Dataset Information

Identification of Long Noncoding RNAs as Predictors of Survival in Triple-Negative Breast Cancer Based on Network Analysis.

ABSTRACT: Breast cancer is the most common cancer observed in adult females, worldwide. Due to the heterogeneity and varied molecular subtypes of breast cancer, the molecular mechanisms underlying carcinogenesis in different subtypes of breast cancer are distinct. Recently, long noncoding RNAs (lncRNAs) have been shown to be oncogenic or play important roles in cancer suppression and are used as biomarkers for diagnosis and therapy. In this study, we identified 134 lncRNAs and 6,414 coding genes were differentially expressed in triple-negative (TN), human epidermal growth factor receptor 2- (HER2-) positive, luminal A-positive, and luminal B-positive breast cancer. Of these, 37 lncRNAs were found to be dysregulated in all four subtypes of breast cancers. Subtypes of breast cancer special modules and lncRNA-mRNA interaction networks were constructed through weighted gene coexpression network analysis (WGCNA). Survival analysis of another public datasets was used to verify the identified lncRNAs exhibiting potential indicative roles in TN prognosis. Results from heat map analysis of the identified lncRNAs revealed that five blocks were significantly displayed. High expressions of lncRNAs, including LINC00911, CSMD2-AS1, LINC01192, SNHG19, DSCAM-AS1, PCAT4, ACVR28-AS1, and CNTFR-AS1, and low expressions of THAP9-AS1, MALAT1, TUG1, CAHM, FAM2011, NNT-AS1, COX10-AS1, and RPARP-AS1 were associated with low survival possibility in TN breast cancers. This study provides novel lncRNAs as potential biomarkers for the therapeutic and prognostic classification of different breast cancer subtypes.

SUBMITTER: Li XX

PROVIDER: S-EPMC7073484 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of Long Noncoding RNAs as Predictors of Survival in Triple-Negative Breast Cancer Based on Network Analysis.

Li Xiao-Xiao XX Wang Li-Juan LJ Hou Jie J Liu Hong-Yang HY Wang Rui R Wang Chao C Xie Wen-Hai WH

BioMed research international 20200303

Breast cancer is the most common cancer observed in adult females, worldwide. Due to the heterogeneity and varied molecular subtypes of breast cancer, the molecular mechanisms underlying carcinogenesis in different subtypes of breast cancer are distinct. Recently, long noncoding RNAs (lncRNAs) have been shown to be oncogenic or play important roles in cancer suppression and are used as biomarkers for diagnosis and therapy. In this study, we identified 134 lncRNAs and 6,414 coding genes were diff ...[more]

PMID: 32190687

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Project description:Triple-negative breast cancer (TNBC), an intrinsic subtype of breast cancer, is characterized by aggressive pathology and shorter overall survival. Yet there is no effective therapy for these patients. Breast cancer stem cells (BCSCs) in TNBC may account for treatment failure. It is urgent to identify new therapeutic targets for TNBC. tRNA-derived small noncoding RNAs (tDRs) represent a new class of small noncoding RNAs (sncRNA), which have been reported in some human diseases and biological processes. However, there is no detailed information about the relationship between tDRs and BCSCs. In this study, a population of CD44+ /CD24-/low cells was isolated and identified by reliable BCSC surface markers. tDR expression profiles in TNBC and non-TNBC CSCs were performed by RNA sequencing. A total of 1327 differentially expressed tDRs contained 18 upregulated and 54 downregulated in TNBC group. Furthermore, the selected tDRs were validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). tDR-000620 expression level was consistently lower in TNBC cell lines CSCs (all P < 0.05) and serum samples (t = 2.597, P = 0.013). tDR-000620 expression was significant association with age (P = 0.018), node status (P = 0.026) and local recurrence (P = 0.019) by chi-square test. Kaplan-Meier method with log-rank test for comparison of recurrence curves. The results showed that the tDR-000620 expression (P = 0.002) and node status (P = 0.001) group were statistically significant with recurrence-free survival. Furthermore, multivariate Cox regression demonstrated that lymphatic metastasis (HR, 3.616; 95% CI, 1.234-10.596; P = 0.019) and low tDR-000620 expression (HR, 0.265; 95% CI, 0.073-0.959; P = 0.043) were two independent adverse predictive factors for recurrence-free survival. Finally, we found that tDR-000620 participated in some important biological processes though GO and KEGG analysis. Taken together, our study reveals the expression profiles of tDRs in TNBC and non-TNBC CSCs. It offers helpful information to understand the tDR-000620 expression is responsible for the aggressive phenotype of BCSCs. It may provide predictive biomarkers and therapeutic targets for TNBC recurrence.

Dataset Information

Identification of Long Noncoding RNAs as Predictors of Survival in Triple-Negative Breast Cancer Based on Network Analysis.

Publications

Identification of Long Noncoding RNAs as Predictors of Survival in Triple-Negative Breast Cancer Based on Network Analysis.

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