A Gene Signature for Predicting Outcome in Patients with Basal-like Breast Cancer

Hallett, Robin; Dvorkin‐Gheva, Anna; Bane, Anita; Hassell, John A.

doi:10.1038/srep00227

Cited by 83 publications

(83 citation statements)

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“…A few multi-gene signatures were reported to predict prognosis of TNBC [6], [14], [15]; however, gene profiling is not cost-effective or convenient for clinical application. miRNAs are considered to be master regulators of many important biological processes [16]–[18].…”

Section: Discussionmentioning

confidence: 99%

A Prognostic Model of Triple-Negative Breast Cancer Based on miR-27b-3p and Node Status

et al. 2014

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ObjectiveTriple-negative breast cancer (TNBC) is an aggressive but heterogeneous subtype of breast cancer. This study aimed to identify and validate a prognostic signature for TNBC patients to improve prognostic capability and to guide individualized treatment.MethodsWe retrospectively analyzed the prognostic performance of clinicopathological characteristics and miRNAs in a training set of 58 patients with invasive ductal TNBC diagnosed between 2002 and 2012. A prediction model was developed based on independent clinicopathological and miRNA covariates. The prognostic value of the model was further validated in a separate set of 41 TNBC patients diagnosed between 2007 and 2008.ResultsOnly lymph node status was marginally significantly associated with poor prognosis of TNBC (P = 0.054), whereas other clinicopathological factors, including age, tumor size, histological grade, lymphovascular invasion, P53 status, Ki-67 index, and type of surgery, were not. The expression levels of miR-27b-3p, miR-107, and miR-103a-3p were significantly elevated in the metastatic group compared with the disease-free group (P value: 0.008, 0.005, and 0.050, respectively). The Cox proportional hazards regression analysis revealed that lymph node status and miR-27b-3p were independent predictors of poor prognosis (P value: 0.012 and 0.027, respectively). A logistic regression model was developed based on these two independent covariates, and the prognostic value of the model was subsequently confirmed in a separate validation set. The two different risk groups, which were stratified according to the model, showed significant differences in the rates of distant metastasis and breast cancer-related death not only in the training set (P value: 0.001 and 0.040, respectively) but also in the validation set (P value: 0.013 and 0.012, respectively).ConclusionThis model based on miRNA and node status covariates may be used to stratify TNBC patients into different prognostic subgroups for potentially individualized therapy.

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Section: Discussionmentioning

confidence: 99%

A Prognostic Model of Triple-Negative Breast Cancer Based on miR-27b-3p and Node Status

et al. 2014

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“…Even though other prognostic gene signatures have been developed from TNBC tissues (29)(30)(31)(32), our study is the first to identify a specific miRNA signature in the serum of patients with TNBC correlated with the high likelihood of tumor relapse. Furthermore, despite their molecular heterogeneity, all newly diagnosed basal-like/TNBC cases are treated with standard adjuvant combination chemotherapy, although with unsatisfactory results.…”

Section: Discussionmentioning

confidence: 99%

A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

Sahlberg

Bottai

Naume

et al. 2015

Clinical Cancer Research

191

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Purpose: Triple-negative breast cancers (TNBC) are associated with high risk of early tumor recurrence and poor outcome. Common prognostic biomarkers give very restricted predictive information of tumor recurrences in TNBC. Human serum contains stably expressed microRNAs (miRNAs), which have been discovered to predict prognosis in patients with cancer. The purpose of this study was to identify circulating biomarkers able to predict clinical outcome in TNBC.Experimental Design: We performed genome-wide serum miRNA expression and real-time PCR analyses to investigate the ability of miRNAs in predicting tumor relapse in serum samples from 60 primary TNBC. Patients were divided into training and testing cohorts.Results: By Cox regression analysis, we identified a four-miRNA signature (miR-18b, miR-103, miR-107, and miR-652) that predicted tumor relapse and overall survival. This miRNA signature was further validated in an independent cohort of 70 TNBC. A high-risk signature score was developed and significantly associated with tumor recurrence and reduced survival. Multivariate Cox regression models indicated that the risk score based on the four-miRNA signature was an independent prognostic classifier of patients with TNBC.Conclusions: This signature may serve as a minimally invasive predictor of tumor relapse and overall survival for patients with TNBC. This prediction model may ultimately lead to better treatment options for patients with TNBC.

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“…A significant function of glycoproteins is that of directing immune response 36 . This is particularly poignant since several gene expression modules associated with immune response have been used to predict TNBC patient outcome [37][38][39][40][41] . Many of the aberrant cancer promoter hypermethylation events affect genes already silenced in the tissue of origin and therefore considered to be passenger events that do not actively contribute to cancer initiation or progression 42 .…”

Section: Articlementioning

confidence: 99%

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value

et al. 2015

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Epigenetic alterations in the cancer methylome are common in breast cancer and provide novel options for tumour stratification. Here, we perform whole-genome methylation capture sequencing on small amounts of DNA isolated from formalin-fixed, paraffin-embedded tissue from triple-negative breast cancer (TNBC) and matched normal samples. We identify differentially methylated regions (DMRs) enriched with promoters associated with transcription factor binding sites and DNA hypersensitive sites. Importantly, we stratify TNBCs into three distinct methylation clusters associated with better or worse prognosis and identify 17 DMRs that show a strong association with overall survival, including DMRs located in the Wilms tumour 1 (WT1) gene, bi-directional-promoter and antisense WT1-AS. Our data reveal that coordinated hypermethylation can occur in oestrogen receptor-negative disease, and that characterizing the epigenetic framework provides a potential signature to stratify TNBCs. Together, our findings demonstrate the feasibility of profiling the cancer methylome with limited archival tissue to identify regulatory regions associated with cancer.

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A Gene Signature for Predicting Outcome in Patients with Basal-like Breast Cancer

Cited by 83 publications

References 50 publications

A Prognostic Model of Triple-Negative Breast Cancer Based on miR-27b-3p and Node Status

A Prognostic Model of Triple-Negative Breast Cancer Based on miR-27b-3p and Node Status

A Serum MicroRNA Signature Predicts Tumor Relapse and Survival in Triple-Negative Breast Cancer Patients

Methylome sequencing in triple-negative breast cancer reveals distinct methylation clusters with prognostic value

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