Fanucchi, Michael

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.

Purpose Gemcitabine as a single agent and the combination of gemcitabine and docetaxel have activity in patients with metastatic soft tissue sarcoma. To determine if the addition of docetaxel to gemcitabine improved clinical outcome of patients with metastatic soft tissue sarcomas, we compared a fixed dose rate infusion of gemcitabine versus a lower dose of gemcitabine with docetaxel. Patients and Methods In this open-label phase II clinical trial, the primary end point was tumor response, defined as complete or partial response or stable disease lasting at least 24 weeks. A Bayesian adaptive randomization procedure was used to produce an imbalance in the randomization in favor of the superior treatment, accounting for treatment-subgroup interactions. Results One hundred nineteen of 122 randomly assigned patients had assessable outcomes. The adaptive randomization assigned 73 patients (60%) to gemcitabine-docetaxel and 49 patients (40%) to gemcitabine alone, indicating gemcitabine-docetaxel was superior. The objective Response Evaluation Criteria in Solid Tumors response rates were 16% (gemcitabine-docetaxel) and 8% (gemcitabine). Given the data, the posterior probabilities that gemcitabine-docetaxel was superior for progression-free and overall survival were 0.98 and 0.97, respectively. Median progression-free survival was 6.2 months for gemcitabine-docetaxel and 3.0 months for gemcitabine alone; median overall survival was 17.9 months for gemcitabine-docetaxel and 11.5 months for gemcitabine. The posterior probability that patients receiving gemcitabine-docetaxel had a shorter time to discontinuation for toxicity compared with gemcitabine alone was .999. Conclusion Gemcitabine-docetaxel yielded superior progression-free and overall survival to gemcitabine alone, but with increased toxicity. Adaptive randomization is an effective method to reduce the number of patients receiving inferior therapy.