Transcriptome research identifies four hub genes related to primary myelofibrosis: a holistic research by weighted gene co-expression network analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34633991", "kind": "science-record", "revision": 4, "content_hash": "sha256:1c4a47dbc023a945d3b911164c9f9eb7c50b758b03717aa55b2ccb43d4d47f61", "created_at": "2026-11-01T17:36:17Z", "updated_at": "2026-11-01T22:04:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptome research identifies four hub genes related to primary myelofibrosis: a holistic research by weighted gene co-expression network analysis.", "doi": "10.18632/aging.203619", "pmid": "34633991", "authors": ["Weihang Li", "Yingjing Zhao", "Dong Wang", "Ziyi Ding", "Chengfei Li", "Bo Wang", "Xiong Xue", "Jun Ma", "Yajun Deng", "Quancheng Liu", "Guohua Zhang", "Ying Zhang", "Kai Wang", "Bin Yuan"], "journal": "Aging", "year": 2021, "abstract": "OBJECTIVES: This study aimed to identify specific diagnostic as well as predictive targets of primary myelofibrosis (PMF).\nMETHODS: The gene expression profiles of GSE26049 were obtained from Gene Expression Omnibus (GEO) dataset, WGCNA was constructed to identify the most related module of PMF. Subsequently, Gene Ontology (GO), Kyoto Encyclopedia Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA) and Protein-Protein interaction (PPI) network were conducted to fully understand the detailed information of the interested green module. Machine learning, Principal component analysis (PCA), and expression pattern analysis including immunohistochemistry and immunofluorescence of genes and proteins were performed to validate the reliability of these hub genes.\nRESULTS: Green module was strongly correlated with PMF disease after WGCNA analysis. 20 genes in green module were identified as hub genes responsible for the progression of PMF. GO, KEGG revealed that these hub genes were primarily enriched in erythrocyte differentiation, transcription factor binding, hemoglobin complex, transcription factor complex and cell cycle, etc. Among them, EPB42, CALR, SLC4A1 and MPL had the most correlations with PMF. Machine learning, Principal component analysis (PCA), and expression pattern analysis proved the results in this study.\nCONCLUSIONS: EPB42, CALR, SLC4A1 and MPL were significantly highly expressed in PMF samples. These four genes may be considered as candidate prognostic biomarkers and potential therapeutic targets for early stage of PMF. The effects are worth expected whether in the diagnosis at early stage or as therapeutic target.", "claims": [{"id": "claim-method", "statement": "The gene expression profiles of GSE26049 were obtained from Gene Expression Omnibus (GEO) dataset, WGCNA was constructed to identify the most related module of PMF.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34633991", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The gene expression profiles of GSE26049 were obtained from Gene Expression Omnibus (GEO) dataset, WGCNA was constructed to identify the most related module of PMF."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data used and analyzed during the current study are available upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34633991", "locator": "sections[21] \"Data availability statement\" paragraph 2", "quote": "The data used and analyzed during the current study are available upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Among them, green module had the strongest correlation (r = 0.46) and the lowest P value (p = 8e-5), elucidating green module was most correlated with PMF, genes in green module were essential in the pathogenesis and oncogenesis of PMF.", "kind": "quantitative", "target": {"value": 0.46, "unit": "correlation coefficient", "tolerance": null, "source": "Among them, green module had the strongest correlation (r = 0.46) and the lowest P value (p = 8e-5), elucidating green module was most correlated with PMF, genes in green module were essential in the pathogenesis and oncogenesis of PMF."}, "evidence": [{"asset": "source:pmid:34633991", "locator": "sections[5] \"Key module identification of PMF\" paragraph 2", "quote": "Among them, green module had the strongest correlation (r = 0.46) and the lowest P value (p = 8e-5), elucidating green module was most correlated with PMF, genes in green module were essential in the pathogenesis and oncogenesis of PMF."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Among them, green module had the strongest correlation (r = 0.46) and the lowest P value (p = 8e-5), elucidating green module was most correlated with PMF, genes in green module were essential in the pathogenesis and oncogenesis of PMF.", "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:34633991"], "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:GSE26049"], "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:GSE26049"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34633991", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.18632/aging.203619", "sha256": 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