METHODS AND KITS FOR PREDICTING THE SENSITIVITY OF A SUBJECT TO IMMUNOTHERAPY
20190331682 ยท 2019-10-31
Inventors
- Laurence Zitvogel (Paris, FR)
- NICOLAS JACQUELOT (THIAIS, FR)
- David Enot (Creully, FR)
- SYLVIE SEIJO-RUSAKIEWICZ (EVIAN LES BAINS, FR)
Cpc classification
G01N33/57492
PHYSICS
G01N2800/52
PHYSICS
International classification
Abstract
The present invention relates to a method of predicting assessing or monitoring the sensitivity of a subject having a cancer to an immunotherapy, and to corresponding kits. The method of predicting, assessing or monitoring the sensitivity of a subject having a tumor to an immunotherapy typically comprises a step a) of determining, in a biological sample from said subject, the presence, absence or expression level of at least one biomarker, for example at least two biomarkers, and when the expression level is determined a step b) of comparing said expression level to reference expression level(s) or to reference expression ratio(s), thereby predicting, assessing or monitoring whether the subject having a tumor is responsive or resistant to the proposed immunotherapy.
Claims
1-21. (canceled)
22. An in vitro method of predicting, assessing or monitoring the sensitivity of a subject having a cancer to an immunotherapy selected from anti-PD-1 monoclonal antibody, anti-PD-L1 monoclonal antibody, anti-CTLA-4 monoclonal antibody, anti-CD137 monoclonal antibody, anti-CD137L monoclonal antibody, anti-TIM3 monoclonal antibody, IFN2a (ROF), IL-2, a combination of anti-PD-1 and anti-CTLA-4 monoclonal antibodies, a combination of anti-PD-1 monoclonal antibody and ROF, a combination of anti-CTLA-4 monoclonal antibody and ROF, and a combination of anti-PD-1 and anti-TIM3 monoclonal antibodies, which method comprises a step a) of determining, in a biological sample from said subject which is a blood sample or a sample comprising tumor cells, the presence, absence or expression level of at least one biomarker selected from PD-1.sup.+CD4.sup.+ T cells, CD8+ T cells and CD25.sup.+CD127.sup.CD4.sup.+ T cells, CD95.sup.+CD4.sup.+ T cells, CD95.sup.+CD8.sup.+ T cells, PD-L1.sup.+CD4.sup.+ T cells, PD-L1.sup.+CD8.sup.+ T cells, CLA.sup.+CD8.sup.+TEM cells, CD137L.sup.+CD4.sup.+ T cells, CD137L.sup.+CD8.sup.+ T cells, CD137.sup.+CD4.sup.+ T cells and CD137.sup.+CD8.sup.+ T cells, and, when the expression level is determined, a step b) of comparing said at least one expression level to a reference expression level or to a reference expression ratio, thereby predicting, assessing or monitoring whether the subject having a cancer is responsive or resistant to the immunotherapy.
23. The method according to claim 22, wherein the step of determining the presence, absence or expression level of the at least one biomarker in a biological sample of the subject is performed before any immunotherapeutic treatment step, and optionally after at least partial tumor resection in the subject.
24. The method according to claim 22, wherein the cancer is selected from melanoma, lung, renal cancer, head and neck cancer, bladder cancer.
25. The method according to claim 22, wherein the immunotherapy is anti-PD-1 monoclonal antibody and the method comprises a step a) of determining, in a blood sample of the subject, the expression level of PD-1.sup.+CD4.sup.+ T cells, and a step b) of comparing said PD-1.sup.+CD4.sup.+ T cells level to a PD-1.sup.+CD4.sup.+ T cells reference expression level, an expression level of PD-1.sup.+CD4.sup.+ T cells above the PD-1.sup.+CD4.sup.+ T cells reference expression level being indicative of sensitivity of the subject to the immunotherapy and an expression level of PD-1.sup.+CD4.sup.+ T cells below the PD-1.sup.+CD4.sup.+ T cells reference expression level being indicative of resistance of the subject to the immunotherapy, and/or a step a) of determining, in a blood sample of the subject, the expression levels of CD8.sup.+ T cells and of CD25.sup.+CD127.sup.CD4.sup.+ T cells, and a step b) of determining the ratio of CD8.sup.+ T cells/CD25.sup.+CD127.sup.CD4.sup.+ T cells, a ratio above the reference expression ratio being indicative of sensitivity of the subject to the immunotherapy and a ratio below the reference expression ratio being indicative of resistance of the subject to the immunotherapy,
26. The method according to claim 25, wherein the PD-1.sup.+CD4.sup.+ T cells reference expression level is the percentage of CD4.sup.+ T cells expressing PD-1, an expression level of PD-1.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing PD-1 above 21.06% being indicative of sensitivity of the subject to the immunotherapy, and an expression level of PD-1.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing PD-1 below 7.45% being indicative of resistance of the subject to the immunotherapy.
27. The method according to claim 25, wherein a ratio above 5.4 is indicative of sensitivity of the subject to the immunotherapy and a ratio below 2.8 is indicative of resistance of the subject to the immunotherapy.
28. The method according to claim 22, wherein the immunotherapy is anti-CTLA-4 monoclonal antibody and the method comprises a step a) of determining, in a biological sample of the subject, the expression level of CD95.sup.+CD4.sup.+ T cells, of determining in a blood sample of the subject the expression level of CD95.sup.+CD8.sup.+ T cells, of determining in a blood sample of the subject the expression level of PD-L1.sup.+CD4.sup.+ T cells, and/or of determining in a blood sample of the subject the expression level of PD-L1.sup.+CD8.sup.+ T cells, and a step b) of comparing said levels to their respective reference expression levels, an expression level above the reference expression level being indicative of resistance of the subject to the immunotherapy, and an expression level below the reference expression level being indicative of sensitivity of the subject to the immunotherapy.
29. The method according to claim 28, wherein the CD95.sup.+CD4.sup.+ T cells reference expression level is the percentage of CD4.sup.+ T cells expressing CD95, an expression level of CD95.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing CD95 above 70.80% in a sample comprising tumor cells or above 68.1% in a blood sample being indicative of resistance of the subject to the immunotherapy, and an expression level of CD95.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing CD95 below 43.79% in a sample comprising tumor cells or below 48.5% in a blood sample being indicative of sensitivity of the subject to the immunotherapy.
30. The method according to claim 28, wherein the CD95.sup.+CD8 T cells reference expression level is the percentage of CD8.sup.+ T cells expressing CD95, an expression level of CD95.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing CD95 above 74.48% being indicative of resistance of the subject to the immunotherapy, and an expression level of CD95.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing CD95 below 44.13% being indicative of sensitivity of the subject to the immunotherapy.
31. The method according to claim 28, wherein the PD-L1.sup.+CD4.sup.+ T cells reference expression level is the percentage of CD4.sup.+ T cells expressing PD-L1, an expression level of PD-L1.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing PD-L1 above 27.76% being indicative of resistance of the subject to the immunotherapy, and an expression level of PD-L1.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing PD-L1 below 6.66% being indicative of sensitivity of the subject to the immunotherapy, and the PD-L1.sup.+CD8.sup.+ T cells reference expression level is the percentage of CD8.sup.+ T cells expressing PD-L1, an expression level of PD-L1.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing PD-L1 above 21.45% being indicative of resistance of the subject to the immunotherapy, and an expression level of PD-L1.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing PD-L1 below 2.53% being indicative of sensitivity of the subject to the immunotherapy.
32. The method according to claim 28, wherein the method comprises a step of determining the expression levels of CD95.sup.+CD4.sup.+ T cells and PD-L1.sup.+CD8.sup.+ T cells in a blood sample of the subject, an expression level of CD95.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing CD95 above 70% together with an expression level of PD-L1.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing PD-L1 above 11% being indicative of resistance of the subject to the immunotherapy.
33. The method according to claim 22, wherein the immunotherapy is anti-CTLA-4 monoclonal antibody and the method comprises a step a) of determining, in a blood sample of the subject three weeks after the first injection of the anti-CTLA4 monoclonal antibody, the percentage and/or absolute number of CLA.sup.+CD8.sup.+ TEM cells, and a step b) of comparing said percentage and/or absolute number with a reference percentage and/or absolute number of CLA.sup.+CD8.sup.+ TEM cells, a percentage and/or absolute number above the reference percentage and/or absolute number being indicative of sensitivity of the subject to the immunotherapy, and a percentage and/or absolute number below the reference percentage and/or absolute number being indicative of resistance of the subject to the immunotherapy.
34. The method according to claim 33, wherein a percentage of CLA.sup.+CD8.sup.+ TEM cells above 26.9 and/or absolute number above 33 cells per mm.sup.3 is indicative of sensitivity of the subject to the immunotherapy and a percentage of CLA.sup.+CD8.sup.+ TEM cells below 6 and/or absolute number below 14 cells per mm.sup.3 is indicative of resistance of the subject to the immunotherapy.
35. The method according to claim 22, wherein the immunotherapy is a combination of anti-PD-1 and anti-CTLA-4 monoclonal antibodies, and the method comprises a step a) of determining, in a blood sample of the subject, the expression level of CD137L.sup.CD4.sup.+ T cells, CD137L.sup.+CD8.sup.+ T cells, CD137.sup.+CD4.sup.+ T cells and/or CD137.sup.+CD8.sup.+ T cells, and a step b) of comparing said level(s) to their respective reference expression level(s), an expression level of CD137L.sup.+CD4.sup.+ T cells and/or CD137L.sup.+CD8.sup.+ T cells above the reference expression level being indicative of resistance of the subject to the immunotherapy, and an expression level of CD137L.sup.+CD4.sup.+ T cells and/or CD137L.sup.+CD8.sup.+ T cells below the reference expression level being indicative of sensitivity of the subject to the immunotherapy, and an expression level of CD137.sup.+CD4.sup.+ T cells and/or CD137.sup.+CD8.sup.+ T cells below the reference expression level being indicative of resistance of the subject to the immunotherapy, and an expression level of CD137.sup.+CD4.sup.+ T cells and/or CD137.sup.+CD8.sup.+ T cells above the reference expression level being indicative of sensitivity of the subject to the immunotherapy.
36. The method according to claim 35, wherein the CD137L.sup.+CD4.sup.+ T cells reference expression level is the percentage of CD4.sup.+ T cells expressing CD137L, an expression level of CD137L.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing CD137L above 25.19% being indicative of resistance of the subject to the immunotherapy, and an expression level of CD137L.sup.+CD4.sup.+ T cells in the subject corresponding to a percentage of CD4.sup.+ T cells expressing CD137L below 9.01% being indicative of sensitivity of the subject to the immunotherapy, and the CD137L.sup.+CD8.sup.+ T cells reference expression level is the percentage of CD8.sup.+ T cells expressing CD137L, an expression level of CD137L.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing CD137L above 16.65% being indicative of resistance of the subject to the immunotherapy, and an expression level of CD137L.sup.+CD8.sup.+ T cells in the subject corresponding to a percentage of CD8.sup.+ T cells expressing CD137L below 7.86% being indicative of sensitivity of the subject to the immunotherapy.
37. The method according to claim 22 wherein the biological sample comprising tumor cells is selected from a tumor biopsy, a whole tumor piece, a tumor bed sample, and a metastatic lymph node cells sample.
38. The method according to claim 22, wherein the anti-CTLA-4 monoclonal antibody is selected from ipilimumab and tremelimumab.
39. The method according to claim 22, wherein the anti-PD-1 monoclonal antibody is selected from nivolumab and pembrolizumab.
40. A method of selecting an appropriate chemotherapeutic 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 using a method according to claim 22.
41. A kit for predicting, assessing or monitoring the sensitivity of a subject having a tumor to a cancer therapy, wherein the kit comprises, as detection means, at least two antibodies selected from the group consisting of an antibody specific to PD-1.sup.+CD4.sup.+ T cells, CD8+ T cells and CD25.sup.+CD127.sup.CD4.sup.+ T cells, CD95.sup.+CD4.sup.+ T cells, CD95.sup.+CD8.sup.+ T cells, PD-L1.sup.+CD4.sup.+ T cells, PD-L1.sup.+CD8.sup.+ T cells, CLA.sup.+CD8.sup.+ TEM, CD137L.sup.+CD4.sup.+ T cells, CD137L.sup.+CD8.sup.+ T cells, CD137.sup.+CD4.sup.+ T cells and CD137.sup.+CD8.sup.+ T cells, and, optionally, a leaflet providing the corresponding reference expression levels.
42. An assay (mLN assay) for determining whether a patient is sensitive or resistant to a cancer therapy, wherein the assay comprises: a first step wherein suspensions of metastatic lymph nodes samples are incubated ex vivo in duplicate wells, each well of each set of the duplicate being in contact with medium, with a control antibody, or with a test immunotherapeutic antibody defining a cancer therapy, said antibody being selected from an anti-PD-1 monoclonal antibody, an anti-PD-L1 monoclonal antibody, an anti-CTLA-4 monoclonal antibody, an anti-CD137 monoclonal antibody, an anti-CD137L monoclonal antibody, an anti-TIM3 monoclonal antibody, an IFN2a (ROF), an IL-2, a combination of anti-PD-1 and anti-CTLA-4 monoclonal antibodies, a combination of anti-PD-1 monoclonal antibody and ROF, a combination of anti-CTLA-4 monoclonal antibody and ROF, or a combination of anti-PD-1 and anti-TIM3 monoclonal antibodies, the first set of wells being incubated for 18h-24h, and the second set of wells being incubated for 4 to 5 days, a second step of measuring T cells, NK cells and/or Treg cells parameters, said parameters consisting in cell biomarker(s) expression, cytokine cell release, interferon cell release, chemokine cell release and/or interleukin cell release in the first set of wells, and Ki67 cell expression and Treg cell proportion in the second set of wells, and a third step of comparing measures obtained in each well with the corresponding measure obtained from the medium and control wells, a 1.5 fold variation of at least two parameters indicating that the patient is sensitive to the cancer therapy.
Description
EXPERIMENTAL PART
Example 1Personalized Immuno-Oncology and Predictors of Responses to Immune Check-Point Blockade in Stage III Melanoma
Results
Functional Assays on Ex Vivo Dissociated mLN Using One or Several Therapeutic mAb.
[0155] The patients' population consisting in stage III MM (Metastatic Melanoma, also herein identified as MMel) benefiting from a surgery for a metastatic lymph node has been previously described (Jacquelot et al JID in press). Briefly, one third presented more than 3 invaded LN (Lymph node), 52% were ulcerated MM, exhibiting in 55% cases a mutated B-RAF oncogene, in >30% cases a dysthyroidism and undergoing an adjuvant therapy in >50% cases. After mechanical and enzymatic digestion of the metastatic draining lymph node (MLN) of MM, CD45.sup. tumor cells represented 4-984.8% SEM of whole cells and tumor composition was analyzed by flow cytometry on live cells in 39 specimen paired with blood. Based on a comprehensive immunophenotyping of 252 parameters per patient featuring cellular types, activation status, nave or memory phenotypes and activating or inhibitory receptors or ligands in paired blood and MLN performed in 39 MM, inventors found that blood markers were as contributive as tumor-associated (TIL) immunotypes, and parameters associated with lymphocyte exhaustion/suppression showed higher clinical significance than those related to activation or lineage (Jacquelot et al JID in press). Inventors previously reported that CD45RA.sup.+CD4.sup.+ and CD3.sup.CD56.sup. TILs appear to be independent prognostic factors of short progression-free survival (PFS) while high NKG2D expression on CD8.sup.+ TILs and low Treg TILs were retained in the multivariate Cox analysis model to predict prolonged overall survival (OS).
[0156] The next step consisted in analyzing the dynamics of these parameters after incubation with monoclonal antibodies (mAb)+/cytokines on 37 patients. Dissociated mLN were incubated for 18 h and up to 5 days in 15 conditions of stimulation aimed at assessing the reactivity of various subsets of CD4.sup.+, CD8.sup.+, CD25.sup.+CD127.sup. T cells, NK, CD3.sup.CD56.sup., CD45.sup. cells to mAb targeting four functional axis (PD-1/PD-L1, CTLA-4, CD137/CD137L, TIM3), cytokines (IFN2a (ROF), IL-2) and their combinations (PD-1+ROF, CTLA-4+ROF, PD-1+TIM3, PD-1+CTLA-4) (
TABLE-US-00001 TABLE 1 Reagents used for stimulation assay in-vitro Stimulation Final Condition Clone Source Concentration Medium control mIgG1 11711 R&D 10 g/ml anti-PD1 PD1m.3 Dr. Chen's lab 10 g/ml anti-PDL1 5H1 Dr. Chen's lab 10 g/ml anti-Tim3 2E2 Dr. Anderson's lab 10 g/ml anti-CTLA4 BMS-734016 Yervoy 10 g/ml anti-CD137 6B4 Dr. Choi's lab 5 g/ml anti-CD137L 5F4 Dr. Choi's lab 5 g/ml IL-2 (Proleukine) 100 IU/ml Norvartis IFN-2A (Roferon) 1000 IU/ml Roche Pharma
[0157] The immunometrics performed in 48 wells' plate that inventors considered to perform (biological readouts henceforth) were the early (18-24 hrs) Th1 cytokine/chemokine secretory profiles of T and NK cells (monitored in flow cytometric intracellular staining), the cytokine/chemokine accumulation in the 18-24 hrs supernatant (multiplex array and ELISA), the late proliferative response of T cell subsets (flow cytometric Ki67 expression at day 4-5) and the decrease in Treg proportions. Inventors arbitrarily defined biological responses, as those exhibiting a >1.5 fold increase over the values obtained with two negative controls (medium and Ig control mAb) in at least two independent biological readouts (out of n=40 immunological assays, 35 were used with a threshold at 95% of detected values) for each of the 15 culture conditions, except for CD4.sup.+FoxP3.sup.+ Treg for which they retained a >1.5 fold decrease compared with the baseline levels in responders over non-responders. The inter-individual variability for specimen manipulation and flow cytometry was minimal, as exemplified for 2 specimens (
[0158] The Venn diagrams detailing all the patterns of immune reactivities are depicted in
TABLE-US-00002 TABLE 2 Detailed responses of patients treated with different ICB and cytokines Stimulation in ex vivo mLN assays anti-PD1 + anti-CD137 anti-PD1 + anti- anti- anti- anti- and/or anti- anti- CTLA4 + anti-PD1 + Patient CTLA4 PD1 CTLA4 anti-CD137L IFNa2a IL-2 TIM3 TIM3 IFN2a IFN2a 955HS + + + + + + + + + + 755MD + + + + + + + + 284FZ + + + + + + + + + + 043AL + + + + + n/d 389BU n/d 511TZ + + + + + + n/d + + 000LH + + + n/d + n/d + 630TB + + n/d + + 459MR + + n/d + + 290FD + n/d 464FX + + + n/d + n/d + 163BX + + + + + + n/d + + 113RU + + + + n/d n/d + 078KA + + + + + + n/d + n/d + 889XX + + + + n/d n/d n/d n/d 802EX n/d + n/d n/d n/d 954HG + + n/d n/d n/d + 146GB + + + + n/d n/d + + 259MR n/d + n/d + 054EK n/d n/d 738KA + + n/d + n/d n/d n/d n/d 647MZ + + n/d n/d n/d + n/d n/d 875GS n/d + n/d n/d n/d + + 472EZ + + + + n/d n/d n/d n/d n/d n/d 396LK + + + n/d n/d n/d n/d n/d n/d 960GS + + + + n/d n/d + + LYON3 + + + n/d n/d n/d n/d 715DD + + + + n/d n/d n/d n/d 274EM + + + + + n/d n/d n/d n/d 171WR + n/d + + n/d n/d n/d n/d 860KX + + + n/d + + n/d n/d n/d n/d 635BB n/d + + n/d n/d n/d n/d 710BB + + n/d + + n/d n/d n/d n/d LYON1 n/d n/d n/d n/d n/d 329AP n/d + + n/d n/d n/d n/d 192DD + + + n/d + + n/d n/d n/d n/d 934LN n/d n/d n/d n/d n/d n/d n/d Total 14/23 16/21 16/18 17/11 25/6 26/6 6/5 6/5 11/4 15/5 R/NR (37.8) (43.2) (47.1) (60.7) (80.6) (81.2) (54.5) (54.5) (73.3) (75) (% of R)
[0159] 60% mLN ( 17/28) responded to agonistic anti-CD137/anti-CD137L Ab, among which 35% ( 6/17) failed to respond to any of the classical ICB (anti-CTLA-4 or anti-PD-1 Ab) (Table 2). Among the responders to anti-CD137 Ab, about 64% responded to either CTLA-4 or PD-1 blockade (Table 2). The likelihood of response to any alternate ICB/mAb combinations when failing to respond to anyone of them is depicted in
[0160] In conclusion, inventors' ex vivo mLN assay is a feasible test requiring at least 10 million viable tumoral cells for a diagnosis of prediction of response to 11 various conditions of stimulation, and indicate proportions of responses compatible with the clinical rates.
Predictive Biomarkers of Response to CTLA-4 Blockade
[0161] Given that the ex vivo mLN assay is labor intensive and expansive, inventors addressed whether a predictive biomarker of response to the ex vivo mLN assay could be found in the 779 parameters that they analyzed. Hence, they next performed correlative analyses between paired blood and tumor immunometrics (previously described in Jacquelot et al. JID in press) and ex vivo responses to individual mAb axis for the whole cohort of 37 stage III MM to search for predictive biomarkers of response to ICB or combination therapies in our model system.
[0162] The two best immunometrics retained in the model of 779 variables were CD95/Fas and CD274/PD-L1 expression levels on CD4.sup.+ and CD8.sup.+ circulating T cells respectively (
[0163] The second predictive immune marker of resistance to CTLA-4 blockade was PD-L1 expression on CD8.sup.+ and CD4.sup.+ blood T cells (AUC=0.80, p<0.036 and AUC=0.81, p<0.0193) (
[0164] Based on the ex vivo mLN functional assay and immunometrics obtained in blood and tumors, inventors hypothetized that CD95/Fas and CD274/PD-L1 expression levels on CD4.sup.+ and CD8.sup.+ circulating T cells respectively contribute to predict resistance to CTLA-4 blockade in MM.
Predictive Biomarkers of Response to PD-1 Blockade
[0165] As inventors did for CTLA-4 blockade, they next address which immunometrics might be able to best predict ex vivo reactivities to PD-1 blockade. Very few immune parameters were found linked to functional responses to anti-PD-1 Ab. The two best immunometrics retained in the model of >779 variables were the ratio between circulating CD8.sup.+ lymphocytes and CD127.sup.lowCD25.sup.highCD4.sup.+ Treg cells, and PD-1 expression levels on circulating CD4.sup.+ T cells (
[0166] Based on the ex vivo mLN functional assay and immunometrics obtained in blood, inventors concluded that the CD8/Treg ratio and PD-1 expression levels on CD4.sup.+ circulating T cells contribute to predict sensitivity to PD-1 blockade in MM.
Predictive Biomarkers of Response to CTLA4+PD-1 Co-Blockade
[0167] Although mediating impressive clinical benefit in MM (ORR>60% with a PFS>11 months), this combinatorial regimen is also quite synergic for immune related adverse events (>50% grade 3-4 hepatitis or colitis) (20), urging investigators to predict clinical outcome. Interestingly, since the proportions of mLN responding to both anti-CTLA4 and anti-PD-1 Ab separately was 11/37 (29%), among which 45% failed to respond to a concomitant coblockade (Table 2,
[0168] The two other best immunometrics retained in the model of 779 variables were the expression levels of CD137/4-1BB on circulating CD4.sup.+ and CD8.sup.+ lymphocytes (
[0169] Based on the ex vivo mLN functional assay and immunometrics obtained in blood, inventors concluded that CD137 and/or CD137L expression level(s) on circulating T cells contribute to predict resistance to CTLA-4/PD-1 co-blockade in stage III MM.
In Vivo Veritas
[0170] To verify the potential validity of their immune biomarkers identified originally from correlative matrices between an ex vivo mLN functional assay and blood or tumor immunometrics, inventors retrospectively analyzed their expressions on several cohorts of stage III-IV MM treated with the first line standard immunotherapy ipilimumab (n=64, Table 3).
TABLE-US-00003 TABLE 3 Ipilimumab-treated patients characteristics enrolled in four centers Memorial University Sloan University All University Hospital of Kettering of patients - of Stanford - Siena - N Cancer Center - Tubingen - N [%] N [%] [%] N [%] N [%] Gender M 37 [57.8] 21 [52.5] 6 [60.0] 7 [63.6] 3 [100.0] F 27 [42.2] 19 [47.5] 4 [40.0] 4 [36.4] 0 [0.0] Age (yrs)* 62.2 [24; 91] 63.0 [38; 90] 55.6 [24; 81] 65 [41; 91] 64 [53; 74] Stage III 34 [53.1] 33 [82.5] 1 [10.0] 0 [0.0] 0 [0.0] IV 30 [46.9] 7 [17.5] 9 [90.0] 11 [100.0] 3 [100.0] LDH** Normal 44 [68.7] 34 [85.0] 2 [20.0] 7 [63.6] 1 [33.3] Elevated 19 [29.7] 6 [15.0] 7 [70.0) 4 [36.4] 2 [66.7] NA.sup.$ 1 [1.6] 0 [0.0] 1 [10.0] 0 [0.0] 0 [0.0] Prior No 21 [32.8] 20 [50.0] 1 [10.0] 0 [0.0] 0 [0.0] therapy Yes 43 [67.2] 20 [50.0] 9 [90.0] 11 [100.0] 3 [100.0] Clinical PD.sup.$$ 26 [40.7] 10 [25.0] 6 [60.0] 7 [63.6] 3 [100.0] response SD.sup.$$ 18 [28.1] 10 [25.0] 4 [40.0] 4 [36.4] 0 [0.0] PR.sup.$$ 10 [15.6] 10 [25.0] 0 [0.0] 0 [0.0] 0 [0.0] CR.sup.$$ 10 [15.6] 10 [25.0] 0 [0.0] 0 [0.0] 0 [0.0] *Mean [Min; Max]; .sup.$NA: Not Available; .sup.$$PD: Progression Disease, SD: Stable Disease, PR: Partial Response, CR: Complete Response
[0171] CD95/Fas and CD274/PD-L1 expression levels on CD4.sup.+ and CD8.sup.+ circulating T cells respectively were analyzed on frozen PBMCs at diagnosis before the first administration of 3 mg/kg of ipilimumab and their expressions were correlated with clinical outcome. Importantly, the CD95 membrane expression on CD4.sup.+ T cells analyzed in 64 patients was lower at diagnosis in patients developing partial and complete responses than in those exhibiting stable or progressive disease at 3 months of ipilimumab and confirmed with the ROC curve (
[0172] Since these two immunometrics appeared to have predictive value for the response to ipilimumab, inventors excluded the possibility that they could also convey a prognosis value in stage III-IV MM by analyzing a retrospective cohort of 39 MM prior to the era of immunomodulators. Indeed, Fas/CD95 expression on CD4.sup.+ T cells was not associated with time to progression (PFS) nor overall survival (OS) (
[0173] Next, inventors carried out the validation of the predictive value for beneficial clinical outcome of the CD137 expression on circulating CD8.sup.+ T cells at diagnosis for the toxic combination of ipilimumab and nivolumab, administered in a Phase II adjuvant trial comparing the efficacy of nivolumab alone versus combined with ipilimumab in stage III MM. The expression levels of CD137 on circulating CD8.sup.+ T cells in this American cohort of patients was within the range of patients described in the French cohort (
Discussion
[0174] For the first time, inventors present a functional method called the ex vivo mLN assay capable of assessing the reactivity of tumor infiltrating immune effectors (T and NK cells) during a stimulation with various immune checkpoint blocking or agonistic immunostimulating mAb and their combinations coupled to a paired blood and tumor immune profiling of mLN in stage III MM with the final aim to correlate immune fingerprints with clinical parameters (21, 22).
[0175] First, they concluded that the method was feasible for almost all mLN specimen containing at least 10 million cells (37/46 were successfully performed and contained enough cells for the ex vivo mLN assay) but could be downscaled at the level of a biopsy if only one or 2 mAb should be tested. The method was also reliable in that both negative controls (18 hrs or 5 days-incubation in the absence of stimulus or in Ig control antibodies) allowed the basal assessment of T cell functions without non specific backgrounds, and positive controls (rIL-2 or IFN type 1) almost invariably triggered effector (and Treg) proliferation and Cxcl10 release respectively in all patients. This method analysed supposingly the most important dynamic T and NK cell parameters relevant to effector functions against cancer, such as proliferation and intracellular production of Th1 cytokines as well as Treg proportions in the coculture model system. Hence, to be on the safe side, inventors arbitrarily set up two independent criteria per mAb or condition of stimulation to score the response as positive, when a >1.5 fold change compared with the two negative controls was achieved. Finally, considering that in patients, these immunomodulators may act, not just at the level of tumor deposits or tumor draining LN but also in other lymphoid compartments (such as bone marrow, non-draining LN, gut, etc.), they monitored cytokine and chemokine release as surrogate markers for effector cell trafficking or homing to inflammatory sites. This mLN ex vivo assay could also be run from frozen specimen (not shown).
[0176] The findings indicated that mLN reactivity to immunomodulators was personalized in that i) a precise and specific typification of immune activation for each mAb or their combinations was not possible, in contrast to generalizable responses to rIL-2 or rIFN type 1, ii) each individual exhibited a specific pattern of response to the panel of stimulatory agents, a clustering/stratification of patients being impossible to establish on this cohort. Interestingly, inventors' long term expertise in this ex vivo tumor restimulation assay underscores the importance of a peculiar tumor microenvironment in the functional outcome. Indeed, GIST responded best to anti-IL-10 or anti-TRAIL Ab or rIFNa2a than to anti-PD-1 or anti-CTLA-4 Ab (Rusakiewicz et al, OncoImmunology, in press).
[0177] The most prominent markers helping the decision making for gearing therapy to ICB are not the obvious candidates. Hence, CD95 expression (and not CTLA-4) on CD4.sup.+ T cells is crucial to predict resistance to anti-CTLA-4 Ab, while CD137 in circulating CD8.sup.+ T cells is important for the reactivity to the combination of anti PD-1 (aPD-1) and anti CTLA-4 (aTLA-4) Ab. The clinical significance of CD95/CD95L has been largely investigated in various human malignancies (23-30). Notably, in breast cancer and melanoma, serum soluble CD95 or CD95L is associated with disease dissemination and dismal prognosis. A mechanism has been proposed in triple negative breast cancers where sCD95L levels are higher than in other breast cancer subtypes and dictate metastatic dissemination whereby metalloproteases-mediated cleavage of CD95L expressed by endothelial cells engage an unconventional CD95 signaling pathway involving EGFR and the Src kinase c-yes, leading to migration of breast tumor cells and not apoptosis (31). Primary and metastatic melanoma lesions express high levels of CD95 and CD95L (28) and melanoma reactive T cells resist to CD95L mediated cell death (30). Here inventors show that membrane associated CD95 on CD4.sup.+ T cells is associated with an activated and/or exhausted phenotype of TEM and TCM in blood and lesions and that it does not convey a prognostic value. However, low CD4.sup.+CD95.sup.+ T cell counts appeared to predict responses to ex vivo stimulation with anti-CTLA-4 Ab, and to in vivo administrations of ipilimumab at 3 months. It would be of utmost interest to assess whether anti-CTLA-4 Ab somehow prevent the shedding of CD95 and/or its ligand from the lymphocyte membrane, preventing the deleterious effects of it soluble form.
[0178] High PD-L1 expression on circulating CD8.sup.+ T cells (but not CD4.sup.+ T cells and maybe due to the low number of patients tested (N=23)) also predicted poor clinical outcome in MM receiving ipilimumab. This result is in line with the recent discovery of a cell autonomous role of the PD-1 signaling pathway on melanoma cells. Indeed, overexpression of the PD-1 receptor or engagement of melanoma-PD-1 by its ligand, PD-L1, in melanoma cells could enhance tumorigenicity in mice. Conversely, PD-L1 inhibition in melanoma or knockout of host PD-L1 both reduced tumor aggressiveness of PD-1 expressing melanomas. The authors showed that the melanoma intrinsic PD-1 expression modulated downstream effectors of the mTOR signaling (15). Inventors postulate that type I IFN enriched tumor microenvironment might regulate PD-L1 expression on surrounding CD8.sup.+ CTLs that in turn could engage with neighbouring melanoma, preventing death and promoting dissemination during ipiliumab therapy. This mechanism could represent another reason explaining the additive effects of the anti-CTLA-4+anti-PD-1 Ab combination.
[0179] These two novel predictive immunometrics have to be included in the long list of putative biomarkers potentially relevant for this ICB. Inventors' previous experiences suggested that high LDH levels and sCD25 concentrations in the serum negatively predicted TTP in ipilimumab treated-stage IV MM (32) while CLA expressing CD8.sup.+ TEM represented a pharmacodynamic trait of sensitivity to CTLA4 blockade (Jacquelot, JCI in press). While HLA subtype (33), genetic polymorphisms (34), and absolute lymphocyte counts (35) have not been validated, a number of alternative parameters such as high baseline levels of Foxp3, IDO expression (34) and increase TILs and TH1 cells at baseline (36) or MDSC numbers (37) or T cell ICOS expression as pharmacodynamic markers (38) or more recently a high mutational load and neoantigen landscape (39) have all to be prospectively studied.
[0180] Biomarkers of response to anti-PD-1/PD-L1 Ab have been largely studied and may be considered as promising for future prospective validation. Selective CD8.sup.+ T cell infiltrations preceding PD-1 blockade, often correlated with PD-L1 expression and with a precise geodistribution at the tumor invasive margins appeared to predict OR in stage IV melanoma (40-42). The immunohistochemical determination of PD-L1 expression, although lacking a methodology for standardization and subjected to variegated expression depending on timing and biopsy sites, may also influence the response to PD-1 blockade and guide the choice between PD-1 versus CTLA-4+PD-1 coblockade (41, 43). Once again, a high mutational load is also associated with clinical responses to PD-1 blockade (39, 44). Inventors herein provide advantageous new blood biomarkers (in particular PD-1 expression on CD4.sup.+ T cells or the CD8/Treg ratio in blood).
Material and Methods
[0181] Patients and Cohorts Characteristics. Prospective Cohort of 37 Patients.
[0182] Patients over 18 years old from Gustave Roussy Cancer Campus and Centre Hospitalier Lyon Sud, with histologically confirmed metastatic and/or resectable melanoma provided written informed consents according with protocols reviewed and approved by institutional ethic committee including the investigator-sponsored MSN study (NCT02105168). Retrospective cohort of 64 patients. University of Tubingen cohort Blood was collected and markers were assessed before Ipilimumab and IL-2 injections from 3 patients participating in a phase II study evaluating safety and efficacy of combined ipilimumab and intratumoral IL-2 treatment in pretreated patients with stage IV melanoma (clinical trial number: NCT01480323). University of Siena cohort. Blood samples were collected before ipilimumab treatment of unresectable stage III and stage IV melanoma at the University Hospital of Siena between July 2011 and June 2015. Markers were assessed after thawing samples. Memorial Sloan Kettering Cancer Center cohort. Blood samples were collected before injections of Ipilimumab from patients suffering of stage IV melanoma (clinical trial number: NCT00495066). Markers were assessed after thawing samples. University of Stanford cohort. Blood samples were collected before injections of Ipilimumab from patients participating in a study evaluating Ipilimumab in adjuvant. Markers were assessed on PBMC after thawing.
[0183] Peripheral Blood Mononuclear Cells (PBMC) Preparations.
[0184] Peripheral blood samples from 23 patients drawn just prior to surgery were carefully layered on top of a Ficoll-Hypaque density gradient media (PAA Laboratories). After washes, PBMC were counted and stained with appropriate Abs as described below and in the Table 4.
TABLE-US-00004 TABLE 4 List of monoclonal antibodies used for the Flow Cytometry in the ex-vivo assay Name Fluorochrome Company Reference Clone CD8 FITC BD 555366 RPA-T8 CD4 PerCP BD 345770 SK3 CD56 PE Cy7 Beckman A21692 N901 CD3 VioBlue Miltenyi 130-094-363 OKT3 Dead cells Yellow Invitrogen L34957 CD45 APC AF750 Beckman A79392 J.33 TIM3 APC eBiosciences 17-3109-42 F38-2E2 CD152 PE BD 555853 BNI3 (CTLA-4) CD137 APC Biolegend 309810 4B4-1 (CD137) CD137L PE BD 559446 C65-485 (CD137L) CD274 APC Biolegend 329708 29E.2A3 (PD-L1) CD95 (Fas) APC BD 558814 DX2 CD178 (FasL) PE eBiosciences 12-9919-42 NOK-1 CD69 APC BD 555531 FN50 CD69 PerCP BioLegend 310928 FN50 CD25 PE BD 555432 M-A251 CD45RA PE BD 555489 HI100 CD314 PE Miltenyi 130-092-672 BAT221 (NKG2D) CD279 (PD-1) PE Cy7 Beckman A78885 PD-1.3.5 CD27 APC BD 558664 M-T271 CD127 APC Miltenyi 130-094-890 MB15- 18C9 LAG3 FITC R&D FAB2319F Polyclonal Ab CD14 FITC BD 555397 M5E2 CD15 PB BioLegend 323022 W6D3 HLA DP/DR/ APC Miltenyi 130-104-824 REA332 DQ HLA DR PB Beckman A74781 Immu-357 CD11c PE Cy7 BioLegend 301608 3.9 CD11b PE Cy7 BD 557743 ICRF44 CD19 PE Cy7 BD 557835 SJ25C1 CD20 PE Miltenyi 130-091-109 LT20 TNF AF647 Biolegend 502916 Mab11 IFN PE BD 559327 B27 Ki67 PE BD 556027 B56 Foxp3 APC eBiosciences 17-4776-42 PCH101 ICOS PE BD 557802 DX29 CCR7 BV421 BioLegend 353208 G043H7 CD40L FITC BD 555699 TRAP1
[0185] Tumor Infiltrated Lymphocyte (TIL) Preparations.
[0186] Resected mLN specimens from 37 MM were cut and placed in dissociation medium, which consisted of RPMI1640, 1% Penicillin/Streptomycine (PEST, GIBCO Invitrogen), Collagenase IV (501U/mL), Hyaluronidase (280 IU/mL), and DNAse I (30 IU/mL) (all from Sigma-Aldrich), and run on a gentle MACS Dissociator (Miltenyi Biotec). Dissociation time lasted one hour under mechanical rotation and did not influence the results of the phenotyping. Cell samples were diluted in PBS, passed through a cell strainer and centrifuged for 5 minutes at 1500 rpm. Cells were finally resuspended in PBS, counted, stained for flow cytometric analyses or resuspended in CryoMaxx medium (PAA Laboratories) for storage in liquid nitrogen. All mLN included in the study were histologically confirmed to be invaded.
[0187] Ex-Vivo MLN Assays.
[0188] Dissociated cells from mLN were incubated in two 48-well plates at 0.310.sup.6/ml in complete medium (RPMI 1640 supplemented with 10% human AB serum [Institut de Biotechnologie Jacques Boy], 1% Penicillin/Streptomycine (PEST, GIBCO Invitrogen), 1% L-glutamine (GIBCO Invitrogen) and 1% of sodium pyruvate (GIBCO Invitrogen)) and with isotype control, agonistics (CD137/CD137L) or antagonistic (PD-1/PD-L1, CTLA-4, Tim-3) mAbs or cytokines (IFN2a [Roferon, ROF], IL-2) or their combinations (PD-1+ROF, CTLA-4+ROF, PD-1+Tim-3, PD-1+CTLA-4) as described in the
[0189] Flow Cytometric Analyses.
[0190] For membranous labeling, PBMC and TILs were stained with fluorochrome-coupled monoclonal antibodies (mAbs detailed in Table 4 and 5), incubated for 20 min at 4 C. and washed. Cell samples were acquired on a Cyan ADP 9-color flow cytometer (Beckman Coulter) with single-stained antibody-capturing beads used for compensation (Compbeads, BD Biosciences). Data were analyzed with Flowjo software v7.6.2 (Tree Star, Inc).
TABLE-US-00005 TABLE 5 List of monoclonal antibodies used for chemokine receptors analysis Specificity Fluorochrome Ab clone Company Reference CXCR5 AF488 RF8B2 BD 558112 CLA FITC HECA-452 BD 561987 CRTH2 FITC BM16 BD 561659 CD103 PE Ber-ACT8 BD 550260 CCR10 PE 314305 R&D FAB3478P CD4 PE-CF594 RPA-T4 BD 562281 CD8 PerCP SK1 BD 345774 CCR9 PerCP Cy5.5 BL/CCR9 Biolegend 346303 CXCR4 PerCP Cy5.5 12G5 Biolegend 306516 CXCR3 PE Cy7 1C6/CXCR3 BD 560831 CD4 PE Cy7 SK3 BD 557852 CCR7 BV421 G043H7 Biolegend 353208 CD14 V500 M5E2 BD 561391 CD15 V500 HI98 BD 561585 CD16 V500 3G8 BD 561394 CD19 V500 HIB19 BD 561121 CD8b APC 2ST8.5H7 BD 641058 CCR6 AF647 11A9 BD 560466 CD45RA APC-H7 HI100 BD 560674 Dead Cells Yellow Invitrogen L34959
[0191] Cytokines and Chemokines Measurements.
[0192] Supernatants from cultured cells were monitored using the human Th1/Th2/Th9/Th17/Th22 13-plex RTU FlowCytomix Kit (eBiosciences), and human Chemokine 6 plex kit FlowCytomix (eBiosciences) according to the manufacturer's instructions and acquired on a Cyan ADP 9-color flow cytometer (Beckman Coulter). Analyses were performed by Flowcytomix Pro 3.0 Software (eBiosciences). Moreover some measurements were done by ELISA with IFNg (BioLegend), IL-9 (BioLegend), TNF (BD Biosciences), CCL2 (BD Biosciences), CCL3 (R&D Systems), CCL4 (R&D Systems), CCL5 (R&D Systems) and CXCL10 (BD Biosciences) kits in accordance with manufacturer's recommendations.
[0193] Statistics.
[0194] Data analyses and representations were performed within the statistical environment R (see Worldwide Website: R-project.org/). In all, 124 (blood) and 128 (tumor) parameters were considered for analyses and reporting. All remaining calculations were performed within R. Individual data points representing the measurement from one patient are systematically graphed alongside with the box and whiskers plot calculated from the corresponding distribution. Comparisons between clinical groups were performed by beta regression for parameters expressed in percentage and by linear modeling for the other parameters and ratios after log transformation. Dispersion was allowed to differ between groups and contrasts of interest are back-transformed and presented as ratios. Overall Survival (OS) and Progression Free Survival (PFS) determined from the date of sampling were used as the primary end-points. Survival curves were estimated by the Kaplan-Meier product-limit method. Survival distributions were compared by Firth's penalized-likelihood Cox regression after adjusting for the BRAF status, gender, number of metastatic lymph nodes, lactate deshydrogenase levels (LDH) thresholded at 250 ui/L and disease stage. Unless stated, p-values are two-sided and 95% confidence intervals for the statistic of interest are reported. Effectiveness of the biomarker was determined from the 0.632 corrected bootstrap (B=199) after log-concave density smoothing of the AUC under the ROC curve. The empirical ROC curve and corresponding AUC are reported and graphed together with the smoothed curves. Optimal cut-off corresponds to the maximum effectiveness of the biomarker followed the Youden index and the confidence intervals were determined on the same bootstrap samples as for the AUC.
Example 2CLA Expression on CD8.SUP.+ T Cells Assessed 3 Weeks after the First Injection Predicts the Response to Ipilimumab Treatment
Significant Changes During Immune Checkpoint Blockade by Ipilimumab
[0195] CTLA4 blockade by the FDA- and EMEA-approved drug ipilimumab induces significant and prolonged (>7 years) antitumor effects in about 20% of metastatic melanoma (MMel) (19, 20). Inventors analyzed all the CC and CXC chemokine receptors described herein (Table 5) in 47 patients diagnosed with stage IV MM treated with ipilimumab (mainly 3 mg/kg (87%)), enrolled at four clinical centers (detailed in Jacquelot et al, JCI in press). Interestingly, although most of the above detailed markers were analyzed, only CLA expression on CD8.sup.+ TEM [cell numbers (
Example 3Predictors of Responses to Immune Checkpoint Blockade in Advanced Melanoma
[0196] Immune checkpoint blockers (ICB) have become pivotal therapies in the clinical armory against metastatic melanoma (MMel). Given the frequency of immune related-adverse events and increasing use of ICB, predictors of response to CTLA-4 and/or PD-1 blockade represent unmet clinical needs. Using a systems biology-based approach on assessment of 779 paired blood and tumor markers in 37 stage III MMel patients, inventors analyzed correlates between blood immune parameters and the functional immune reactivity of tumor-infiltrating cells after ex vivo exposure to ICB. Based on this assay, they retrospectively validated in 8 cohorts, enrolling 190 MMel patients, that high PD-L1 expression on peripheral T cells was the best marker predicting shorter progression free- and overall-survival to ipilimumab. Moreover, detectable CD137 on circulating CD8.sup.+ T cells was associated with the disease-free status of resected stage III MMel patients after adjuvant ipilimumab+nivolumab (but not nivolumab alone).
[0197] The recent development of immune checkpoint blockers (ICB) has rekindled interest in the field of immune cancer therapies (3,4). Cancer vaccines (5), adoptive T cell transfer and CAR T cells (6,7), bispecific antibodies (8), ICBs (9,10) and oncolytic viruses (11) have come of age and many immune agents have recently entered the oncological armory. However, to date, immunotherapy has only been shown to provide durable clinical benefit in a fraction of patients. The recent characterization of multiple immune resistance mechanisms by which tumors can evade the immune system has fueled the development of novel agents that circumvent such limitations, targeting new immune checkpoints. It is likely that the use of combination strategies will increase the number of cancer patients that might benefit from immunotherapy (12). Nonetheless, several critical problems remain to be solved. First, the scientific rationale supporting the use of combinatorial regimens needs to be defined. Second, it must be determined whether the future of immuno-oncology (I-O) will rely on patient stratification in large cohorts or will be personalized to each patient. Depending on tumor characteristics (e.g., PD-L1 or PD-1 expression on tumor cells for anti-PD-1 mAb (13-15), HMGB1 and LC3B for immunogenic chemotherapy (16), or tumor microenvironment hallmarks such as IDO expression (17), macrophage density (18), tumor-infiltrating lymphocytes [TIL], or Th1 fingerprints (19)), one might envisage more specific and individualized I-O clinical management strategies. Third, predictive immune profiles or biomarkers will need to be validated prospectively to guide I-O utilization in a personalized or stratified manner.
[0198] Inventors attempted to address some of these questions in patients with stage III melanoma (45), given that (i) optimizing adjuvant I-O therapies for metastatic melanoma (MMel) remains an unmet clinical need, (ii) MMel represents a clinical niche for the development of many mAbs and ICBs, (iii) in these patients, metastatic lymph nodes (mLN) are surgically resected, enabling immunological investigations, and (iv) immune prognostic parameters have been recently described in stage III/IV MMel (46, 47). The tumor microenvironment has a complex regulation. Each checkpoint/co-stimulatory pathway displays an independent mechanism of action and this call for a comprehensive analysis of their mode of action in the tumor microenvironment in a given patient to design appropriate combinatorial approaches and to discover specific biomarkers of response. Herein, inventors used a systems biology-based approach aimed at defining relevant immunometrics for prediction of an in situ response to cytokines and monoclonal antibodies (mAb) (i.e., agonists and blockers of immune checkpoints) in patients with resected stage III melanoma. They describe a suitable ex vivo metastatic lymph node (mLN) assay (see example 1), and through this assay they demonstrate, in multivariate analyses performed on 8 pooled cohorts gathering 190 samples of unresectable stage III and IV melanoma. They demonstrated that the best markers predicting resistance to ipilimumab were high PD-L1 expression in peripheral blood CD4.sup.+ and CD8.sup.+ T cells (for progression free survival (PFS) and overall survival (OS)), while in stage III melanoma, detectable CD137.sup.+CD8.sup.+ peripheral blood T cells predicted a lack of relapse with ipilimumab+nivolumab combination therapy. They conclude that i) the ex vivo metastatic lymph node (mLN) assay represents a suitable method to identify biomarkers for ICB, ii) PD-L1 expression on blood CD8.sup.+ T cells is a strong marker of resistance to CTLA4 blockade.
Results
Functional Immunological Assays on Ex Vivo Dissociated mLN.
[0199] The study population consisted of stage III MMel patients undergoing surgery for lymph node metastases, as previously described (46). Of these patients, one third presented with more than 3 involved LN at surgery, 55% had a mutated BRAF oncogene, >30% had thyroid dysfunction, and >50% were scheduled to undergo adjuvant therapy. Of primary lesions, 52% were ulcerated. After mechanical and enzymatic digestion of mLN (46), CD45.sup. cells represented 4-984.8% of all cells. The composition of tumor-infiltrating immune cells was analyzed by flow cytometry with gating on live cells in 39 tumor specimens that were paired with autologous peripheral blood cells. Analyses were based on a comprehensive immunophenotyping of 252 parameters per patient, featuring cell type, activation status, nave or memory phenotype, and activating or inhibitory receptors or ligands. Inventors previously found that peripheral blood cell markers were as relevant as TIL immunotypes for prognosis, and parameters associated with lymphocyte exhaustion/suppression were associated with greater clinical significance compared to those related to activation or lineage (46). The next step consisted of analyzing the dynamics of these parameters after incubation with mAbs+/cytokines on 37 patients. Comprehensive assessment of the reactivity of various subsets of infiltrating tumor cells targeting four functional axes, cytokines and their combinations is described (
[0200] The Venn diagrams detailing the patterns of immune reactivities are depicted in
Predictive Biomarkers of Resistance to CTLA-4 Blockade
[0201] Inventors next addressed whether predictive biomarkers of a functional response obtained in the ex vivo mLN assay could be inferred from the 779 blood/tumor parameters. Very few statistically significant immune parameters predicting responses to CTLA-4 blockade could be found (
[0202] The stronger predictive biomarkers of ex vivo resistance to CTLA-4 blockade were elevated PD-L1 expression on circulating CD4.sup.+ T cells (
[0203] Ipilimumab not only improves overall survival in stage IV MMel but also impacts overall-survival, recurrence-free survival and distant metastasis-free survival in resected high-risk stage III melanoma (48, 49). In order to validate their immune biomarkers selected in the ex vivo mLN assay, inventors retrospectively analyzed this blood T cell phenotype, focusing on PD-L1 and CD95, in 8 cohorts from different centers including 190 unresectable stage III and IV MMel patients treated with 3 mg/kg (in 90% cases) of ipilimumab with a median follow-up of 30 months [95% CI: 26-34] (patients' characteristics presented in Table 7).
TABLE-US-00006 TABLE 7 Cohorts and patient's characteristics Overall (190) CA (19) CH (16) DE (3) DK (67) FR (15) IT (10) OR (20) JE (40) Gender Female 93 (49%) 8 (42%) 5 (31%) 0 (0%) 36 (54%) 12 (80%) 4 (40%) 9 (45%) 19 (47%) Male 97 (51%) 11 (58%) 11 (69%) 3 (100%) 31 (46%) 3 (20%) 6 (60%) 11 (55%) 21 (53%) Age Mean 61 (13) 64 (12) 58 (15) 64 (11) 63 (12) 66 (14) 56 (16) 59 (13) 58 (14) (SD) LDH Low 112 (62%) 6 (32%) 13 (100%) 1 (33%) 56 (85%) 11 (73%) 2 (22%) 6 (30%) 17 (47%) High 69 (38%) 13 (68%) 0 (0%) 2 (67%) 10 (15%) 4 (27%) 7 (78%) 14 (70%) 19 (53%) Missing 9 0 3 0 1 0 1 0 4 Tumor stage III 13 (7%) 1 (5%) 2 (12%) 0 (0%) 0 (0%) 8 (53%) 1 (10%) 1 (5%) 0 (0%) IV 177 (93%) 18 (95%) 14 (88%) 3 (100%) 67 (100%) 7 (47%) 9 (90%) 19 (95%) 40 (100%) Tumor PD 127 (67%) 11 (58%) 13 (81%) 3 (100%) 42 (63%) 2 (13%) 6 (60%) 17 (85%) 33 (83%) response SD 31 (16%) 1 (5%) 1 (6%) 0 (0%) 14 (21%) 7 (47%) 4 (40%) 0 (0%) 4 (10%) PR 18 (9%) 6 (32%) 0 (0%) 0 (0%) 9 (13%) 2 (13%) 0 (0%) 1 (5%) 0 (0%) CR 14 (7%) 1 (5%) 2 (12%) 0 (0%) 2 (3%) 4 (27%) 0 (0%) 2 (10%) 3 (8%) Previous CT Yes 71 (42%) 9 (47%) 8 (50%) 2 (67%) 11 (16%) 3 (20%) 8 (80%) 0 (0%) 30 (75%) Missing 20 0 0 0 0 0 0 20 0 Previous IT Yes 66 (35%) 4 (21%) 1 (6%) 1 (33%) 19 (28%) 11 (73%) 3 (30%) 14 (70%) 13 (32%) Previous PKI Yes 16 (9%) 2 (11%) 3 (19%) 1 (33%) 3 (4%) 1 (7%) 3 (30%) 0 (0%) 3 (8%) Missing 20 0 0 0 0 0 0 20 0 Ipilimumab 3 mg/kg 143 (88%) 0 (0%) 16 (100%) 3 (100%) 67 (100%) 15 (100%) 10 (100%) 20 (100%) 12 (100%) dose 10 mg/kg 19 (12%) 19 (100%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) Missing 28 0 0 0 0 0 0 0 28 Co-treatment GMCSF 19 (10%) 19 (100%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) IL2 3 (2%) 0 (0%) 0 (0%) 3 (100%) 0 (0%) 0 (0%) 0 (0%) 0 (0%) 0 (0%)
[0204] PD-L1 and CD95 were evaluated retrospectively at diagnosis in whole blood or PBMCs (after density gradient separation of cells) by flow cytometry gating on CD4.sup.+ and/or CD8.sup.+ T cells using a standardized methodology validated for all centers (either performed by inventors' laboratory, after thawing of cryopreserved cells or by the investigators themselves using inventors' antibodies and procedures). CD95 expression levels were higher in MMel compared with HV in blood T cells (
[0205] Next, PD-L1 and CD95 biomarkers have been analyzed on a continuous scale.
[0206] First, the tumor response evaluated at 3 months was categorized into 4 groups: progressive disease (PD, n=127 (67%), stable disease (SD, n=31, 16%), partial response (PR, n=18, 9%) and complete response (CR, n=14, 7%) (Table 7). The chosen binary outcome for the logistic regression model was: PD (n=127) versus SD+PR+CR (n=63). Table 8 shows the impact of clinical covariates on tumor response and survival endpoints (PFS and OS).
TABLE-US-00007 TABLE 8 Clinical prognostic parameters for Ipilimumab responses (PD vs SD + PR + CR), OS and PFS Tumor Overall Progression - response survival free survival Age 1.002 0.992 0.992 [0.997; 1.007] [0.977; 1.006] [0.979; 1.006] P = 0.468 P = 0.268 P = 0.253 Gender 0.94 1.09 1.26 (ref = female) [0.83; 1.07] [0.76; 1.58] [0.89; 1.77] P = 0.38 P = 0.63 P = 0.20 LDH 0.87 2.31 1.51 (ref = low) [0.74; 1.01] [1.47; 3.62] [0.96; 2.38] P = 0.068 P < 0.001 P = 0.073 Previous CT 0.92 1.62 1.01 (ref = no) [0.79; 1.08] [1.02; 2.58] [0.68; 1.48] P = 0.32 P = 0.043 P = 0.97 Previous IT 1.08 0.71 0.77 (ref = no) [0.94; 1.25] [0.47; 1.08] [0.53; 1.13] P = 0.27 P = 0.11 P = 0.18 Previous PKI 0.74 2.04 1.95 (ref = no) [0.58; 0.93] [1.01; 4.09] [1.04; 3.67] P = 0.012 P = 0.046 P = 0.038 Tumor stage 1.03 1.01 0.55 (ref = stage III) [0.77; 1.40] [0.29; 3.47] [0.21; 1.43] P = 0.83 P = 0.99 P = 0.22
[0207] All models were stratified on the center. Odds Ratio (for the tumor response) and Hazard Ratio (for the survival endpoints) with 95% confidence intervals. CT: chemotherapy and/or radiation, IT: immunotherapy, PKI: protein kinase inhibitors.
[0208] Even if the gender, the age and the tumor stage were not significant in the univariate analysis, inventors kept these variables in the final model as they are recognized as potential prognostic factors. Hence, for the following analyses, the final models were stratified based on the centers and adjusted for LDH (low or high, meaning below or above the normal value for each individual clinical center), previous chemotherapy (yes or no), previous immunotherapy (yes or no), previous protein kinase inhibitor (yes or no), gender (male or female), age (continuous scale) and tumor stage (III or IV). When considering the predictive value of CD95 or PD-L1 in blood CD4.sup.+ and CD8.sup.+ T cells for response rates assessed after 4 cycles of ipilimumab, and adjusting for all of the other clinical variables (Table 8), inventors found that the only immunometrics associated with clinical responses at 12 weeks were CD95 on CD4.sup.+ T cells (
[0209] Next, inventors analyzed the impact of those biomarkers on PFS (in 169 MMel including 143 events) and OS (in 189 MMel including 121 events) (
TABLE-US-00008 TABLE 6 Association between CD95 and PD-L1 (continuous scale) and the progression free- and overall survivals Model CD95.CD4 CD95.CD8 PDL1.CD4 PDL1.CD8 Progression free survival Univariate 1.007 0.996 1.021 1.021 [0.997; 1.017] [0.986; 1.006] [0.999; 1.043] [1.001; 1.042] P = 0.19 P = 0.44 P = 0.057 P = 0.040 Stratify on center 1.001 0.998 1.022 1.016 [0.989; 1.012] [0.986; 1.009] [0.993; 1.051] [0.986; 1.046] P = 0.92 P = 0.69 P = 0.15 P = 0.30 Stratify on center 1.004 0.999 1.044 1.032 Adjust for LDH, [0.991; 1.017] [0.984; 1.015] [1.011; 1.079] [0.999; 1.065] gender age, tumor P = 0.59 P = 0.93 P = 0.009 P = 0.056 stage, CT, IT and PKI* Overall Survival Univariate 1.010 1.013 1.036 1.043 [0.999; 1.022] [1.001; 1.025] [1.012; 1.059] [1.023; 1.063] P = 0.082 P = 0.031 P = 0.003 P < 0.001 Stratify on center 1.009 1.001 1.027 1.045 [0.996; 1.022] [0.989; 1.014] [0.993; 1.062] [1.015; 1.076] P = 0.16 P = 0.83 P = 0.12 P = 0.003 Stratify on center 1.010 1.009 1.041 1.053 Adjust for LDH, [0.994; 1.027] [0.991; 1.028] [0.995; 1.089] [1.012; 1.096] gender, age, tumor P = 0.21 P = 0.33 P = 0.081 P = 0.011 stage, CT, IT and PKI* Hazard ratios and 95% confidence intervals. Final model designated with an *.
[0210] Similarly, elevated levels of those biomarkers on pre-treatment T cells were also significantly associated with OS with PD-L1.sup.+CD8.sup.+ T cells (
[0211] Moreover, a combination of these two markers, PD-L1.sup.+/CD8.sup.+ (according to the median value) and CD95.sup.+/CD4.sup.+ (according to the cut-off value at 70%) was feasible according to the low coefficient of correlation between these parameters enabling a segregation of the cohort into 4 arms with patients harboring both a high expression of PD-L1 and CD95 who were found to be associated with a shorter overall survival (
[0212] Altogether, inventors' data indicate that high frequencies of circulating PD-L1.sup.+ T cells predict resistance to CTLA-4 blockade (mostly 3 mg/kg) for RR, PFS and OS in unresectable stage III and IV MMel.
Predictive Biomarkers of Response to CTLA-4+PD-1 Co-Blockade
[0213] The regimen of ipilimumab and nivolumab has demonstrated impressive clinical benefit in MMel (objective response rate [ORR]>60% with a PFS>11 months), but is also associated with a high rate of immune related adverse events (>50% grade 3-4 events) (20). This supports further investigation into biomarkers which may predict which patient may derive the most benefit to spare primarily resistant patients the toxicity of the treatment. Given that the proportion of mLN that respond to both anti-CTLA-4 and anti-PD-1 mAb separately was 11/37 (29%), among which 45% failed to respond to combined blockade (Table 2,
[0214] To validate the predictive value of CD137 expression on circulating CD8.sup.+ T cells at baseline for clinical benefit from the combination of ipilimumab and nivolumab, inventors analyzed this parameter in PBMCs obtained from a phase II adjuvant trial assessing the efficacy of nivolumab and ipilimumab combination therapy in resected stage IIIc and IV MMel. The median follow up of this study was 13 months. The expression levels of CD137 on circulating CD8.sup.+ T cells at baseline in this cohort of patients was within the range of those described above in patients with metastatic disease (
[0215] Of note, CD137 expression on CD8.sup.+ T cells did not predict relapse in patients with high-risk resected melanoma treated with nivolumab alone as anticipated from our correlative matrices (
[0216] Altogether, this study demonstrates that the ex vivo mLN assay as well as the preselected predictive biomarkers of response or resistance to the mAbs may the identification of patients likely to respond to fail the proposed therapy.
Discussion
[0217] Inventors describe new predictive biomarkers of response to CTLA-4 blockade and to effective but potentially toxic combination therapy composed of anti-CTLA-4+anti-PD-1 mAbs. These results are based on a functional method herein called the ex vivo mLN assay, capable of assessing the reactivity of tumor infiltrating immune effectors (T and NK cells) during stimulation with various ICB or agonistic mAbs and their combinations. This was coupled with a paired blood and tumor immune profiling of mLN in stage III MMel with the intention of correlating immune fingerprints with clinical parameters(21, 22). Inventors elucidated the relevance of PD-L1 expression on circulating T cells for the prediction of resistance to ipilimumab, alone or in combination with IL-2 or GM-CSF. Moreover, their study shows that detectable levels of CD137 on circulating CD8.sup.+ T cells after LN or metastatic resection in stage IIIc and IV melanoma tends to predict longer PFS for the anti-CTLA-4+anti-PD-1 co-blockade.
[0218] The ex vivo mLN assay was feasible for almost all mLN specimens containing at least 10.sup.7 cells (37/46 were successfully performed and contained enough cells for the ex vivo mLN assay). Of note, this method could be downscaled to the size of a biopsy if only 1 or 2 mAbs had to be tested. The method is also reliable in that the two negative controls used (18-24 h or a 4-5 day incubation in the absence of stimulus or in the presence of Ig control mAb) allow the basal assessment of T cell functions to be determined (46) with low non-specific backgrounds. The high dose rIL-2 and rIFN2a positive controls almost invariably triggered effector (and Treg) proliferation and CXCL10 release, respectively, in all patients. Inventors showed that this method can analyze important dynamic T and NK cell parameters relevant to effector functions against cancer, such as proliferation and release of Th1 cytokines as well as proportions of Tregs in the co-culture system. Cytokine and chemokine release could be considered as surrogate markers for effector cell trafficking or homing to inflammatory sites.
[0219] The findings from inventors' study indicate that the mLN reactivity to immunomodulators is specific for each patient since (i) a precise and specific pattern of immune activation for each mAb or their various combinations across patients was not possible, in contrast to generalizable responses to rIL-2 or rIFN2a; (ii) each individual patient exhibited a specific pattern of response to the panel of stimulatory agents, therefore a clustering/stratification of patients was impossible to establish in this cohort. Interestingly, their long-term expertise with this ex vivo tumor restimulation assay underscores the relevance of the tumor microenvironment in dictating the functional outcome. Indeed, GIST responded best to anti-IL-10 or anti-TRAIL mAbs or rIFN2a, rather than to anti-PD-1 or anti-CTLA-4 mAbs (50).
[0220] Inventors' study also uncovers, for the first time, two biomarkers of resistance or response to I-O regimens: ipilimumab alone or combined with PD-1 blockade. Herein, inventors found that the most prominent markers predicting response to such regimens are not the obvious candidates. PD-L1 (and not CTLA-4) on T cells was found crucial for the prediction of resistance to anti-CTLA-4 mAb, whereas CD137 expression on circulating CD8.sup.+ T cells appears a promising predictor of long term (>13 months) relapse-free survival mediated by the combination of anti-PD-1 and anti-CTLA-4 mAbs in the adjuvant setting.
[0221] Most previous biomarker studies with PD-1/PD-L1 antibodies have focused on the prognostic significance of PD-L1 (and/or PD-L2) expression on tumor cells or myeloid cells of the TME. Expression of both PD-L1 and PD-L2 significantly correlated with increasing densities of immune cells in the tumor specimens and with immunotype. Positive PD-L2 expression alone or combination with PD-L1 expression, was associated with improved overall survival (51). High PD-L1 expression on melanoma were found predominantly in regions of abundant inflammation or TIL infiltrates, even in sanctuaries like brain metastases (52), but it failed to predict responses to ICB in MMel. To inventors' knowledge, this is the first comprehensive analysis of the predictive role of PD-L1 expression on peripheral blood T cells in melanoma. This expression might reflect the chronic exposure to type 1-type 2 IFNs in the TME in recirculating TILs ((47) and not shown), as already reported in tumor cells themselves (53).
[0222] Inventors believe that given its biological relevance (24-31, 54-56) and co-expression of a variety of inhibitory receptors on CD95.sup.+CD4.sup.+ T cells (such as PD1, and HLA-DR,
[0223] The combination of immune checkpoint inhibitors ipilimumab and nivolumab has been FDA-approved for first-line treatment of unresectable MMel. This approval followed the results of CheckMate 067(20)-069(57), trials where the combination of ipilimumab and nivolumab outperformed each single agent alone in terms of response rates, PFS and OS. Additionally, recently published data in non-small cell lung cancer patients have shown promising results for the combination of anti-PD-L1 and anti-CTLA-4 mAbs in a phase 1b clinical trial (58). Hence, such combinations may be integrated into the ever-changing melanoma treatment algorithm, and will be most likely extended to other malignancies sensitive to PD-1 blockade. However, drug-related adverse events of grade 3 or 4 have been reported in 54% of patients receiving ipilimumab/nivolumab combination therapy, as compared with 24% of patients receiving ipilimumab monotherapy (59, 60). Such immune-related adverse events are generally reversible with immunosuppressive medications. Given the efficacy and relative safety of nivolumab alone, finding a predictor of response to such potentially toxic combinations is an urgent unmet clinical need. Here, inventors reveal a biomarker of response to ipilimumab+nivolumab: the presence of detectable levels of CD137 on blood CD8.sup.+ T cells, which appears to be significantly associated with a lack of relapse in resected high-risk, treatment-nave stage III MMel. This novel biomarker is based on the following data: (i) circulating T lymphocytes expressing CD137 could be found in the blood of patients with no evidence of disease at 13 months who received the combination in an adjuvant setting (and not in those where nivolumab was administered alone); (ii) the finding from the ex vivo mLN assay that CD137 is upregulated in CD4.sup.+ and CD8.sup.+ TILs in lesions qualifying as responding to ex vivo stimulation with the combination of anti-PD-1+anti-CTLA-4 mAbs (and not to anti-PD-1 mAb or to other combinatorial regimens). It is therefore conceivable that this combinatorial stimulation leads to the engagement of the CD137/CD137L co-stimulatory pathway, required for T cell fitness and recirculation in the blood of responders (47). However, this pathway did not appear responsible for immediate tumor rejection mediated by the combination regimen in mouse models, although the addition of an agonistic CD137 mAb to the combination therapy further delayed tumor outgrowth in a therapeutic MCA-induced sarcoma model (MJS, unpublished data). This data confirms a previous study performed in mouse ovarian carcinomas, where agonistic anti-CD137 mAb augmented the impact of anti-PD-1+anti-CTLA-4 mAb therapy (61).
[0224] These novel predictive immunometrics add to the long list of putative biomarkers potentially relevant for ICB therapies. Inventors previous experience suggested that high LDH levels, CXCL11 and sCD25 concentrations in the serum negatively predict time to progression in ipilimumab-treated stage IV MMel (32, 62-64), whereas CLA expressing CD8.sup.+ TEM represent a pharmacodynamic signature of sensitivity to CTLA-4 blockade (47). HLA subtype (33), genetic polymorphisms (34), and absolute lymphocyte counts (35) have not been validated as immunotherapy biomarkers, a number of alternative parameters such as high baseline levels of Foxp3 and IDO expression (34), increased TILs and Th1 cells at baseline (36), MDSC numbers (62, 37, 65), T cell ICOS expression as pharmacodynamic markers (38), and (more recently) high mutational load and neoantigen landscape (39, 66), have yet to be prospectively studied as biomarkers for the efficacy of immunotherapy for melanoma. A number of biomarkers of response to anti-PD-1/PD-L1 mAbs have been considered promising for future prospective validation. For example, selective CD8.sup.+ T cell tumor infiltration (often correlated with PD-L1 expression) and their distribution at tumor invasive margins preceding PD-1 blockade appear to predict ORR in stage IV melanoma (40-42). Similarly, the immunohistochemical determination of PD-L1 expression (although lacking a standardized methodology and subject to variable expression depending on timing and biopsy sites) may guide the choice between PD-1 blockade versus CTLA-4+PD-1 co-blockade (41-43). A high mutational load is also associated with clinical responses to the PD-1 regimen (39, 44). Moreover, high relative eosinophil count, and lymphocyte count, low LDH and absence of metastasis other than soft-tissue or lung at baseline are associated with a favorable OS in patients treated with pembrolizumab (67). The proposed blood biomarkers herein identified (PD1 expression on CD4.sup.+ T cells, PD-L1 expression on CD4.sup.+ and CD8.sup.+ T cells, or the CD8.sup.+ T cell/Treg ratio in blood) are also useful to predict the efficacy of PD-1 blockade. Inventors' findings indicate that prospective ICB adjuvant trials in stage III-IV MMel can be personalized based on i) ex vivo mLN assays or ii) blood biomarkers capable of predicting such response.
Materials and Methods
Experimental Design
[0225] In a cohort of stage III MMel patients, inventors previously reported the immune parameters that were significantly associated with outcome (example 1). They established an ex vivo assay based on the reactivity of immune cells from 37 dissociated metastatic lymph nodes to mAbs and cytokines. They arbitrarily defined responding lesions, those exhibiting a more than 1.5-fold change over two different controls (medium and IgG) in two independent biological readouts (out of 40 readouts measured, 35 were retained with a threshold of 95% of detected values). This stratification into responders (R) versus non-responders (NR) enabled them to define in a retrospective manner which parameters expressed by peripheral or infiltrating T cells were essential for this response. Furthermore, they demonstrated the validity of the method by analyzing the predictive value of some parameters on retrospective clinical cohorts including 190 unresectable stage III-IV MMel patients.
Patients and Cohorts
[0226] Study Approval.
[0227] Institutional review board approvals were granted by the University of Tubingen, the University of California, the University Hospital of Copenhagen, the University Hospital of Zrich, the University Hospital of Siena, the Sharett Institute of Oncology, the Aarhus University Hospital, the Centre Hospitalier de Nantes, and the Providence Cancer Center (for the ipilimumab-treated cohorts), the Laura & Isaac Perlmutter Cancer Center (for ipilimumab+nivolumab) and Gustave Roussy/Kremlin Bictre and Centre Hospitalier Lyon-Sud for the prospective cohort and retrospective cohorts (
[0228] Prospective Cohorts of 37 Patients.
[0229] This cohort and its clinical parameters have been previously described (example 1).
[0230] Retrospective Cohorts of 190 Ipilimumab-Treated Patients.
[0231] Patients enrolled in this study were from the University of Tubingen, University of Siena, University of California, University Hospital of Copenhagen, University Hospital of Zurich, Sharett Institute of Oncology, Aarhus University Hospital, Centre Hospitalier de Nantes, and Providence Cancer Center (Table 7). In all cohorts, blood samples were collected before injections of ipilimumab from patients participating in evaluations of ipilimumab as adjuvant therapy. Markers were assessed on PBMCs with the exception of the JE cohort (assessed on whole blood) after thawing. Patients' characteristics can be found in Table 7.
[0232] Retrospective Study on the Adjuvant Phase II Trial Testing Nivolumab+Ipilimumab Versus Nivolumab-Treated Patients.
[0233] Information regarding this clinical trial can be found in reference (70).
[0234] Peripheral blood mononuclear cells (PBMC) and TILs preparations have already been described (example 1).
[0235] Ex-Vivo mLN Assays.
[0236] See example 1.
[0237] Inventors arbitrarily defined biological responses, as those exhibiting a >1.5 fold increase over the values obtained with two negative controls (medium and Ig control mAb) in at least two independent biological readouts, except for CD4.sup.+FoxP3.sup.+ Treg for which a response was defined as a >1.5 fold decrease compared with the baseline levels in responders compared to non-responders.
[0238] Flow Cytometric Analyses.
[0239] For membrane labeling, PBMC and TILs were stained with fluorochrome-coupled mAbs (detailed in Table 4), incubated for 20 min at 4 C. and washed. Cell samples were acquired on a Cyan ADP 9-color (Beckman Coulter), BD FACS Canto II flow-cytometers or on an 18-color BD LSRII (BD Biosciences) with single-stained antibody-capturing beads used for compensation (Compbeads, BD Biosciences or UltraComp eBeads, eBiosciences). Data were analyzed with Flowjo software v7.6.5 or v10 (Tree Star, Ashland, Oreg., USA).
[0240] Cytokine and Chemokine Measurements.
[0241] Supernatants from cultured cells were monitored using the human Th1/Th2/Th9/Th17/Th22 13-plex RTU FlowCytomix Kit (eBiosciences), and human chemokine 6-plex kit FlowCytomix (eBiosciences) according to the manufacturer's instructions and acquired on a Cyan ADP 9-color flow cytometer (Beckman Coulter). Analyses were performed by FlowCytomix Pro 3.0 Software (eBiosciences). Some measurements were performed by ELISA with IFN (BioLegend), IL-9 (BioLegend), TNF (BD Biosciences), CCL2 (BD Biosciences), CCL3 (R&D Systems), CCL4 (R&D Systems), CCL5 (R&D Systems) and CXCL10 (BD Biosciences) kits in accordance with the manufacturer's recommendations.
[0242] Statistics.
[0243] Data analyses were performed with the statistical environment R (see Worldwide Website: R-project.org/). Graphical representations were performed either with the statistical environment R or Prism 5 (GraphPad, San Diego, Calif., USA). In all, 124 (blood) and 128 (tumor) parameters were considered in analyses and reporting. Individual data points representing individual patient measurements are systematically graphed within box and whiskers plots calculated from the corresponding distribution. Comparisons between clinical groups were performed by Wilcoxon rank sum test for parameters expressed in percentage and ratios after log transformation. Logistic regressions (univariate and multivariate) have been used to evaluate the association of covariates on binary endpoint (i.e. tumor response). Overall survival (OS) was defined as the time from the date of sampling to death or the last follow-up, whichever occurred first. Progression-free survival (PFS) was defined as the time from the date of sampling to death, disease progression or the last follow-up, whichever occurred first. For both survival endpoints (OS and PFS), survival curves were estimated using the Kaplan-Meier method by dichotomizing biomarkers through their median value or a chosen cut-off. Cox models have been used to perform univariate and multivariate analysis. Graphical visualization of the effect of continuous biomarkers has been performed by modeling them through splines with 2 degrees of freedom. All the logistic and Cox models evaluated the biomarkers based on a continuous scale, were stratified on the centers, and adjusted for LDH, gender, age, tumor stage, CT, IT and PKI as indicated in Table 6 and Tables 8-10. Unless stated, p-values are two-sided and 95% confidence intervals for the statistic of interest are reported. Effectiveness of the biomarker was determined from empirical ROC curve and corresponding AUC are reported and graphed together with Wilcoxon rank sum test p-values in order to determine the best immunometrics in the ex-vivo mLN assay.
TABLE-US-00009 TABLE 9 Association between CD95 and PD-L1 (continuous scale) and the ipilimumab responses (PD vs SD + PR + CR) Model CD95.CD4 CD95.CD8 PDL1.CD4 PDL1.CD8 Univariate 0.978 0.992 0.996 0.977 [0.959; 0.997] [0.973; 1.011] [0.959; 1.034] [0.947; 1.006] P = 0.023 P = 0.40 P = 0.84 P = 0.13 Stratify on center 0.979 1.007 0.995 0.972 [0.958; 1.001] [0.984; 1.032] [0.941; 1.053] [0.924; 1.020] P = 0.060 P = 0.56 P = 0.87 P = 0.25 Stratify on center 0.980 1.000 0.963 0.937 Adjust for LDH, [0.955; 1.005] [0.968; 1.031] [0.893; 1.033] [0.869; 1.001] gender, age, P = 0.12 P = 0.98 P = 0.31 P = 0.068 tumor stage, CT, IT and PKI* Odds ratios and 95% confidence intervals. Final model designated with an *.
TABLE-US-00010 TABLE 10 Association between CD95/CD4 (>70 vs. _70) and overall survival Hazard Ratio 95% CI p-value Expression of CD95/CD4 1.96 [1.10-3.48] 0.022 (>70 vs. 70) LDH status 2.61 [1.51-4.52] 0.001 Age 0.979 [0.963-0.996] 0.018 Gender 0.90 [0.58-1.42] 0.66 Tumor stage 0.61 [0.11-3.29] 0.56 Previous CT 1.36 [0.78-2.39] 0.28 Previous IT 0.76 [0.46-1.24] 0.27 Previous PKI 1.33 [0.60-2.95] 0.48 CI: confidence interval. Adjusting covariates are in italic
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