美国哈佛大学Steven A. Carr等研究人员合作绘制出肺腺癌蛋白质基因组特征图谱，从而揭示了肿瘤的治疗弱点。相关论文于2020年7月9日发表在《细胞》杂志上。
Author: Michael A. Gillette, Shankha Satpathy, Song Cao, Saravana M. Dhanasekaran, Suhas V. Vasaikar, Karsten Krug, Francesca Petralia, Yize Li, Wen-Wei Liang, Boris Reva, Azra Krek, Jiayi Ji, Xiaoyu Song, Wenke Liu, Runyu Hong, Lijun Yao, Lili Blumenberg, Sara R. Savage, Michael C. Wendl, Bo Wen, Kai Li, Lauren C. Tang, Melanie A. MacMullan, Shayan C. Avanessian, M. Harry Kane, Chelsea J. Newton, MacIntosh Cornwell, Ramani B. Kothadia, Weiping Ma, Seungyeul Yoo, Rahul Mannan, Pankaj Vats, Chandan Kumar-Sinha, Emily A. Kawaler, Tatiana Omelchenko, Antonio Colaprico, Yifat Geffen, Yosef E. Maruvka, Felipe da Veiga Leprevost, Maciej Wiznerowicz, Zeynep H. Gümü, Rajwanth R. Veluswamy, Galen Hostetter, David I. Heiman, Matthew A. Wyczalkowski, Tara Hiltke, Mehdi Mesri, Christopher R. Kinsinger, Emily S. Boja, Gilbert S. Omenn, Arul M. Chinnaiyan, Henry Rodriguez, Qing Kay Li, Scott D. Jewell, Mathangi Thiagarajan, Gad Getz, Bing Zhang, David Feny, Kelly V. Ruggles, Marcin P. Cieslik, Ana I. Robles, Karl R. Clauser, Ramaswamy Govindan, Pei Wang, Alexey I. Nesvizhskii, Li Ding, D.R. Mani, Steven A. Carr, Alex Webster, Alicia Francis, Alyssa Charamut, Amanda G. Paulovich, Amy M. Perou, Andrew K. Godwin
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.