Understanding how genetic changes drive cancer is one of the biggest challenges in biomedical research. Traditionally, scientists look at DNA to find these changes, but now researchers are turning to RNA for even more answers. A team led by researchers from Nationwide Children’s Hospital has developed a new tool called VarRNA that analyzes RNA sequencing data to uncover important cancer-related genetic variants.

RNA sequencing doesn’t just show what genes are present, it reveals how those genes are being used. That’s important because some mutations can appear more strongly, or not at all, when cells actually make RNA from DNA. VarRNA uses machine learning to sort through these RNA changes and figure out which ones are inherited, which ones are specific to the tumor, and which ones might be errors. The tool was trained and tested on pediatric cancer samples and outperformed older methods of analyzing RNA data.

Overview of all steps performed by VarRNA using RNA-Seq data as input

The output results are an annotated variant table including classifier results for each sample. Files called out in white boxes are kept in the final output.

What makes VarRNA especially exciting is its ability to find mutations that are missed by traditional DNA testing, and to highlight mutations in cancer-driving genes where the RNA shows far more activity than expected. This could help doctors better understand how a cancer behaves and respond to treatments. With tools like VarRNA, RNA sequencing is becoming a key method not only for detecting hidden genetic variants but also for understanding the unique biology of each tumor.

Availability – The models developed and the code used to process RNA-Seq data presented in this manuscript are open-source and available for download under the BSD 3-Clause license at https://github.com/nch-igm/VarRNA.