OC_logo
Contents
  • Home
  • Browse by tumor type
  • Ion channel
  • Ion channel EMT correlation
  • Ion channel Co-expression
  • Downloads
  • FAQs
  • Contact Us

Contents

  • Home
  • Browse by tumor type
  • Ion channels
  • Ion channel EMT correlation
  • Ion channel Co-expression
  • Downloads
  • FAQs
  • Contact Us


ONCOchannelome is a comprehensive data resource to investigate dysregulated ion channels across tumor types. The resource contains details about the dysregulated ion channels in 15 different tumors identified using transcriptomic data obtained from The Cancer Genome Atlas (TCGA) and MET500 metastatic cancer cohort. Furthermore, downstream analysis was performed including correlations with epithelial and mesenchymal gene signatures, identification of ion channels transcriptional regulators, ion channel co-expression gene modules and enrichment in terms of biological function, molecular processes and cellular compartments. “ONCOchannelome” may serve as a platform to the scientific community by encouraging future research to study the role of dysregulated ion channels across tumors.


Statistics

Primary site 14
Tumor type 15
Primary tumor samples 5442
Metastatic samples 588
Normal samples 2421
Ion channels 493

References:

Parthasarathi, K. T. S., Ramu, S., Jolly, M. K., Sharma, J. (2025). ONCOchannelome: A computational framework to investigate altered ion channels across tumor types. [Preprint]

Parthasarathi, K. T. S., Choudhary, S., Sharma, J. (2025). A multiOmics approach to identify altered ion channels across breast cancer subtypes. In Silico Research in Biomedicine. [Article]

Parthasarathi, K. T. S., Mandal, S., George, J. P., Gaikwad, K. B., Sasidharan, S., Gundimeda, S., Jolly, M. K., Pandey, A., Sharma, J. (2023). Aberrations in ion channels interacting with lipid metabolism and epithelial mesenchymal transition in esophageal squamous cell carcinoma. Frontiers in Molecular Biosciences. [PubMed]

Parthasarathi, K. T. S., Mandal, S., Singh, S., Gundimeda, S., Jolly, M. K., Pandey, A. and Sharma, J. (2022). In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer. Cancers 14(6), 1444. [PubMed]

Primary sites

home_img

Total visitors: Loading...

Powered by © Institute of Bioinformatics