligand 1 Immunohistochemistry in Lung Cancer: In what state is this art? J. Thorac. Oncol. 10, 985-989. [0163] Larkin, J., Chiarion-Sileni, V., Gonzalez, R., Grob, J.-J., Rutkowski, P., Lao, C. D., Cowey, C. L., Schadendorf, D., Wagstaff, J., Dummer, R., et al. (2019). Five-Year Survival with Combined Nivolumab and Ipilimumab in Advanced Melanoma. N. Engl. J. Med. 381, 1535-1546 [0164] Marabelle, A., Fakih, M., Lopez, J., Shah, M., Shapira-Frommer, R., Nakagawa, K., Chung, H. C., Kindler, H. L., Lopez-Martin, J. A., Miller, W. H. J., et al. (2020). Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet. Oncol. 21, 1353-1365. [0165] Tumeh, P. C., Harview, C. L., Yearley, J. H., Shintaku, I. P., Taylor, E. J. M., Robert, L., Chmielowski, B., Spasic, M., Henry, G., Ciobanu, V., et al. (2014). PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 515, 568-571. [0166] Vanhersecke, L., Brunet, M., Gugan, J.-P., Rey, C., Bougouin, A., Cousin, S., Le Moulec, S., Besse, B., Loriot, Y., Larroquette, M., et al. (2021). Mature tertiary lymphoid structures predict immune checkpoint inhibitor efficacy in solid tumors independently of PD-L1 expression. Nat. Cancer 2, 794-802. [0167] Wagle, N., Emery, C., Berger, M. F., Davis, M. J., Sawyer, A., Pochanard, P., Kehoe, S. M., Johannessen, C. M., Macconaill, L. E., Hahn, W. C., et al. (2011). Dissecting therapeutic resistance to RAF inhibition in melanoma by tumor genomic profiling. J. Clin. Oncol. 29, 3085-3096.