Blood Test May Pinpoint Best Patients for New Lung Cancer Treatments

NASHVILLE, June 6 -- Researchers here said they've found a way to tell which lung cancer patients will benefit from new targeted -- and expensive -- therapies.

Using techniques borrowed from physics and chemistry, David Carbone, M.D., Ph.D., of Vanderbilt-Ingram Cancer Center, and colleagues said a pattern in the blood of non-small-cell lung cancer patients predicts whether they'll respond to drugs that target the epidermal growth factor receptor (EGFR).

Their study is one of two in the June 6 issue of the Journal of the National Cancer Institute reporting on the use of mass spectrometry to classify non-small cell lung cancer.

In the other, a Japanese team led by Kiyoshi Yanagisawa, M.D., Ph.D., of Nagoya University, reported that a pattern of 25 proteins identified by mass spectrometry was associated with both relapse-free and overall survival.

Dr. Carbone and colleagues, on the other hand, said the pattern they found is more than just prognostic. It actually reveals which patients will benefit from the so-called tyrosine kinase inhibitors, erlotinib (Tarceva) and gefitinib (Iressa).

"There's a real clinical need to identify which patients will benefit from targeted therapies," Dr. Carbone said. "If our findings are confirmed, we will be able to use a simple and inexpensive blood test to select the most beneficial therapy for each patient."

Mass spectrometry is used to find the composition of a physical sample by vaporizing and ionizing it, in order to generate a spectrum representing the masses of its components.

Dr. Carbone and colleagues used the technique to analyze blood samples of 139 patients who had been treated with gefitinib and found a spectrum that allowed them to classify patients into those who did well on the drugs and those who did poorly.

Next, the researchers tested their spectrum on two validation cohorts, one from an Italian study including patients treated with gefitinib and the other from a U.S. study including patients treated with erlotinib.

In the first cohort, they found that patients with the "good" spectrum had a significantly longer median time to progression than the patients in the "poor" group-84 days versus 61, respectively. The hazard ratio for progression was 0.56 (with a 95% confidence interval from 0.28 to 0.89, and P=0.02).

There was also a significant difference (P=0.0054) in median overall survival, at 207 days versus 92. The hazard ratio of death was 0.50 with a 95% confidence interval from 0.24 to 0.78.

Results were similar in the U.S. cohort, the researchers reported. For instance, patients classified in the "good" group had a median survival of 306 days versus 107 for those in the "poor" group. The hazard ratio was 0.41, with a 95% confidence interval from 0.24 to 0.70, which was significant at P <0.001.

To rule out the possibility that the test was simply prognostic, Dr. Carbone and colleagues tested it against three cohorts of patients who were not treated with either tyrosine kinase inhibitor, and found no differences in either progression-free or overall survival.

The researchers are currently planning a prospective study of the test.

"This is a convincing set of data from multiple institutions and multiple cohorts of patients, and we're excited to test the prediction algorithm in a prospective way," Dr. Carbone said.

"If it holds up, we will be able to separate patients into two groups-one that would benefit more from chemotherapy and the other from targeted (tyrosine kinase inhibitors)-and treat them accordingly."

But in an accompanying editorial, commentators cautioned that previous attempts to use mass spectrometry were difficult to reproduce and led to a "general skepticism" about the procedure.

It will need "additional validation" to show that the results are actually useful in the clinic, according to Ming-Sound Tsao, M.D., and colleagues from the University Health Network and the Ontario Cancer Institute in Toronto.

Despite that caution, they said the study is "an important milestone" in the development of blood tests that can predict outcomes in non-small-cell lung cancer.

Dr. Yanagisawa and colleagues conducted a similar study, but without the focus on tyrosine kinase inhibitors. They used mass spectrometry to analyze 116 cancer tissue samples and 20 specimens of normal lung tissue in a so-called training set.

From that, they derived a "signature" of 25 proteins that was associated with better survival, which they then tested in a blinded fashion against a validation set consisting of 58 cancer and seven normal samples.

The signature was significantly associated with both overall survival and progression-free survival. Specifically:

• The hazard ratio of death for patients in the high-risk group compared with those in the low-risk group was 61.1, with a 95% confidence interval from 8.9 to 419.2, which was significant at P <0.001.
• The hazard ratio of relapse was 11.7, with a 95% confidence interval from 3.1 to 44.8, which was also significant at P <0.001.

The Japanese study was supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan. The authors said they had no financial conflicts.