Eswaran Sangavi, Adiga Divya, Khan G Nadeem, S Sriharikrishnaa, Kabekkodu Shama Prasada
Department of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, India.
Department of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, India.
Am J Med Sci. 2022 Jun;363(6):526-537. doi: 10.1016/j.amjms.2021.12.008. Epub 2022 Jan 5.
Cervical cancer (CC) is the fourth most common gynecological malignancy globally. This suggests the need for improved markers for prognosis, better understanding of the molecular mechanism, and targets for therapy. The defective exocytosis pathway is proposed as bona fide drivers of carcinogenesis. This study aimed to identify the exocytosis pathway network and its contribution to CC.
We screened exocytosis genes from the The Cancer Genome Atlas Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC) dataset and performed differential expression and methylation, Kaplan-Meier survival, and pathway enrichment analysis. We constructed the protein-protein interaction networks (PPIN), predicted the possible metastatic genes, and identified FDA approved drugs to target the exocytosis network in CC.
Integrated bioinformatics analysis identified 245 differentially methylated genes, including 153 hypermethylated and 92 hypomethylated genes. Further, 89 exocytosis pathway genes were differentially expressed, including 60 downregulated and 29 upregulated genes in CC. The overlapping analysis identified 39 genes as methylation regulated genes and showed an inverse correlation between methylation and expression. The HCMDB database identified nine of the identified genes (GRIK5, PTPN6, GAB2, ATP8B4, HTR2A, SPARC, CLEC3B, VWF, and S100A11) were linked with metastasis in CC. Moreover, the Kaplan-Meier survival analysis identified that high expression of PTPN6 and low expression of CLEC3B were significantly linked with poor overall survival (OS) in patients with CC. The KEGG pathway enrichment analysis identified differentially expressed genes that were mainly involved with proteoglycans in cancer, TGF-beta signaling, PI3K-Akt signaling, MAPK signaling pathway, and others. The PPIN identified 89 nodes, 192 edges with VWF, MMP9, THBS1, IGF1, CLU, A2M, IGF2, SPARC, VAMP2, and FIGF as top 10 hub genes. The drug-gene interaction analysis identified 188 FDA approved drugs targeting 32 genes, including 5 drugs that are already in use for treating CC.
In summary, we have identified the exocytosis pathway networks, candidate genes, and novel drugs for better management of CC.
宫颈癌（CC）是全球第四大常见妇科恶性肿瘤。这表明需要改进预后标志物，更好地理解分子机制以及确定治疗靶点。胞吐途径缺陷被认为是致癌的真正驱动因素。本研究旨在确定胞吐途径网络及其对宫颈癌的作用。
我们从癌症基因组图谱子宫颈鳞状细胞癌和子宫颈管腺癌（TCGA-CESC）数据集中筛选胞吐基因，并进行差异表达和甲基化、Kaplan-Meier生存分析以及通路富集分析。我们构建了蛋白质-蛋白质相互作用网络（PPIN），预测可能的转移基因，并确定针对宫颈癌胞吐网络的FDA批准药物。
综合生物信息学分析确定了245个差异甲基化基因，包括153个高甲基化基因和92个低甲基化基因。此外，89个胞吐途径基因存在差异表达，其中宫颈癌中有60个基因下调，29个基因上调。重叠分析确定了39个基因作为甲基化调控基因，并显示甲基化与表达之间呈负相关。HCMDB数据库确定所鉴定的9个基因（GRIK5、PTPN6、GAB2、ATP8B4、HTR2A、SPARC、CLEC3B、VWF和S100A11）与宫颈癌转移有关。此外，Kaplan-Meier生存分析确定PTPN6高表达和CLEC3B低表达与宫颈癌患者的总生存期（OS）差显著相关。KEGG通路富集分析确定差异表达基因主要涉及癌症中的蛋白聚糖、TGF-β信号通路、PI3K-Akt信号通路、MAPK信号通路等。PPIN确定了89个节点、192条边，其中VWF、MMP9、THBS1、IGF1、CLU、A2M、IGF2、SPARC、VAMP2和FIGF为前10个枢纽基因。药物-基因相互作用分析确定了188种FDA批准的针对32个基因的药物，其中包括5种已用于治疗宫颈癌的药物。
总之，我们已经确定了胞吐途径网络、候选基因和新型药物，以更好地管理宫颈癌。
