In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer

K. T.Shreya Parthasarathi, Susmita Mandal, Smrita Singh, Seetaramanjaneyulu Gundimeda, Mohit Kumar Jolly, Akhilesh Pandey, Jyoti Sharma

Research output: Contribution to journalArticlepeer-review

Abstract

Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein–protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan–Meier five-year survival analysis and Cox regressions indicated the expression of CACNA1B, ANO6, TRPV3, VDAC1 and VDAC2 to be potentially associated with poor survival. Deregulated ion channels correlate with EMT-related genes and have a crucial role in breast cancer-associated tumorigenesis. Most likely, they are potential candidates for the determination of prognosis in patients with breast cancer.

Original languageEnglish (US)
Article number1444
JournalCancers
Volume14
Issue number6
DOIs
StatePublished - Mar 1 2022

Keywords

  • Bioinformatics
  • Interaction networks
  • Membrane proteins
  • Microarray
  • Prognosis
  • RNA-Seq

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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