Gene expression changes predict future response for cervical cancer patients
Image courtesy of GE Healthcare  
BOSTON–Changes in gene expression during chemoradiation can predict the likelihood of response to therapy for women with locally advanced cervical cancer, according to research presented this week at the 50th annual meeting of the American Society for Therapeutic Radiology and Oncology (ASTRO).

The research was presented by the Radiation Therapy Oncology Group (RTOG), a clinical research component of the American College of Radiology (ACR) and a National Cancer Institute (NCI)-funded national clinical trials group.

RTOG investigators examined tissue samples from 22 patients, including 13-paired samples, obtained prior to treatment and midway through treatment. The investigators found that changes in the gene signature pattern of seven genes predicted whether the woman’s cervical cancer would respond to treatment with a COX-2 inhibitor combined with chemoradiotherapy. 

According to the results, they did not find a pre-treatment or mid-treatment marker that predicted local control on its own, but rather it was the changes in gene expression from pre- to mid-treatment that predicted future response in 100 percent of the samples. The results were validated by leave one out and two-fold cross validation.

The tissue samples were from patients entered on RTOG 0128, a phase I/II study of chemoradiation given with a COX-2 inhibitor for women with locally advanced cervical cancer.  The women enrolled received a five-week course of external radiation together with chemotherapy followed by brachytherapy which involved the insertion of two to five radioactive implants into the tumor site.  Biopsies were done prior to the start of treatment and again at the time of the first brachytherapy application, the researchers noted.

According to Joanne Weidhaas, MD, PhD, lead author of the research from the Yale University Cancer Center, the study is an important first step towards tailoring therapy to individual patients.  “If we can predict midway through treatment how well a patient will respond to their therapy we can make treatment alterations earlier with a greater probability of improving outcome,” Weidhaas said.