Abstract LB197: An SU2C-Mark Foundation Lung collaborative update: integrative genomics identifies distinct transcriptional states associated with checkpoint blockade resistance

Abstract

The advent of PD-1/PD-L1 agents has transformed the therapeutic landscape of many advanced cancers, including non-small cell lung cancer (NSCLC). However, our understanding of the genomic biomarkers underlying effective treatment response remain limited. Here we provide updated results from our ongoing effort, the Stand Up To Cancer Lung (SU2C-Lung)/Mark Foundation EXTOLConsortium, a multi-institution collaboration to expand our understanding of the molecular determinants of immunotherapy response in NSCLC. Comprising a set of nearly 400 patients, this cohort enables evaluation of both genomic and transcriptomic factors associated with checkpoint blockade response. In addition to validating previously known associations including TMB and neoantigen burden, we examined transcriptional predictors associated with response. We generated a list of differentially expressed genes with respect to best overall response (BOR), and performed dimensionality reduction using semi-supervised Bayesian Non-Negative Factorization (ssBNMF). We identified 3 distinct clusters with strong sample membership. Characterization of these subtypes revealed varying levels of immune infiltrate, histologic composition, and response rates to checkpoint blockade. Of these three subtypes, two were associated with low response rates to PD-1/PD-L1 blockade, suggesting the existence of distinct avenues toward resistance. To further characterize these transcriptional subtypes, we used ssBNMF marker genes to classify publicly available NSCLC samples from The Cancer Genome Atlas (TCGA), along with gene expression from a smaller cohort of large-cell neuroendocrine (LCNE) samples. Histologic composition showed good concordance with our SU2C samples, and redemonstrated observations within our smaller SU2C cohort of distinct immuno-suppressive and immuno-depleted milieus associated with resistance. Citation Format: Monica B. Arniella, Arvind Ravi, Justin Gainor, Chip Stewart, Sam Freeman, Mark Awad, Patrick Forde, Valsamo Anagnostou, Brian Henick, Jonathan W. Riess, Don Gibbons, Nathan Pennell, Vamsidhar Velcheti, Ignaty Leshchiner, Jaegil Kim, Subba Digumarthy, Mari Mino-Kenudson, John Heymach, Nir Hacohen, Naiyer Rizvi, Roy Herbst, Victor E. Velculescu, Julie Brahmer, Kurt Schalper, Pasi Janne, Jedd Wolchok, Alice Shaw, Gad Getz, Matthew D. Hellman. An SU2C-Mark Foundation Lung collaborative update: integrative genomics identifies distinct transcriptional states associated with checkpoint blockade resistance [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 LB197.