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CBioProfiler: A Web and Standalone Pipeline for Cancer Biomarker and Subtype Characterization
Xiaoping Liu1,2,3, Zisong Wang1, Hongjie Shi3,4
1Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
Genomics, Proteomics & Bioinformatics
|June 13, 2024
Summary
A new tool, Cancer Biomarker and subtype Profiler (CBioProfiler), aids in identifying cancer biomarkers and subtypes to predict patient survival. This resource offers standardized pipelines and curated data for improved cancer research and clinical applications.
Area of Science:
- Oncology
- Bioinformatics
- Computational Biology
Background:
- Cancer remains a major global health challenge, necessitating accurate prediction of patient survival for effective treatment and prognosis.
- Current tools for exploring cancer biomarkers and subtypes lack standardization, hindering research and clinical application.
Purpose of the Study:
- To introduce Cancer Biomarker and subtype Profiler (CBioProfiler), a novel web server and standalone application.
- To provide standardized pipelines for analyzing cancer biomarkers and subtypes to predict patient survival.
Main Methods:
- Developed two distinct pipelines: one for cancer biomarker identification and annotation using machine learning, and another for cancer subtype identification using unsupervised learning.
- Integrated CuratedCancerPrognosisData, an R package with curated gene expression and clinical data from 268 studies covering 43 tumor types and 47,686 samples.
Main Results:
- CBioProfiler offers a comprehensive platform for analyzing cancer survival-related biomarkers and identifying distinct cancer subtypes.
- The integrated dataset provides a robust resource for validating findings across a wide range of cancer types.
Conclusions:
- CBioProfiler addresses the need for standardized tools in cancer biomarker and subtype analysis.
- This resource facilitates improved risk stratification, treatment selection, and prognostic assessment for cancer patients.
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