Gene Expression Profile Helps Predict Chemotherapy Response In Ovarian Cancer Patients

Source: Beth Israel Deaconess Medical Center
Date: 2005-11-07

Gene Expression Profile Helps Predict Chemotherapy Response In Ovarian
Cancer Patients

A newly identified gene expression profile could help predict how patients
with advanced ovarian cancer will respond to chemotherapy treatment.
Described in a study in the November 1, 2005 issue of The Journal of
Clinical Oncology (JCO), the new findings further establish an important
role for microarray gene profiling as a predictor of clinical outcome in
ovarian cancer, and could eventually provide clinicians with insights into
the mechanisms of drug resistance.

"In many patients with advanced ovarian cancer, post-operative treatment
with first-line chemotherapy will result in an excellent clinical
response," says senior author Stephen A. Cannistra, MD, director of
gynecologic oncology at Beth Israel Deaconess Medical Center (BIDMC) and
professor of medicine at Harvard Medical School.

"However," he adds, "due to the lingering presence of
chemotherapy-resistant cancer cells, most patients will unfortunately
experience a relapse. The goal of our current research is to help
determine which patients will relapse and which will not, and to better
understand the reasons for this."

Cannistra's group has been working to develop a genetic profile of ovarian
cancer that will enable clinicians to more accurately determine a
patient's prognosis. As a first step in this process, he and his
colleagues last year identified a gene expression profile known as the
Ovarian Cancer Prognostic Profile (OCPP), which is predictive of survival
in patients with advanced ovarian cancer. (These study results appear in
the December 2004 issue of the JCO.)

Their work makes use of a DNA technology known as microarray analysis, in
which genes expressed by cancer cells are labeled and applied to a glass
slide containing embedded sequences of thousands of known human genes. The
genes that are present in the tumor cell bind to their counterpart
sequences on the slide and can then be identified through computer
analysis.

In this new study, the authors conducted microarray testing on samples
from 60 ovarian cancer patients treated at BIDMC and Memorial
Sloan-Kettering Cancer Center to determine if tumor tissue obtained at a
patient's initial diagnosis expressed a gene profile predictive of
findings at second-look surgery. (Second-look surgery is currently the
most sensitive investigational approach for detecting residual disease in
patients with advanced ovarian cancer who have achieved a complete
clinical remission following chemotherapy, explains Cannistra.)

The expression of 93 genes, collectively referred to as the Chemotherapy
Response Profile (CRP), was found to predict which patients would
experience a complete response to chemotherapy, as defined by the absence
of disease at the time of second-look surgery. The CRP also confirmed the
importance of genes such as BAX in this process, which regulate the cell's
response to chemotherapy agents such as paclitaxel.

The authors then went on to compare the results of the CRP and the OCPP.
"We found that together these two gene profiles [CRP and OCPP] are a more
powerful predictor of a patient's prognosis than either profile
separately," says Cannistra. "This represents the first time that two
profiles have been combined to yield such a powerful result in this
disease."

One of the most difficult types of cancer to treat, advanced ovarian
cancer accounts for approximately 26,000 new cases and 16,000 deaths in
the U.S. each year.

"Being able to identify the expression pattern of these genes from the
original tumor sample [i.e. whether genes were 'turned on' or 'turned
off'] provides us with valuable information about a patient's prognosis as
this type of information cannot always be obtained from standard clinical
features, such as tumor grade or residual disease status," notes
Cannistra. "And with the identification of each new gene expression
profile, we come one step closer to eventually being able to develop
treatments tailored to individual ovarian cancer patients."

Coauthors of the study include BIDMC investigators Dimitrios Spentzos, MD,
Douglas Levine, MD, Towia A. Libermann, PhD, Shakirahimed Kolia and Hasan
Out and Jeff Boyd, PhD, of Memorial Sloan-Kettering Cancer Center in New
York.



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