Network-Based Stratification helps Identify Cancer Subtypes: New Treatment

A recent study looks at cancerous subtypes and how genetics play a role in finding new medications or treatments could potentially help relieve the health issue. 

Researchers from the University of California, San Diego, looked at a new approach called network-based stratification (NBS), which works to identify cancer subtypes via singular mutations of individual patients, but also by how those mutations affect shared genetic network systems, according to background information from the study.

"Subtyping is the most basic step toward the goal of personalized medicine," said principal investigator Trey Ideker, PhD, division chief of genetics in the UC San Diego School of Medicine and a professor in the departments of Medicine and Bioengineering at UC San Diego, via a press release. "Based on patient data, patients are placed into subtypes with associated treatments. For example, one subtype of cancer is known to respond well to drug A, but not drug B. Without subtyping, every patient looks the same by definition, and you have no idea how to treat them differently."

Recent advances have made it easier as well as less expensive to provide sequencing for individual genomes, including the treatment of cancer, which is fundamentally a disease of various genes.

However, Ideker notes that genes are "wildly heterogeneous," and the combination is often influenced by other factors, including mutations that can cause cancer and greatly affect the outcomes of clinical treatments.

"When you look at patients' data at the level of genes, everybody looks different," said Ideker, via the release. "But when you look at impacted biological networks and systems, groupings do appear. No genes are mutated in exactly the same place, but the mutations do appear in the same genetic pathways."

Study authors looked at somatic mutations that are present in tumors but not health tissues from the lung, uterine and ovarian cancer tissues of several patients compiled by The Cancer Genome Atlas.

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More information regarding the study can be found via the online edition of Nature Methods.