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Gene-Expression Profiling May Help Select Best Drugs for Pancreatic Cancer

February 2013, Vol 4, No 2

San Francisco, CA—Gene-expression profiling (GEP) of circulating tumor cells (CTCs) may help to personalize chemotherapy for patients with pancreatic cancer by predicting how patients will respond to certain treatments, according to a study reported at the 2013 Gastrointestinal Cancers Symposium.

The approach described combines an assay for CTCs with a pharmaco­genomic model that examines a patient’s genetic response to chemotherapy regimens.

CTCs are shed by tumors and can be obtained easily via a blood sample. CTC sampling offers a much less invasive means of evaluating the molecular profile of a tumor than a standard biopsy. CTCs can also be used to monitor a patient’s response to treatment, as is already being done with breast cancer treatment.

“This research lays important groundwork for customizing treatments according to a patient’s genetic composition,” said Kenneth Yu, MD, of Memorial Sloan-Kettering Cancer Center, New York. “We’re seeing encouraging signs that this strategy can help us to determine which patients will benefit most from chemotherapy and to more quickly identify the development of treatment resistance, even before physical changes in the tumor appear.”

In the study, 50 patients with unresectable stage II to IV pancreatic cancer receiving 12 different drug regimens had CTCs collected before chemotherapy and upon disease progression; total RNA was extracted and gene-expression analysis was performed. A pharmacogenomics model for the 12 chemotherapy regimens was applied to the patients’ genetic profiles to predict sensitivity to chemotherapy. The genetic profiles of patients whose disease continued to respond to their treatment were compared with the genetic profiles of patients whose disease progressed.

The researchers investigated whether this pharmacogenomics model would predict treatment response and resistance, and whether the patients’ pharmacogenomics profiles would change when their cancer progressed. Indeed, differences were seen in gene-expression profiles and in outcomes among the first 20 evaluable patients: 6 patients received treatment that the model predicted would be effective, 6 received a regimen predicted to elicit an “intermediate” response, and 8 received a regimen that was predicted to be ineffective. 

“Patients who received a treatment that was predicted to be more effective actually did better,” Dr Yu reported. For the group predicted to have an effective treatment, median time to progression was 7.3 months compared with 5.3 months for the intermediate group and 3.7 months for the resistant group.

Changes in chemotherapy sensitivity patterns were evident at disease progression, reflecting the development of treatment resistance. The disruption of particular genetic pathways predicted shorter or longer treatment responses, and some pathways were disrupted at the time of progression, but not before.

Dr Yu and his team concluded that pathway analysis can play a prognostic role in pancreatic cancer and in the identification of drug resistance. “Ultimately, we hope that this strategy could be used to determine which drug cocktail would be most suitable for the patient and to monitor patients during the course of therapy, so that treatments can be modified at the earliest molecular sign of disease worsening,” Dr Yu said.

Neal J. Meropol, MD, Chief of Hematology and Oncology, University Hospitals Case Medical Center at Case Western Reserve University, Cleveland, commented at a press briefing that this study “highlights the direction that the field of oncology is going, both for research and clinical practice,” toward the molecular characterization of tumors. “We are starting to use genetic makeup to make treatment decisions regarding which drugs work best against a patient’s tumor, and which may not work at all,” Dr Meropol added.

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