Integrating proteomics and transcriptomics for the identification of potential targets in early colorectal cancer

Int J Oncol. 2019 Aug;55(2):439-450. doi: 10.3892/ijo.2019.4833. Epub 2019 Jun 27.

Abstract

Colorectal cancer (CRC) is one of the most common malignancies worldwide. At present, CRC can often be treated upon diagnosis at stage I or II, or when dysplasia is detected; however, 60‑70% of cases are not diagnosed until they have developed into late stages of the disease or until the malignancy is identified. Diagnosis of CRC at an early stage remains a challenge due to the absence of early‑stage‑specific biomarkers. To identify potential targets of early stage CRC, label‑free proteomics analysis was applied to paired tumor‑benign tissue samples from patients with stage II CRC (n=21). A total of 2,968 proteins were identified; corresponding RNA‑Sequencing data were retrieved from The Cancer Genome Atlas‑colon adenocarcinoma. Numerous bioinformatics methods, including differential expression analysis, weighted correlation network analysis, Gene Ontology and protein‑protein interaction analyses, were applied to the proteomics and transcriptomics data. A total of 111 key proteins, which appeared as both differentially expressed proteins and mRNAs in the hub module, were identified as key candidates. Among these, three potential targets [protein‑arginine deiminase type‑2 (PADI2), Fc fragment of IgG binding protein (FCGBP) and phosphoserine aminotransferase 1] were identified from the pathological data. Furthermore, the survival analysis indicated that PADI2 and FCGBP were associated with the prognosis of CRC. The findings of the present study suggested potential targets for the identification of early stage CRC, and may improve understanding of the mechanism underlying the occurrence of CRC.

MeSH terms

  • Adenocarcinoma / genetics
  • Adenocarcinoma / metabolism
  • Adenocarcinoma / pathology*
  • Biomarkers, Tumor / genetics*
  • Biomarkers, Tumor / metabolism*
  • Colorectal Neoplasms / genetics
  • Colorectal Neoplasms / metabolism
  • Colorectal Neoplasms / pathology*
  • Computational Biology / methods
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic*
  • Gene Ontology
  • Gene Regulatory Networks
  • Humans
  • Male
  • Middle Aged
  • Prognosis
  • Protein Interaction Maps
  • Proteome / analysis*
  • Survival Rate
  • Transcriptome*

Substances

  • Biomarkers, Tumor
  • Proteome