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The genetically heterogeneous triple-negative breast cancer (TNBC) continues to be an intractable disease, due to lack of effective targeted therapies. Gene amplification is a major event in tumorigenesis. Genes with amplification-dependent expression are being explored as therapeutic targets for cancer treatment. In this study, we have applied Analytical Multi-scale Identification of Recurring Events analysis and transcript quantification in the TNBC genome across 222 TNBC tumors and identified 138 candidate genes with positive correlation in copy number gain (CNG) and gene expression. siRNA-based loss-of-function screen of the candidate genes has validated EGFR, MYC, ASAP1, IRF2BP2, and CCT5 genes as drivers promoting proliferation in different TNBC cells. MYC, ASAP1, IRF2BP2, and CCT5 display frequent CNG and concurrent expression over 2173 breast cancer tumors (cBioPortal dataset). More frequently are MYC and ASAP1 amplified in TNBC tumors (>30%, n = 320). In particular, high expression of ASAP1, the ADP-ribosylation factor GTPase-activating protein, is significantly related to poor metastatic relapse-free survival of TNBC patients (n = 257, bc-GenExMiner). Furthermore, we have revealed that silencing of ASAP1 modulates numerous cytokine and apoptosis signaling components, such as IL1B, TRAF1, AIFM2, and MAP3K11 that are clinically relevant to survival outcomes of TNBC patients. ASAP1 has been reported to promote invasion and metastasis in various cancer cells. Our findings that ASAP1 is an amplification-dependent TNBC driver gene promoting TNBC cell proliferation, functioning upstream apoptosis components, and correlating to clinical outcomes of TNBC patients, support ASAP1 as a potential actionable target for TNBC treatment.
Pubmed ID: 32235890
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Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsA federated data sharing platform and infrastructure that provides access to real-time clinical, imaging and biospecimen data across jurisdictions, institutions and diseases. The web-based platform provides a secure infrastructure that advances health research by linking privacy-protected and ethically approved data among a wide network of health collaborators. Access to de-identified health records data is granted to authorized researchers after an application process so patient privacy and intellectual property are protected. BioGrid Australia''s approved researchers are provided access to multiple institutional databases, via the BioGrid interface, preventing gaps in patient records and research analysis. This legal and ethical arrangement with participating collaborators allows BioGrid to connect data through a common platform where data governance and access is managed by a highly skilled team. Data governance, security and ethics are at the core of BioGrid''s federated data sharing platform that securely links patient level clinical, biospecimen, genetic and imaging data sets across multiple sites and diseases for the purpose of medical research. BioGrid''s infrastructure and data management strategies address the increasing need by authorized researchers to dynamically extract and analyze data from multiple sources whilst protecting patient privacy. BioGrid has the capability to link data with other datasets, produce tailored reports for auditing and reporting and provide statistical analysis tools to conduct more advanced research analysis. In the health sector, BioGrid is a trusted independent virtual real-time data repository. Government investment in BioGrid has facilitated a combination of technology, collaboration and ethics approval processes for data sharing that exist nowhere else in the world.
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsA portal that provides visualization, analysis and download of large-scale cancer genomics data sets.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsCell line BT-549 is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsCell line Hs 578T is a Cancer cell line with a species of origin Homo sapiens (Human)
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
