Abstract 2138: Whole genome cfDNA profiles reveal common signatures of Immune checkpoint inhibition response in kidney, melanoma, and lung cancers

Abstract

Immune checkpoint inhibition (ICI) via anti-PD-1/PD-L1 and anti-CTLA4, has improved clinical outcomes for multiple cancers, including non-small cell lung cancer (NSCLC), kidney cancer, and melanoma. Despite this success, response rates remain low, highlighting the need for more robust predictive biomarkers. In this study, we used cell-free DNA (cfDNA) profiles from patients undergoing ICI therapy to identify common signatures associated with responses shared among the three cancers. Whole-genome sequencing (mean coverage=18X) of cfDNA was performed on pre-treatment plasma samples from 126 patients across three cancers (NSCLC, n=91; kidney, n=21; melanoma, n=14). Transcriptional activation for protein-coding genes was then inferred by modeling fragment distribution around each transcription start site (TSS-GAP). Transcription factor binding activity (TFBA) was estimated by measuring binding site accessibility across the genome. To delineate potential signatures of response, we performed a gene set enrichment analysis (GSEA) based on weighted average effect sizes of TSS-GAP levels between response groups across the three cancer types. GSEA results showed an enrichment of DNA repair and cell cycle genes in non-responders and of EMT processing genes in responders. To identify shared signatures of ICI response, we performed a meta-analysis by (1) computing the effect size between response groups for TFBA and TSS-GAP features in each cancer type; (2) calculating a weighted-average effect size across cancer types; (3) performing gene selection based on the degree of heterogeneity among cancer types, followed by false discovery rate correction and assessment of significance through Monte Carlo permutation testing. This analysis identified 13 transcription factors and 269 genes consistently enriched in response groups across these cancer types. Notably, this analysis revealed significantly higher accessibility in STAT5A (p=0.02), JUN (p=0.02) and JUNB (p=0.03) in non-responders, suggesting JAK/STAT-pathway dependency as a common feature in ICI resistance. Using our platform that detects both tumor and non-tumor-derived signals, we identified common signatures of ICI response, revealing a potential pathway of resistance through JAK/STAT signaling and a possible EMT signature of response in kidney, melanoma, and NSCLC. These findings warrant further investigation into using cfDNA signatures for patient stratification and response monitoring. Citation Format: Hayley Donnella, Yue Zhang, Irving Wang, Francesco Vallania, Maggie Louie, C. Jimmy Lin. Whole genome cfDNA profiles reveal common signatures of Immune checkpoint inhibition response in kidney, melanoma, and lung cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2138.