Integrative ontology and pathway-based approach identifies distinct molecular signatures in transcriptomes of esophageal squamous cell carcinoma

Adv Protein Chem Struct Biol. 2022:131:177-206. doi: 10.1016/bs.apcsb.2022.04.003. Epub 2022 Jun 17.

Abstract

Esophageal squamous cell carcinoma (ESCC) remains a serious concern globally due to many factors that including late diagnosis, lack of an ideal biomarker for diagnosis and prognosis, and high rate of mortality. In this study, we aimed to identify the essential dysregulated genes and molecular signatures associated with the progression and development of ESCC. The dataset with 15 ESCCs and the 15 adjacent normal tissue samples from the surrounding histopathologically tumor-free mucosa was selected. We applied bioinformatics pipelines including various topological parameters from MCODE, CytoNCA, and cytoHubba to prioritize the most significantly associated DEGs with ESCC. We performed functional enrichment annotation for the identified DEGs using DAVID and MetaCore™ GeneGo platforms. Furthermore, we validated the essential core genes in TCGA and GTEx datasets between the normal mucosa and ESCC for their expression levels. These DEGs were primarily enriched in positive regulation of transferase activity, negative regulation of organelle organization, cell cycle mitosis/S-phase transition, spindle organization/assembly, development, and regulation of angiogenesis. Subsequently, the DEGs were associated with the pathways such as oocyte meiosis, cell cycle, and DNA replication. Our study identified the eight-core genes (AURKA, AURKB, MCM2, CDC20, TPX2, PLK1, FOXM1, and MCM7) that are highly expressed among the ESCC, and TCGA dataset. The multigene comparison and principal component analysis resulted in elevated signals for the AURKA, MCM2, CDC20, TPX2, PLK1, and FOXM1. Overall, our study reported GO profiles and molecular signatures that might help researchers to grasp the pathological mechanisms underlying ESCC development and eventually provide novel therapeutic and diagnostic strategies.

Keywords: Cancer; Differentially expressed genes; Esophageal squamous cell carcinoma; MetaCore; Protein-protein interaction; TopGO.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aurora Kinase A / genetics
  • Aurora Kinase A / metabolism
  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Cell Cycle Proteins / genetics
  • Cell Cycle Proteins / metabolism
  • Computational Biology / methods
  • Esophageal Neoplasms* / genetics
  • Esophageal Neoplasms* / metabolism
  • Esophageal Neoplasms* / pathology
  • Esophageal Squamous Cell Carcinoma* / genetics
  • Esophageal Squamous Cell Carcinoma* / metabolism
  • Esophageal Squamous Cell Carcinoma* / pathology
  • Gene Expression Profiling / methods
  • Gene Expression Regulation, Neoplastic
  • Humans
  • Transcriptome / genetics

Substances

  • Biomarkers, Tumor
  • Cell Cycle Proteins
  • Aurora Kinase A