AI Article Synopsis

  • The study looked at gene-expression patterns to see if they could help predict how well chemotherapy would work in women with a specific type of breast cancer.
  • Researchers compared two different chemotherapy treatments to see which was better at stopping the cancer from growing.
  • They found that certain gene signs could accurately predict whether patients would have a complete response to the treatment, meaning their tumors could disappear almost completely.

Article Abstract

Background: We have previously described gene-expression signatures that predict growth inhibitory and cytotoxic effects of common chemotherapeutic drugs in vitro. The aim of this study was to confirm the validity of these gene-expression signatures in a large series of patients with oestrogen-receptor-negative breast tumours who were treated in a phase III neoadjuvant clinical trial.

Methods: This trial compares a non-taxane regimen (fluorouracil, epirubicin, and cyclophosphamide [FEC] for six cycles) with a taxane regimen (docetaxel for three cycles followed by epirubicin plus docetaxel [TET] for three cycles) in women with oestrogen-receptor-negative breast cancer. The primary endpoint of the study is the difference in progression-free survival based on TP53 status and will be reported later. Predicting response with gene signatures was a planned secondary endpoint of the trial and is reported here. Pathological complete response, defined as complete disappearance of the tumour with no more than a few scattered tumour cells detected by the pathologist in the resection specimen, was used to assess chemosensitivity. RNA was prepared from sections of frozen biopsies taken at diagnosis and hybridised to Affymetrix X3P microarrays. In-vitro single-agent drug sensitivity signatures were combined to obtain FEC and TET regimen-specific signatures. This study is registered on the clinical trials site of the US National Cancer Institute website http://www.clinicaltrials.gov/ct/show/NCT00017095.

Findings: Of 212 patients with oestrogen-receptor-negative tumours assessed, 87 patients were excluded. 125 oestrogen-receptor-negative tumours (55 that showed pathological complete responses) were tested: 66 in the FEC group (28 that showed pathological complete responses) and 59 in the TET group (27 that showed pathological complete responses). The regimen-specific signatures significantly predicted pathological complete response in patients treated with the appropriate regimen (p<0.0001). The FEC predictor had a sensitivity of 96% (27 of 28 patients [95% CI 82-99]), specificity of 66% (25 of 38 patients [50-79]), positive predictive value (PPV) of 68% (27 of 40 patients [52-80]), and negative predictive value (NPV) of 96% (25 of 26 patients [81-99]). The TET predictor had a sensitivity of 93% (25 of 27 patients [77-98]), specificity 69% (22 of 32 patients [51-82]), PPV of 71% (25 of 35 patients [55-84]), and NPV of 92% (22 of 24 patients [74-98]). Analysis of tumour size, grade, nodal status, age, and regimen-specific signatures showed that the genomic signatures were the only independent variables predicting pathological complete response at p<0.01. Selection of patients with these signatures would increase the proportion of patients with pathological complete responses from 44% to around 70% in the patients studied here.

Interpretation: We have validated the use of regimen-specific drug sensitivity signatures in the context of a multicentre randomised trial. The high NPV of both signatures may allow early selection of patients with breast cancer who should be considered for trials with new drugs.

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http://dx.doi.org/10.1016/S1470-2045(07)70345-5DOI Listing

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