Identification of Biomarkers Associated With Paget's Disease of Bone and Bone Metastasis From Breast Cancer Patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39233667", "kind": "science-record", "revision": 4, "content_hash": "sha256:e8e35df55c25eb600c54e1549dcae439956282fa55e755181cf4414baf63a298", "created_at": "2026-11-01T20:29:22Z", "updated_at": "2026-11-01T22:55:05Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Biomarkers Associated With Paget's Disease of Bone and Bone Metastasis From Breast Cancer Patients.", "doi": "10.1002/cnr2.70003", "pmid": "39233667", "authors": ["Mahima Bhardwaj", "Farhana Begum", "Duleswar Singh", "Srirama Krupanidhi", "Virendra Kumar Yadav", "Dipak Kumar Sahoo", "Ashish Patel", "Sachidanand Singh"], "journal": "Cancer reports (Hoboken, N.J.)", "year": 2024, "abstract": "BACKGROUND: The bone is among the most frequently chosen sites for the metastatic spread of breast cancer. The prediction of biomarkers for BM (Bone Metastasis) and PDB (Paget's disease of bone) initiated from breast cancer could be critically important in categorizing individuals with a higher risk and providing targeted treatment for PDB and BM.\nAIMS: This research aims to investigate the common key candidate biomarkers that contribute to BM-BCa (Bone metastasis of breast cancer) and PDB by employing network decomposition and functional enrichment studies.\nMETHODS AND RESULTS: This research analyzed high-throughput transcriptome sequencing (RNA-Seq). For this work, the dataset (GSE121677) was downloaded from GEO (Gene Expression Omnibus), and DEGs were identified using Galaxy and R script 4.3. Using STRING (Search Tool for the Retrieval of Interacting Genes), high-throughput research created a protein-protein interaction network (PPIN). The BM-PDB-interactome was created using Cytoscape 3.9.1 and PDB biomarkers, with the top 3% DEGs from BM-BCa. Functional Enrichment Analysis (Funrich 3.1.3) and DAVID 6.8 performed functional and gene set enrichment analysis (GSEA) of putatively essential biomarkers. TCGA (The Cancer Genome Atlas) validated the discovered genes. Based on our research, we identified 1262 DEGs; among these DEGs, 431 genes were upregulated, and 831 genes were downregulated. During the third growth of the interactome, 20 more genes were pinned to the BM-PDB interactome. RAC2, PIAS1, EP300, EIF2S1, and LRP6 are among the additional 25% of genes identified to interact with the BM-PDB interactome. To corroborate the findings of the research presented, additional functional and gene set enrichment analyses have been performed.\nCONCLUSION: Of the five reported genes (RAC2, PIAS1, EP300, EIF2S1, and LRP6), RAC2 was identified to function as the common key potential biomarker in the BM-PDB interactome analysis and validated by TCGA in the study presented.", "claims": [{"id": "claim-method", "statement": "The raw counts of each of the SRA sample files (SRR8097383, SRR8097384, SRR8097385, SRR8097386, SRR8097387, SRR8097388, SRR8097389, SRR8097390, SRR8097391, SRR8097392, SRR8097393, SRR8097394, SRR8097395, SRR8097396, SRR8097397, SRR8097398, SRR8097399, SRR8097400, SRR8097401, SRR8097402, SRR8097403, SRR8097404, SRR8097405, and SRR8097406) of the GEO dataset GSE121677 were processed independently as a counts data file and col data file for quality control and differential gene expression analysis was performed by R script using the DESeq2 tool as a computational approach.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39233667", "locator": "sections[5] \"Differential Expression Analysis\" paragraph 2", "quote": "The raw counts of each of the SRA sample files (SRR8097383, SRR8097384, SRR8097385, SRR8097386, SRR8097387, SRR8097388, SRR8097389, SRR8097390, SRR8097391, SRR8097392, SRR8097393, SRR8097394, SRR8097395, SRR8097396, SRR8097397, SRR8097398, SRR8097399, SRR8097400, SRR8097401, SRR8097402, SRR8097403, SRR8097404, SRR8097405, and SRR8097406) of the GEO dataset GSE121677 were processed independently as a counts data file and col data file for quality control and differential gene expression analysis was performed by R script using the DESeq2 tool as a computational approach."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data that supports the findings of this study are available in the supplementary files and also provided by the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39233667", "locator": "sections[24] \"Data Availability Statement\" paragraph 2", "quote": "The data that supports the findings of this study are available in the supplementary files and also provided by the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Of the five reported genes (RAC2, PIAS1, EP300, EIF2S1, and LRP6), RAC2 was identified to function as the common key potential biomarker in the BM‐PDB interactome analysis and validated by TCGA in the study presented.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39233667", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Of the five reported genes (RAC2, PIAS1, EP300, EIF2S1, and LRP6), RAC2 was identified to function as the common key potential biomarker in the BM‐PDB interactome analysis and validated by TCGA in the study presented."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Of the five reported genes (RAC2, PIAS1, EP300, EIF2S1, and LRP6), RAC2 was identified to function as the common key potential biomarker in the BM‐PDB interactome analysis and validated by TCGA in the study presented.", "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:39233667"], "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:GSE121677"], "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:GSE121677"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39233667", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/cnr2.70003", "sha256": 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upon reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data that supports the findings of this study are available in the supplementary files and also provided by the corresponding author upon reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3443254", "GSM3443255", "GSM3443256", "GSM3443257", "GSM3443258", "GSM3443259"], "sample_count": 6, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "Bone metastatic variant of MCF7 cells", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:PRJNA498077", "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=PRJNA498077", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "PRJNA498077", "version": null, "note": "The data that supports the findings of this study are available in the supplementary files and also provided by the corresponding author upon reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data that supports the findings of this study are available in the supplementary files and also provided by the corresponding author upon reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": [], "sample_count": null, "group_sizes": null, "group_sizes_basis": null, "platform": null, "taxon": null, "title": null, "resolution_checked_at": "2026-11-01T20:16:20Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE121677 not downloaded", "asset:data:geo:GSE121677 licence not read", "asset:data:geo:PRJNA498077 not downloaded", "asset:data:geo:PRJNA498077 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "deseq2", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The raw counts of each of the SRA sample files (SRR8097383, SRR8097384, SRR8097385, SRR8097386, SRR8097387, SRR8097388, SRR8097389, SRR8097390, SRR8097391, SRR8097392, SRR8097393, SRR8097394, SRR8097395, SRR8097396, SRR8097397, SRR8097398, SRR8097399, SRR8097400, SRR8097401, SRR8097402, SRR8097403, SRR8097404, SRR8097405, and SRR8097406) of the GEO dataset GSE121677 were processed independently 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For this work, the dataset (GSE121677) was", "ULTS: This research analyzed high-throughput transcriptome sequencing (RNA-Seq). 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