NEW YORK (Reuters Health) - Researchers have identified a gene expression profile that can reliably predict prognosis in patients with epithelial ovarian cancer.
The Ovarian Cancer Prognostic Profile (OCPP) uses expression of 115 genes to classify epithelial ovarian cancer patients into unfavorable and favorable categories.
Among the 68 patients whose tumor tissue was used to validate the OCPP, those with an unfavorable profile had a median 30-month survival, while those with a favorable profile had not yet reached median survival during the 49-month follow-up period, Dr. Stephen A. Cannistra of Beth Israel Deaconess Medical Center in Boston and colleagues report. Patients in the unfavorable group were 4.8 times more likely to die than those in the favorable category.
Among the genes overexpressed in the unfavorable group, the researchers note, many already have been implicated in poor prognosis in ovarian cancer and several are potential therapeutic targets.
“In the short term, I envision that this kind of test might be best used in the context of clinical trials, in order to stratify patients more accurately on the basis of risk,” Dr. Cannistra told Reuters Health.
“We are currently interested in focusing on perhaps 20 genes and developing a profile that could lend itself to simplified assay procedures, like immunohistochemistry or RT-PCR,” he continued. “If this proves to be possible, and if the test is validated on larger numbers of patients, then it may become a useful clinical tool in the future.”
The OCPP retained its predictive value within groups of patients classified by standard prognostic features, such as optimal surgical debulking, age, tumor stage and grade.
The researchers also identified a subgroup of patients with a 70% chance of survival at 5 years, suggesting the presence of a survival plateau. However, Dr. Cannistra cautioned against over-interpretation of the survival plateau, which he noted could change with extended follow-up.
“What is new is the ability to identify a group of patients who can be predicted to have a very good long-term survival, despite being diagnosed with advanced stage ovarian cancer,” he added. “Commonly used clinical prognostic factors like grade or amount of residual disease do not appear to provide this level of prognostic ability.”
Dr. Beth Karlan of Cedars Sinai Medical Center points out in an accompanying editorial that 81% of patients with an unfavorable profile had complete remission after first-line chemotherapy, and second-look laparoscopy found 55% of a subset of this group were disease-free. However, “this observation does challenge our belief that clinical or pathological complete response after first-line chemotherapy is a good in vivo biomarker for long-term survival,” Dr. Karlan writes.
The “most exciting insights” of the study come from the functional classification of genes identified within the OCPP, Dr. Karlan continues, pointing out that many, including growth factor receptors, tumor invasion genes, angiogenesis genes, and hormone receptor associated genes, could be therapeutic targets.
“This is a good example of how the microarray approach, evaluating hundreds of genes simultaneously, might provide more powerful prognostic information compared to using only a handful of clinical prognostic markers such as grade and debulking status,” Dr. Cannistra told Reuters Health. “But we are also excited about the possibility that this approach will provide important insights into the biology of ovarian cancer, specifically as it relates to the nature of drug resistance.”
Source: J Clin Oncol 2004;22:4611-4612,4648-4658. [ Google search on this article ]
MeSH Headings:Behavioral Sciences: Data Collection: Demography: Behavioral Disciplines and Activities: Environment and Public Health: Epidemiologic Methods: Genetic Techniques: Health: Health Occupations: Health Services Administration: Information Science: Medicine: Investigative Techniques: Mortality: Population Characteristics: Preventive Medicine: Public Health: Quality of Health Care: Social Sciences: Specialties, Medical: Vital Statistics: Epidemiologic Measurements: Survival Rate: Health Care Quality, Access, and Evaluation: Health Care Evaluation Mechanisms: Gene Expression Profiling: Analytical, Diagnostic and Therapeutic Techniques and Equipment: Anthropology, Education, Sociology and Social Phenomena: Biological Sciences: Health Care: Information Science: Psychiatry and PsychologyCopyright © 2002 Reuters Limited. All rights reserved. Republication or redistribution of Reuters content, including by framing or similar means, is expressly prohibited without the prior written consent of Reuters. Reuters shall not be liable for any errors or delays in the content, or for any actions taken in reliance thereon. Reuters and the Reuters sphere logo are registered trademarks and trademarks of the Reuters group of companies around the world.
