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Microarray Provides Three Genomic Guides to Breast Cancer Treatment Decisions

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Three genomic tests separately predict the likelihood that a patient's breast cancer will reoccur after surgery without additional treatment, and the cancer's vulnerability to chemotherapy or hormone therapy, researchers at The University of Texas M. D. Anderson Cancer Center report at the first American Society of Clinical Oncology ASCO Breast Cancer Symposium Sept. 7-8 in San Francisco.

Each predictor - of prognosis, of sensitivity to chemotherapy and sensitivity to hormone therapy - is independent of the others, providing unique information to physicians and patients considering treatment options, says W. Fraser Symmans, M.D., professor in M. D. Anderson's Department of Pathology.

"Existing genomic tests for breast cancer provide information about future risk in general, but not the likely benefit of each treatment option separate from a patient's overall prognosis if no treatment followed surgery. It is important to independently assess these three variables," Symmans says.

Symmans and Lajos Pusztai, M.D., Ph.D., associate professor in M. D. Anderson's Department of Breast Medical Oncology will present two research updates on the genomic predictors, which can be reported from a single microarray analysis of a needle biopsy of a patient's breast cancer.

Symmans will present results from two studies involving 960 patients validating a 200-gene index that predicts a patient's response to hormone-suppressing therapy. About 70 percent of breast cancers express the estrogen receptor (ER), indicating that their growth is fueled to some extent by the female hormone estrogen.

Anti-estrogen therapies such as tamoxifen only benefit about half of these patients. The challenge is to predict exactly who will be helped and who should seek additional treatment.

In the two studies the Sensitivity to Endocrine Therapy (SET) Index score predicted distant relapse free survival among 453 patients who received tamoxifen for five years. The index did not predict prognosis among 507 patients who did not receive hormone therapy.

"We believe this is the first genomic test to predict sensitivity to hormone therapy independent of a patient's prognosis if no post-surgical treatment is received," Symmans says.

"A patient with ER-positive breast cancer probably still would choose to receive hormonal therapy, but better understanding of their cancer's sensitivity to endocrine therapy would help patients and their doctors decide on a treatment strategy," Symmans notes.

Pusztai will present a poster showing what the three predictors reported in two groups of breast cancer patients. "These three predictors were developed and validated separately, now we've put them together for the intended purpose - to provide all the necessary information for physicians and patients to decide on the best therapy or combination of therapies for breast cancer from a single assay," Pusztai says.

The 3 clinical outcome predictors are:

• A 76-gene prognostic test that indicates whether a patient is at high or low risk of the cancer recurring after surgery developed by investigators at Erasmus University (Rotterdam, Netherlands) and Veridex LLC.

• A 30-gene predictor of the cancer's sensitivity to chemotherapy developed by M. D. Anderson investigators.

• The 200-gene index (SET) of sensitivity to hormone (endocrine) therapy developed by M. D. Anderson in collaboration with Nuvera Biosciences Inc.

The ASCO poster describes gene expression profiles analyzed from 198 patients with stage 1 or stage 2 breast cancer that had not spread to the lymph nodes and who had not been given chemotherapy or endocrine therapy after surgery.

Among the 198 patients, 55 were predicted to be at relatively low risk that the cancer would return. Of those low-risk patients, 21 were predicted to have cancer vulnerable to chemotherapy and 16 were predicted to have tumors susceptible to endocrine therapy. Two had cancers sensitive to both therapies.

Of the 143 patients predicted to have a high risk of recurrence, the analysis predicted 109 had cancer unlikely to respond to endocrine therapy, 64 were predicted to be insensitive to chemotherapy, and 38 were predicted to be unlikely to respond to both therapies.

Ultimately, Pusztai says, the predictors will help guide the decision whether to follow surgery with chemotherapy, endocrine therapy, both, or neither. A planned prospective clinical trial at M. D. Anderson will use these predictors to select treatment options for new patients.

"Let's say a new patient has a needle biopsy performed, and the microarray analysis of the tumor's gene expression predicts she is at low risk of recurrence and also has cancer that is insensitive to both chemo- and endocrine therapies; in this cases the best option is relatively clear; surgery alone," Pusztai explains.

"However, it is important to know the sensitivity of the cancer to chemo- or endocrine therapies independent of the risk of recurrence alone. For example, a person even with low risk for cancer recurrence might elect to receive further therapy if her cancer is known to be highly susceptible to treatment."

Similarly, a patient with highly endocrine-sensitive cancer that is resistant to chemotherapy could avoid potentially toxic chemotherapy. Even individuals who are at high risk of recurrence and show genomic signs of low sensitivity to chemo and endocrine therapies could benefit from this knowledge; they might choose to participate in clinical trials with novel drugs.

The researchers' poster also covers genomic analysis of another 40 patients who received paclitaxel/FAC chemotherapy before surgery. Of those, 14 were predicted at low risk or recurrence (were they treated with surgery alone), four of whom (28 percent) had a complete pathologic response - no sign of cancer - supporting the investigators' claim that some low-risk individuals are highly responsive to chemotherapy.

The remaining 26 were predicted to be at high risk of recurrence, four of whom had a complete pathologic response (15 percent). Eight of the high-risk patients had cancer that was predicted to be vulnerable to endocrine therapy.