2021
DOI: 10.3390/ijms22052442
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Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients

Abstract: Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study… Show more

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Cited by 18 publications
(8 citation statements)
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“…Specifically, some TME-related genes were potentially able to predict prognosis. The same conclusions could be drawn from other studies [10,21]. Immediately thereafter, a total of 749 upregulated and 42 downregulated genes were detected between groups with high and low ImmuneScores and StromalScores, respectively.…”
Section: Discussionsupporting
confidence: 84%
“…Specifically, some TME-related genes were potentially able to predict prognosis. The same conclusions could be drawn from other studies [10,21]. Immediately thereafter, a total of 749 upregulated and 42 downregulated genes were detected between groups with high and low ImmuneScores and StromalScores, respectively.…”
Section: Discussionsupporting
confidence: 84%
“…Yang et al 28 constructed a signature based on the immune‐related genes to predict survival. Wang et al 29 constructed a cervical cancer prognostic model based on 10 immune‐related genes (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR), while AUC of 0.738 in the TCGA public database. Tian et al 30 identified that the cervical cancer patients with five notable nonsynonymous mutant genes (PIK3CA, BRAF, GNA11, FBXW7, and CDH1) metastatic relapse significantly mutated mutations had significantly poor DFS and OS.…”
Section: Discussionmentioning
confidence: 99%
“…Therefrom, we confirmed immunotherapy treatment effective and survival outcome discrepancy between the two METAscore groups, which was a compelling clue that METAscore could evaluate the sensitivity to antitumor immunotherapy. Incumbent data on the scoring system and the prognostic scores of CESC mainly concentrated on the perspectives of immunogenomics and genetic alteration ( Cai et al, 2020 ; Li et al, 2019 ; Wang et al, 2021 ; Zhang et al, 2021 ) . Comparatively, the METAscore developed in our study was a promising breakthrough on the immunometabolism, offering novel insights into CESC immune diversity from the metabolic landscape and highlighting that METAscore could predict sensitivity to immunotherapy.…”
Section: Discussionmentioning
confidence: 99%