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

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2024-09-05 DOI:10.1002/cnr2.70003

Mahima Bhardwaj, Farhana Begum, Duleswar Singh, Srirama Krupanidhi, Virendra Kumar Yadav, Dipak Kumar Sahoo, Ashish Patel, Sachidanand Singh

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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.

Aims

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.

Methods 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.

Conclusion

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.

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鉴定与乳腺癌患者骨质沉着病和骨转移相关的生物标志物

背景：骨骼是乳腺癌转移扩散最常选择的部位之一。目的：本研究旨在通过网络分解和功能富集研究，探讨导致 BM-BCa（乳腺癌骨转移）和 PDB 的常见关键候选生物标志物：本研究分析了高通量转录组测序（RNA-Seq）。从 GEO（Gene Expression Omnibus，基因表达总库）下载数据集（GSE121677），使用 Galaxy 和 R 脚本 4.3 识别 DEGs。利用 STRING（检索相互作用基因的搜索工具），高通量研究创建了蛋白质-蛋白质相互作用网络（PPIN）。使用 Cytoscape 3.9.1 和 PDB 生物标记创建了 BM-PDB-interactome，其中包括来自 BM-BCa 的前 3% DEGs。功能富集分析（Funrich 3.1.3）和 DAVID 6.8 对推测的重要生物标记物进行了功能和基因组富集分析（GSEA）。TCGA（癌症基因组图谱）对发现的基因进行了验证。根据我们的研究，我们确定了 1262 个 DEGs；在这些 DEGs 中，431 个基因上调，831 个基因下调。在相互作用组的第三次增长中，又有 20 个基因被归入 BM-PDB 相互作用组。RAC2、PIAS1、EP300、EIF2S1和LRP6等25%的基因与BM-PDB相互作用组发生了相互作用。为了证实上述研究结果，还进行了其他功能和基因组富集分析：结论：在报告的五个基因（RAC2、PIAS1、EP300、EIF2S1 和 LRP6）中，RAC2 被确定为 BM-PDB 相互作用组分析中常见的关键潜在生物标志物，并在报告的研究中得到了 TCGA 的验证。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.