MCAM abnormal expression and clinical outcome associations are highly cancer dependent as revealed through pan-cancer analysis

Yunxia An, Nan Wei, Xiangsong Cheng, Ying Li, Haiyang Liu, Jia Wang, Zhiwei Xu, Zhifu Sun, Xiaoju Zhang

Research output: Contribution to journalReview article

Abstract

MCAM (CD146) is a cell surface adhesion molecule that has been reported to promote cancer development, progression and metastasis and is considered as a potential tumor biomarker and therapeutic target. However, inconsistent reports exist, and its clinical value is yet to be confirmed. Here we took advantage of several large genomic data collections (Genotype-Tissue Expression, The Cancer Genome Atlas and Cancer Cell Line Encyclopedia) and comprehensively analyzed MCAM expression in thousands of normal and cancer samples and cell lines along with their clinical phenotypes and drug response information. Our results show that MCAM is very highly expressed in large vessel tissues while majority of tissues have low or minimal expression. Its expression is dramatically increased in a few tumors but significantly decreased in most other tumors relative to their pairing normal tissues. Increased MCAM expression is associated with a higher tumor stage and worse patient survival for some less common tumors but not for major ones. Higher MCAM expression in primary tumors may be complicated by tumor-associated or normal stromal blood vessels yet its significance may differ from the one from cancer cells. MCAM expression is weakly associated with the response to a few small molecular drugs and the association with targeted anti-BRAF agents suggests its involvement in that pathway which warrants further investigation.

Original languageEnglish (US)
Pages (from-to)709-718
Number of pages10
JournalBriefings in bioinformatics
Volume21
Issue number2
DOIs
StatePublished - Mar 23 2020

Keywords

  • CCLE
  • CD146
  • GTEx
  • MCAM
  • Pan-cancer analysis
  • TCGA
  • patient survival
  • tumor progression
  • tumor stage

ASJC Scopus subject areas

  • Information Systems
  • Molecular Biology

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