Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35127939", "kind": "science-record", "revision": 5, "content_hash": "sha256:7c660dffc9dcce75186ab1b74d8512be9827d1198cb4385d1a01d9d28f136625", "created_at": "2026-11-01T17:36:52Z", "updated_at": "2026-11-01T22:05:48Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach.", "doi": "10.1155/2022/1776082", "pmid": "35127939", "authors": ["Md Rakibul Islam", "Lway Faisal Abdulrazak", "Mohammad Khursheed Alam", "Bikash Kumar Paul", "Kawsar Ahmed", "Francis M Bui", "Mohammad Ali Moni"], "journal": "BioMed research international", "year": 2022, "abstract": "BACKGROUND: Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB.\nMETHODS: A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣log fold change | >1 and P < 0.05. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network.\nRESULTS: Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.", "claims": [{"id": "claim-method", "statement": "Using stored data of R2, survival analysis was performed, and hub genes that were sharply connected with survival were identified through Kaplan–Meier (KM) survival analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35127939", "locator": "sections[7] \"2.5. Survival Analysis\" paragraph 2", "quote": "Using stored data of R2, survival analysis was performed, and hub genes that were sharply connected with survival were identified through Kaplan–Meier (KM) survival analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the present study were downloaded from the GEO, Enrichr, and STRING databases. All of the resources are free and publicly accessible.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35127939", "locator": "sections[17] \"Data Availability\" paragraph 2", "quote": "The datasets used and/or analyzed during the present study were downloaded from the GEO, Enrichr, and STRING databases. All of the resources are free and publicly accessible."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The analysis showed that the expressions of MAD2L1 (P value 1.6e-08), PPP2R5E (P value 2.4e-06), CCNA2 (P value 2.5e-06), and GNG2 (P value 2.2e-04) were reversely connected with patients' survival time (Figures 10(a)–10(f)).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35127939", "locator": "sections[12] \"2.7. Survival Analysis\" paragraph 2", "quote": "The analysis showed that the expressions of MAD2L1 (P value 1.6e-08), PPP2R5E (P value 2.4e-06), CCNA2 (P value 2.5e-06), and GNG2 (P value 2.2e-04) were reversely connected with patients' survival time (Figures 10(a)–10(f))."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The analysis showed that the expressions of MAD2L1 (P value 1.6e-08), PPP2R5E (P value 2.4e-06), CCNA2 (P value 2.5e-06), and GNG2 (P value 2.2e-04) were reversely connected with patients' survival time (Figures 10(a)–10(f)).", "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:35127939"], "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:GSE22139"], "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:GSE22139"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35127939", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/1776082", "sha256": "sha256:2d21fffdfda4d2f22528e8e1351b0bb0a7169c61ed037d6998e479b1ecf34a66", "bytes": 28656, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/1776082", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8816556", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE22139", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22139", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE22139", "version": null, "note": "The datasets used and/or analyzed during the present study were downloaded from the GEO, Enrichr, and STRING databases. 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