ArticleCancer reports (Hoboken, N.J.)2024
Identification of Biomarkers Associated With Paget's Disease of Bone and Bone Metastasis From Breast Cancer Patients.
Article in Cancer reports (Hoboken, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Harnessing plasma transcriptomics for non-invasive cancer biomarker identification: a comprehensive review.Discover oncology · 2025Review
- Integrated bioinformatics and clinical data identify three novel biomarkers for osteoarthritis diagnosis and synovial immune.Scientific reports · 2025Article
- Editorial: Gastrointestinal (GI) disorders and antioxidant therapeutics.Frontiers in endocrinology · 2025Article
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Authors and funding
8 authors.
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Abstract
backgroundThe 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.
aimsThis 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. METHODS AND
resultsThis 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.
conclusionOf 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.
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