University of California San Francisco
Helen Diller Family Comprehensive Cancer Center

New Lung Cancer Test Predicts Survival

By Jason Bardi | January 26, 2012

In the two largest clinical studies ever conducted on the molecular genetics of lung cancer, an international team led by scientists at the University of California, San Francisco (UCSF) has demonstrated that an available molecular test can predict the likelihood of death from early-stage lung cancer more accurately than conventional methods. The work may eventually help improve the odds of survival for hundreds of thousands of patients each year.

Reported this week in The Lancet, the two studies demonstrated how the test, which measures the activity of fourteen genes in cancerous tissue, improves the accuracy of prognosis. This in turn could guide treatments for patients with the most common form of the disease, non-squamous non-small cell lung cancer.
The research exemplifies UCSF’s efforts to advance patient care toward precision medicine, in which an individual’s genetic makeup or specific molecular markers of their disease help to drive treatment decisions.

The two independent clinical trials included one blinded study involving the analysis of tissue samples from 433 people with early-stage lung cancer in northern California and another study involving 1,006 people with early-stage lung cancer in China. In both trials, the team showed that the test could accurately predict whether the odds of death within five years of surgery to remove a lung cancer were low, intermediate, or high.

“It’s quite exciting,” said David Jablons, MD, the Ada Distinguished Professor in Thoracic Oncology and leader of the Thoracic Oncology Program at the Helen Diller Family Comprehensive Cancer Center at UCSF. “This has the potential to help hundreds of thousands of people every year survive longer.” Jablons co-led the study with Michael Mann, MD, a UCSF Associate Professor of Cardiothoracic Surgery.

Today, doctors assess early-stage lung cancers by their size, location and microscopic appearance. This information, known as staging, is then used to guide the use of additional treatment following surgery. If doctors could more precisely gauge prognosis, more people who might benefit from additional therapy could receive it immediately after surgery, before any residual cancer has had a chance to grow.

Evidence from other studies suggests that chemotherapy given in early-stage lung cancer helps thwart recurrence when there is evidence of lymph node involvement. Such involvement increases the risk of other, undetectable metastasis.

The scientists plan to design a large clinical trial that would seek to confirm that using the algorithm to guide therapy helps people with lung cancer survive longer.

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