New research offers a genetic explanation for why some patients' lung tumors disappear almost completely when treated with the drug erlotinib, while other patients' responses are far less dramatic.
For some patients with lung cancer, the drug erlotinib is a near miracle. Within weeks, it can shrink tumors with a particular mutation to near vanishing. But the drug does not work equally well in all patients. For others with the same mutation, the results can be disappointing. Tumors may only shrink by 30 percent. Good, but not good enough.
New research from Howard Hughes Medical Institute (HHMI) investigator Charles Sawyers at Memorial Sloan Kettering Cancer Center offers a genetic explanation for why people with lung cancer respond differently to erlotinib. The work, published in the March 24, 2011, issue of the journal Nature, reveals a strategy that might be used to improve the effectiveness of lung cancer drugs.
Patients with high IκB have the best outcome in those studies. They survived. They had no progression of disease.
Charles L. Sawyersstudy pinpoin
The cancer drug erlotinib (marketed as Tarceva) works by blocking the activity of a protein called epidermal growth factor receptor (EGFR), which is often mutated and overactive in cancer cells. Tarceva was approved by the Food and Drug Administration for the treatment of lung cancer in 2004. But even among patients whose tumors are known to have the same mutated form of EGFR, the drug’s effectiveness varies. “Some patients with lung cancer had these sort of amazing responses,” Sawyers said. “But not everyone that has the mutation had the same response. Some responders saw tumors shrink by only 30 percent. Others had 99 percent shrinkage.”
Sawyers suspected genetics might help explain these dramatically different responses. So he collaborated with HHMI researcher Gregory Hannon at Cold Spring Harbor Laboratory to investigate whether certain genes might improve cells’ response to the drug. Working with cancer cells that responded only slightly to the drug, the researchers shut off, one by one, more than 2,000 genes with known cancer connections. To do this, they used inhibitory molecules called small hairpin RNAs, which can target specific genes and block their ability to produce a protein. Then they treated the cells with erlotinib and measured whether their response had changed. The challenge revealed that shutting off any of 36 genes made the cancer cells suddenly vulnerable to erlotinib.
“You always get hits,” Sawyers said. “The challenge is sorting out a pattern.” And a pattern quickly emerged. Half of the genes that made the once-resistant cells die in the presence of the cancer drug were associated in some way with Nuclear Factor Kappa B (NF-κB), a protein known for its role in cell survival.
While NF-κB wasn’t driving the cancer—the driver was the EGFR mutation—it looked very much like an accessory to the crime, Sawyers said.
“The screen showed we could inhibit NF-κB and make cells more sensitive” to the cancer drug, Sawyers said. “Then we could do the reverse, and take cells that were very sensitive, activate NF-κB, and see it flip back to a 30 percent responder.”
The researchers transplanted human tumors with the EGFR mutation into mice. Using small hairpin RNA, the researchers knocked down NF-κB expression in some tumors. Those shrank by 50 percent in the presence of erlotinib. But when NF-κB wasn’t inhibited, the tumors wouldn’t shrink at all.
At the moment, there is no NF-κB inhibitor in clinical use to test in cancer patients, Sawyers said. “That leaves you with the question, are these models effective in patients?” To find out, Sawyers worked with a group of researchers in Barcelona, Spain who ran earlier trials studying EGFR inhibitors in lung cancer.
“They did a remarkable job collecting biopsy material of every EGFR-mutant lung cancer patient who went into the trials,” Sawyers said. “It is a critical and unique dataset.” The Spanish researchers not only preserved the biopsy materials, they also knew how every patient represented in this tissue bank fared when treated with EGFR inhibitors.
Sawyers asked the Spanish group to test the samples for a number of genes in the NF-κB pathway. Among those genes was one called IκB, an inhibitor of NF-κB. Its presence, it turned out, guaranteed robust response to the cancer drug, Sawyers said.
“Patients with high IκB have the best outcome in those studies. They survived. They had no progression of disease,” he said. “Seventy percent were still progression-free at three years. At the same time point, only 10 percent of the low IκB patients were still progression free. It also affected overall survival.”
The finding suggests IκB would make an effective marker for drug response, Sawyers said. Until a drug is developed that enhances IκB expression, doctors might test a patient’s IκB levels before administering EGFR inhibitors, Sawyers said. “If they make very little IκB, their response to the drug might not be so durable and they may be better off with standard therapy.”
Sawyers added that studies at Sloan Kettering a decade ago demonstrated that the presence of IκB made no difference in the survival of patients with EGFR-mutant lung cancer who were treated with chemotherapy. That shows the inhibitor doesn’t affect the malignancy of the cancer itself, he explained, but only comes into play in the presence of EGFR inhibitors such as erlotinib.
“It’s entirely possible NF-κB could be important in maintaining survival of cancer cells driven by other kinases,” he said, noting EGFR mutations are also common in the brain cancer glioblastoma and some forms of leukemia and melanoma.
Ultimately, successful cancer treatment will be about developing drugs against multiple specific targets, Sawyers said. “Today, the way we move forward with drug combinations is very empiric—let’s try this, let’s try that. We do a giant experiment to see which one is best. That’s just hopeless I think. In the long run, you need to pursue specific targets.”