Computer Program 'Lights Up' Cancerous Gene Mutations

Program uses archived samples from patients with known treatment outcomes to accelerate research in predicting therapeutic responses for future patients with cancer.

A new computer program, named Lumos-Var, has been developed to light up cancer-causing genetic variants or mutations in order to determine the best course of treatment for future patients, according to a new study published in the scientific journal Frontiers in Oncology. Lumos-Var was developed by Translational Genomics Research Institute (TGen), an affiliate of City of Hope, as a tool to accurately identify cancer-causing mutations from patient tumor samples.

The program will use archived samples from patients with known treatment outcomes in order to accelerate research in predicting responses for future patients administered particular treatments.

According to lead study author Dr. Rebecca Halperin, collecting large amounts of patient genomic data linked to treatment responses and clinical outcomes is the only way to accurately answer current oncological questions.

"The approach we outline in this study should enable researchers to use archival samples more effectively. Accurately calling, or identifying, somatic variants—those DNA changes specific to a patient's cancer—are the first step in any analysis,” Halperin said.

Archived tumor samples are not often accompanied by a patient’s normal or germline genetic information, which makes it difficult to distinguish between a patient’s normal DNA variants and their mutated and cancerous DNA changes, according to the press release.

Therefore, Lumos-Var offers a unique answer by detecting cancerous DNA from a patient sample, but by also differentiating the adjacent normal DNA from the patient’s sample. This comparison is critical in assessing whether or not a cancerous sample is benign and ensuring that the tissue sample analysis is accurate.

The level of accuracy will inform the physician within precision medicine and will determine the treatment on a patient-by-patient basis.

"The sequencing of DNA from tissue adjacent to the tumor could help identify somatic, or cancer-causing, mutations when another source of normal tissue is not available," said senior study author Dr. Sara Byron.