Bhadresha Kinjal P, Patel Maulikkumar, Jain Nayan K, Rawal Rakesh M
Department of Life Science, School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
Department of Botany, Bioinformatics and Climate Change Impacts Management School of Sciences, Gujarat University, Ahmedabad, Gujarat, India.
J Bone Oncol. 2021 Jun 10;29:100374. doi: 10.1016/j.jbo.2021.100374. eCollection 2021 Aug.
Bone metastases is one of the common metastatic site and leading cause of cancer-related mortality in progressive cancer patients. The purpose of the present study is to establish a liquid biopsy based multi-gene classifier and associated signalling pathways for early diagnosis of bone metastases. We used publically available microarray datasets and analysed them in a platform/chip-specific manner using GeneSpring software. Analyses of gene expression datasets identified 15 consistently over-expressed genes with statistical significance. Further, expression profile of same set of 15 genes were compared in breast and lung cancer exosome derived mRNA with (n = 10) and without (n = 10) bone metastases against healthy controls. ROC curve analysis performed individually for all the 15 genes shortlisted the 5 most relevant genes with significant sensitivity and specificity in both cancers. This liquid biopsy-based bone metastases predictor using multi-gene panel is a unique approach with potential clinical applications for effective management of aggressive cancers.
骨转移是进展期癌症患者常见的转移部位之一，也是癌症相关死亡的主要原因。本研究的目的是建立一种基于液体活检的多基因分类器及相关信号通路，用于骨转移的早期诊断。我们使用了公开可用的微阵列数据集，并使用GeneSpring软件以平台/芯片特异性方式对其进行分析。基因表达数据集的分析确定了15个持续过度表达且具有统计学意义的基因。此外，将这15个相同基因的表达谱在有骨转移（n = 10）和无骨转移（n = 10）的乳腺癌和肺癌外泌体衍生mRNA中与健康对照进行比较。对所有15个入围基因分别进行ROC曲线分析，筛选出在两种癌症中具有显著敏感性和特异性的5个最相关基因。这种基于液体活检的使用多基因面板的骨转移预测器是一种独特的方法，对侵袭性癌症的有效管理具有潜在的临床应用价值。
