Evidence map›Paper›PMID 33509222›Full record

ArticleCancer cell international2021

Tumor mutation burden in connection with immune-related survival in uterine corpus endometrial carcinoma.

Ling Zhao, Xueshu Fu, Xiling Han, Yanjun Yu, Yaping Ye, Jun Gao

Abstract read
In one paragraph

Article in Cancer cell international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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  10. Identification of 8-gene risk prediction signature associated withJournal of gastrointestinal oncology · 2022
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  18. Multiomics analysis of tumor mutational burden across cancer types.Computational and structural biotechnology journal · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ling ZhaoDepartment of Gynecology, Second Affiliated Hospital of Guizhou Medical University, Qiandongnan Second People's Hospital, Kaili, 556000, Guizhou, China.
Xueshu FuDepartment of Gynecology, Huaian Maternity and Child Health Care Hospital, Huaian, 223002, Jiangsu, China.
Xiling HanDepartment of Obstetrics and Gynecology, Clinical Medical College of Yangzhou University, Yangzhou, 225001, Jiangsu, China.
Yanjun YuDepartment of Gynecologic Oncology, Dalian Medical University, Dalian, 116000, Liaoning, China.
Yaping YeDepartment of Gynecologic Oncology, Dalian Medical University, Dalian, 116000, Liaoning, China.
Jun GaoDepartment of Obstetrics and Gynecology, Northern Jiangsu People's Hospital, 98 W Nantong Rd, Yangzhou, 225001, Jiangsu, China. gaojunyefeng@163.com.ORCID http://orcid.org/0000-0002-8875-2826

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUCEC is the most common gynecological malignancy in many countries, and its mechanism of occurrence and development is related to tumor mutation burden (TMB) and immune cell infiltration. Therefore, it is necessary to systematically explore the TMB-related gene profile in immune cells to improve the prognosis of UCEC.

methodsWe integrated TMB-related genes with basic clinical information of UCEC patients based on TCGA dataset. Differentially expressed genes (DEGs) were selected through differential expression screening, PPI, and enrichment analysis. Additionally, we analyzed the components of immune cell infiltration of the DEGs to obtain the differential immunity-related genes. A single factor and multifactor Cox regression analyses were conducted to establish new prognostic indicators of OS and DFS based on TMB-related immune genes. To further study the correlation between survival and immune cell infiltration, a Cox model based on these immune infiltration compositions was built. Using the clinical variables, we established nomograms for OS and DFS.

results393 DEGs were significantly associated with clinical outcomes and the immune component in patients with UCEC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway and protein-protein interaction network (PPI) analyses revealed the role of these genes and information on related pathways. Then, two prognostic models were established based on the differential immune genes for OS (GFAP and MX2) and DFS (MX2, GFAP, IGHM, FGF20, and TRAV21). In DFS, the differential immune genes were related to CD4+ T cell, CD8+ T cell, macrophage, and neutrophil (all P < 0.05). B cell and CD8+ T cell were independent prognostic factors from among the immune cell elements in UCEC. Finally, the risk scores of these models were combined with the clinical elements-based nomogram models, and the AUC values were all over 0.7.

conclusionsOur results identified several clinically significant differential immune genes and established relevant prognostic models, providing a basis for the molecular analysis of TMB and immune cells in UCEC, and identified potential prognostic and immune-related genes for UCEC. We added clinical related conditions for further analysis to confirm the identity of the genes and clinical elements-based models.

Indexed as

Endometrial carcinomaImmune-related survivalTCGATumor mutation burden

Identifiers

PMID33509222
PMCPMC7842022

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