39 research outputs found

    Gene expression profile predicts outcome after anthracycline-based adjuvant chemotherapy in early breast cancer

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    International audiencePrognosis of early beast cancer is heterogeneous. Today, no histoclinical or biological factor predictive for clinical outcome after adjuvant anthracycline-based chemotherapy (CT) has been validated and introduced in routine use. Using DNA microarrays, we searched for a gene expression signature associated with metastatic relapse after adjuvant anthracycline-based CT without taxane. We profiled a multicentric series of 595 breast cancers including 498 treated with such adjuvant CT. The identification of the prognostic signature was done using a metagene-based supervised approach in a learning set of 323 patients. The signature was then tested on an independent validation set comprising 175 similarly treated patients, 128 of them from the PACS01 prospective clinical trial. We identified a 3-metagene predictor of metastatic relapse in the learning set, and confirmed its independent prognostic impact in the validation set. In multivariate analysis, the predictor outperformed the individual current prognostic factors, as well as the Nottingham Prognostic Index-based classifier, both in the learning and the validation sets, and added independent prognostic information. Among the patients treated with adjuvant anthracycline-based CT, with a median follow-up of 68 months, the 5-year metastasis-free survival was 82% in the "good-prognosis" group and 56% in the "poor-prognosis" group. Our predictor refines the prediction of metastasis-free survival after adjuvant anthracycline-based CT and might help tailoring adjuvant CT regimens

    Association of GATA3, P53, Ki67 status and vascular peritumoral invasion are strongly prognostic in luminal breast cancer

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    International audienceIntroduction: Breast cancers are traditionally divided into hormone-receptor positive and negative cases. This classification helps to guide patient management. However, a subgroup of hormone-receptor positive patients relapse irrespective of hormonal therapy. Gene expression profiling has classified breast tumours into five major subtypes with significant different outcome. The two luminal subtypes, A and B, show high expression of ESR1, GATA3 and FOXA1 genes. Prognostic biomarkers for oestrogen receptor (ER)-positive cases include progesterone receptor (PR) and androgen receptor (AR), and proteins related to proliferation or apoptotic resistance. The aim of this study was to identify the best predictors of success of hormonal therapy.Methods: By immunohistochemistry we studied 10 markers in a consecutive series of 832 cases of breast carcinoma treated at the Paoli-Calmettes Institute from 1990 to 2002 and deposited onto tissue microarrays (TMA). These markers were luminal-related markers ER, PR, AR, FOXA1 and GATA3 transcription factors, proliferation-related Ki67 and CCND1, ERBB2, anti-apoptotic BCL2 and P53. We also measured vascular peritumoural invasion (VPI), size, grade and lymph node involvement. For 143 cases, gene expression profiles were available. Adjuvant chemotherapy and hormonal therapy were given to high- and low-risk patients, respectively. The 162 events observed and taken into account were metastases.Results: Molecular expression of the 10 parameters and subtype with ER status were strongly correlated. Of the 67 luminal A cases of this series, 63 were ER-positive. Multivariate analyses showed the highly significant prognostic value of VPI (hazard ratio (HR) = 2.47), Ki67 (HR = 2.9), P53 (HR = 2.9) and GATA3 (HR = 0.5) for the 240 patients who received hormonal therapy.Conclusions: A panel of three antibodies (Ki67, P53 and GATA3) associated with VPI can significantly improve the traditional prognosticators in predicting outcome for ER-positive breast cancer patients receiving hormonal therapy

    Chimiothérapie ciblée du cancer du sein basée sur une analyse génomique de la tumeur

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    International audienceThe purpose of this review of the literature is to document how breast cancer patients perceive the use of tumor gene profiling approaches to better adapt treatments, and to identify the features of these approaches that may impact their clinical application. In general, the use of tumor genomic analysis was perceived by patients as an approach facilitating personalized medicine and received considerable support. Nevertheless, a number of confusions and worries about these practices were also identified. Improving the quality of provider/patient communications should enable patients to play a more active part in the decision-making about their treatment. This will ensure that those who agree to their tumor gene analysis have realistic expectations and sound deductions of the final result disclosure process

    Circulating Tumor Cells and Bevacizumab Pharmacokinetics during Neoadjuvant Treatment Combining Chemotherapy and Bevacizumab for Early Breast Cancer: Ancillary Analysis of the AVASTEM Trial

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    International audienceThe phase II AVASTEM trial explored the impact of chemotherapy-bevacizumab combination on breast cancer stem cells in the neoadjuvant setting. We aimed to identify biological features associated with preoperative chemotherapy efficacy and prognosis by analyses of circulating tumor cells (CTCs) and bevacizumab pharmacokinetics (PK). The main objective was to assess the prognostic (relapse-free survival and overall survival) and predictive (pathological complete response, pCR) values of CTCs (CellSearch technology) and bevacizumab PK (ELISA). Seventy-five patients were included. Out of them 50 received bevacizumab-chemotherapy and 25 received chemotherapy alone. CTC results were available for 60 patients and PK data for 29 patients in the experimental arm. The absence of CTC at inclusion was correlated to better outcome. Five-years overall survival (OS) was 91% for CTC-negative patients vs. 54% for CTC-positive cases (HR = 6.21; 95%CI (1.75–22.06), p = 0.001, log-rank test). Similar results were observed for RFS with 5 y-RFS of 78% vs. 44% (HR = 3.51; 95%CI (1.17–10.52), p = 0.017, log-rank test). However, CTC status at baseline was not predictive of pCR (p = 0.74). CTC status after one cycle was not a significant prognostic factor (HR = 1.56; 95%CI (0.19–12.67); p = 0.68 for OS and HR = 2.76; 95%CI (0.60–12.61); p = 0.17 for RFS, log-rank test). Bevacizumab serum levels could not predict pCR and survival. PK values were not associated with treatment-related toxicities. In conclusion, CTCs detection at baseline is a prognostic marker for breast cancer receiving a neoadjuvant chemotherapy-bevacizumab combination independently of tumor response

    Are there candidates for high-dose chemotherapy in ovarian carcinoma?

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    International audienceUNLABELLED: ABSTRACT: BACKGROUND: Prognosis of advanced ovarian carcinomas (AOC) remains poor with a 5-year survival of 30%. Benefit from high-dose chemotherapy (HDC) in this disease has not been demonstrated to date. METHODS: To evaluate the value of HDC as consolidation treatment after surgery and platinum/taxane-based therapy, we designed a monocentric retrospective comparative study. We used a subset approach to identify parameters associated with HDC efficacy. RESULTS: One hundred and three AOC patients treated with conventional chemotherapy alone (CCA) were compared to 60 patients receiving HDC plus hematopoietic stem cell support. After a median follow-up of 47.5 months there was no overall survival (OS) advantage for the HDC group in the whole population (p=0.29). Nevertheless, HDC was associated to a better outcome in young patients (≀50 years), both in term of progression-free survival (p=0.02, log-rank test) and OS (p=0.05, log-rank test). Median OS was 54.6 and 36 months in the HDC and CCA groups, respectively. CONCLUSIONS: Although randomized trials failed to demonstrate any benefit for HDC in AOC patients, this study suggests that young patients may derive a substantial advantage from receiving it after the standard treatment. Further prospective studies are warranted to confirm this gain and to search for the biological processes associated with this improvement
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