通过生物信息学分析和机器学习识别和验证甲状腺乳头状癌和桥本甲状腺炎的潜在常见生物标志物。
Identification and validation of potential common biomarkers for papillary thyroid carcinoma and Hashimoto's thyroiditis through bioinformatics analysis and machine learning.
发表日期:2024 Jul 06
作者:
Hui Jiang, Yanbin He, Xiaofeng Lan, Xiang Xie
来源:
Disease Models & Mechanisms
摘要:
越来越多的证据表明桥本甲状腺炎 (HT) 可能会增加患甲状腺乳头状癌 (PTC) 的风险。然而,HT 和 PTC 之间的确切关系仍不完全清楚。本研究的目的是确定可能与 PTC 和 HT 相关的潜在常见生物标志物。收集来自 GEO 数据库的三个微阵列数据集和来自 TCGA 数据库的 RNA-seq 数据集,以识别 HT 和 PTC 之间共享的差异表达基因 (DEG)。通过GO和KEGG分析,共有101个基因被鉴定为常见DEG,主要富集了炎症和免疫相关通路。我们进行了蛋白质-蛋白质相互作用分析,并确定了 6 个重要模块,总共包含 29 个基因。随后,使用随机森林(RF)算法选择树中心基因(CD53、FCER1G、TYROBP)来开发三种诊断模型。人工神经网络(ANN)模型表现出卓越的性能。值得注意的是,CD53 对 ANN 模型输出的影响最大。我们使用人类蛋白质图谱数据库分析了这三个基因的蛋白质表达。此外,我们通过免疫浸润分析观察到各种失调的免疫细胞与中枢基因显着相关。免疫荧光染色证实了CD53、FCER1G和TYROBP的差异表达以及免疫浸润分析的结果。最后,我们假设苄青霉酰聚赖氨酸和阿司匹林可能有效治疗 HT 和 PTC,并可能预防 HT 癌变。本研究表明CD53、FCER1G和TYROBP在HT和PTC的发展中发挥作用,并可能有助于HT进展为PTC。这些中心基因有可能作为 PTC 和 HT 的诊断标记和治疗靶点。© 2024。作者。
There is a growing body of evidence suggesting that Hashimoto's thyroiditis (HT) may contribute to an increased risk of papillary thyroid carcinoma (PTC). However, the exact relationship between HT and PTC is still not fully understood. The objective of this study was to identify potential common biomarkers that may be associated with both PTC and HT. Three microarray datasets from the GEO database and RNA-seq dataset from TCGA database were collected to identify shared differentially expressed genes (DEGs) between HT and PTC. A total of 101 genes was identified as common DEGs, primarily enriched inflammation- and immune-related pathways through GO and KEGG analysis. We performed protein-protein interaction analysis and identified six significant modules comprising a total of 29 genes. Subsequently, tree hub genes (CD53, FCER1G, TYROBP) were selected using random forest (RF) algorithms for the development of three diagnostic models. The artificial neural network (ANN) model demonstrates superior performance. Notably, CD53 exerted the greatest influence on the ANN model output. We analyzed the protein expressions of the three genes using the Human Protein Atlas database. Moreover, we observed various dysregulated immune cells that were significantly associated with the hub genes through immune infiltration analysis. Immunofluorescence staining confirmed the differential expression of CD53, FCER1G, and TYROBP, as well as the results of immune infiltration analysis. Lastly, we hypothesise that benzylpenicilloyl polylysine and aspirinmay be effective in the treatment of HT and PTC and may prevent HT carcinogenesis. This study indicates that CD53, FCER1G, and TYROBP play a role in the development of HT and PTC, and may contribute to the progression of HT to PTC. These hub genes could potentially serve as diagnostic markers and therapeutic targets for PTC and HT.© 2024. The Author(s).