The IFN-γ-related long non-coding RNA signature predicts prognosis and indicates immune microenvironment infiltration in uterine corpus endometrial carcinoma

被引:9
作者
Gu, Chunyan [1 ]
Lin, Chen [2 ]
Zhu, Zheng [3 ]
Hu, Li [4 ]
Wang, Fengxu [5 ]
Wang, Xuehai [5 ]
Ruan, Junpu [5 ]
Zhao, Xinyuan [5 ]
Huang, Sen [1 ]
机构
[1] Nantong Haimen Peoples Hosp, Dept Obstet & Gynecol, Nantong, Peoples R China
[2] Ctr Dis Prevent & Control Pudong New Area Shanghai, Vectors & Parasitosis Control & Prevent Sect, Shanghai, Peoples R China
[3] Nanjing Med Univ, Affiliated Hosp 1, Dept Urol, Nanjing, Peoples R China
[4] Nanjing Med Univ, Kangda Coll, Dept Med, Lianyungang, Peoples R China
[5] Nantong Univ, Sch Publ Hlth, Dept Occupat Med & Environm Toxicol, Nantong Key Lab Environm Toxicol, Nantong, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2022年 / 12卷
基金
中国国家自然科学基金;
关键词
interferon-gamma; bioinformatics; signature; immunology; endometrial carcinoma; INTERFERON-GAMMA; LNCRNA SIGNATURE; SURVIVAL;
D O I
10.3389/fonc.2022.955979
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundOne of the most common diseases that have a negative impact on women's health is endometrial carcinoma (EC). Advanced endometrial cancer has a dismal prognosis and lacks solid prognostic indicators. IFN-gamma is a key cytokine in the inflammatory response, and it has also been suggested that it has a role in the tumor microenvironment. The significance of IFN-gamma-related genes and long non-coding RNAs in endometrial cancer, however, is unknown. MethodsThe Cancer Genome Atlas (TCGA) database was used to download RNA-seq data from endometrial cancer tissues and normal controls. Genes associated with IFN-gamma were retrieved from the gene set enrichment analysis (GSEA) website. Co-expression analysis was performed to find lncRNAs linked to IFN-gamma gene. The researchers employed weighted co-expression network analysis (WGCNA) to find lncRNAs that were strongly linked to survival. The prognostic signature was created using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression. The training cohort, validation cohort, and entire cohort of endometrial cancer patients were then split into high-risk and low-risk categories. To investigate variations across different risk groups, we used survival analysis, enrichment analysis, and immune microenvironment analysis. The platform for analysis is R software (version X64 3.6.1). ResultsBased on the transcript expression of IFN-gamma-related lncRNAs, two distinct subgroups of EC from TCGA cohort were formed, each with different outcomes. Ten IFN-gamma-related lncRNAs were used to build a predictive signature using Cox regression analysis and the LASSO regression, including CFAP58, LINC02014, UNQ6494, AC006369.1, NRAV, BMPR1B-DT, AC068134.2, AP002840.2, GS1-594A7.3, and OLMALINC. The high-risk group had a considerably worse outcome (p < 0.05). In the immunological microenvironment, there were also substantial disparities across different risk categories. ConclusionOur findings give a reference for endometrial cancer prognostic type and immunological status assessment, as well as prospective molecular markers for the disease.
引用
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页数:15
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