Proteogenomic Characterization Reveals Estrogen Signaling as a Target for Never-Smoker Lung Adenocarcinoma Patients without EGFR or ALK Alterations

被引:2
作者
Park, Seung-Jin [1 ,2 ]
Ju, Shinyeong [3 ]
Goh, Sung-Ho [4 ]
Yoon, Byoung-Ha [1 ,5 ]
Park, Jong-Lyul [1 ]
Kim, Jeong-Hwan [1 ]
Lee, Seonjeong [3 ,6 ]
Lee, Sang-Jin [4 ]
Kwon, Yumi [3 ]
Lee, Wonyeop [4 ]
Park, Kyung Chan [1 ,2 ]
Lee, Geon Kook [4 ]
Park, Seog Yun [4 ]
Kim, Sunshin [4 ]
Kim, Seon-Young [1 ,2 ,5 ]
Han, Ji-Youn [4 ]
Lee, Cheolju [3 ,6 ]
机构
[1] Korea Res Inst Biosci & Biotechnol, Daejeon, South Korea
[2] Univ Sci & Technol UST, Dept Biosci, Daejeon, South Korea
[3] Korea Inst Sci & Technol, Chem & Biol Integrat Res Ctr, Seoul 02792, South Korea
[4] Natl Canc Ctr, Goyang 10408, South Korea
[5] Korea Res Inst Biosci & Biotechnol, Korea Bioinformat Ctr KOBIC, 125 Gwahak Ro, Daejeon 305806, South Korea
[6] Univ Sci & Technol, KIST Sch, Div Biomed Sci & Technol, Seoul, South Korea
基金
新加坡国家研究基金会;
关键词
BIOCONDUCTOR PACKAGE; MOLECULAR SIGNATURES; CANCER;
D O I
10.1158/0008-5472.CAN-23-1551
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Never-smoker lung adenocarcinoma (NSLA) is prevalent in Asian populations, particularly in women. EGFR mutations and anaplastic lymphoma kinase (ALK) fusions are major genetic alterations observed in NSLA, and NSLA with these alterations have been well studied and can be treated with targeted therapies. To provide insights into the molecular profile of NSLA without EGFR and ALK alterations (NENA), we selected 141 NSLA tissues and performed proteogenomic characterization, including whole genome sequencing (WGS), transcriptomic, methylation EPIC array, total proteomic, and phosphoproteomic analyses. Forty patients with NSLA harboring EGFR and ALK alterations and seven patients with NENA with microsatellite instability were excluded. Genome analysis revealed that TP53 (25%), KRAS (22%), and SETD2 (11%) mutations and ROS1 fusions (14%) were the most frequent genetic alterations in NENA patients. Proteogenomic impact analysis revealed that STK11 and ERBB2 somatic mutations had broad effects on cancer-associated genes in NENA. DNA copy number alteration analysis identified 22 prognostic proteins that influenced transcriptomic and proteomic changes. Gene set enrichment analysis revealed estrogen signaling as the key pathway activated in NENA. Increased estrogen signaling was associated with proteogenomic alterations, such as copy number deletions in chromosomes 14 and 21, STK11 mutation, and DNA hypomethylation of LLGL2 and ST14. Finally, saracatinib, an Src inhibitor, was identified as a potential drug for targeting activated estrogen signaling in NENA and was experimentally validated in vitro. Collectively, this study enhanced our understanding of NENA NSLA by elucidating the proteogenomic landscape and proposed saracatinib as a potential treatment for this patient population that lacks effective targeted therapies.
引用
收藏
页码:1491 / 1503
页数:13
相关论文
共 38 条
  • [11] Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma
    Gillette, Michael A.
    Satpathy, Shankha
    Cao, Song
    Dhanasekaran, Saravana M.
    Vasaikar, Suhas V.
    Krug, Karsten
    Petralia, Francesca
    Li, Yize
    Liang, Wen-Wei
    Reva, Boris
    Krek, Azra
    Ji, Jiayi
    Song, Xiaoyu
    Liu, Wenke
    Hong, Runyu
    Yao, Lijun
    Blumenberg, Lili
    Savage, Sara R.
    Wendl, Michael C.
    Wen, Bo
    Li, Kai
    Tang, Lauren C.
    MacMullan, Melanie A.
    Avanessian, Shayan C.
    Kane, M. Harry
    Newton, Chelsea J.
    Cornwell, MacIntosh
    Kothadia, Ramani B.
    Ma, Weiping
    Yoo, Seungyeul
    Mannan, Rahul
    Vats, Pankaj
    Kumar-Sinha, Chandan
    Kawaler, Emily A.
    Omelchenko, Tatiana
    Colaprico, Antonio
    Geffen, Yifat
    Maruvka, Yosef E.
    Leprevost, Felipe da Veiga
    Wiznerowicz, Maciej
    Gumus, Zeynep H.
    Veluswamy, Rajwanth R.
    Hostetter, Galen
    Heiman, David, I
    Wyczalkowski, Matthew A.
    Hiltke, Tara
    Mesri, Mehdi
    Kinsinger, Christopher R.
    Boja, Emily S.
    Omenn, Gilbert S.
    [J]. CELL, 2020, 182 (01) : 200 - +
  • [12] Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods
    Haas, Brian J.
    Dobin, Alexander
    Li, Bo
    Stransky, Nicolas
    Pochet, Nathalie
    Regev, Aviv
    [J]. GENOME BIOLOGY, 2019, 20 (01)
  • [13] GSVA: gene set variation analysis for microarray and RNA-Seq data
    Haenzelmann, Sonja
    Castelo, Robert
    Guinney, Justin
    [J]. BMC BIOINFORMATICS, 2013, 14
  • [14] Estrogen, Estrogen Receptor and Lung Cancer
    Hsu, Li-Han
    Chu, Nei-Min
    Kao, Shu-Huei
    [J]. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2017, 18 (08)
  • [15] MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability
    Jia, Peng
    Yang, Xiaofei
    Guo, Li
    Liu, Bowen
    Lin, Jiadong
    Liang, Hao
    Sun, Jianyong
    Zhang, Chengsheng
    Ye, Kai
    [J]. GENOMICS PROTEOMICS & BIOINFORMATICS, 2020, 18 (01) : 65 - 71
  • [16] Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
    Kuleshov, Maxim V.
    Jones, Matthew R.
    Rouillard, Andrew D.
    Fernandez, Nicolas F.
    Duan, Qiaonan
    Wang, Zichen
    Koplev, Simon
    Jenkins, Sherry L.
    Jagodnik, Kathleen M.
    Lachmann, Alexander
    McDermott, Michael G.
    Monteiro, Caroline D.
    Gundersen, Gregory W.
    Ma'ayan, Avi
    [J]. NUCLEIC ACIDS RESEARCH, 2016, 44 (W1) : W90 - W97
  • [17] The Molecular Signatures Database Hallmark Gene Set Collection
    Liberzon, Arthur
    Birger, Chet
    Thorvaldsdottir, Helga
    Ghandi, Mahmoud
    Mesirov, Jill P.
    Tamayo, Pablo
    [J]. CELL SYSTEMS, 2015, 1 (06) : 417 - 425
  • [18] Universal Patterns of Selection in Cancer and Somatic Tissues
    Martincorena, Inigo
    Raine, Keiran M.
    Gerstung, Moritz
    Dawson, Kevin J.
    Haase, Kerstin
    Van Loo, Peter
    Davies, Helen
    Stratton, Michael R.
    Campbell, Peter J.
    [J]. CELL, 2017, 171 (05) : 1029 - +
  • [19] Maftools: efficient and comprehensive analysis of somatic variants in cancer
    Mayakonda, Anand
    Lin, De-Chen
    Assenov, Yassen
    Plass, Christoph
    Koeffler, H. Phillip
    [J]. GENOME RESEARCH, 2018, 28 (11) : 1747 - 1756
  • [20] The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
    McKenna, Aaron
    Hanna, Matthew
    Banks, Eric
    Sivachenko, Andrey
    Cibulskis, Kristian
    Kernytsky, Andrew
    Garimella, Kiran
    Altshuler, David
    Gabriel, Stacey
    Daly, Mark
    DePristo, Mark A.
    [J]. GENOME RESEARCH, 2010, 20 (09) : 1297 - 1303