Abstract A007: Proteogenomic landscape of KRASG12C lung adenocarcinomas reveals new subtypes and potential combination therapies

Abstract Despite the presence of the KRASG12C oncogene, not all patients respond to KRASG12C inhibitors (e.g., sotorasib, adagrasib) and duration of response has been variable. We hypothesized that subtypes of KRASG12C lung cancers could be responsible for such differential effects. To define subtypes, we performed targeted exon sequencing, transcriptomics, proteomics, and phosphoproteomics on 46 frozen surgically resected KRASG12C lung adenocarcinomas. We employed unbiased consensus clustering methods, pathway analysis, and PTM-SEA to identify kinase signatures from phosphoproteomics data. Transcriptomics data revealed 4 clusters. Pathway enrichment showed that gene cluster (GC) 1 was enriched for immune pathways including interferon gamma response. Epithelial-mesenchymal transition (EMT), assessed by a TGF-β gene signature, was also enriched in GC1. 100% of GC1 overlapped the Proximal-Inflammatory subtype (Wilkerson et al.) and 53% with the mesenchymal subtype (Daemen et al.). GC2 was enriched for inflammatory response and TNF-alpha signaling. GC3 represented a metabolic phenotype with enriched xenobiotic metabolism and other metabolism pathways. 83% of GC3 overlapped with the Terminal Respiratory Unit subtype (Wilkerson et al.) and 56% with the proliferative subtype (Daemen et al.). GC4 only had 5 samples and did not have any significant enrichment. We next identified four proteomic clusters with distinct biology. Protein Cluster 1 (PC1) was enriched for immune pathways, PC2 was enriched for EMT, and PC3 was enriched for TNF/NF-κβ signaling. PC4 was enriched for xenobiotic and fatty acid metabolism and had significantly more KEAP1 mutations. We observed concordance of protein based clusters with mRNA based clusters, as PC1 largely overlapped with GC1 (70%) and PC4 largely overlapped with GC3 (86%). Cell type inference using xCell largely recapitulated the immune subtypes identified by transcriptomics and proteomics. GC1/PC1 had significantly more CD8+ effector memory T-cells, CD4+ Th2 T-cells, and M1 macrophages, while GC3/PC4 had significantly less of these same cell types. Collectively, GC1/PC1 represents 43% of the cohort and was defined by enrichment of immune pathways, elevated immune populations, and significantly higher PD-L1. Finally, we leveraged the phosphoproteomics data to determine whether signaling activity differs across subtypes. Using PTM-SEA, we identified phosphoproteomic signatures of activity for 50 kinases and pathways. We identified 26% of samples (N=12) with high EGFR activity, which is known to affect sensitivity of cells to KRASG12C inhibitors. The EGFR-high samples were observed across all genomic, transcriptomic, and proteomic subtypes. Our results suggest concordance of some transcriptomic and proteomic subtypes, including an immune subtype, while a metabolic protein subtype and EGFR high signaling subtype may provide additional subclasses with potential relevance for treatment responses. Additional phosphoproteomics signatures such as PLK1 and AKT1 may identify subtypes amenable to combination therapy approaches. Citation Format: Paul A. Stewart, Hitendra Solanki, Eric Welsh, Yaakov Stern, Denis Imbody, Yonghong Zhang, Bruna Pellini, Bin Fang, Sean Yoder, Steven Eschrich, Jamie Teer, John Koomen, Eric B. Haura. Proteogenomic landscape of KRASG12C lung adenocarcinomas reveals new subtypes and potential combination therapies [abstract]. In: Proceedings of the AACR Special Conference: Targeting RAS; 2023 Mar 5-8; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Res 2023;21(5_Suppl):Abstract nr A007.