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Non-Small-Cell Lung Cancer (NSCLC)

Researchers Link Genetic Mutations to Improved Outcomes in Lung Cancer Patients

Posted on September 30, 2019
Post Views: 888

Non-Small-Cell Lung Cancer (NSCLC)Researchers have presented new findings related to lung cancer at the European Society for Medical Oncology (ESMO) conference in Barcelona, Spain. These new findings by Yale Cancer Center scientists have found that higher levels of genetic mutations in a tumor are linked to improved clinical outcomes to treat non-small cell lung cancer. According to this new study, oncologists will soon be able to match the use of pembrolizumab to lung cancer patients.

The lead study author, Roy S. Herbst, M.D., Ph.D., Chief of Medical Oncology at Smilow Cancer Hospital and Associate Cancer Center Director for Translational Research at Yale Cancer Center said, “As is the case for all such immunotherapeutic drugs, pembrolizumab does not help a subset of patients.” “Because of that, the oncology community has searched for a test than can tailor therapy for use of these agents to treat lung and other cancers,” he added.

They worked to analyze two different clinical trials that tested use of pembrolizumab as single therapy in patients with advanced NSCLC. Keynote – 010 tested the drug in patients who had been previously tested and Keynote – 042 enrolled naïve patients. For each study, the researchers have found that improvements in overall survival, progression-free survival and overall response rate were associated with lung cancer patients with high tTMB. They determined tissue tumor burden (tTMB) in 24% of patients with Keynote -010 and in 62% patients in Keynote – 042. The patients were classified as having PD-L1+ lung cancer. This refers to PD-1 pathway that cancer uses to hide from killer immune cells. By switching on this pathway, it works to stop such immune cells from attacking cancer cells. This, in turns, helps pembrolizumab to block this pathway.

The team also cautions that the results are exploratory analysis and are limited to observational subsets of enrolled patients.

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