Can Biomarkers Help Guide Treatment For Lung Cancer?

Ruzanna Harutyunyan's picture

Today a large, national clinical trial for non-small cell lung cancer was launched to validate whether a biomarker can predict clinical benefit in the treatment of this disease. Biomarkers, which are molecules found in the body that can signal an abnormal process or disease, would identify a target, known as epidermal growth factor receptor (EGFR). This receptor can be increased in some lung cancers due to the presence of extra copies of its coding gene. These extra copies can result in activation of tumor growth, so drugs that block this activation could have a significant impact on lung cancer treatment. This study, sponsored by the National Cancer Institute (NCI), part of the National Institutes of Health, is called MARVEL (Marker Validation for Erlotinib in Lung Cancer) and will attempt to definitively establish the future value of selecting patients for treatment based on the presence or absence of EGFR activation.

Approximately 1,200 lung cancer patients will be tested for the status of this biomarker, and then will be randomly assigned to treatment based on the test results. Both EGFR-positive and EGFR-negative patients will receive either the chemotherapy drugs erlotinib (Tarceva, Genentech) or pemetrexed (Alimta, Eli Lilly) after they have received their initial, standard chemotherapy. Erlotinib specifically targets EGFR, whereas pemetrexed blocks tumor cell growth by another mechanism.

It is hypothesized that erlotinib will be superior in the patients with EGFR-positive lung cancer, whereas pemetrexed would be favored in patients with EGFR-negative lung cancer, based on knowledge from earlier, smaller studies. MARVEL will incorporate genetic studies for erlotinib and pemetrexed that will be important to further identify patients with different sensitivity and toxicity profiles to these therapies.


Lung cancer is expected to claim 161,840 lives in 2008, and 215,020 people are expected to be diagnosed with the disease this year, making it the number one cancer killer. Non-small cell lung cancer represents about 85 to 90 percent of all lung cancers.

"Because lung cancer is such a lethal disease and because it is particularly difficult to treat, especially if diagnosed in its later stages, the MARVEL trial is of major importance because it could define, based on a single test, the best therapy for this disease. The future of moving highly targeted agents from the lab to the clinic will be heavily dependent on biomarkers for patient selection," said NCI director John E. Niederhuber, M.D.

Both erlotinib and pemetrexed are approved treatments for advanced NSCLC. Among the factors that appear to influence responsiveness to erlotinib, in addition to the level of EGFR activation, are whether the resulting cancer cells are classified as adenocarcinomas (as opposed to squamous or other types of cell), female gender, Asian ethnicity, and whether the patient was ever a smoker. However, no forward-looking study has been performed to definitively address which factors are most important.

MARVEL, also known as N0723, is a phase III study that will be led by the North Central Cancer Treatment Group (NCCTG) and include many other NCI-sponsored clinical trial groups. The trial will enroll patients over a four year period and test them for EGFR status. It will randomly assign about 950 of the 1,200 tested patients to the treatment protocol (assuming that 80 percent of the tests will successfully allow classification of patients as either EGFR-positive or EGFR-negative), and, after a minimum of one to two years of follow-up, accrue data on disease-free and overall patient survival rates as well as determine if markers are good predictive and prognostic tools. It will also establish whether erlotinib provides a meaningful benefit over the patients' initial, standard chemotherapy.

This trial is the outcome of a unique and innovative collaboration, formed in 2006, called the Oncology Biomarkers Qualification Initiative (OBQI) between NCI, the U.S. Food and Drug Administration (FDA), and the Centers for Medicare and Medicaid Services. OBQI was designed to qualify biomarkers for use in clinical trials and, ultimately, to speed better agents to cancer patients.

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The epidermal growth factor receptor (EGFR) is a protein on the surface of a cell. EGFR inhibiting drugs certainly do target specific genes, but even knowing what genes the drugs target doesn't tell you the whole story. Both Iressa and Tarceva target EGFR protein-tyrosine kinases. But all the EGFR mutation or amplificaton studies can tell us is whether or not the cells are potentially susceptible to this mechanism of attack. It doesn't tell you if Iressa is better or worse than Tarceva or other drugs which may target this. There are differences. The drugs have to get inside the cells in order to target anything. So, in different tumors, either Iressa or Tarceva might get in better or worse than the other. And the drugs may also be inactivated at different rates, also contributing to sensitivity versus resistance. Many patients are treated not only with a targeted therapy but with a combination of chemotherapy drugs. Therefore, existing DNA or RNA sequences or expression of individual proteins often examine only one component of a much larger, interactive process. The oncologist might need to administer several chemotherapy drugs at varying doses because tumor cells express survival factors with a wide degree of individual cell variability. Molecular pathways inside cells have a incredible amount of "cross talk," so blocking one molecule precisely is like trying to keep one person from talking while expecting the rumor will not spread just as fast. Cancer cells have several pathways to accomplish critical survival functions, so blocking many at the same time with an anti-cancer drug is more likely to be successful than only blocking a single one. The are many pathways to altered cellular (forest) function, hence all the different ‘trees’ which correlate in different situations. Improvement can be made by measuring what happens at the end of all processes (the effects on the forest), rather than the status of the individual trees (pathways). You still need to measure the net effect of all processes, not just the individual molecular ‘targets.’ Gregory D. Pawelski