An integrated bioinformatics analysis to dissect kinase dependency in triple negative breast cancer.
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ABSTRACT:
SUBMITTER: Ryall KA
PROVIDER: S-EPMC4682411 | biostudies-literature | 2015
REPOSITORIES: biostudies-literature
Publications
An integrated bioinformatics analysis to dissect kinase dependency in triple negative breast cancer.
Ryall Karen A KA Kim Jihye J Klauck Peter J PJ Shin Jimin J Yoo Minjae M Ionkina Anastasia A Pitts Todd M TM Tentler John J JJ Diamond Jennifer R JR Eckhardt S Gail SG Heasley Lynn E LE Kang Jaewoo J Tan Aik Choon AC
BMC genomics 20151209
<h4>Background</h4>Triple-Negative Breast Cancer (TNBC) is an aggressive disease with a poor prognosis. Clinically, TNBC patients have limited treatment options besides chemotherapy. The goal of this study was to determine the kinase dependency in TNBC cell lines and to predict compounds that could inhibit these kinases using integrative bioinformatics analysis.<h4>Results</h4>We integrated publicly available gene expression data, high-throughput pharmacological profiling data, and quantitative ...[more]
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Project description:BackgroundTriple-negative breast cancer (TNBC) is a heterogeneous disease with a worse prognosis. However, current therapies have rarely improved the outcome of patients with TNBC. Here we sought to identify novel biomarkers or targets for TNBC.Materials and methodsPatients GSE76275 clinic traits and their corresponding mRNA profiles for 198 TNBC and 67 non-TNBC were obtained from the GEO database. Weighted gene co-expression network analysis (WGCNA) of the GSE76275 keyed out hub genes, and the differentially expressed genes (DEGs) were identified with the cut-off of adjusted P (adj. P) <0.01 and |log2 fold-change (FC)| > 1.5. The hub - DEGs overlapping genes, as key genes, were considered for further study using Kaplan-Meier plotter online analysis. Subsequently, Breast Cancer Gene-Expression Miner v4.0 and tissue microarray analysis were applied to determine the transcriptional and translational levels of every key gene. Following plasmid transfection for overexpression, the proliferation of TNBC cells was determined by CCK8 and colony formation assay. Moreover, xenograft tumor models were canvassed to investigate their effect upon in vivo tumor growth.ResultsFour genes (SIDT1, ANKRD30A, GPR160, and CA12) were found to be associated with relapse-free survival (RFS) in TNBC through WGCNA and DEGs integrated analysis. Patients with a higher level of SIDT1 had significantly better RFS compared to those with lower levels. The transcriptional and translational levels of SIDT1 were validated as downregulated in patients with triple-negative status, negative estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Furthermore, SIDT1 inhibited proliferation of breast cancer cells (MDA-MB-231 and MDA-MB-468) and xenograft studies demonstrated that SIDT1 can suppress tumor growth in vivo.ConclusionThis study suggests that SIDT1 may play a crucial role in TNBC progression and has the potential as a prognostic biomarker of TNBC.
| S-EPMC6792947 | biostudies-literature
Project description:Purpose:Triple-negative breast cancer refers to breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (Her2). This study aimed to identify the key pathways and genes and find the potential initiation and progression mechanism of triple-negative breast cancer (TNBC). Methods:We downloaded the gene expression profiles of GSE76275 from Gene Expression Omnibus (GEO) datasets. This microarray Super-Series sets are composed of gene expression data from 265 samples which included 67 non-TNBC and 198 TNBC. Next, all the differentially expressed genes (DEGs) with p<0.01 and fold change ?1.5 or ?-1.5 were identified. Result:56 upregulated and 151 downregulated genes were listed and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was performed. These significantly changed genes were mainly involved in the biological process termed prostate gland morphogenesis, inner ear morphogenesis, cell maturation, digestive tract morphogenesis, autonomic nervous system development, monovalent inorganic anion homeostasis, neural crest cell development, regulation of dendrite extension and glial cell proliferation, immune system process termed T cell differentiation, regulation of immune response, and macrophage activation. Genes are mainly involved in the KEGG pathway termed Oocyte meiosis. All DEGs underwent survival analysis using datasets from The Cancer Genome Atlas (TCGA) integrated by cBioPortal, of which amplification of SRY-related HMG-box 8 (SOX8), androgen receptor (AR), and Chromosome 9 Open Reading Frame 152 (C9orf152) were significantly negative while Nik Related Kinase (NRK) and RAS oncogene family 30 (RAB30) were positively correlated to the life expectancy (p<0.05). Conclusions:In conclusion, these pathways and genes identified could help understanding the mechanism of development of TNBC. Besides, SOX8, AR, C9orf152, NRK and RAB30, and other key genes and pathways might be promising targets for the TNBC treatment.
| S-EPMC6098886 | biostudies-literature
Project description:Triple-negative breast cancers (TNBC), negative for estrogen receptor, progesterone receptor, and ERBB2 amplification, are resistant to standard targeted therapies and exhibit a poor prognosis. Furthermore, they are highly heterogeneous with respect to genomic alterations, and common therapeutic targets are lacking though substantial evidence implicates dysregulated kinase signaling. Recently, six subtypes of TNBC were identified based on gene expression and were proposed to predict sensitivity to a variety of therapeutic agents including kinase inhibitors. To test this hypothesis, we screened a large collection of well-characterized, small molecule kinase inhibitors for growth inhibition in a panel of TNBC cell lines representing all six subtypes. Sensitivity to kinase inhibition correlated poorly with TNBC subtype. Instead, unsupervised clustering segregated TNBC cell lines according to clinically relevant features including dependence on epidermal growth factor signaling and mutation of the PTEN tumor suppressor. We further report the discovery of kinase inhibitors with selective toxicity to these groups. Overall, however, TNBC cell lines exhibited diverse sensitivity to kinase inhibition consistent with the lack of common driver mutations in this disease. Although our findings support specific kinase dependencies in subsets of TNBC, they are not associated with gene expression-based subtypes. Instead, we find that mutation status can be an effective predictor of sensitivity to inhibition of particular kinase pathways for subsets of TNBC.
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Project description:The WEE1 G2 checkpoint kinase acts as a negative cell cycle regulator for entry into mitosis (G2-to-M transition). This comment extends a recent Advanced Science paper by reporting higher WEE1-dependency of triple negative breast cancer (TNBC) cell lines, pejorative prognostic value of WEE1 expression in TNBC clinical samples as well as higher expression of biomarkers of sensitivity to WEE1 inhibitor.
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Project description:Background:Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor clinical outcome and limited treatment options. Lacking molecular targets, chemotherapy is the main adjuvant treatment for TNBC patients. Materials and methods:To explore potential therapeutic targets for TNBC, we analyzed three microarray datasets (GSE38959, GSE45827, and GSE65194) derived from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) between TNBC and normal tissue. Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery to identify the pathways and functional annotation of DEGs. Protein-protein interaction of these DEGs was analyzed based on the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. In addition, we used the online Kaplan-Meier plotter survival analysis tool to evaluate the prognostic value of hub genes expression in breast cancer patients. Results:A total of 278 upregulated DEGs and 173 downregulated DEGs were identified. Among them, ten hub genes with a high degree of connectivity were picked out. Overexpression of these hub genes was associated with unfavorable prognosis of breast cancer, especially, CCNB1 overexpression was observed and indicated poor outcome of TNBC. Conclusion:Our study suggests that CCNB1 was overexpressed in TNBC compared with normal breast tissue, and overexpression of CCNB1 was an unfavorable prognostic factor of TNBC patients. Further study is needed to explore the value of CCNB1 in the treatment of TNBC.
| S-EPMC6054764 | biostudies-literature
Project description:Triple-negative breast cancer (TNBC) accounts for ?20% of all breast cancer (BC) cases. The management of TNBC represents a challenge due to its worse prognosis, heterogeneity and lack of targeted therapy. Moreover, its mechanisms are not fully clear. The aim of the study is to identify crucial genes between TNBC and non-TNBC for underlying targets for diagnostic and therapeutic methods of TNBC. The differentially expressed genes (DEGs) between TNBC and non-TNBC were selected from the Gene Expression Omnibus (GEO) database after the integrated analysis of two datasets (GSE65194 and GSE76124). Then Gene ontology (GO) and KEGG analysis were performed by DAVID database, protein-protein interaction (PPI) of DEGs was constructed by Search Tool for the Retrieval of Reciprocity Genes (STRING) database. Furthermore, centrality analysis and module analysis were carried out by Cytoscape to analyze the TNBC-related PPI. Subsequently, overall survival (OS) analysis was performed by GEPIA. Finally, the expressions of these key genes in TNBC and non-TNBC tissues were tested by qRT-PCR. The results showed that 955 DEGs were obtained, which were mainly enriched in ribosome, ribosomal subunit, and so on. Moreover, 19 candidate genes were focused on by centrality analysis and module analysis. Furthermore, we found the low expressions of ribosomal protein S9 (RPS9), ribosomal protein S14 (RPS14), ribosomal protein S27 (RPS27), ribosomal protein L11 (RPL11) and ribosomal protein L14 (RPL14) were related to a poor OS in BC patients. Additionally, qRT-PCR results suggested that these five genes were notably down-regulated in TNBC tissues. In summary, the present study suggests that ribosomal proteins are related to TNBC, and they may play an important role in the diagnosis, treatment and prognosis of TNBC.
| S-EPMC7789804 | biostudies-literature
Project description:Triple negative breast cancer (TNBC) is a highly heterogeneous and aggressive disease, and although no effective targeted therapies are available to date, about one-third of patients with TNBC achieve pathologic complete response (pCR) from standard-of-care anthracycline/taxane (ACT) chemotherapy. The heterogeneity of these tumors, however, has hindered the discovery of effective biomarkers to identify such patients.We performed whole exome sequencing on 29 TNBC cases from the MD Anderson Cancer Center (MDACC) selected because they had either pCR (n = 18) or extensive residual disease (n = 11) after neoadjuvant chemotherapy, with cases from The Cancer Genome Atlas (TCGA; n = 144) and METABRIC (n = 278) cohorts serving as validation cohorts. Our analysis revealed that mutations in the AR- and FOXA1-regulated networks, in which BRCA1 plays a key role, are associated with significantly higher sensitivity to ACT chemotherapy in the MDACC cohort (pCR rate of 94.1% compared to 16.6% in tumors without mutations in AR/FOXA1 pathway, adjusted p = 0.02) and significantly better survival outcome in the TCGA TNBC cohort (log-rank test, p = 0.05). Combined analysis of DNA sequencing, DNA methylation, and RNA sequencing identified tumors of a distinct BRCA-deficient (BRCA-D) TNBC subtype characterized by low levels of wild-type BRCA1/2 expression. Patients with functionally BRCA-D tumors had significantly better survival with standard-of-care chemotherapy than patients whose tumors were not BRCA-D (log-rank test, p = 0.021), and they had significantly higher mutation burden (p < 0.001) and presented clonal neoantigens that were associated with increased immune cell activity. A transcriptional signature of BRCA-D TNBC tumors was independently validated to be significantly associated with improved survival in the METABRIC dataset (log-rank test, p = 0.009). As a retrospective study, limitations include the small size and potential selection bias in the discovery cohort.The comprehensive molecular analysis presented in this study directly links BRCA deficiency with increased clonal mutation burden and significantly enhanced chemosensitivity in TNBC and suggests that functional RNA-based BRCA deficiency needs to be further examined in TNBC.
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Project description:PurposeWhile chemotherapy remains the standard treatment for triple-negative breast cancer (TNBC), identifying and managing chemoresistant tumors has proven elusive. We sought to discover hallmarks and therapeutically actionable features of refractory TNBC through molecular analysis of primary chemoresistant TNBC specimens.Experimental designWe performed transcriptional profiling of tumors from a phase II clinical trial of platinum chemotherapy for advanced TNBC (TBCRC-009), revealing a gene expression signature that identified de novo chemorefractory tumors. We then employed pharmacogenomic data mining, proteomic and other molecular studies to define the therapeutic vulnerabilities of these tumors.ResultsWe reveal the RAS-GTPase-activating protein (RAS-GAP) RASAL2 as an upregulated factor that mediates chemotherapy resistance but also an exquisite collateral sensitivity to combination MAP kinase kinase (MEK1/2) and EGFR inhibitors in TNBC. Mechanistically, RASAL2 GAP activity is required to confer kinase inhibitor sensitivity, as RASAL2-high TNBCs sustain basal RAS activity through suppression of negative feedback regulators SPRY1/2, together with EGFR upregulation. Consequently, RASAL2 expression results in failed feedback compensation upon co-inhibition of MEK1/2 and EGFR that induces synergistic apoptosis in vitro and in vivo. In patients with TNBC, high RASAL2 levels predict clinical chemotherapy response and long-term outcomes, and are associated via direct transcriptional regulation with activated oncogenic Yes-Associated Protein (YAP). Accordingly, chemorefractory patient-derived TNBC models exhibit YAP activation, high RASAL2 expression, and tumor regression in response to MEK/EGFR inhibitor combinations despite well-tolerated intermittent dosing.ConclusionsThese findings identify RASAL2 as a mediator of TNBC chemoresistance that rewires MAPK feedback and cross-talk to confer profound collateral sensitivity to combination MEK1/2 and EGFR inhibitors.
| S-EPMC8416935 | biostudies-literature
Project description:PurposeBreast cancer is a heterogeneous disease usually including four molecular subtypes such as luminal A, luminal B, HER2-enriched, and triple-negative breast cancer (TNBC). TNBC is more aggressive than other breast cancer subtypes. Despite major advances in ER-positive or HER2-amplified breast cancer, there is no targeted agent currently available for TNBC, so it is urgent to identify new potential therapeutic targets for TNBC.MethodsWe first used microarray analysis to compare gene expression profiling between TNBC and non-TNBC. Furthermore an integrated analysis was conducted based on our own and published data, leading to more robust, reproducible and accurate predictions. Additionally, we performed qRT-PCR in breast cancer cell lines to verify the findings in integrated analysis.ResultsAfter searching Gene Expression Omnibus database (GEO), two microarray studies were obtained according to the inclusion criteria. The integrated analysis was conducted, including 30 samples of TNBC and 77 samples of non-TNBC. 556 genes were found to be consistently differentially expressed (344 up-regulated genes and 212 down-regulated genes in TNBC). Functional annotation for these differentially expressed genes (DEGs) showed that the most significantly enriched Gene Ontology (GO) term for molecular functions was protein binding (GO: 0005515, P = 6.09E-21), while that for biological processes was signal transduction (GO: 0007165, P = 9.46E-08), and that for cellular component was cytoplasm (GO: 0005737, P = 2.09E-21). The most significant pathway was Pathways in cancer (P = 6.54E-05) based on Kyoto Encyclopedia of Genes and Genomes (KEGG). DUSP1 (Degree = 21), MYEOV2 (Degree = 15) and UQCRQ (Degree = 14) were identified as the significant hub proteins in the protein-protein interaction (PPI) network. Five genes were selected to perform qRT-PCR in seven breast cancer cell lines, and qRT-PCR results showed that the expression pattern of selected genes in TNBC lines and non-TNBC lines was nearly consistent with that in the integrated analysis.ConclusionThis study may help to understand the pathogenesis of different breast cancer subtypes, contributing to the successful identification of therapeutic targets for TNBC.
| S-EPMC4478040 | biostudies-literature
Project description:Triple‑negative breast cancer (TNBC) is a heterogeneous disease characterized by an aggressive phenotype and reduced survival. The aim of the present study was to investigate the molecular mechanisms involved in the carcinogenesis of TNBC and to identify novel target molecules for therapy. The differentially expressed genes (DEGs) in TNBC and normal adjacent tissue were assessed by analyzing the GSE41970 microarray data using Qlucore Omics Explorer, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes. Pathway enrichment analyses for DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery online resource. A protein‑protein interaction (PPI) network was constructed using Search Tool for the Retrieval of Interacting Genes, and subnetworks were analyzed by ClusterONE. The PPI network and subnetworks were visualized using Cytoscape software. A total of 121 DEGs were obtained, of which 101 were upregulated and 20 were downregulated. The upregulated DEGs were significantly enriched in 14 pathways and 83 GO biological processes, while the downregulated DEGs were significantly enriched in 18 GO biological processes. The PPI network with 118 nodes and 1,264 edges was constructed and three subnetworks were extracted from the entire network. The significant hub DEGs with high degrees were identified, including TP53, glyceraldehyde‑3‑phosphate dehydrogenase, cyclin D1, HRAS and proliferating cell nuclear antigen, which were predominantly enriched in the cell cycle pathway and pathways in cancer. A number of critical genes and pathways were revealed to be associated with TNBC. The present study may provide an improved understanding of the pathogenesis of TNBC and contribute to the development of therapeutic targets for TNBC.
| S-EPMC5367345 | biostudies-literature