单细胞RNA序列数据分析揭示了喉部鳞状细胞癌(LSCC)的分子标记和可能的治疗靶点:一种计算机方法。

In silico pharmacology Pub Date : 2025-06-17 eCollection Date: 2025-01-01 DOI:10.1007/s40203-025-00382-w
Md Hasan Jafre Shovon, Partha Biswas, Md Imtiaz, Shirajut Mobin, Md Nazmul Hasan
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引用次数: 0

摘要

喉鳞状细胞癌(LSCC)是一种由基因突变驱动的复杂癌症,对其检测和治疗提出了重大挑战。单细胞RNA测序(scRNA-seq)已成为揭示癌症细胞异质性和确定新的治疗靶点的有前途的工具。在本研究中,我们使用scRNA-seq数据(GSE252490)来探索LSCC诊断和治疗的分子生物标志物。在对数据进行处理和标准化后,我们进行主成分分析以识别高度可变的基因。细胞聚类显示12个不同的簇,具有独特的分子特征。差异基因表达分析鉴定出6434个差异表达基因(deg),并利用基因本体富集技术对其进行进一步分析,以探索与LSCC进展相关的生物学过程。蛋白质-蛋白质相互作用(PPI)网络分析揭示了20个与关键癌症途径相关的中心基因。通过KEGG进行的途径富集分析强调了这些基因在各种癌症相关途径中的参与。值得注意的是,CCL3、EPCAM和IL8等基因的表达升高与LSCC的生存结果有关。这项全面的分析为LSCC的分子景观提供了有价值的见解,确定了潜在的生物标志物和治疗靶点,以改善诊断和治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Single-cell RNA seq data analysis reveals molecular markers and possible treatment targets for laryngeal squamous cell carcinoma (LSCC): an in-silico approach.

Laryngeal squamous cell carcinoma (LSCC), a complex cancer driven by genetic mutations, poses significant challenges for detection and treatment. Single-cell RNA sequencing (scRNA-seq) has emerged as a promising tool to uncover the cellular heterogeneity in cancer and identify novel therapeutic targets. In this study, we used scRNA-seq data (GSE252490) to explore molecular biomarkers for LSCC diagnosis and treatment. After processing and standardizing the data, we performed principal component analysis to identify highly variable genes. Cell clustering revealed 12 distinct clusters with unique molecular features. Differential gene expression analysis identified 6434 differentially expressed genes (DEGs), which were further analyzed using gene ontology enrichment to explore biological processes involved in LSCC progression. Protein-protein interaction (PPI) network analysis revealed 20 central genes associated with key cancer pathways. Pathway enrichment analysis through KEGG highlighted the involvement of these genes in various cancer-related pathways. Notably, genes such as CCL3, EPCAM, and IL8, with elevated expression, were linked to survival outcomes in LSCC. This comprehensive analysis provides valuable insights into the molecular landscape of LSCC, identifying potential biomarkers and therapeutic targets for improved diagnosis and treatment.

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