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Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer.

ABSTRACT: Cancer stem cells (CSCs) are subsets of cells with the ability of self-renewal and differentiation in neoplasm, which are considered to be related to tumor heterogeneity. It has been reported that CSCs act on tumorigenesis and tumor biology of triple-negative breast cancer (TNBC). However, the key genes that cause TNBC showing stem cell characteristics are still unclear. We combined the RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and mRNA expression-based stemness index (mRNAsi) to further analyze mRNAsi with regard to molecular subtypes, tumor depth, and pathological staging characteristics of breast cancer (BC). Secondly, we extract the differential gene expression of tumor vs. normal group and TNBC vs. other subtypes of BC group, respectively, and intersect them to achieve precise results. We used a weighted gene coexpression network analysis (WGCNA) to screen significant gene modules and the functions of selected genes including BIRC5, CDC25A, KIF18B, KIF2C, ORC1, RAD54L, and TPX2 were carried out through gene ontology (GO) functional annotation. The Oncomine, bc-GenExMiner v4.4, GeneMANIA, Kaplan-Meier Plotter (KM-plotter), and GEPIA were used to verify the expression level and functions of key genes. In this study, we found that TNBC had the highest stem cell characteristics in BC compared with other subtypes. The lower the mRNAsi score, the better the overall survival and treatment outcome. Seven key genes of TNBC were screened and functional annotation indicated that there were strong correlations between them, relating to nuclear division, organelle fission, mitotic nuclear division, and other events that determine cell fate. Among these genes, we found four genes that were highly associated with adverse survival events. Seven key genes identified in this study were found to be closely related to the maintenance of TNBC stemness, and the overexpression of four showed earlier recurrence. The overall survival (OS) curves of all key genes between differential expression level crossed at around nine-year follow-up, which was consistent with the trend of the OS curve related to mRNAsi. These findings may provide new ideas for screening therapeutic targets in order to depress TNBC stemness.

SUBMITTER: Suo HD

PROVIDER: S-EPMC7374213 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer.

Suo Huan-Dan HD Tao Zuo Z Zhang Lei L Jin Zi-Ning ZN Li Xiao-Ying XY Ma Wei W Wang Zhen Z Qiu Yue Y Jin Feng F Chen Bo B Cao Yu Y

BioMed research international 20200711

Cancer stem cells (CSCs) are subsets of cells with the ability of self-renewal and differentiation in neoplasm, which are considered to be related to tumor heterogeneity. It has been reported that CSCs act on tumorigenesis and tumor biology of triple-negative breast cancer (TNBC). However, the key genes that cause TNBC showing stem cell characteristics are still unclear. We combined the RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and mRNA expression-based stemness ...[more]

PMID: 32766313

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Project description:BackgroundTriple-negative breast cancer is a subtype 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 recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible.Methodology/principal findingsClinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis 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-? signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer.Conclusions/significanceGene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.

Project description:PurposeTriple negative breast cancers (TNBCs) are enriched in cells bearing stem-like features, i.e., cancer stem cells (CSCs), which underlie cancer progression. Thus, targeting stemness may be an interesting treatment approach. The epigenetic machinery is crucial for maintaining the stemness phenotype. Bromodomain and extra-terminal domain (BET) epigenetic reader family members are emerging as novel targets for cancer therapy, and have already shown preclinical effects in breast cancer. Here, we aimed to evaluate the effect of the BET inhibitor JQ1 on stemness in TNBC.MethodsTranscriptomic, functional annotation and qRT-PCR studies were performed on JQ1-exposed TNBC cells in culture. The results obtained were confirmed in spheroids and spheroid-derived tumours. In addition, limiting dilution, secondary and tertiary tumour sphere formation, matrigel invasion, immunofluorescence and flow cytometry assays were performed to evaluate the effect of JQ1 on CSC features. For clinical outcome analyses, the online tool Kaplan-Meier Plotter and an integrated response database were used.ResultsWe found that JQ1 modified the expression of stemness-related genes in two TNBC-derived cell lines, MDA-MB-231 and BT549. Among these changes, the CD44 Antigen/CD24 Antigen (CD44/CD24) ratio and Aldehyde Dehydrogenase 1 Family Member A1 (ALDH1A1) expression level, i.e., both classical stemness markers, were found to be decreased by JQ1. Using a validated spheroid model to mimic the intrinsic characteristics of CSCs, we found that JQ1 decreased surface CD44 expression, inhibited self-renewal and invasion, and induced cell cycle arrest in G0/G1, thereby altering the stemness phenotype. We also found associations between four of the identified stemness genes, Gap Junction Protein Alpha 1 (GJA1), CD24, Epithelial Adhesion Molecule (EPCAM) and SRY-related HMG-box gene 9 (SOX9), and a worse TNBC patient outcome. The expression of another two of the stemness-related genes was found to be decreased by JQ1, i.e., ATP Binding Cassette Subfamily G Member 2 (ABCG2) and RUNX2, and predicted a low response to chemotherapy in TNBC patients, which supports a role for RUNX2 as a potential predictive marker for chemotherapy response in TNBC.ConclusionsWe identified a stemness-related gene panel associated with JQ1 and describe how this inhibitor modifies the stemness landscape in TNBC. Therefore, we propose a novel role for JQ1 as a stemness-targeting drug. Loss of the stem cell phenotype via JQ1 treatment could lead to less aggressive and more chemo-sensitive tumours, reflecting a better patient prognosis. Thus, the identified gene panel may be of interest for the clinical management of patients with aggressive TNBC.

Dataset Information

Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer.

Publications

Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer.

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