肿瘤细胞治疗研究
英文原题：In silico analysis of driver genes in squamous cell carcinoma of the cervix: insights into their biological functions, prognosis, immune infiltration, and therapy.
我们的分析描述了SCC中的驱动基因和突变特征。本研究采用的多队列和基于网络的框架识别了值得在宫颈癌中进一步临床研究的候选枢纽基因。
宫颈癌是全球范围内影响女性生殖系统的第四大常见癌症。尽管多项研究报告了宫颈鳞状细胞癌（SCC）中的复发性突变，但对其临床相关驱动基因的全面理解仍然有限。与以往基于单队列或基于频率的报告不同，本研究整合了四个独立的宫颈鳞状细胞癌（SCC）队列，并结合基于网络的分析、多终点生存评估以及药物-基因相互作用，以优先筛选具有功能性和临床相关性的驱动枢纽基因。
在本研究中，我们对一个由467个样本组成的4例宫颈鳞状细胞癌（SCCs）队列进行了基因组分析，以识别驱动基因及其临床意义。通过功能富集分析检验了受影响的关键通路和生物学功能。使用相互作用基因/蛋白质检索工具（STRING）和CytoHubba工具构建了蛋白质-蛋白质相互作用网络（PPIN）并识别了枢纽基因。其他分析包括癌症标志物富集评估、生存评估、免疫细胞浸润谱分析和药物-基因相互作用研究。
我们的分析揭示了44个驱动基因中的9,749,109个突变。PIK3CA、KMT2C、KMT2D、FBXW7、FAT1、EP300、TP53、NOTCH1、STK11和CASP8是前10个突变基因。根据PPIN和Cytohubba分析的结果，PIK3CA、NOTCH1、PTEN、KRAS、ERBB2、TP53、ARID1A、EP300、STK11和FBXW7成为前10个枢纽基因。此外，我们在枢纽基因突变的样本中观察到2型辅助性T细胞、NK 细胞、树突状细胞和γδT细胞组成的显著差异。药物与枢纽基因相互作用的优先级分析揭示了112种临床相关化合物，尤其是HER2靶向治疗（曲妥珠单抗）、PI3K抑制剂（阿培利司）和mTOR抑制剂（依维莫司）。
BACKGROUND: Cervical cancer is the fourth most common cancer affecting the female reproductive system worldwide. Although several studies have reported recurrent mutations in cervical squamous cell carcinoma (SCC), a comprehensive understanding of the clinically relevant driver genes remains limited. Unlike previous single-cohort or frequency-based reports, this study integrates four independent cervical squamous cell carcinoma (SCC) cohorts with network-based analysis, multiendpoint survival assessment, and drug-gene interaction to prioritize functionally and clinically relevant driver hub genes. MATERIALS AND METHODS: In this study, we performed a genomic analysis of a cohort of 4 squamous cell carcinomas of the cervix (SCCs), consisting of 467 samples, to identify driver genes and their clinical significance. Key pathways and biological functions affected were tested by functional enrichment analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and CytoHubba tools were used to construct a protein‒protein interaction network (PPIN) and identify the hub genes. Additional analyses included enrichment assessment of cancer hallmarks, survival evaluation, immune cell infiltration profiling, and drug‒gene interaction studies. RESULTS: Our analysis revealed 9,749,109 mutations across 44 driver genes. PIK3CA, KMT2C, KMT2D, FBXW7, FAT1, EP300, TP53, NOTCH1, STK11, and CASP8 were the top 10 mutated genes. PIK3CA, NOTCH1, PTEN, KRAS, ERBB2, TP53, ARID1A, EP300, STK11, and FBXW7 emerged as the top 10 hub genes according to the results of the PPIN and Cytohubba analyses. In addition, we observed significant differences in T helper cell type 2, natural killer cell, dendritic cell, and gamma delta T-cell composition in samples with hub gene mutations. Prioritization analysis of drug and hub gene interactions revealed 112 clinically relevant compounds, especially HER2-directed therapies (trastuzumab), PI3K inhibitors (alpelisib), and mTOR inhibitors (everolimus). CONCLUSION: Collectively, our analysis describes the driver genes and mutation characteristics in SCC. The multi-cohort and network-based framework employed in this study identifies candidate hub genes that warrant further clinical investigation in cervical cancer.
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