Gene Signatures Help Provide Breast Cancer Patients With More 'tailored Therapy'

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Main Category: Breast Cancer
Also Included In: Cancer / Oncology;  Genetics
Article Date: 14 Nov 2007 - 7:00 PDT

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Gene signatures can help breast cancer patients receive better targeted therapy - tailored therapy, according to a report in The Lancet Oncology. In this study, approximately 44% of all patients who were given chemotherapy prior to surgery had a pathological complete response where the tumor completely disappeared.

The authors explain that gene signatures, if they had been used with those patients to decide which type of chemotherapeutic drugs to utilize, would have given a response rate of around 70%*. "This is such a big improvement that we need to do another study to make sure it is really true, but if it is confirmed, it will make a big difference to the way doctors treat breast cancer, " the researchers say.**

Overall breast cancer survival improves when the patient receives systemic chemotherapy. Novel chemotherapy regimens which contain taxanes improve survival rates even more - however, these new regimes are costly, toxic, and sometimes only benefit a reduced percentage of patients. Therefore, if one were able to lower the number of women receiving taxanes without undermining efficacy, there would be further benefit for the patient(s).

Professor Hervé Bonnefoi (Institut Bergonié, University of Bordeaux, France) and team carried out a large randomized multi-center trial using tumor samples from patients. The patients were randomly selected to receive either׃

1. Fluorouracil, epirubicin, plus cyclophosphamide in the FEC group - a non-taxane regimen
2. Docetaxel followed by epirubicin plus docetaxel in the TET group - a taxane regimen

The researchers calculated how well patients might respond to the two regimens***. They found a strong link between the regimen-predictive gene signature and pathological complete response (invasive component of primary tumor disappeared, with few scattered tumor cells identified by the pathologist in the resection specimen at most) in patients treated in the appropriate group.

The researchers said "The treatment allocation model suggests that selection of the treatment regimen with our genomic signatures has the potential to increase the pathological response rate from 44% to around 70%."

Moreover, the NPV (negative predictive value) for each regimen-predictive gene signature was more than 90%, therefore identifying patients who would probably not achieve complete disappearance of the tumor after FEC or TET treatment - these include the most commonly used breast cancer chemotherapy drugs.

The authors wrote "It would be sensible to offer these patients treatment with new drugs, by using the gene signatures to select patients for inclusion in clinical trials with new drugs or adding new drugs. By doing this, it should be possible to do much smaller trials."

"If the results are confirmed in the follow-up study, then it would be well worth using our gene signatures to select the treatment for patients with breast cancer," the scientists concluded.

*The results only relate to a subgroup of patients with tumors that are insensitive to hormonal therapy - about 30% of patients have this kind of tumor
** Every quotes is from the author directly and cannot be found in the text of the article
*** The mathematical formula used was devised by statisticians in Joe Nevins' group at Duke University in North Carolina, USA. They used a special form of statistics called Bayesian statistics

"Validation of gene signatures that predict the response of breast cancer to neoadjuvant chemotherapy: a substudy of the EORTC 10994/BIG 00-01 clinical trial"
Hervé Bonnefoi, Anil Potti, Mauro Delorenzi, Louis Mauriac, Mario Campone, Michèle Tubiana-Hulin, Thierry Petit, Philippe Rouanet, Jacek Jassem, Emmanuel Blot, Véronique Becette, Pierre Farmer, Sylvie André, Chaitanya R Acharya, Sayan Mukherjee, David Cameron, Jonas Bergh, Joseph R Nevins, Richard D Iggo
The Lancet Oncology - DOI:10.1016/S1470-2045(07)70345-5
http://oncology.thelancet.com

Written by - Christian Nordqvist
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