| Literature DB >> 32649874 |
Michael A Gillette1, Shankha Satpathy2, Song Cao3, Saravana M Dhanasekaran4, Suhas V Vasaikar5, Karsten Krug6, Francesca Petralia7, Yize Li3, Wen-Wei Liang3, Boris Reva7, Azra Krek7, Jiayi Ji8, Xiaoyu Song8, Wenke Liu9, Runyu Hong9, Lijun Yao3, Lili Blumenberg10, Sara R Savage11, Michael C Wendl3, Bo Wen11, Kai Li11, Lauren C Tang12, Melanie A MacMullan13, Shayan C Avanessian6, M Harry Kane6, Chelsea J Newton14, MacIntosh Cornwell10, Ramani B Kothadia6, Weiping Ma7, Seungyeul Yoo7, Rahul Mannan4, Pankaj Vats4, Chandan Kumar-Sinha4, Emily A Kawaler9, Tatiana Omelchenko15, Antonio Colaprico16, Yifat Geffen6, Yosef E Maruvka6, Felipe da Veiga Leprevost4, Maciej Wiznerowicz17, Zeynep H Gümüş7, Rajwanth R Veluswamy18, Galen Hostetter14, David I Heiman6, Matthew A Wyczalkowski3, Tara Hiltke19, Mehdi Mesri19, Christopher R Kinsinger19, Emily S Boja19, Gilbert S Omenn20, Arul M Chinnaiyan4, Henry Rodriguez19, Qing Kay Li21, Scott D Jewell14, Mathangi Thiagarajan22, Gad Getz6, Bing Zhang11, David Fenyö9, Kelly V Ruggles10, Marcin P Cieslik4, Ana I Robles19, Karl R Clauser6, Ramaswamy Govindan23, Pei Wang7, Alexey I Nesvizhskii24, Li Ding3, D R Mani6, Steven A Carr25.
Abstract
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.Entities:
Keywords: CPTAC; acetylation; adenocarcinoma; genomics; lung cancer; mass spectrometry; phosphorylation; protein; proteogenomics; proteomics
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Year: 2020 PMID： 32649874 PMCID： PMC7373300 DOI： 10.1016/j.cell.2020.06.013
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 41.582