AS-CMC: a pan-cancer database of alternative splicing for molecular classification of cancer

被引:0
|
作者
Jiyeon Park
Jin-Ok Lee
Minho Lee
Yeun-Jun Chung
机构
[1] The Catholic University of Korea,Precision Medicine Research Center, College of Medicine
[2] The Catholic University of Korea,Integrated Research Center for Genome Polymorphism
[3] The Catholic University of Korea,Department of Biomedicine and Health Sciences, Graduate School
[4] Dongguk University-Seoul,Department of Life Science
[5] The Catholic University of Korea,Department of Microbiology, College of Medicine
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Alternative splicing (AS) is a post-transcriptional regulation that leads to the complexity of the transcriptome. Despite the growing importance of AS in cancer research, the role of AS has not been systematically studied, especially in understanding cancer molecular classification. Herein, we analyzed the molecular subtype-specific regulation of AS using The Cancer Genome Atlas data and constructed a web-based database, named Alternative Splicing for Cancer Molecular Classification (AS-CMC). Our system harbors three analysis modules for exploring subtype-specific AS events, evaluating their phenotype association, and performing pan-cancer comparison. The number of subtype-specific AS events was found to be diverse across cancer types, and some differentially regulated AS events were recurrently found in multiple cancer types. We analyzed a subtype-specific AS in exon 11 of mitogen-activated protein kinase kinase 7 (MAP3K7) as an example of a pan-cancer AS biomarker. This AS marker showed significant association with the survival of patients with stomach adenocarcinoma. Our analysis revealed AS as an important determinant for cancer molecular classification. AS-CMC is the first web-based resource that provides a comprehensive tool to explore the biological implications of AS events, facilitating the discovery of novel AS biomarkers.
引用
收藏
相关论文
共 50 条
  • [31] The Pan-Cancer Atlas: a New Chapter in Cancer Molecular Targeting Therapy
    Hu, Hao-Liang
    Zeng, Dan-Dan
    Zang, Jing-Lei
    Chen, Zhe
    PATHOLOGY & ONCOLOGY RESEARCH, 2020, 26 (03) : 1997 - 1999
  • [32] A Pan-Cancer Analysis of Alternative Splicing Events Reveals Novel Tumor-Associated Splice Variants of Matriptase
    Dargahi, Daryanaz
    Swayze, Richard D.
    Yee, Leanna
    Bergqvist, Peter J.
    Hedberg, Bradley J.
    Heravi-Moussavi, Alireza
    Dullaghan, Edie M.
    Dercho, Ryan
    An, Jianghong
    Babcook, John S.
    Jones, Steven J. M.
    CANCER INFORMATICS, 2014, 13 : 167 - 177
  • [33] Pan-cancer analysis of Chromobox (CBX) genes for prognostic significance and cancer classification
    Naqvi, Ahmad Abu Turab
    Rizvi, Syed Afzal Murtaza
    Hassan, Md. Imtaiyaz
    BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR BASIS OF DISEASE, 2023, 1869 (01):
  • [34] Transcriptome instability as a molecular pan-cancer characteristic of carcinomas
    Anita Sveen
    Bjarne Johannessen
    Manuel R Teixeira
    Ragnhild A Lothe
    Rolf I Skotheim
    BMC Genomics, 15
  • [35] Pan-cancer clinical and molecular analysis of racial disparities
    Lara, Olivia D.
    Wang, Ying
    Asare, Amma
    Xu, Tao
    Chiu, Hua-Sheng
    Liu, Yuexin
    Hu, Wei
    Sumazin, Pavel
    Uppal, Shitanshu
    Zhang, Lin
    Rauh-Hain, J. Alejandro
    Sood, Anil K.
    CANCER, 2020, 126 (04) : 800 - 807
  • [36] Transcriptome instability as a molecular pan-cancer characteristic of carcinomas
    Sveen, Anita
    Johannessen, Bjarne
    Teixeira, Manuel R.
    Lothe, Ragnhild A.
    Skotheim, Rolf I.
    BMC GENOMICS, 2014, 15
  • [37] A pan-cancer transcriptome analysis of exitron splicing identifies novel cancer driver genes and neoepitopes
    Wang, Ting-You
    Liu, Qi
    Ren, Yanan
    Alam, Sk Kayum
    Wang, Li
    Zhu, Zhu
    Hoeppner, Luke H.
    Dehm, Scott M.
    Cao, Qi
    Yang, Rendong
    MOLECULAR CELL, 2021, 81 (10) : 2246 - +
  • [38] Pan-cancer genomic analyses uncover molecular drivers
    David Killock
    Nature Reviews Clinical Oncology, 2018, 15 : 263 - 263
  • [39] Pan-Cancer Biomarkers Changing the Landscape of Molecular Testing
    Yao, Jinjuan
    Arcila, Maria E.
    Ladanyi, Marc
    Hechtman, Jaclyn F.
    ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE, 2021, 145 (06) : 692 - 698
  • [40] Pan-cancer classification by regularized multi-task learning
    Hossain, Sk Md Mosaddek
    Khatun, Lutfunnesa
    Ray, Sumanta
    Mukhopadhyay, Anirban
    SCIENTIFIC REPORTS, 2021, 11 (01)