Bioinformatics Analysis of Key Genes and Pathways for Medulloblastoma as a Therapeutic Target

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30678435", "kind": "science-record", "revision": 5, "content_hash": "sha256:f31e3902bef731d332aa8d62f7b9133a4a7b0d92d6113cad22f904e54542b46e", "created_at": "2026-11-01T15:40:41Z", "updated_at": "2026-11-01T21:21:56Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Bioinformatics Analysis of Key Genes and Pathways for Medulloblastoma as a Therapeutic Target", "doi": "10.31557/APJCP.2019.20.1.221", "pmid": "30678435", "authors": ["Fateme Shaabanpour Aghamaleki", "Behrouz Mollashahi", "Nika Aghamohammadi", "Nematollah Rostami", "Zeinab Mazloumi", "Hamidreza Mirzaei", "Afshin Moradi", "Mojgan Sheikhpour", "Abolfazl Movafagh"], "journal": "Asian Pacific journal of cancer prevention : APJCP", "year": 2019, "abstract": "Introduction: One of the major challenges in cancer treatment is the lack of specific and accurate treatment in cancer. Data analysis can help to understand the underlying molecular mechanism that leads to better treatment. Increasing availability and reliability of DNA microarray data leads to increase the use of these data in a variety of cancers. This study aimed at applying and evaluating microarray data analyzing, identification of important pathways and gene network for medulloblastoma patients to improve treatment approaches especially target therapy. Methods: In the current study, Microarray gene expression data (GSE50161) were extracted from Geo datasets and then analyzed by the affylmGUI package to predict and investigate upregulated and downregulated genes in medulloblastoma. Then, the important pathways were determined by using software and gene enrichment analyses. Pathways visualization and network analyses were performed by Cytoscape. Results: A total number of 249 differentially expressed genes (DEGs) were identified in medulloblastoma compared to normal samples. Cell cycle, p53, and FoxO signaling pathways were indicated in medulloblastoma, and CDK1, CCNB1, CDK2, and WEE1 were identified as some of the important genes in the medulloblastoma. Conclusion: Identification of critical and specific pathway in any disease, in our case medulloblastoma, can lead us to better clinical management and accurate treatment and target therapy.", "claims": [{"id": "claim-method", "statement": "Next, all normalized and appropriate data were analyzed by the linear method, that all result was demonstrated through the volcano plot and differential expression (logfc).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30678435", "locator": "sections[3] \"Microarray gene expression data analyses\" paragraph 2", "quote": "Next, all normalized and appropriate data were analyzed by the linear method, that all result was demonstrated through the volcano plot and differential expression (logfc)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Microarray gene expression data (GSE50161) of 22 medulloblastoma patients and 13 healthy individuals were extracted from NCBI Gene Expression Omnibus (GEO) database, which based on GPL570 ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array, Affymetrix Inc, Denver, USA) and deposited by Donson et al., (2014) and Griesinger et al., (2013).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30678435", "locator": "sections[3] \"Microarray gene expression data analyses\" paragraph 2", "quote": "Microarray gene expression data (GSE50161) of 22 medulloblastoma patients and 13 healthy individuals were extracted from NCBI Gene Expression Omnibus (GEO) database, which based on GPL570 ([HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array, Affymetrix Inc, Denver, USA) and deposited by Donson et al., (2014) and Griesinger et al., (2013)."}], "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:30678435"], "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:GSE50161"], "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:GSE50161"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:30678435", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.31557/APJCP.2019.20.1.221", "sha256": "sha256:5c1e9654afaf034bd7d262dd8495b72f0f0084ff7e20d1f735be4fbca0f7e837", "bytes": 28382, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.31557/APJCP.2019.20.1.221", "version": null, "note": "Full article fetched from PMC; 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Cell cycle and p53 signaling pathways have the highest and significant fold enrichment", "rows": [["Term", "P-Value", "Fold Enrichment", "Bonferroni", "Benjamini", "FDR"], ["Cell cycle", "1.79E-16", "38.91535", "6.88E-15", "6.88E-15", "1.89E-13"], ["p53 signaling pathway", "4.31E-04", "24.54661", "0.013265", "0.003333", "0.36938"], ["FoxO signaling pathway", "0.003282", "12.17961", "0.096898", "0.020178", "2.784925"], ["Viral carcinogenesis", "0.073799", "6.232537", "0.907131", "0.327057", "48.24269"], ["DNA replication", "0.08173", "22.16013", "0.928866", "0.314494", "51.929"]], "row_count": 6, "column_count": 6, "numeric_cells": 26, "header_rows": 1, "locator": "section[11]/table-wrap[1]#T1"}}], "gaps": ["asset:data:geo:GSE50161 not downloaded", "asset:data:geo:GSE50161 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "linear method", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Next, all normalized and appropriate data were analyzed by the linear method, that all result was demonstrated through the volcano plot and differential expression (logfc)."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "method", "blocked_on": "method:not_determinable", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (linear method), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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