# MiRank: A bioinformatics tool for gene/miRNA ranking and pathway profiling with TCGA-KEGG data sets

**Authors:** Siddharth G. Reddy, Weimin Xiao, Preethi H. Gunaratne  
**arXiv:** [1210.0286](https://arxiv.org/abs/1210.0286)  
**Date:** 2012-10-01  
**Summary page:** https://www.summarizepaper.com/en/paper/1210.0286v2/

## Key points

- The Cancer Genome Atlas (TCGA) is a valuable resource for researchers, providing clinicopathological data and genomic characterizations of various carcinomas.
- TCGA includes expression microarrays for genes and microRNAs, which regulate gene expression through RNA interference.
- TCGA offers fields such as days_to_death and days_to_last_followup for each tumor sample.
- Authors Siddharth G. Reddy, Weimin Xiao, and Preethi H. Gunaratne developed MiRank to screen TCGA data sets to identify genes and miRNAs with functional involvement in specific cancers.
- MiRank ranks genes/miRNAs based on the correlation of their expression misregulation with differential patient survival.
- By analyzing the ovarian serous cystadenocarcinoma (OV) data set, MiRank identified highly ranked pathways and functional groups of genes like VEGF, Jun, and Fos implicated in epithelial ovarian carcinomas.
- Dysfunction of the Wnt signaling pathway has a significant impact on the survival of ovarian cancer patients.
- MiRank provides a comprehensive approach to identifying key genes and miRNAs involved in cancer progression by analyzing TCGA data sets within relevant biological pathways for further investigation.

## Summary

The Cancer Genome Atlas (TCGA) is a valuable resource for researchers, providing clinicopathological data and genomic characterizations of various carcinomas. This includes expression microarrays for genes and microRNAs, which are short RNA strands that regulate gene expression through RNA interference. Additionally, TCGA offers fields such as days_to_death and days_to_last_followup for each tumor sample. In this study, authors Siddharth G. Reddy, Weimin Xiao, and Preethi H. Gunaratne aimed to develop a software tool called MiRank that screens TCGA data sets to identify genes and miRNAs with functional involvement in specific cancers. The computational pipeline they created generates visualizations that place the screened outputs in a pathway-centric context. The screening process involves ranking genes/miRNAs based on the correlation of their expression misregulation with differential patient survival. Genes or miRNAs consistently misregulated in patients with poor survival rates but expressed more normally in patients with longer survival rates are ranked highly. Conversely, those without such correlation with patient survival are ranked lower. By running the ovarian serous cystadenocarcinoma (OV) data set through their analysis pipeline, the authors identified several highly ranked pathways and functional groups of genes like VEGF, Jun, and Fos that have been implicated in the development of epithelial ovarian carcinomas. They also noted that dysfunction of the Wnt signaling pathway has a significant impact on the survival of ovarian cancer patients. Overall, MiRank provides a comprehensive approach to identifying key genes and miRNAs involved in cancer progression by analyzing TCGA data sets and placing them within relevant biological pathways for further investigation.