BIOMARKERS OF RESPONSE AND TOXICITY TO CANCER THERAPY: THE WHOLE IS GREATER THAN THE SUM OF ITS PARTS (SY01)
Jennifer A. Wargo, MD (University of Texas, MD Anderson Cancer Center, Houston, TX, USA) discussed about challenges and opportunities of biomarkers of response and toxicity to cancer therapy to date, the role of the microbiome and other provocative biomarkers that should be considered. Translational research in patients with analysis of longitudinal tissue and blood samples has allowed a better understanding of response and resistance to cancer therapy. For example, potential markers of toxicity were identified in patients with a more diverse T cell repertoire in the periphery and higher expression of CD27/28. In a phase II study assessing a potential advantage of the use of neoadjuvant immune checkpoint blockade in patients with high-risk resectable melanoma, treatment with neoadjuvant ipilimumab (ipi) + nivolumab (nivo) was associated with a higher response rate, pathological complete response (pCR) rate (ipi + nivo 45% vs. nivo 25%), and improved relapse-free survival (RFS) over nivo monotherapy. However, treatment with combination therapy was associated with a high rate of adverse events. Correlative analyses of these patient samples revealed known and novel biomarkers/targets for therapeutic resistance (unpublished). Another likely biomarker is microbes that co-exist with humans and influence on immunity and therapeutic responses. Responders to anti-PD-1 had a higher diversity of gut bacteria along with additional compositional differences, which was associated with more favorable immune profiles in the tumor microenvironment. In the cohort of trials, a gut microbiome “signature” with a high likelihood of response to anti-PD-1 was identified, suggesting that the gut microbiome could be used as a biomarker of response to immune checkpoint blockade. Her group also studies the influence of diet, probiotic use, gender/sex hormones, and life style factors on response and toxicity. In one of neoadjuvant studies, a strong sexual dimorphism was observed in response to therapy. Potential implications of these findings should be well considered to understand the numerous factors that contribute to therapeutic response, novel biomarkers and targets of response to immune checkpoint blockade.
IMMUNE CELL INFILTRATES PREDICTS RESPONSE TO THE PD-1 CHECKPOINT INHIBITOR PEMBROLIZUMAB IN THE NEOADJUVANT I-SPY 2 TRIAL (CTPL01_CT003)
On behalf of I-SPY2 investigators, Michael J. Campbell, PhD (University of California San Francisco, San Francisco, CA, USA) presented data from the neoadjuvant I-SPY 2 TRIAL (NCT01042379), evaluating the association of immune biomarkers with response to pembrolizumab in breast cancer patients. This was an exploratory study, and pre-treatment biopsies from 54 patients were analyzed for identification of biomarkers by the presence and spatial proximity of immune cell populations using multiplex multispectral imaging. PD-L1 expression in tumor cells, stromal cells, and combination, all associated with pathological complete response (pCR) in the pembrolizumab arm. As for immune biomarkers, infiltrates of immune cells, including CD3+ T cells (p = 0.0003), cytotoxic T (Tc) cells (p = 0.05), FoxP3+ regulatory T cells (p = 0.003), and PD-1+ T cells (p = 0.05), strongly corresponded to pCR of breast cancer patients but not in triple negative breast cancer (TNBC). In contrast, the ratios of macrophage:T cells and macrophage:Tc cells were significantly associated with non-responders. Spatial proximity score (SPS) was developed to differentiate intracellular special distance to tumor. The SPS of T cells (p = 0.004) and Tc cells (p = 0.032) also indicated the strong association with pCR in patients with breast cancer including TNBC, but not with HR+HER2-. Overall, cell density, immune cell ratios and spatial resolution provide insights to response and resistance to immunotherapy. The group confirmed the observation that T cell density predicts pCR, but more specifically that Treg and PD1+ T cell densities increase the chance of pCR. An increase in macrophages relative to Tc cells predicts resistance. The closer the T cells are to the tumor, the better the response. These results demonstrate the utility of characterizing the immune microenvironment, in the context of therapy with immuno-oncology agents, not only to predict response but also to gain insight and learn how to potentiate agents and combinations.
ADVANCES IN NOVEL IMMUNOTHERAPEUTICS GENOMIC ANALYSES AND IMMUNOTHERAPY IN ADVANCED MELANOMA (CTMS01_CT037)
F. Stephen Hodi, MD (Dana-Farber Cancer Institute, Boston, MA, USA) presented data from two randomized phase III trials CheckMate 066 (NCT01721772) and CheckMate 067 (NCT01844505), evaluating nivolumab (nivo) vs. dacarbazine (D) and nivo + ipilimumab (ipi) combination therapy or nivo vs. ipi, respectively, in advanced melanoma. Increased tumor mutational burden (TMB) and inflammation are associated with improved clinical outcomes to immuno-oncology (I-O) therapy in many tumor types. In this study, genomic correlates of response to nivo vs. D (CheckMate 066) and nivo + ipi combination therapy or nivo vs. ipi (CheckMate 067) were evaluated for association of TMB and an inflammatory gene signature with clinical outcomes in melanoma patients. In CheckMate 066, TMB was evaluable in 122 of 411 patients. progression-free survival (PFS) and overall survival (OS) were significantly longer in patients treated with nivo, but not with D, for TMB-high vs. TMB-low tumors, determined by whole-exome sequencing. PFS and OS benefited by treatment with nivo vs. D was greater in patients with TMB-high than TMB-low (nivo/PFS – high vs. low: HR 0.33 [95% CI: 0.16-0.69, p = 0.0031]; nivo/OS – high vs. low: HR 0.43 [95% CI: 0.2-0.91, p = 0.027]). In CheckMate 067, 583 of 937 patients were evaluable for TMB and 299 were evaluable using an inflammatory signature assessed by RNAseq. PFS and OS were longer in each treatment arm in patients with TMB-high vs. TMB-low. Across treatment arms, a numerical benefit was observed for PFS and OS in patients with high vs. low inflammatory signature. High TMB and high inflammatory signature were each associated with benefit to I-O for nivo + ipi combination and nivo monotherapy, relative to ipi alone. Thus, TMB-high and a high inflammatory signature scores were not correlated and independently associated with clinical outcomes. Higher inflammatory status increased clinical response and longer survival for nivo +ipi and nivo, suggesting further evaluation of these biomarkers to better characterize the response to I-O regimens in melanoma.
THE PERSONALIZED VACCINE NEO-PV-01 WITH NIVOLUMAB INDUCES NEOANTIGEN-SPECIFIC DE NOVO IMMUNE RESPONSES IN PATIENTS WITH ADVANCED METASTATIC MELANOMA (MS. IM02.03_942)
Lakshmi Srinivasan, PhD (Neon therapeutics, Cambridge, MA, USA) described the data from NT-001, a Phase 1b study of NEO-PV-01 in combination with nivolumab in either first or later line therapy for patients with metastatic melanoma (NCT02897765). NEO-PV-01 is a personal neoantigen vaccine designed based on a patient’s neoantigen and HLA profile, which is directed at tumor-specific T cell responses to neoantigens. Serial blood and tumor biopsies were scheduled for collection: i) prior to treatment, ii) after 12 weeks of nivolumab monotherapy, and iii) after completion of NEO-PV-01 vaccination. Predicted class I epitope quality by the proprietary RECON algorithm, was correlated with durable clinical benefit (DCB) which was defined as non-progression by 36 weeks from the initiation of anti-PD-1 therapy in 23 patients. In a cohort of 12 melanoma patients, 55% of 189 analyzed peptides generated any T cell immune response measured by IFNγ ELISpot. T cell responses were neoantigen-specific for most peptides tested (87%). Vaccine-induced immune responses were durable in 4 out of 7 patients at weeks 52 after initiation of anti-PD-1 therapy. Most T cell responses were polyfunctional, as evident by secretion of multiple cytokines, exhibited a memory and effector memory phenotype and were cytolytic. Epitope spread, which is a cascade of neoantigen recognition beyond those included in the vaccine, was observed in 8 out of 8 melanoma patients with DCB. Furthermore, majority of patients with DCB exhibited pathologic response only after vaccination, not while they received anti-PD1 therapy. Tumor microenvironment analysis showed higher expression of MHC class II, B cell gene signature, NK cell gene signature, and presence of TCF7+ CD8 T cells were associated with DCB. Additional factors analyzed for correlation with DCB will be presented on Apr 3, 2019 (Poster 5006).
Glossary
CI = confidence interval
DCB = durable clinical benefit
HR = hazard ratio
HSV = Herpes Simplex Virus
I-O = immuno-oncology
OS = overall survival
pCR = pathological complete response
PD-1 = programmed cell death protein-1
PD-L1 = Programmed death-ligand 1
PFS = progression-free survival
RFS = relapse-free survival
TAMs = tumor associated macrophages
TMB = tumor mutational burden
TN = triple negative
TNBC = triple negative breast cancer