|Publication Type||Journal Article|
|Year of Publication||2020|
|Authors||Gillette, MA, Satpathy, S, Cao, S, Dhanasekaran, SM, Vasaikar, SV, Krug, K, Petralia, F, Li, Y, Liang, W-W, Reva, B, Krek, A, Ji, J, Song, X, Liu, W, Hong, R, Yao, L, Blumenberg, L, Savage, SR, Wendl, MC, Wen, B, Li, K, Tang, LC, MacMullan, MA, Avanessian, SC, M Kane, H, Newton, CJ, Cornwell, MI, Kothadia, RB, Ma, W, Yoo, S, Mannan, R, Vats, P, Kumar-Sinha, C, Kawaler, EA, Omelchenko, T, Colaprico, A, Geffen, Y, Maruvka, YE, Leprevost, Fda Veiga, Wiznerowicz, M, Gümüş, ZH, Veluswamy, RR, Hostetter, G, Heiman, DI, Wyczalkowski, MA, Hiltke, T, Mesri, M, Kinsinger, CR, Boja, ES, Omenn, GS, Chinnaiyan, AM, Rodriguez, H, Li, QKay, Jewell, SD, Thiagarajan, M, Getz, G, Zhang, B, Fenyö, D, Ruggles, KV, Cieslik, MP, Robles, AI, Clauser, KR, Govindan, R, Wang, P, Nesvizhskii, AI, Ding, L, Mani, DR, Carr, SA|
|Corporate Authors||Clinical Proteomic Tumor Analysis Consortium|
|Date Published||2020 Jul 09|
To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.