Abstract PO014: Early lung adenocarcinoma subtyping based on MHC-I and II immunogenic response

Abstract

Abstract Lung adenocarcinoma (ADC) is a heterogeneous group of tumors associated with dramatically different survival rates, even when detected at an early stage. Here, we hypothesized that early ADCs can be further classified based on their immune profiles allowing for the characterization of cellular determinants of early lung ADC behavior. We used a mass cytometry panel of 34 antibodies, including protein markers for cell lineage, canonical cancer pathways and quality control, to stain a set of 71 early stage ADC patient samples. We identified cellular subpopulations of epithelial cancer cells (ECC) and the tumor microenvironment (TME) by clustering and analyzed differences in their distribution. Matching RNA sequencing was obtained for 61 patients. Computed tomography–based Score Indicative of Lung Cancer Aggression (SILA), a score ranging from 0 to 1 that predicts the degree of histologic tissue invasion and patient survival in ADC, was obtained for all patients. Our antibody panel captured major cell types such as endothelial, mesenchymal, myeloid, CD8+ and CD4+ T cells, as well as ECC. The later was further dissected resulting in 3 main ECC clusters (ECCc): 1. High MHC-I and MHC-II expression and moderate EGFR and MET; 2. Proliferative (Ki67+), moderate Vimentin expression and no MHC-I or II expression; 3. Mildly proliferative and no MHC-I or II expression. The ADC samples were clustered based on their cell type composition and we found 3 groups of patients: G1. ECCc1 and myeloid cells enriched, T cells, ECCc 2 and 3 depleted; G2. ECCc1, T and myeloid cells enriched, ECCc2 and 3 depleted; G3. ECCc2 and 3 enriched, T and myeloid cells depleted. G1 was the only group in which there was no non-smoker patients. Although no significant difference was found on the SILA scores between the 3 groups of patients, median MHC-II expression in ECC was negatively correlated with SILA score (r=-0.32, p=0.012). We further characterized the profiles of these groups of patients by differential gene expression and pathway analysis on the matching transcriptomic dataset. G1 was enriched in P53 pathway genes, downregulated KRAS signaling, and fatty acid metabolism. G2 was enriched in INF gamma response, TNF alpha signaling via NFKB, MTORC1 signaling, epithelial mesenchymal transition and inflammatory response genes. G3 was enriched in fatty acid metabolism, oxidative phosphorylation, reactive oxygen species and peroxisome genes. Our results demonstrate different biologic profiles among early ADCs reflected at the proteomic and transcriptomic levels. By virtue of proteomic single cell analysis, we were able to dissect the TME and the ECC compartment and identify subpopulations which presence and relative abundance might be key in the characterization and prediction of early ADC behavior. Our results also suggest that high MHC-II expression in tumor cells and its role in the TME is associated with better prognosis. This work deserves further validation at the cellular and molecular level to gain further insights into tumor behavior. Citation Format: Maria-Fernanda Senosain, Yong Zou, Khushbu Patel, Jonathan M. Irish, Vera Pancaldi, Pierre P. Massion. Early lung adenocarcinoma subtyping based on MHC-I and II immunogenic response [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO014.