Parikh, Kaushal

Abstract Purpose Preclinical and clinical data have shown promise in using antiangiogenic agents to treat malignant pleural mesothelioma (MPM). We conducted this phase II study to evaluate the efficacy and toxicity of single-agent pazopanib in patients with MPM. Materials and Methods Patients with MPM who had received 0–1 prior chemotherapy regimens were eligible to receive pazopanib at a dose of 800 mg daily. The primary endpoint was progression-free survival rate at 6 months (PFS6), with a preplanned interim analysis for futility. Secondary endpoints included overall survival (OS), PFS, adverse events assessment and clinical benefit (complete response, partial response [PR], and stable disease [SD]). Results Thirty-four evaluable patients were enrolled, with a median age of 73 years (49–84). The trial was closed early because of lack of efficacy at the preplanned interim analysis. Only 8 patients (28.6%; 95% confidence interval [CI], 13.2–48.7%) in the first 28 evaluable were progression-free at 6 months. PFS6 was 32.4% (95% CI, 17.4–50.5). There were 2 PR (5.9%) and 16 SD (47.1%). The overall median PFS and OS were 4.2 months (95% CI, 2.0–6.0) and 11.5 months (95% CI: 5.3–18.2), respectively. The median PFS and OS for the previously untreated patients was 5.4 months (95% CI, 2.7–8.5) and 16.6 months (95% CI, 6.6–30.6), respectively; and 2.0 months (95% CI, 1.3–4.2) and 5.0 months (95% CI: 3.0–11.9), respectively, for the previously treated patients. Grade 3 or higher adverse events were observed in 23 patients (67.6%). Conclusion Single-agent pazopanib was poorly tolerated in patients with MPM. The primary endpoint of PFS6 was not achieved in the current study. ClinicalTrials.gov identification number. NCT00459862. Implications for Practice Single-agent pazopanib did not meet its endpoint in this phase II trial in malignant mesothelioma. Pazopanib is well tolerated in mesothelioma patients with a manageable toxicity profile. There is a need to better identify signals of angiogenesis that can be targeted in mesothelioma. Encouraging findings in frontline treatment warrant further investigations in combination with chemotherapy or immunotherapy.

Abstract The goal of this study is to evaluate the potential use of gene expression profile of peripheral blood mononuclear cells (PBMCs) as a non-invasive biomarker for predicting the response of anti-PD-1 therapy in non-small cell lung cancer (NSCLC) subjects. Peripheral blood of NSCLC stage 4 subjects treated with an anti-PD-1 monoclonal antibody was collected prior to treatment (week 0) and subsequent infusions. Total RNA was extracted, and libraries were prepared using TruSeq Stranded mRNA LT Sample Prep Kit and sequenced by Illumina NextSeq. The paired-end reads were mapped to human reference hg38 using STAR and gene expressions were calculated using RSEM. Preliminary analysis of differential gene expression (DE) was performed among the responders at respectively (T1) weeks 3-4, (T2) weeks 6-9 and (T3) weeks 12-16 after treatment, compared with the baseline at T0. Further DE analysis was performed between the baseline samples of responders and non-responders. Genes with FDR-adjusted p values less than 0.05 were selected for pathway enrichment analysis with DAVID. Altogether 30 RNA-Seq samples of seven subjects were collected at multiple time points before and after treatment. According to standard RECIST 1.1 criteria, five subjects had a partial response to the therapy, whereas two subjects had stable disease or no response. In addition, liquid biopsy results were available for selected samples. Among the responders, there are 203 DE genes for T1 with log2 fold change (LFC) of gene expression from -2.4 to 3.5, 859 DE genes for T2 with LFC from -3.4 to 3.3, and 395 DE genes for T3 with LFC from -3 to 6.8. Among the DE genes for the three time points, 155 genes are common to T1/T2, 250 common to T2/T3, and 104 common to T1/T2/T3. Pathway enrichment test using Gene Ontology Biological Process terms shows that the strongest DE pathways for initial response after treatment at T1 are regulation of immune response (FDR adjusted p = 2.5E-5), oxygen transport (p = 5.5E-3) and T cell costimulation (p = 3.9E-3). Based on the 104 common DE genes, oxygen transport (p = 0.029) is the only pathway consistently perturbed due to an increase in hemoglobin. When comparing the baseline of responders and non-responders, we identified a candidate gene signature, with some of the genes also reported in other studies. However, more samples are required to establish its statistical significance. Systemic immune response after first dose of anti-PD1 treatment is reflected by DE genes in blood samples collected in weeks 3-4. Tumor regression might be indicated by the consistent increase in hemoglobin level. The results of these analyses show promise of developing a predictive signature for the response of anti-PD-1 immunotherapy in NSCLC subjects based on the gene expression profile of PBMCs. While these are preliminary results, we continue to recruit subjects, and will present the up-to-date results at the conference. Citation Format: Yee Him Cheung, Jie Wu, Weihua Huang, Changhong Yin, Katherine Linder, Kaushal Parikh, Ke Tang, Christopher Kasbek, Jun Huang, Zeil Rosenberg, Michael Fanucchi, John Fallon, Nevenka Dimitrova. Differential gene expression analysis reveals pathways involved in anti-pd-1 therapy response prediction [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 4994.

6581 Background: While AC is recommended for all patients with stage IIA, IIB, and IIIA NSCLC, its use and benefit among the elderly population is unclear. Methods: We identified patients with stage IIA, IIB, or IIIA NSCLC using the National Cancer Database from 2006-2014. Patients were divided into age groups ≤65, 66-70, 71-75, 76-80, > 80 years. Trends in AC use, factors influencing AC administration, and outcomes associated with AC were studied. Results: Out of 27368 patients, 13464 received AC and 13904 did not. 11% had stage IIA disease, 50% had stage IIB disease and 39% had stage IIIA disease. AC use was lower with increasing age (49% age ≤65 vs. 3% age > 80 (P < 0.0001)). Temporal use of chemotherapy for each age group was unchanged from 2006-2014. In multivariate logistic regression analysis, factors predictive of lower AC use were older age, Medicare or Medicaid insurance, academic center, and higher Charlson Comorbidity Index (CCI). Stage IIIA (OR 1.4, 95% CI 1.3-1.6) and Stage IIB (OR 1.3, 95% CI 1.2-1.4) had a higher chance of receiving AC than stage IIA. In a Cox proportional hazard model, younger age, female sex, academic center, private insurance, higher income, lower CCI, West coast center and AC were associated with better outcomes. When stratified by age and stage, AC was still associated with better survival (Table). Conclusions: AC utilization in stages IIA, IIB and IIIA NSCLC remains low, despite its association with improved survival in the elderly. Future clinical trials may be needed focused on elderly patients to establish the best regimen to optimize outcomes. [Table: see text]

2621 Background: TMB is an emerging predictor of survival with immunotherapy. TMB is determined by taking the difference between somatic and germline datasets when tumor-normal pairs are available. In the case of commonly utilized tumor-only sequencing, additional steps are needed to estimate the somatic alterations. Computational tools have been developed that determine germline contribution based on sample copy state, purity estimates and occurrence of the variant in population databases. Given the potential bias of population datasets, we hypothesized that tumor-only filtering approaches may overestimate the actual TMB. Methods: We assessed the TMB from 50 tumors in 10 diseases including all missense, indels, and frameshift variants with an allelic fraction (AF) ≥5% and Coverage ≥100X within the tumor. Tumor-only TMB was evaluated against the gold standard of matched germline subtracted TMB at three levels. Level 1 removed all the tumor-only variants with AF in the non-TCGA ExAC database ≥1%. Level 2 removed all variants observed in population databases simulating a naive approach of removing germline variation. Level 3 used an internal tumor-only pipeline for calculating TMB. Results: There were significantly higher estimates of TMB with Level 1, Level 2 and Level 3 tumor-only filtering approaches than that determined by germline subtraction, resulting in significant bias. Whereas there was no correlation between TMB estimates and tumor-germline TMB for Level 1 filtering, there were improvements in correlations for Level 2 and Level 3. Conclusions: The tumor-only approaches that filter variants in population databases overestimate TMB compared to that determined by germline subtraction. Despite improved correlations with more stringent filtering approaches, these falsely elevated estimates may result in the inappropriate categorization of tumor specimens and negatively impact clinical trial results and patient outcomes. [Table: see text]