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Jayarathna DK, Rentería ME, Batra J, Gandhi NS. A supervised machine learning approach identifies gene-regulating factor-mediated competing endogenous RNA networks in hormone-dependent cancers. J Cell Biochem 2022; 123:1394-1408. [PMID: 35757968 PMCID: PMC9542250 DOI: 10.1002/jcb.30300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 06/10/2022] [Accepted: 06/13/2022] [Indexed: 11/17/2022]
Abstract
Competing endogenous RNAs (ceRNAs) have become an emerging topic in cancer research due to their role in gene regulatory networks. To date, traditional ceRNA bioinformatic studies have investigated microRNAs as the only factor regulating gene expression. Growing evidence suggests that genomic (e.g., copy number alteration [CNA]), transcriptomic (e.g., transcription factors [TFs]), and epigenomic (e.g., DNA methylation [DM]) factors can influence ceRNA regulatory networks. Herein, we used the Least absolute shrinkage and selection operator regression, a machine learning approach, to integrate DM, CNA, and TFs data with RNA expression to infer ceRNA networks in cancer risk. The gene‐regulating factors‐mediated ceRNA networks were identified in four hormone‐dependent (HD) cancer types: prostate, breast, colorectal, and endometrial. The shared ceRNAs across HD cancer types were further investigated using survival analysis, functional enrichment analysis, and protein–protein interaction network analysis. We found two (BUB1 and EXO1) and one (RRM2) survival‐significant ceRNA(s) shared across breast‐colorectal‐endometrial and prostate–colorectal–endometrial combinations, respectively. Both BUB1 and BUB1B genes were identified as shared ceRNAs across more than two HD cancers of interest. These genes play a critical role in cell division, spindle‐assembly checkpoint signalling, and correct chromosome alignment. Furthermore, shared ceRNAs across multiple HD cancers have been involved in essential cancer pathways such as cell cycle, p53 signalling, and chromosome segregation. Identifying ceRNAs' roles across multiple related cancers will improve our understanding of their shared disease biology. Moreover, it contributes to the knowledge of RNA‐mediated cancer pathogenesis.
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Affiliation(s)
- Dulari K Jayarathna
- Centre for Genomics and Personalized Health, School of Chemistry and Physics, Queensland University of Technology, Brisbane, QLD, Australia.,Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Jyotsna Batra
- Centre for Genomics and Personalized Health, School of Chemistry and Physics, Queensland University of Technology, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia.,Australian Prostate Cancer Research Centre-Queensland, Woolloongabba, QLD, Australia
| | - Neha S Gandhi
- Centre for Genomics and Personalized Health, School of Chemistry and Physics, Queensland University of Technology, Brisbane, QLD, Australia.,Cancer and Ageing Research Program, Translational Research Institute, Woolloongabba, QLD, Australia
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Puig RR, Boddie P, Khan A, Castro-Mondragon JA, Mathelier A. UniBind: maps of high-confidence direct TF-DNA interactions across nine species. BMC Genomics 2021; 22:482. [PMID: 34174819 PMCID: PMC8236138 DOI: 10.1186/s12864-021-07760-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 05/27/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Transcription factors (TFs) bind specifically to TF binding sites (TFBSs) at cis-regulatory regions to control transcription. It is critical to locate these TF-DNA interactions to understand transcriptional regulation. Efforts to predict bona fide TFBSs benefit from the availability of experimental data mapping DNA binding regions of TFs (chromatin immunoprecipitation followed by sequencing - ChIP-seq). RESULTS In this study, we processed ~ 10,000 public ChIP-seq datasets from nine species to provide high-quality TFBS predictions. After quality control, it culminated with the prediction of ~ 56 million TFBSs with experimental and computational support for direct TF-DNA interactions for 644 TFs in > 1000 cell lines and tissues. These TFBSs were used to predict > 197,000 cis-regulatory modules representing clusters of binding events in the corresponding genomes. The high-quality of the TFBSs was reinforced by their evolutionary conservation, enrichment at active cis-regulatory regions, and capacity to predict combinatorial binding of TFs. Further, we confirmed that the cell type and tissue specificity of enhancer activity was correlated with the number of TFs with binding sites predicted in these regions. All the data is provided to the community through the UniBind database that can be accessed through its web-interface ( https://unibind.uio.no/ ), a dedicated RESTful API, and as genomic tracks. Finally, we provide an enrichment tool, available as a web-service and an R package, for users to find TFs with enriched TFBSs in a set of provided genomic regions. CONCLUSIONS UniBind is the first resource of its kind, providing the largest collection of high-confidence direct TF-DNA interactions in nine species.
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Affiliation(s)
- Rafael Riudavets Puig
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0349, Oslo, Norway
| | - Paul Boddie
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0349, Oslo, Norway
| | - Aziz Khan
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0349, Oslo, Norway
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | | | - Anthony Mathelier
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, 0349, Oslo, Norway.
- Department of Medical Genetics, Oslo University Hospital, Oslo, 0424, Norway.
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