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Background: Phase Ib, single-arm trials are common in oncology development. Since these trials are not powered for statistical significance, Go/No-Go decisions are largely driven by observed trends in ORR relative to historic control. Here we develop a bootstrapping method to systematically compare secondary endponts, such as the waterfall plot, to historic control data. In addition, we identify an actionable Go threshold and estimate the expected false positive and false negative rates associated with that threshold. Method: A proprietary mathematical model was used to simulate thousands of single-arm trials (n = 30) with a combination of pembrolizumab and a novel agent with miserable (Rx0), modest (Rx1), moderate (Rx2) or magnificent (Rx3) efficacy. A bootstrapping method was used to compare waterfall plots from these trials to a simulated Phase III pembrolizumab monotherapy control arm (n = 511). Results: The bootstrapping method provides a visualization of the observed waterfall plot for the single-arm combination trial relative to the range of possible outcomes from historic control data (5th, median, 95th percentile). The method also provides a score reflecting the probability that the observed data is different from the historic control. An ROC analysis showed a strong ability to separate drugs with modest (AUROC = 83%), moderate (AUROC = 96%) and magnificent combination efficacy (AUROC = 99%) from drugs with miserable efficacy. The method was shown to effectively move drugs with a range of efficacy through an in-silico pipeline while rejecting drugs without combination efficacy. Conclusion: This bootstrapping method allows comparisons of secondary endpoints from early clinical trials to historic control data. The visualization is intuitive, and the quantification provides an actionable Go-threshold. The method also provides an estimate of the risk associated with that recommendation. We suggest incorporation of this as a component of Go/No-Go decision making in early oncology trials. Citation Format: Aparna Mohan, Raunak Dutta, Jacqueline Buros-Novik, Omobolaji Akala, Brian Gregory Topp. A bootstrapping method to optimize go/no-go decisions from single-arm, signal-finding studies in oncology. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4375.

Non-alcoholic steatohepatitis (NASH) is a rising health challenge, with no approved drugs. We used a computational drug repositioning strategy to uncover a novel therapy for NASH, identifying a GABA-B receptor agonist, AZD3355 (Lesogaberan) previously evaluated as a therapy for esophageal reflux. AZD3355’s potential efficacy in NASH was tested in human stellate cells, human precision cut liver slices (hPCLS), and in vivo in a well-validated murine model of NASH. In human stellate cells AZD3355 significantly downregulated profibrotic gene and protein expression. Transcriptomic analysis of these responses identified key regulatory nodes impacted by AZD3355, including Myc, as well as MAP and ERK kinases. In PCLS, AZD3355 down-regulated collagen1α1, αSMA and TNF-α mRNAs as well as secreted collagen1α1. In vivo, the drug significantly improved histology, profibrogenic gene expression, and tumor development, which was comparable to activity of obeticholic acid in a robust mouse model of NASH, but awaits further testing to determine its relative efficacy in patients. These data identify a well-tolerated clinical stage asset as a novel candidate therapy for human NASH through its hepatoprotective, anti-inflammatory and antifibrotic mechanisms of action. The approach validates computational methods to identify novel therapies in NASH in uncovering new pathways of disease development that can be rapidly translated into clinical trials.

Objectives: Dynamics of tumor size have long been used for the clinical diagnosis, staging, prognosis and treatment of non-small cell lung cancer (NSCLC). The aim of this work was to develop a joint statistical framework to interrogate the longitudinal tumor burden, the appearance of new lesions, and changes in therapy following progression in a population of NSCLC patients treated with an EGFR inhibitor gefinitib to predict, given early results, time to progression (PFS) and overall survival at both population and individual levels. Methods: The model builds on a previously developed joint model for tumor size and survival. The tumor size model was extended to estimate the probability of a new lesion. For the survival submodel, two additional biomarkers were evaluated: the derivative of the sum of longest diameters (SLD) and the probability of new lesions. The model was fitted in a Bayesian framework using STAN. Model was developed from 434 EGFR+, NSCLC patients treated with gefitinib or carboplatin+paclitaxel (‘IPASS’, NCT00322452). Predictive performance was evaluated on a cohort of 102 EGFR+ NSCLC patients (‘IFUM’, NCT01203917). Results: Overall, the model fit well to the observed data and the predictive performance was strong in both within- and out-of-sample evaluations. Surprisingly, SLD derivative and new-lesion association parameters appear to negatively impact model performance, indicating further improvement of these submodels might be necessary. The model recapitulates response evaluation criteria in solid tumors (RECIST) outcomes with nearly 90% accuracy. When comparing progression-specific hazards, it appears the drug effect is mediated by tumor size dynamics rather than new lesion incidence. Conclusion: This Bayesian joint model of tumor size and survival accurately recapitulates the RECIST-based outcomes and generates well calibrated predictions of survival. It offers insights regarding the relative predictive value of the components of RESICT in NSCLC. Citation Format: James Dunyak, Jacqueline Buros-Novik, Eric Novik, Hong Yan, Nidal Al-Huniti. Prediction of survival based on tumor size dynamics and new lesions in EGFR mutation-positive non-small cell lung cancer patients treated with gefitinib or carboplatin and paclitaxel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1674.

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: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.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 (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.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 1 (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 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 pretreatment tumor samples as well as TCR-seq 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. Patients with DCB displayed a higher proportion of tumor-infiltrating T lymphocytes (TIL) (n = 24, Mann-Whitney p = 0.047). Pretreatment 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 pretreatment peripheral blood TCR clonality with elevated PD-L1 IC staining in tumor tissue was strongly associated with poor clinical outcomes (n = 10, hazard ratio (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 PFS 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. 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., Alexandra Snyder and colleagues reveal the complex nature of the immune response to checkpoint blockade in metastatic urothelial cancer patients. Time-varying effects of somatic mutation load on survival are reported., Author summary Why was this study done? A new type of cancer treatment called checkpoint blockade therapy activates the immune system to fight cancer. When these therapies work, patients with advanced disease can experience long-lasting disease control or even cures. However, most patients will not experience these benefits, and it is crucial to identify these patients in advance so that we can develop better treatments for them. What did the researchers do and find? In this study, we studied 29 patients with advanced bladder cancers treated with a checkpoint blockade drug called atezolizumab. We examined features of the tumor and the immune system, as well as clinical features. We found that these features were related to each other, and to the success of therapy, in various ways. Patients who had a diverse repertoire of T cells in their blood tended to survive longer. Patients who had poor clinical prognostic factors, like having cancer that had traveled to their liver, tended to have worse survival. What did the research findings mean? This study demonstrates that we need to take the tumor, immune system, and clinical picture into account if we are to improve the efficacy of immune-mobilizing therapies in cancer. Some patients may be too sick to benefit from checkpoint blockade therapy, despite, in some cases, having biomarkers in their tumors that would predict benefit.

4518Background: Mutation load and neoantigen burden predict benefit from anti-PD1 therapy across several cancers but are generally low in RCC. Pan-cancer comparisons highlight RCC for its enriched ...

Combination immune checkpoint blockade has demonstrated promising benefit in lung cancer, but predictors of response to combination therapy are unknown. Using whole-exome sequencing to examine non-small-cell lung cancer (NSCLC) treated with PD-1 plus CTLA-4 blockade, we found that high tumor mutation burden (TMB) predicted improved objective response, durable benefit, and progression-free survival. TMB was independent of PD-L1 expression and the strongest feature associated with efficacy in multivariable analysis. The low response rate in TMB low NSCLCs demonstrates that combination immunotherapy does not overcome the negative predictive impact of low TMB. This study demonstrates the association between TMB and benefit to combination immunotherapy in NSCLC. TMB should be incorporated in future trials examining PD-(L)1 with CTLA-4 blockade in NSCLC.