MethSurv: A Web Tool to Perform Multivariable Survival Analysis Using DNA Methylation Data

Abstract

Aim: To develop a web tool for survival analysis based on CpG methylation patterns. Materials & methods: We utilized methylome data from ‘The Cancer Genome Atlas’ and used the Cox proportional-hazards model to develop an interactive web interface for survival analysis. Results: MethSurv enables survival analysis for a CpG located in or around the proximity of a query gene. For further mining, cluster analysis for a query gene to associate methylation patterns with clinical characteristics and browsing of top biomarkers for each cancer type are provided. MethSurv includes 7358 methylomes from 25 different human cancers. Conclusion: The MethSurv tool is a valuable platform for the researchers without programming skills to perform the initial assessment of methylation-based cancer biomarkers.

Keywords::

• biomarkers
• cancer survival analysis
• clustering
• Cox Proportional-Hazards
• DNA methylation
• epigenetics
• Illumina 450 K
• Kaplan–Meier
• prognosis
• TCGA

Supplementary data

To view the supplementary data that accompany this paper please visit the journal website at: www.tandfonline.com/doi/full/10.2217/epi-2017-0118

Acknowledgements

The authors would like to thank I Kuzmin and the high-performance computing team of the University of Tartu for their kind assistance to address the technical issues. We also thank S Kasela for her constructive feedback on statistical matters. We thank TCGA research network (http://cancergenome.nih.gov) for making their data publicly available. MethSurv performs survival analysis based on TCGA data.

Financial & competing interests disclosure

The research was funded by the European Commission Horizon 2020 research and innovation programme under grant agreement 692065 (project WIDENLIFE), and has also been supported by grant IUT34-16 and IUT34-4 from the Estonian Research Council and ERDF through EXCITE Center of Excellence. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

No writing assistance was utilized in the production of this manuscript.

Additional information

Funding

The research was funded by the European Commission Horizon 2020 research and innovation programme under grant agreement 692065 (project WIDENLIFE), and has also been supported by grant IUT34-16 and IUT34-4 from the Estonian Research Council and ERDF through EXCITE Center of Excellence. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed. No writing assistance was utilized in the production of this manuscript.