Construction and Comprehensive Analysis of a ceRNA Network to Reveal Potential Novel Biomarkers for Triple-Negative Breast Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32821169", "kind": "science-record", "revision": 7, "content_hash": "sha256:995565c4b8802f16aa8261df9b1ff2e764abca2fc028ed8dde3ebb750c6cec2b", "created_at": "2026-11-01T15:41:08Z", "updated_at": "2026-11-01T22:02:03Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction and Comprehensive Analysis of a ceRNA Network to Reveal Potential Novel Biomarkers for Triple-Negative Breast Cancer.", "doi": "10.2147/CMAR.S260150", "pmid": "32821169", "authors": ["Lifei Ma", "Guiqin Song", "Meiyu Li", "Xiuqing Hao", "Yong Huang", "Jinping Lan", "Siqian Yang", "Zetian Zhang", "Guohui Zhang", "Jiao Mu"], "journal": "Cancer management and research", "year": 2020, "abstract": "BACKGROUND: Triple-negative breast cancer (TNBC) is the most common and aggressive type of breast cancer with an unfavourable outcome worldwide. Novel therapeutic targets are urgently required to explore this malignancy. This study explored the ceRNA network and the important genes for predicting the therapeutic targets.\nMETHODS: It identified the differentially expressed genes of mRNAs, lncRNAs and miRNAs between TNBC and non-TNBC samples in four cohorts (TCGA, GSE38959, GSE45827 and GSE65194) to explore the novel therapeutic targets for TNBC. Downstream analyses, including functional enrichment analysis, ceRNA network, protein-protein interaction and survival analysis, were then conducted by bioinformatics analysis. Finally, the potential core protein of the ceRNA network in TNBC was validated by immunohistochemistry.\nRESULTS: A total of 1,045 lncRNAs and 28 miRNAs were differentially expressed in the TCGA TNBC samples, and the intersections of 282 mRNAs (176 upregulations and 106 downregulations) between the GEO and TCGA databases were identified. A ceRNA network composed of 7 lncRNAs, 62 mRNAs, 12 miRNAs and 244 edges specific to TNBC was established. The functional assay showed dysregulated genes, and GO, DO and KEGG enrichment analysis were performed. Survival analysis showed that mRNA LIFR and lncRNA AC124312.3 were significantly correlated with the overall survival of patients with TNBC in the TCGA databases (P < 0.05). Finally, the LIFR protein was validated, and immunohistochemical results showed the upregulated expression of LIFR in TNBC tissues.\nCONCLUSION: Thus, our study presents an enhanced understanding of the ceRNA network in TNBC, where the key gene LIFR may be a new promising potential therapeutic target for patients with TNBC.", "claims": [{"id": "claim-method", "statement": "To further explore the role of genes in the ceRNA network, the Overall Survival (OS) Kaplan–Meier Estimate was applied for survival analysis by using the survival R package. The datasets involved in this study were composed of TCGA breast cancer samples and filtered using the negative expressions of ER, PR and HER-2 according to their clinical information. For each gene, the cancerous samples were divided into two subgroups according to the optimal cut-off value (50%) of the gene expression, and the Logrank Test P value of less than 0.05 was presented.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32821169", "locator": "sections[8] \"Survival Analysis of ceRNA Network\" paragraph 2", "quote": "To further explore the role of genes in the ceRNA network, the Overall Survival (OS) Kaplan–Meier Estimate was applied for survival analysis by using the survival R package."}, {"asset": "source:pmid:32821169", "locator": "sections[8] \"Survival Analysis of ceRNA Network\" paragraph 2", "quote": "The datasets involved in this study were composed of TCGA breast cancer samples and filtered using the negative expressions of ER, PR and HER-2 according to their clinical information."}, {"asset": "source:pmid:32821169", "locator": "sections[8] \"Survival Analysis of ceRNA Network\" paragraph 2", "quote": "For each gene, the cancerous samples were divided into two subgroups according to the optimal cut-off value (50%) of the gene expression, and the Logrank Test P value of less than 0.05 was presented."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data analyzed in this study can be downloaded from the TCGA and GEO.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32821169", "locator": "sections[20] \"Data Sharing Statement\" paragraph 2", "quote": "The data analyzed in this study can be downloaded from the TCGA and GEO."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:32821169"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE38959"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE38959"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32821169", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/CMAR.S260150", "sha256": 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The datasets involved in this study were composed of TCGA breast cancer samples and filtered using the negative expressions of ER, PR and HER-2 according to their clinical information. 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