Reliable epithelial-mesenchymal transition biomarkers for colorectal cancer detection

Kaitlin A. Goettsch, Ling Zhang, Amar B. Singh, Punita Dhawan, Dhundy K. Bastola

Research output: Contribution to journalArticlepeer-review

Abstract

Aims: To combat increases in colorectal cancer (CRC) incidence and mortality, biomarkers among differentially expressed genes (DEGs) have been identified to objectively detect cancer. However, DEGs are numerous, and additional parameters may identify more reliable biomarkers. Here, CRC DEGs were filtered into a prioritized list of biomarkers. Materials & methods: Two independent datasets (COAD-READ [n = 698] and GSE50760 [n = 36]) were input alternatively to the recently published data-driven reference method. Results were filtered based on epithelial-mesenchymal transition enrichment (χ-square statistic: 919.05; p = 2.2e-16) to produce 37 potential CRC biomarkers. Results: All 37 genes reliably classified CRC samples and ETV4, CLDN1 and CA2 together were top-ranked by DDR (accuracy: 89%; F1 score: 0.89). Conclusion: Biological and statistical information were combined to produce a better set of CRC detection biomarkers.

Original languageEnglish (US)
Pages (from-to)889-901
Number of pages13
JournalBiomarkers in Medicine
Volume16
Issue number12
DOIs
StatePublished - Aug 2022

Keywords

  • CRC
  • DDR
  • EMT
  • biomarkers
  • classification
  • colorectal cancer
  • data-driven reference
  • epithelial-mesenchymal transition

ASJC Scopus subject areas

  • Drug Discovery
  • Clinical Biochemistry
  • Biochemistry, medical

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