{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T09:44:30Z","timestamp":1753868670546,"version":"3.41.2"},"reference-count":68,"publisher":"Wiley","issue":"9","license":[{"start":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T00:00:00Z","timestamp":1725494400000},"content-version":"vor","delay-in-days":4,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Reports"],"published-print":{"date-parts":[[2024,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Aims<\/jats:title><jats:p>This research aims to investigate the common key candidate biomarkers that contribute to BM\u2010BCa (Bone metastasis of breast cancer) and PDB by employing network decomposition and functional enrichment studies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods and Results<\/jats:title><jats:p>This research analyzed high\u2010throughput transcriptome sequencing (RNA\u2010Seq). 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\u2010throughput research created a protein\u2010protein interaction network (PPIN). The BM\u2010PDB\u2010interactome was created using Cytoscape 3.9.1 and PDB biomarkers, with the top 3% DEGs from BM\u2010BCa. 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\u2010PDB interactome. RAC2, PIAS1, EP300, EIF2S1, and LRP6 are among the additional 25% of genes identified to interact with the BM\u2010PDB interactome. To corroborate the findings of the research presented, additional functional and gene set enrichment analyses have been performed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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\u2010PDB interactome analysis and validated by TCGA in the study presented.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cnr2.70003","type":"journal-article","created":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T09:01:22Z","timestamp":1725526882000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Identification of Biomarkers Associated With Paget's Disease of Bone and Bone Metastasis From Breast Cancer Patients"],"prefix":"10.1002","volume":"7","author":[{"given":"Mahima","family":"Bhardwaj","sequence":"first","affiliation":[{"name":"Department of Biotechnology, 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