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印度亚组中口腔鳞状细胞癌患者的转录组特征分析。

Transcriptomic Profiling of OSCC Patients in an Indian Subset.

机构信息

Department of Microbiology, School of Science, RK University, Rajkot, Gujarat, India.

Shashwat Haemato Onco Associates, Rajkot, Gujarat, India.

出版信息

Asian Pac J Cancer Prev. 2024 Jan 1;25(1):233-239. doi: 10.31557/APJCP.2024.25.1.233.

Abstract

BACKGROUND

Tumor-specific biomarkers are needed for accomplishing antidote in early detection, as well as prognosis and designing therapeutic strategies. Comprehensive transcriptome profiling offers critical insights into the disease and reveal new avenue for drug discovery.

METHODS

Total 5 cancerous and histopathological normal tissue pairs of 5 OSCC patients included in the petite study. Transcriptome sequencing was performed using Roche's 454 sequencing platform followed by CLC Genomics Workbench was used to examine gene expression in OC development.

RESULTS

A total 2082 genes were differentially expressed across all the five tumor-control pairs collected from the OC patients during the surgery. From these 1092 upregulated and 273 downregulated genes, whereas 717 genes were found to be non-significant. The genes with pvalue <0.05 and log2foldchange > 1 or log2foldchange < -1 were considered for further enrichment analysis. Topfunn was used for gene enrichment analysis to identify gene enrichment pathway analysis found some cancer related pathways such as TNF signaling, p53 signaling pathway, cGMP-PKG signaling pathway, Apelin signaling pathway and IL-17 signaling pathway were strikingly involved in proliferation and apoptosis of tumor cells. The PPI network construction was performed and identified 8 best protein interactions.

CONCLUSION

The current study reports molecular biomarkers including INHBA, FJX1, OLR1, CDK2, IGHM, CXCL11, SH2D5 and FABP5 associated with cancer that can led to identify potential therapeutic targets for the better prognosis of the cancer patients. The signature candidate can be translated to clinical practice to increase early diagnostic accuracy.

摘要

背景

需要肿瘤特异性生物标志物来实现早期检测的解毒剂,以及预后和设计治疗策略。综合转录组谱分析为疾病提供了关键的见解,并为药物发现开辟了新途径。

方法

这项小型研究共纳入了 5 名 OSCC 患者的 5 对癌组织和组织病理学正常组织。使用罗氏 454 测序平台进行转录组测序,然后使用 CLC Genomics Workbench 检查 OC 发生过程中的基因表达。

结果

总共在 5 名手术期间的 OC 患者的所有 5 对肿瘤-对照中检测到 2082 个差异表达基因。这些基因中,有 1092 个上调基因和 273 个下调基因,而 717 个基因没有显著差异。将 p 值 <0.05 且 log2foldchange > 1 或 log2foldchange < -1 的基因用于进一步的富集分析。使用 Topfunn 进行基因富集分析,以确定基因富集通路分析发现了一些与癌症相关的通路,如 TNF 信号通路、p53 信号通路、cGMP-PKG 信号通路、Apelin 信号通路和 IL-17 信号通路,这些通路与肿瘤细胞的增殖和凋亡密切相关。进行了 PPI 网络构建,并确定了 8 个最佳的蛋白质相互作用。

结论

本研究报告了与癌症相关的分子生物标志物,包括 INHBA、FXJ1、OLR1、CDK2、IGHM、CXCL11、SH2D5 和 FABP5,这些标志物可用于确定潜在的治疗靶点,以改善癌症患者的预后。该签名候选物可以转化为临床实践,以提高早期诊断的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/114b/10911733/92a84b89ed91/APJCP-25-233-g001.jpg

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