CancerLivER: Liver Cancer Expression Resource

CancerLivER is a comprehensive web-based database developed for the analysis of liver cancer-associated gene expression datasets and biomarkers. The platform integrates transcriptomics datasets, biomarker information, clinical data, and analysis tools to facilitate liver cancer research and biomarker discovery.

Web Server: https://webs.iiitd.edu.in/raghava/cancerliver/

ZENODO LINK : https://doi.org/10.5281/zenodo.20073349

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Citation

Kaur, H., Bhalla, S., Kaur, D., & Raghava, G. P. S. (2020).
CancerLivER: a database of liver cancer gene expression resources and biomarkers.
Database, 2020, baaa012.
https://doi.org/10.1093/database/baaa012

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About the Database

CancerLivER was developed to provide a centralized resource for liver cancer transcriptomics and biomarker data. The database integrates uniformly processed expression datasets along with experimentally validated biomarkers collected from published studies.

The resource contains:

• 115 liver cancer expression datasets
• 9611 samples
• 594 liver cancer biomarkers
• Multiple liver cancer types including:
  • Hepatocellular carcinoma (HCC)
  • Cholangiocarcinoma
  • Hepatoblastoma
  • Fibrolamellar carcinoma

Data were collected from:

• GEO
• TCGA/GDC
• PubMed
• Liverome

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Key Features

• Uniformly processed gene expression datasets
• Curated liver cancer biomarker repository
• Clinical information associated with samples
• Gene-wise and pathway-wise expression analysis
• GO term and ssGSEA analysis tools
• Interactive visualization and graphical plots
• Downloadable dataset matrices

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Biomarker Statistics

CancerLivER contains:

• 341 diagnostic biomarkers
• 165 prognostic biomarkers
• 51 predictive biomarkers
• Biomarkers based on:
  • RNA
  • Protein
  • miRNA
  • Metabolites
  • lncRNA

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Applications

CancerLivER can be used for:

• Liver cancer biomarker discovery
• Transcriptomics analysis
• Drug target identification
• Survival and prognosis studies
• Development of prediction models
• Functional genomics research

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Technologies Used

• Apache HTTP Server
• MySQL
• PHP
• HTML5/CSS3
• JavaScript
• R/Bioconductor pipelines

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Contact

Prof. Gajendra P. S. Raghava
Department of Computational Biology
IIIT Delhi, India

Email: raghava@iiitd.ac.in

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License

Open Access under CC-BY 4.0 License

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Acknowledgements

Supported by:

• Department of Science and Technology (DST), India
• CSIR, India
• ICMR, India