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通过文本挖掘和数据分析鉴定与头颈部鳞状细胞癌放射抵抗相关的四基因标志物。

A Four-Gene Signature Associated with Radioresistance in Head and Neck Squamous Cell Carcinoma Identified by Text Mining and Data Analysis.

机构信息

Department of Oncology, The First Hospital of Hebei Medical University, Shijiazhuang, 050031 Hebei, China.

Department of Neurology, The First Hospital of Hebei Medical University, Shijiazhuang, 050031 Hebei, China.

出版信息

Comput Math Methods Med. 2022 Sep 27;2022:5693806. doi: 10.1155/2022/5693806. eCollection 2022.

DOI:10.1155/2022/5693806
PMID:36203528
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9532131/
Abstract

PURPOSE

Head and neck squamous cell carcinoma (HNSCC) is the sixth leading cancer globally, and radiotherapy plays a crucial part in its treatment. This study was designed to identify potential genes related to radiation resistance in HNSCC.

METHOD

We first used text mining to obtain common genes related to radiotherapy resistance and HNSCC in published articles. Functional enrichment analyses were conducted to identify the significantly enriched pathways and genes. Protein and protein interactions were performed, and the most significant gene modules were determined; then, genes in the gene modules were validated at transcriptional levels and overall survival. Gene set variation analysis (GSVA) score was calculated, and the association between GSVA score and survival/pathway was estimated. Immune cell infiltration, methylation, and genetic alteration analysis of these genes was conducted in HNSCC patients. Finally, potential sensitive anticancer drugs related to target genes were obtained.

RESULT

We identified 583 common genes through text mining. After further validation, a four-gene signature (EPHB2, SPP1, SERPINE1, and VEGFC) was constructed. The patients with higher GSVA scores have a worse prognosis than those with lower GSVA scores. Differences in methylation of these four genes in HNSCC tumor tissue and normal tissue were compared, with higher methylation levels of EBPH2 and SPP1 in normal tissue and higher methylation levels of SERPINE1 in the tumor. Immune cell infiltration revealed that the increased expression of these genes was closely related to the infiltration level of CD4+ T cell, neutrophil, macrophage, and dendritic cell. Thirty drugs, including 22 positively and eight negatively correlated drugs that most correlated with related genes, were available for treating HNSCC.

CONCLUSION

In this study, we identified four potential genes as well as corresponding drugs that might be related to radioresistance in HNSCC patients. These candidate genes may provide a promising avenue to further elevate radiotherapy efficacy.

摘要

目的

头颈部鳞状细胞癌(HNSCC)是全球第六大常见癌症,放射治疗在其治疗中起着至关重要的作用。本研究旨在鉴定与 HNSCC 放射抵抗相关的潜在基因。

方法

我们首先使用文本挖掘从已发表的文章中获取与放疗抵抗和 HNSCC 相关的常见基因。进行功能富集分析以鉴定显著富集的通路和基因。进行蛋白质和蛋白质相互作用,确定最显著的基因模块;然后,在转录水平和总体生存中验证基因模块中的基因。计算基因集变异分析(GSVA)评分,并估计 GSVA 评分与生存/通路的相关性。对 HNSCC 患者进行这些基因的免疫细胞浸润、甲基化和遗传改变分析。最后,获得与靶基因相关的潜在敏感抗癌药物。

结果

我们通过文本挖掘确定了 583 个常见基因。进一步验证后,构建了一个由四个基因(EPHB2、SPP1、SERPINE1 和 VEGFC)组成的特征基因。GSVA 评分较高的患者预后较 GSVA 评分较低的患者差。比较这些四个基因在 HNSCC 肿瘤组织和正常组织中的甲基化差异,发现正常组织中 EBPH2 和 SPP1 的甲基化水平较高,肿瘤组织中 SERPINE1 的甲基化水平较高。免疫细胞浸润表明,这些基因的表达增加与 CD4+T 细胞、中性粒细胞、巨噬细胞和树突状细胞的浸润水平密切相关。有 30 种药物,包括 22 种与相关基因最相关的阳性药物和 8 种阴性药物,可用于治疗 HNSCC。

结论

在这项研究中,我们鉴定了四个可能与 HNSCC 患者放射抵抗相关的潜在基因和相应药物。这些候选基因可能为进一步提高放射治疗效果提供有希望的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/e8c405fbe8c7/CMMM2022-5693806.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/80242051e5e6/CMMM2022-5693806.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/a09a28fbdfd5/CMMM2022-5693806.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/1d9e4153c60e/CMMM2022-5693806.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/9101840e74a3/CMMM2022-5693806.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/257e3e5f2906/CMMM2022-5693806.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/26e9f3596858/CMMM2022-5693806.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/e8c405fbe8c7/CMMM2022-5693806.007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/80242051e5e6/CMMM2022-5693806.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/a09a28fbdfd5/CMMM2022-5693806.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/1d9e4153c60e/CMMM2022-5693806.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/9101840e74a3/CMMM2022-5693806.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/257e3e5f2906/CMMM2022-5693806.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/26e9f3596858/CMMM2022-5693806.006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc19/9532131/e8c405fbe8c7/CMMM2022-5693806.007.jpg

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