Molecular Characterization of Triple-negative Breast Cancer
Date Issued
2015
Date
2015
Author(s)
Chang, Yao-Yin
Abstract
Abstract Introduction Triple-negative breast cancer, immunohistochemically defined by lacks of expression of estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, is a type of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and its recurrence rates are high. Recent studies have shown that deregulated gene expression is heavily involved in the progression of human cancer. However, the gene expression characteristics in triple-negative breast cancer are still poorly understood. Moreover, although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome in published literatures, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis using gene expression data is not yet possible. Methods In this study, clinicopathological information and gene expression microarray data from 51 triple-negative and 106 luminal breast cancers were collected at National Taiwan University Hospital. Gene expression data of triple-negative breast cancer tissues were collected using Agilent oligonucleotide microarrays. Gene expression data along with distant metastasis follow-up information of the triple-negative breast cancer patients were analyzed in this work. In addition, microRNA (miRNA) expression data of 24 triple-negative breast cancers and 14 adjacent normal tissues were analyzed using deep sequencing technology. Expression levels of miRNA reads from each sample were normalized with the quantile-quantile scaling method. Quantitative reverse transcription PCR was performed for validation of deregulated miRNAs in triple-negative breast cancer. Potential target candidates of miRNAs were predicted using the miRanda target prediction algorithm and were further verified using luciferase reporter assays. Previously validated miRNA target genes of the deregulated miRNAs were investigated and their molecular pathways associated with cancer progression were discussed. Results and discussion Hierarchical clustering analysis of the gene expression data revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04-5.06, Cox p = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer. Deep sequencing analyses of miRNA expression revealed that a novel 25-miRNA signature was able to effectively distinguish triple-negative breast cancers from surrounding normal tissues. We documented the evidence of seven polycistronic miRNA clusters preferentially harboring deregulated miRNA genes in triple-negative breast cancer. Two of these miRNA clusters (miR-143-145 at 5q32 and miR-497-195 at 17p13.1) were markedly down-regulated in triple-negative breast cancer, while the other five miRNA clusters (miR-17-92 at 13q31.3, miR-183-182 at 7q32.2, miR-200-429 at 1p36.33, miR-301b-130b at 22q11.21, and miR-532-502 at Xp11.23) were up-regulated in triple-negative breast cancer. Noticeably, miR-130b-5p from the miR-301b-130b cluster was shown to directly target the cyclin G2 (CCNG2) tumor-suppressor gene in luciferase reporter assays. Overexpression of miR-130b-5p was shown to significantly repress CCNG2 expression and enhance cell cycle progression in triple-negative breast cancer cells. Conclusions Our work delivers a clear picture of the global messenger RNA and miRNA regulatory characteristics in triple-negative breast cancer. A novel 45-gene prognostic signature was found to be statistically predictive in distant metastasis of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant metastasis for early-stage triple-negative patients. Moreover, miRNA expression of triple-negative breast cancer was measured using deep sequencing technology. A panel of 25 differentially expressed miRNAs identified from 24 triple-negative breast cancers and 14 adjacent normal tissues was found to effectively distinguish triple-negative breast cancers from surrounding normal tissues. Real-time PCR validations of the deregulated miRNAs further supported our findings from the sequencing analyses. The miR-130b-5p-CCNG2 axis identified in this study may play a role in the malignant progression of triple-negative breast cancer.
Subjects
Triple-negative breast cancer
gene expression profiling
microarray analysis
deep sequencing analysis
miRNA expression
SDGs
Type
thesis
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