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CAMOIP: a web server for comprehensive analysis on multi-omics of immunotherapy in pan-cancer.

Anqi LinChang QiTing WeiMengyao LiQuan ChenZaoqu LiuPeng LuoJian Zhang
Published in: Briefings in bioinformatics (2022)
Immune checkpoint inhibitors (ICIs) have completely changed the approach pertaining to tumor diagnostics and treatment. Similarly, immunotherapy has also provided much needed data about mutation, expression and prognosis, affording an unprecedented opportunity for discovering candidate drug targets and screening for immunotherapy-relevant biomarkers. Although existing web tools enable biologists to analyze the expression, mutation and prognostic data of tumors, they are currently unable to facilitate data mining and mechanism analyses specifically related to immunotherapy. Thus, we effectively developed our own web-based tool, called Comprehensive Analysis on Multi-Omics of Immunotherapy in Pan-cancer (CAMOIP), in which we are able to successfully screen various prognostic markers and analyze the mechanisms involved in biomarker expression and function, as well as immunotherapy. The analyses include information relevant to survival analysis, expression analysis, mutational landscape analysis, immune infiltration analysis, immunogenicity analysis and pathway enrichment analysis. This comprehensive analysis of biomarkers for immunotherapy can be carried out by a click of CAMOIP, and the software should greatly encourage the further development of immunotherapy. CAMOIP provides invaluable evidence that bridges the information between the data of cancer genomics based on immunotherapy, providing comprehensive information to users and assisting in making the value of current ICI-treated data available to all users. CAMOIP is available at https://www.camoip.net.
Keyphrases
  • electronic health record
  • machine learning
  • big data
  • transcription factor
  • deep learning
  • high throughput
  • health information