An assay which measures the activity of 14 genes in lung cancer tumors can accurately predict who will respond well to surgery and who will probably die within five years, researchers from the University of California, San Francisco, reported in The Lancet. 80% of lung cancer patients have NSCLC (non-small-cell lung cancer) – their long term prognosis is poor, even after surgical interventions at stages I and II of the disease (early stages), the authors wrote.

An assay is an analysis that is carried out to determine something.

Outcomes for patients with NSCLC are generally poor because the cancer has usually spread (metastasized) without being detected. Dr Michael J Mann and Professor David M Jablons and team showed that the gene test can predict who will be cured by surgery and who will not.

The test (assay) measures the activity of 14 genes within the patient’s tumor. It is carried out after surgery, and the tumor is sent to the laboratory. Gene activity patterns are analyzed, and the pathologist can rate the patient’s risk category from low, intermediate, to high. The authors explained that the assay has been extensively tested independently in two large blinded studies, soon to be published in the same journal.

The University of California, San Francisco (UCSF) scientists initially created the concept of the assay. It was then developed and licenced into its present form by molecular diagnostics company, Pinpoint Genomics, Inc. Kaiser Permanente Hospitals, Northern California validated it, and then further confirmed its validity after carrying out a trial in China (China Clinical Trials Consortium).

Trials in Northern California found that 71% of patients were deemed low-risk (of dying before five years after surgery). The Chinese trial had similar results (71%).

The researchers wrote:

“The molecular assay was the strongest predictor of 5-year mortality compared with standard criteria such as sex, age, smoking status, tumour size, and even disease stage, and outperformed National Comprehensive Cancer Network guidelines used to identify high-risk patients with stage I disease.

This assay provides prognostic differentiation of patients with early stage disease and might be helpful in the identification of the most appropriate application of treatment guidelines to improve clinical outcomes.”

The researchers are now preparing for a prospective study, which will include those identified as high risk by the gene test. They will be randomly selected into two groups – a chemotherapy or observation group. They will also see how effective new adjuvant therapy guidelines are, based on utilizing this new assay.

The authors emphasize that it will be many years before this gene test can be used in clinical settings. The prospective study will be extensive and cover several years.

They wrote:

“Current guidelines already recommend consideration of chemotherapy in stage I patients whose tumors show various characteristics that are felt to place them at high risk of mortality. The data reported in The Lancet indicate that this molecular assay outperforms all of those criteria in terms of accurately identifying the patients at highest risk.”

Dr Yang Xie and Professor John Minna, University of Texas, Southwestern Medical Center, Dallas, wrote:

“In addition to identifying patients with bad prognosis that need additional treatment it will be important to have biomarker signatures that that will be predictive of better survival when coupled with a specific type of adjuvant chemotherapy-a different type of information than biomarkers for prognosis.

Together, prognostic and predictive markers will allow ‘personalised medicine’ for each lung cancer patient- determining who needs additional therapy and what specific type of therapy to use. Of course it is possible a signature could contain both prognostic and predictive information.

Further studies will tell whether the genes in this new assay are of functional relevance and whether they also will provide information on how a lung cancer patient will respond to adjuvant therapy.”

Written by Christian Nordqvist