Samuel Funt

The Role of Neoadjuvant Trials in Drug Development for Solid Tumors.

The relatively low success rate of phase II oncology trials in predicting success of novel drugs in phase III trials and in gaining regulatory approval may be due to reliance on the endpoint of response rate defined by the RECIST. The neoadjuvant treatment paradigm allows the antitumor activity of a novel therapy to be determined on a pathologic basis at the time of surgery instead of by RECIST, which was not developed to guide clinical decision making or correlate with long-term outcomes. Indeed, the FDA endorsed pathologic complete response (pCR) as a surrogate for overall survival (OS) in early-stage breast cancer and granted accelerated approval to pertuzumab based on this endpoint. We propose that pCR is a biologically rational method of determining treatment effect that may be more likely to predict OS. We discuss some advantages of the neoadjuvant trial design, review the use of neoadjuvant therapy as standards of care, and consider the neoadjuvant platform as a method for drug development. Clin Cancer Res; 22(10); 2323–8. ©2016 AACR.

Efficacy and toxicity of therapy immediately after treatment with nivolumab in relapsed multiple myeloma

As part of the drug development process, combinations utilizing approved or experimental agents are routinely explored. However, developing a rational framework for prioritizing the investigation o...

Genomic Differences Between “Primary” and “Secondary” Muscle-invasive Bladder Cancer as a Basis for Disparate Outcomes to Cisplatin-based Neoadjuvant Chemotherapy

BACKGROUNDnCisplatin-based neoadjuvant chemotherapy (NAC) followed by radical cystectomy (RC) is the standard of care for patients with muscle-invasive bladder cancer (MIBC). It is unknown whether this treatment strategy is appropriate for patients who progress to MIBC after treatment for prior noninvasive disease (secondary MIBC).nnnOBJECTIVEnTo determine whether clinical and genomic differences exist between primary and secondary MIBC treated with NAC and RC.nnnDESIGN, SETTING, AND PARTICIPANTSnClinicopathologic outcomes were compared between 245 patients with clinical T2-4aN0M0-stage primary MIBC and 43 with secondary MIBC treated with NAC and RC at Memorial Sloan Kettering Cancer Center (MSKCC) from 2001 to 2015. Genomic differences were assessed in a retrospective cohort of 385 prechemotherapy specimens sequenced by whole-exome or targeted exon capture by the Cancer Genome Atlas or at MSKCC. Findings were confirmed in an independent validation cohort of 94 MIBC patients undergoing prospective targeted exon sequencing at MSKCC.nnnOUTCOME MEASUREMENTS AND STATISTICAL ANALYSISnPathologic response rates, recurrence-free survival (RFS), bladder cancer-specific survival (CSS), and overall survival (OS) were measured. Differences in somatic genomic alteration rates were compared using Fishers exact test and the Benjamini-Hochberg false discovery rate method.nnnRESULTS AND LIMITATIONSnPatients with secondary MIBC had lower pathologic response rates following NAC than those with primary MIBC (univariable: 26% vs 45%, multivariable: odds ratio=0.4 [95% confidence interval=0.18-0.84] p=0.02) and significantly worse RFS, CSS, and OS. Patients with secondary MIBC treated with NAC had worse CSS compared with cystectomy alone (p=0.002). In a separate genomic analysis, we detected significantly more likely deleterious somatic ERCC2 missense mutations in primary MIBC tumors in both the discovery (10.9% [36/330] vs 1.8% [1/55], p=0.04) and the validation (15.7% [12/70] vs 0% [0/24], p=0.03) cohort.nnnCONCLUSIONSnPatients with secondary MIBC treated with NAC had worse clinical outcomes than similarly treated patients with primary MIBC. ERCC2 mutations predicted to result in increased cisplatin sensitivity were enriched in primary versus secondary MIBC. Prospective validation is still needed, but given the lack of clinical benefit with cisplatin-based NAC in patients with secondary MIBC, upfront RC or enrollment in clinical trials should be considered.nnnPATIENT SUMMARYnA retrospective cohort study of patients with primary and secondary muscle-invasive bladder cancer (MIBC) treated with chemotherapy before surgical removal of the bladder identified lower response rates and shorter survival in patients with secondary MIBC. Tumor genetic sequencing of separate discovery and validation cohorts revealed that chemotherapy-sensitizing DNA damage repair gene mutations occur predominantly in primary MIBC tumors and may underlie the greater sensitivity of primary MIBC to chemotherapy. Prospective validation is still needed, but patients with secondary MIBC may derive greater benefit from upfront surgery or enrollment in clinical trials rather than from standard chemotherapy.

Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

Background: Inhibition of programmed death-ligand one (PD-L1) with atezolizumab can induce durable clinical benefit (DCB) in patients with metastatic urothelial cancers, including complete remissions in patients with chemotherapy refractory disease. Although mutation load and PD-L1 immune cell (IC) staining have been associated with response, they lack sufficient sensitivity and specificity for clinical use. Thus, there is a need to evaluate the peripheral blood immune environment and to conduct detailed analyses of mutation load, predicted neoantigens and immune cellular infiltration in tumors to enhance our understanding of the biologic underpinnings of response and resistance. Methods and Findings: We performed whole exome sequencing (WES), RNA sequencing (RNA-seq), and T cell receptor sequencing (TCR-seq) of pre-treatment tumor samples as well as TCR sequencing of matched, serially collected peripheral blood pre- and post-treatment with atezolizumab. These parameters were assessed for correlation with DCB (defined as progression free survival (PFS) > 6 months) and overall survival (OS), both alone and in the context of clinical and intratumoral parameters known to be predictive of survival in this disease state. Patients with DCB displayed a higher proportion of tumor infiltrating T lymphocytes (TIL) (n=24, Mann-Whitney p=0.047). Pre-treatment peripheral blood TCR clonality below the median was associated with improved PFS (n=29, log-rank p=0.048) and OS (n=29, log-rank p=0.011). Patients with DCB also demonstrated more substantial expansion of tumor-associated TCR clones in the peripheral blood 3 weeks after starting treatment (n=22, Mann-Whitney p=0.022). The combination of high pre-treatment peripheral blood TCR clonality with elevated PD-L1 IC staining in tumor tissue was strongly associated with poor clinical outcomes (n=10, HR=86.22, 95% CI (2.55, 491.65)). Marked variations in mutation loads were seen with different somatic variant calling methodologies, which in turn impacted associations with clinical outcomes. Missense mutation load, predicted neoantigen load and expressed neoantigen load did not demonstrate significant association with DCB (n=25, Mann-Whitney p=0.22, n=25, Mann-Whitney p=0.55, and n=25, Mann-Whitney p=0.29 respectively). Instead, we found evidence of time-varying effects of somatic mutation load on progression-free survival in this cohort (n=25, p=0.044). Conclusions: These results demonstrate the complex nature of immune response to checkpoint blockade and the compelling need for greater interrogation and data integration of both host and tumor factors. Incorporating these variables in prospective studies will facilitate identification and treatment of resistant patients.Background: Inhibition of programmed death-ligand one (PD-L1) with atezolizumab can induce durable clinical benefit (DCB) in patients with metastatic urothelial cancers, including complete remissions in patients with chemotherapy refractory disease. Although mutation load and PD-L1 immune cell (IC) staining have been associated with response, they lack sufficient sensitivity and specificity for clinical use. Thus, there is a need to evaluate the peripheral blood immune environment and to conduct detailed analyses of mutation load, predicted neoantigens and immune cellular infiltration in tumors to enhance our understanding of the biologic underpinnings of response and resistance.nnMethods and Findings: The goals of this study were to (1) evaluate the association of mutation load and predicted neoantigen load with therapeutic benefit, and (2) determine whether intratumoral and peripheral blood T cell receptor (TCR) clonality inform clinical outcomes in urothelial carcinoma treated with atezolizumab. We hypothesized that an elevated mutation load in combination with T cell clonal dominance among intratumoral lymphocytes prior to treatment or among peripheral T cells after treatment would be associated with effective tumor control upon treatment with anti-PD-L1 therapy. We performed whole exome sequencing (WES), RNA sequencing (RNA-seq), and T cell receptor sequencing (TCR-seq) of pre-treatment tumor samples as well as TCR sequencing of matched, serially collected peripheral blood collected before and after treatment with atezolizumab. These parameters were assessed for correlation with DCB (defined as progression free survival (PFS) > 6 months), PFS, and overall survival (OS), both alone and in the context of clinical and intratumoral parameters known to be predictive of survival in this disease state.nnPatients with DCB displayed a higher proportion of tumor infiltrating T lymphocytes (TIL) (n=24, Mann-Whitney p=0.047). Pre-treatment peripheral blood TCR clonality below the median was associated with improved PFS (n=29, log-rank p=0.048) and OS (n=29, log-rank p=0.011). Patients with DCB also demonstrated more substantial expansion of tumor-associated TCR clones in the peripheral blood 3 weeks after starting treatment (n=22, Mann-Whitney p=0.022). The combination of high pre-treatment peripheral blood TCR clonality with elevated PD-L1 IC staining in tumor tissue was strongly associated with poor clinical outcomes (n=10, HR (mean)=89.88, HR (median)=23.41, 95% CI (2.43, 506.94), p(HR>1)=0.0014). Marked variations in mutation loads were seen with different somatic variant calling methodologies, which in turn impacted associations with clinical outcomes. Missense mutation load, predicted neoantigen load and expressed neoantigen load did not demonstrate significant association with DCB (n=25, Mann-Whitney p=0.22, n=25, Mann-Whitney p=0.55, and n=25, Mann-Whitney p=0.29 respectively). Instead, we found evidence of time-varying effects of somatic mutation load on progression-free survival in this cohort (n=25, p=0.044). A limitation of our study is its small sample size (n=29), a subset of the patients treated on IMvigor 210 (NCT02108652). Given the number of exploratory analyses performed, we intend for these results to be hypothesis-generating.nnConclusions: These results demonstrate the complex nature of immune response to checkpoint blockade and the compelling need for greater interrogation and data integration of both host and tumor factors. Incorporating these variables in prospective studies will facilitate identification and treatment of resistant patients.

A Multifactorial Model of T Cell Expansion and Durable Clinical Benefit in Response to a PD-L1 Inhibitor

Checkpoint inhibitor immunotherapies have had major success in treating patients with late-stage cancers, yet the minority of patients benefit [1]. Mutation load and PD-L1 staining are leading biomarkers associated with response, but each is an imperfect predictor. A key challenge to predicting response is modeling the interaction between the tumor and immune system. We begin to address this challenge with a multifactorial model for response to anti-PD-L1 therapy. We train a model to predict immune response in patients after treatment based on 36 clinical, tumor, and circulating features collected prior to treatment. We analyze data from 21 bladder cancer patients [2] using the elastic net high-dimensional regression procedure [3] and, as training set error is a biased and overly optimistic measure of prediction error, we use leave-one-out cross-validation to obtain unbiased estimates of accuracy on held-out patients. In held-out patients, the model explains 79% of the variance in T cell clonal expansion. This predicted immune response is multifactorial, as the variance explained is at most 23% if clinical, tumor, or circulating features are excluded. Moreover, if patients are triaged according to predicted expansion, only 38% of non-durable clinical benefit (DCB) patients need be treated to ensure that 100% of DCB patients are treated. In contrast, using mutation load or PD-L1 staining alone, one must treat at least 77% of non-DCB patients to ensure that all DCB patients receive treatment. Thus, integrative models of immune response may improve our ability to anticipate clinical benefit of immunotherapy.