Dataset Information

Validation cohort for genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer

ABSTRACT: PURPOSE: To develop a predictive test for response and survival following neoadjuvant taxane-anthracycline chemotherapy for HER2-negative invasive breast cancer. METHODS: We developed a microarray-based gene expression test from pre-treatment tumor biopsies (310 patients) to predict favorable outcome based on estrogen receptor (ER) status,pathologic response to chemotherapy, 3-year disease outcomes, and sensitivity to endocrine therapy. Tumors were classified as treatment-sensitive if predicted to have pathologic response (and not resistance) to chemotherapy, or sensitive to endocrine therapy. We tested predictive accuracy, with 95% confidence interval (CI), for pathologic response (PPV, positive predictive value), distant relapse-free survival (DRFS), and absolute risk reduction at median follow-up in 198 other patients. Independence from clinical-pathologic factors was assessed in a multivariate Cox regression analysis based on the likelihood ratio test. Other evaluable, published response predictors (genomic grade index (GGI), intrinsic subtype (PAM50), pCR predictor (DLDA30)) were compared. Neoadjuvant validation cohort of 198 HER2-negative breast cancer cases treated with taxane-anthracycline chemotherapy pre-operatively and endocrine therapy if ER-positive. Response was assessed at the end of neoadjuvant treatment and distant-relapse-free survival was followed for at least 3 years post-surgery.

OTHER RELATED OMICS DATASETS IN: PRJNA142759PRJNA142731PRJNA134729

ORGANISM(S): Homo sapiens

SUBMITTER: Tatiana Vidaurre Frankie Holmes W F Symmans Miguel Martin Christos Hatzis Eduardo Souchon

PROVIDER: E-GEOD-25065 | ArrayExpress | 2011-05-11

SECONDARY ACCESSION(S): GSE25065PRJNA142731

REPOSITORIES: GEO, ArrayExpress

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A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer.

Hatzis Christos C Pusztai Lajos L Valero Vicente V Booser Daniel J DJ Esserman Laura L Lluch Ana A Vidaurre Tatiana T Holmes Frankie F Souchon Eduardo E Wang Hongkun H Martin Miguel M Cotrina José J Gomez Henry H Hubbard Rebekah R Chacón J Ignacio JI Ferrer-Lozano Jaime J Dyer Richard R Buxton Meredith M Gong Yun Y Wu Yun Y Ibrahim Nuhad N Andreopoulou Eleni E Ueno Naoto T NT Hunt Kelly K Yang Wei W Nazario Arlene A DeMichele Angela A O'Shaughnessy Joyce J Hortobagyi Gabriel N GN Symmans W Fraser WF

JAMA 20110501 18

<h4>Context</h4>Prediction of high probability of survival from standard cancer treatments is fundamental for individualized cancer treatment strategies.<h4>Objective</h4>To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer.<h4>Design, setting, and patients</h4>Prospective multicenter study conducted from June 2000 to March 2010 at the M. D. Anderson Cancer Center to develop and test genomic predictors for neoadjuvant chemotherapy. Patients ...[more]

PMID: 21558518

Similar Datasets

Project description:CONTEXT:Prediction of high probability of survival from standard cancer treatments is fundamental for individualized cancer treatment strategies. OBJECTIVE:To develop a predictor of response and survival from chemotherapy for newly diagnosed invasive breast cancer. DESIGN, SETTING, AND PATIENTS:Prospective multicenter study conducted from June 2000 to March 2010 at the M. D. Anderson Cancer Center to develop and test genomic predictors for neoadjuvant chemotherapy. Patients were those with newly diagnosed ERBB2 (HER2 or HER2/neu)-negative breast cancer treated with chemotherapy containing sequential taxane and anthracycline-based regimens (then endocrine therapy if estrogen receptor [ER]-positive). Different predictive signatures for resistance and response to preoperative (neoadjuvant) chemotherapy (stratified according to ER status) were developed from gene expression microarrays of newly diagnosed breast cancer (310 patients). Breast cancer treatment sensitivity was then predicted using the combination of signatures for (1) sensitivity to endocrine therapy, (2) chemoresistance, and (3) chemosensitivity, with independent validation (198 patients) and comparison with other reported genomic predictors of chemotherapy response. MAIN OUTCOME MEASURES:Distant relapse-free survival (DRFS) if predicted treatment sensitive and absolute risk reduction ([ARR], difference in DRFS between 2 predicted groups) at median follow-up (3 years). RESULTS:Patients in the independent validation cohort (99% clinical stage II-III) who were predicted to be treatment sensitive (28%) had 56% (95% CI, 31%-78%) probability of excellent pathologic response and DRFS of 92% (95% CI, 85%-100%), with an ARR of 18% (95% CI, 6%-28%). Survival was predicted in ER-positive (30% predicted sensitive; DRFS, 97% [95% CI, 91%-100%]; ARR, 11% [95% CI, 0.1%-21%]) and ER-negative (26% predicted sensitive; DRFS, 83% [95% CI, 68%-100%]; ARR, 26% [95% CI, 4%-48%]) subsets and was significant in multivariate analysis. Other genomic predictors showed paradoxically worse survival for patients predicted to be responsive to chemotherapy. CONCLUSION:A genomic predictor combining ER status, predicted chemoresistance, predicted chemosensitivity, and predicted endocrine sensitivity identified patients with high probability of survival following taxane and anthracycline chemotherapy.

Project description:Background:Germline genetic polymorphisms in certain genes are associated with response to anthracycline- and taxane-based neoadjuvant chemotherapy in breast cancer (BC). Recent evidence has indicated that microRNA (miRNA) let-7 expression is associated with response to chemotherapeutics. This study aims to evaluate the potential role of let-7 miRNA-related single nucleotide polymorphisms (mirSNPs) in the prediction of pathologic complete response to taxane- and platinum-based neoadjuvant chemotherapy in locally advanced breast cancer (LABC). Methods:We genotyped the SNPs that reside in and around miRNA let-7 binding sites of two target genes: hypoxia-inducible factor 1 subunit alpha inhibitor (HIF1AN) and claudin 12 (CLDN12). The distribution frequencies of the SNPs were genotyped in LABC patients who received taxane- and platinum-based neoadjuvant chemotherapy. Associations among tumour-relevant biomarkers, genotype and pathological complete response (pCR) were evaluated using Student's t-test for continuous variables and the chi-square or Fisher's exact tests for non-categorical variables. The modified odds ratios (ORs) with their 95% confidence intervals (CIs) were calculated by a multivariate logistic regression analysis to explore the association of genotype with pCR. Results:For rs11292, which is located in the 3'-untranslated region (UTR) of HIF1AN, significant differences were detected in codominant, dominant and overdominant models between the patients who achieved pCR and those who did not (non-pCR) (P<0.05) in a multivariate analysis. For rs1017105, which is located in the 3'-UTR of CLDN12, significant differences were observed in the recessive model between the pCR and non-pCR patients with luminal-type BC. Conclusions:Let-7-related mirSNPs could predict pathologic complete response to taxane- and platinum-based neoadjuvant chemotherapy in LABC, which suggests the potential role of variants of miRNA let-7-related gene networks as predictive markers in a clinical setting.

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