Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms.
Proteogenomics of non-small cell lung cancer reveals molecular subtypes associated with specific therapeutic targets and immune evasion mechanisms.
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非小细胞肺癌的蛋白质基因组学研究揭示了与特定治疗靶点及免疫逃逸机制相关的分子亚型。
DOI:
10.1038/s43018-021-00259-9
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发表时间:
2021-11
期刊:
影响因子:
22.7
通讯作者:
Orre LM
中科院分区:
文献类型:
--
作者:
Lehtiö J;Arslan T;Siavelis I;Pan Y;Socciarelli F;Berkovska O;Umer HM;Mermelekas G;Pirmoradian M;Jönsson M;Brunnström H;Brustugun OT;Purohit KP;Cunningham R;Foroughi Asl H;Isaksson S;Arbajian E;Aine M;Karlsson A;Kotevska M;Gram Hansen C;Drageset Haakensen V;Helland Å;Tamborero D;Johansson HJ;Branca RM;Planck M;Staaf J;Orre LM
Despite major advancements in lung cancer treatment, long-term survival is still rare, and a deeper understanding of molecular phenotypes would allow the identification of specific cancer dependencies and immune evasion mechanisms. Here we performed in-depth mass spectrometry (MS)-based proteogenomic analysis of 141 tumors representing all major histologies of non-small cell lung cancer (NSCLC). We identified six distinct proteome subtypes with striking differences in immune cell composition and subtype-specific expression of immune checkpoints. Unexpectedly, high neoantigen burden was linked to global hypomethylation and complex neoantigens mapped to genomic regions, such as endogenous retroviral elements and introns, in immune-cold subtypes. Further, we linked immune evasion with LAG3 via STK11 mutation-dependent HNF1A activation and FGL1 expression. Finally, we develop a data-independent acquisition MS-based NSCLC subtype classification method, validate it in an independent cohort of 208 NSCLC cases and demonstrate its clinical utility by analyzing an additional cohort of 84 late-stage NSCLC biopsy samples.
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影响因子:
14.9
作者:
Almeida LG;Sakabe NJ;deOliveira AR;Silva MC;Mundstein AS;Cohen T;Chen YT;Chua R;Gurung S;Gnjatic S;Jungbluth AA;Caballero OL;Bairoch A;Kiesler E;White SL;Simpson AJ;Old LJ;Camargo AA;Vasconcelos AT
通讯作者:
Vasconcelos AT
影响因子:
64.5
作者:
Gillette, Michael A.;Satpathy, Shankha;Carr, Steven A.
通讯作者:
Carr, Steven A.
影响因子:
15.8
作者:
Azuma T;Zhu G;Xu H;Rietz AC;Drake CG;Matteson EL;Chen L
通讯作者:
Chen L
影响因子:
64.8
作者:
Cabrita, Rita;Lauss, Martin;Jonsson, Goran
通讯作者:
Jonsson, Goran
影响因子:
64.5
作者:
Helwak A;Kudla G;Dudnakova T;Tollervey D
通讯作者:
Tollervey D