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. 2022 Jul 22:13:912037.
doi: 10.3389/fgene.2022.912037. eCollection 2022.

Identification and Validation of Cuproptosis-Related Prognostic Signature and Associated Regulatory Axis in Uterine Corpus Endometrial Carcinoma

Yun Chen  1
Affiliations

Identification and Validation of Cuproptosis-Related Prognostic Signature and Associated Regulatory Axis in Uterine Corpus Endometrial Carcinoma

Yun Chen. Front Genet. .

Abstract

Background: Uterine corpus endometrial carcinoma (UCEC) is a common gynecological malignancy globally with high recurrence and mortality rates. Cuproptosis is a new type of programmed cell death involved in tumor cell proliferation and growth, angiogenesis, and metastasis. Methods: The difference in cuproptosis-related genes (CRGs) between UCEC tissues and normal tissues deposited in The Cancer Genome Atlas database was calculated using the "limma" R package. LASSO Cox regression analysis was conducted to construct a prognostic cuproptosis-related signature. Kaplan-Meier analysis was conducted to compare the survival of UCEC patients. A ceRNA network was constructed to identify the lncRNA-miRNA-mRNA regulatory axis. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was performed to verify CRG expression in UCEC. Results: The expression of FDX1, LIAS, DLAT, and CDKN2A were upregulated, whereas the expression of LIPT1, DLD, PDHB, MTF1, and GLS were downregulated in UCEC versus normal tissues. The genetic mutation landscape of CRGs in UCEC was also summarized. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that these CRGs were enriched in the tricarboxylic acid (TCA) cycle, glycolysis, and HIF-1 signaling pathway. LASSO Cox regression analysis was performed and identified a cuproptosis-related prognostic signature including these three prognostic biomarkers (CDKN2A, GLS, and LIPT1). UCEC patients with high risk scores had a poor prognosis with an area under the curve of 0.782 and 0.764 on 3- and 5-year receiver operating characteristic curves. Further analysis demonstrated a significant correlation between CDKN2A and pTNM stage, tumor grade, immune cell infiltration, drug sensitivity, tumor mutational burden (TMB) score, and microsatellite instable (MSI) score. The data validation of qRT-PCR further demonstrated the upregulation of CDKN2A and the downregulation of LIPT1 and GLS in UCEC versus normal tissues. The ceRNA network also identified lncRNA XIST/miR-125a-5p/CDKN2A regulatory axis for UCEC. Conclusion: The current study identified a cuproptosis-related prognostic signature including these three prognostic biomarkers (CDKN2A, GLS, and LIPT1) for UCEC. The ceRNA network also identified that lncRNA XIST/miR-125a-5p/CDKN2A regulatory axis may be involved in the progression of UCEC. Further in vivo and in vitro studies should be conducted to verify these results.

Keywords: CDKN2A; cuproptosis; immunotherapy; prognostic signature; uterine corpus endometrial carcinoma.

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Conflict of interest statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Expression of cuproptosis-related genes (CRGs) in uterine corpus endometrial carcinoma (UCEC). (A) The mRNA level of CRG in UCEC versus normal tissues. (B) The correlation between each member of CRG in UCEC. *p < 0.05; **p < 0.01; and ***p < 0.001;—p > 0.05.
FIGURE 2
FIGURE 2
Mutation landscape of cuproptosis-related genes (CRGs) in uterine corpus endometrial carcinoma (UCEC). (A,B) Single nucleotide variation analysis of CRG in UCEC. (C) Copy number variation analysis of CRG in UCEC.
FIGURE 3
FIGURE 3
Enrichment analysis of cuproptosis-related genes in uterine corpus endometrial carcinoma. (A) Enriched items in gene ontology analysis. (B) Enriched items in Kyoto Encyclopedia of Genes and Genomes. BP, biological process; CC, cellular component; MF molecular function.
FIGURE 4
FIGURE 4
Prognostic significance of cuproptosis-related genes (CRGs) in uterine corpus endometrial carcinoma (UCEC). (A) Result of overall survival analysis of CRGs in UCEC. (B) Result of progression-free survival analysis of CRGs in UCEC. (C) Result of disease-free survival analysis of CRGs in UCEC. OS, overall survival; PFS, progression-free survival; DFS, disease-free survival.
FIGURE 5
FIGURE 5
A cuproptosis-related prognostic signature in uterine corpus endometrial carcinoma (UCEC). (A,B) Coefficient and partial likelihood deviance of prognostic signature. (C) The risk score distribution, patient survival status, and cuproptosis-related gene expression profile of prognostic signature. (D,E) Survival curve of UCEC patients with high/low-risk score and ROC curve of prognostic signature.
FIGURE 6
FIGURE 6
Development of a predictive nomogram. (A,B) Univariate and multivariate Cox regression considering clinical parameters and cuproptosis-related prognostic biomarkers. (C,D) Predictive nomogram to predict the 3- and 5-year survival of uterine corpus endometrial carcinoma patients. Calibration curve for the survival nomogram model in the discovery group. A dashed diagonal line represents the ideal nomogram.
FIGURE 7
FIGURE 7
Expression of cuproptosis-related prognostic biomarkers in different groups of uterine corpus endometrial carcinoma (UCEC) patients. (A–C) Expression of CDKN2A, GLS, and LIPT1 in UCEC patients in different pTNM stages. (D–F) Expression of CDKN2A, GLS, and LIPT1 in UCEC patients in different tumor grades.
FIGURE 8
FIGURE 8
Immune cell infiltration and drug sensitivity analysis of cuproptosis-related prognostic biomarkers in uterine corpus endometrial carcinoma (UCEC). (A–C) Correlation between the expression of CDKN2A, GLS, and LIPT1 and immune cell infiltration in UCEC. (D–F) Correlation between copy number variation of CDKN2A, GLS, and LIPT1 and immune cell infiltration in UCEC. (G) Correlation between the expression of CDKN2A, GLS, and LIPT1 and drug sensitivity in UCEC. GDSC, genomics of drug sensitivity in cancer.
FIGURE 9
FIGURE 9
TMB and MSI of cuproptosis-related prognostic biomarkers in uterine corpus endometrial carcinoma (UCEC). (A-C) Correlation between the expression of CDKN2A, GLS, and LIPT1 and TMB score in UCEC. (D–F) Correlation between the expression of CDKN2A, GLS, and LIPT1 and MSI score in UCEC. TMB, tumor mutation burden; MSI, microsatellite instability.
FIGURE 10
FIGURE 10
lncRNA–miRNA–mRNA regulatory axis in uterine corpus endometrial carcinoma (UCEC). (A) The miRNA targets predicted by TargetScan, miRWalk, and StarBase. (B–D) The expression and prognosis significance of miRNA target in UCEC. (F) The lncRNA targets predicted by lncBase and StarBase. (F,G) Expression and prognosis significance of lncRNA XIST in UCEC.
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