A transatlantic team of researchers has created a bioinformatic pipeline to infer the progression of cancer from genome data. When applied to colorectal cancer, the open-source pipeline deduced the role of genes such as KRAS and BRAF while also suggesting there is value in investigating less well known players including FBXW7 and AXIN2.
In a paper published in Proceedings of the National Academy of Science, the researchers outline how they developed a tool called Pipeline for Cancer Inference (PiCnIc). The bioinformatics pipeline is designed to use sequencing data to make predictions about how various mutations will affect the progression of a tumor.
“Our work focuses on ‘causality-like’ relationships among several genes and their mutations that drive the cancer progression as the tumor environment reacts to changes, such as lack of oxygen, cell mobility or immune response,” Bud Mishra, a New York University professor and co-author of the study, said in a statement. “It then uses the model to predict how a tumor’s genomes will change over time.”
The long-term goal is to gain the ability to make more accurate predictions about cancer progression timelines, such as how long it will take for the tumor to metastasize or evolve resistance to a drug. Mishra’s team at NYU is working to advance the capabilities of the pipeline by looking at the results in combination with other technologies, including cancer image analysis.
Ultimately though, the effectiveness of the pipeline is tied to the quantity and quality of data that are available for analysis. With sequencing capacity increasing and initiatives including the White House’s Cancer Moonshot prioritizing data sharing, the availability of suitable public omics databases should become less of a barrier to effectiveness of the pipeline in the years to come.
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