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作为候选预后生物标志物的泛癌分析及其与免疫浸润的关联。

Pan-cancer analysis of as a candidate prognostic biomarker and associated with immune infiltration.

作者信息

Jia Boquan, Liu Jun, Hu Xin, Xia Lu, Han Ying

机构信息

Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, China.

Department of Clinical Laboratory, Affiliated Xiaoshan Hospital, Hangzhou Normal University, Hangzhou, China.

出版信息

Ann Transl Med. 2022 Dec;10(24):1355. doi: 10.21037/atm-22-5598.

DOI:10.21037/atm-22-5598
PMID:36660720
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9843344/
Abstract

BACKGROUND

DEP domain containing 1 (DEPDC1) gene is upregulated in several malignancies and contributes to tumorigenesis. Although the role of DEPDC1 in tumor is becoming increasingly popular, the function of DEPDC1 in pan-cancer still needs to be systematically elucidated.

METHODS

Data were downloaded from Genotype-Tissue Expression Data (GTEx), The Cancer Genome Atlas (TCGA) TIMER2.0, TISIDB, STRING, and CancerSEA databases and analyzed to determine the functionality of the . The results were visualized using tools provided by the databases and the R language.

RESULTS

The results showed that was significantly upregulated in 29 of the 33 human cancers analyzed. In addition, there were significant differences in expression among cancer immune and molecular subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that was mainly involved in the cell cycle, and CancerSEA analysis showed that promoted cell cycle, DNA repair, DNA damage, and proliferation in pan-cancer. Receiver operating characteristic (ROC) curve analysis showed high predictive accuracy for pan-cancer. expression was positively correlated with activated CD4 T helper 2 cells and common lymphoid progenitor cells, and negatively correlated with natural killer (NK) T cells, CD4 central memory T cells, and CD4 effector memory T cells. Furthermore, was significantly positively correlated with T cell exhaustion marker genes, such as , transforming growth factor beta receptor 1 (TGFBR1), kinase insert domain receptor (KDR), programmed cell death 1 ligand 2 (PDCD1LG2), granzyme B (), and granulysin (). Additionally, was associated with overall survival (OS), disease-specific survival (DSS), and progress-free interval (PFI) prognosis in multiple tumor types. The ROC analysis showed high predictive accuracy for pan-cancer.

CONCLUSIONS

Collectively, is aberrantly expressed and plays an immune-oncogenic role in pan-cancer, and may serve as a biomarker for cancer diagnosis and therapy.

摘要

背景

含DEP结构域蛋白1(DEPDC1)基因在多种恶性肿瘤中上调并促进肿瘤发生。尽管DEPDC1在肿瘤中的作用越来越受到关注,但其在泛癌中的功能仍需系统阐明。

方法

从基因型-组织表达数据(GTEx)、癌症基因组图谱(TCGA)、TIMER2.0、TISIDB、STRING和CancerSEA数据库下载数据并进行分析,以确定[具体基因名称]的功能。结果使用数据库提供的工具和R语言进行可视化。

结果

结果显示,在分析的33种人类癌症中的29种中,[具体基因名称]显著上调。此外,癌症免疫和分子亚型之间的[具体基因名称]表达存在显著差异。基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析表明,[具体基因名称]主要参与细胞周期,CancerSEA分析表明,[具体基因名称]在泛癌中促进细胞周期、DNA修复、DNA损伤和增殖。受试者工作特征(ROC)曲线分析显示对泛癌具有较高的预测准确性。[具体基因名称]表达与活化的CD4辅助性T细胞2和常见淋巴祖细胞呈正相关,与自然杀伤(NK)T细胞、CD4中央记忆T细胞和CD4效应记忆T细胞呈负相关。此外,[具体基因名称]与T细胞耗竭标记基因,如[具体基因名称]、转化生长因子β受体1(TGFBR1)、激酶插入结构域受体(KDR)、程序性细胞死亡1配体2(PDCD1LG2)、颗粒酶B([具体基因名称])和颗粒溶素([具体基因名称])显著正相关。此外,[具体基因名称]与多种肿瘤类型的总生存期(OS)、疾病特异性生存期(DSS)和无进展生存期(PFI)预后相关。ROC分析显示对泛癌具有较高的预测准确性。

结论

总体而言,[具体基因名称]在泛癌中异常表达并发挥免疫致癌作用,[具体基因名称]可能作为癌症诊断和治疗的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/3738b0f98cb2/atm-10-24-1355-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/887237834e1f/atm-10-24-1355-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/925d9ad35627/atm-10-24-1355-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/a4c894e5b2e6/atm-10-24-1355-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/13aad36d0161/atm-10-24-1355-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/89aecd48b4c0/atm-10-24-1355-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/29ec228c9411/atm-10-24-1355-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/56aa6aed4848/atm-10-24-1355-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/b73823ceaf28/atm-10-24-1355-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/3738b0f98cb2/atm-10-24-1355-f9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/887237834e1f/atm-10-24-1355-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/925d9ad35627/atm-10-24-1355-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/a4c894e5b2e6/atm-10-24-1355-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/13aad36d0161/atm-10-24-1355-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/89aecd48b4c0/atm-10-24-1355-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/29ec228c9411/atm-10-24-1355-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/56aa6aed4848/atm-10-24-1355-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/b73823ceaf28/atm-10-24-1355-f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0c06/9843344/3738b0f98cb2/atm-10-24-1355-f9.jpg

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