The researchers have identified potential treatment strategies for lung cancer patients not responding to standard chemotherapies or targeted therapies

x-ray-image-568241_640

Image: The assay provides complementary information to oncologists for more accurate clinical decision making. Photo: Courtesy of toubibe from Pixabay.

Scientists from Institute for Systems Biology (ISB) in the US have developed a new method to accurately predict lung cancer patients’ response to different cancer therapies, and impact of treatments on physiological performance and survival of patients.

The researchers used single-cell analysis to measure metabolic activities in rare disseminated tumour cells taken from non-small cell lung cancer (NSCLC) patients.

In addition, researchers have also found the fundamental molecular basis for the metabolic states and identified potential treatment strategies for lung cancer patients not responding to standard chemotherapies or targeted therapies. The research results are published in Nature Communications.

ISB assistant professor Wei Wei said: “Our metabolic assay can provide unique information complementary to tumor genetics and other clinical factors for improved cancer diagnostics. For example, tumor genetics can identify whether the patients are bearing targetable driver oncogene mutations and thus segregate patients into various chemo- and targeted therapy regimens.

“Our metabolic assay can further reveal whether patients are likely — or unlikely — to benefit from the standard chemo- or targeted therapies identified by tumor genetics. This is important particularly for newly diagnosed patients who may benefit from such predictions prior to the onset of therapy.”

Research findings are now being validated with a larger lung cancer patient group

The single-cell metabolic assay developed as part of the research work is a simple, least invasive, and can be performed in any clinical lab equipped with a fluorescence imaging system.

By providing complementary information to oncologists for more accurate clinical decision making, the assay could save valuable treatment time for patients who are not responding to standard clinical management.

The researchers are currently working on validating the research findings with a larger patient cohort to make the way clear for translation into the clinical setting. Advanced stage NSCLC is the most common and lethal cancer types across the world, which has no simple and cost-effective clinical method to predict patient response prior to the beginning of therapy, or to identify potential drug resistance in patients while they are undergoing therapy.

Wei added: “The notion of precision cancer medicine has been mostly driven by tumor genomics. Except for PET imaging, functional assays are rarely used as diagnostic tools for clinical decision-making.

“Our results highlight the promise of using cellular metabolic functions to address some of the most challenging questions in cancer diagnostics, namely predicting the diverse therapy responses for patients with similar tumor genetics in order to match the right patient with the right therapy.”