Construction of a prognostic model of luteolin for endometrial carcinoma

Am J Transl Res. 2023 Mar 15;15(3):2122-2139. eCollection 2023.

Abstract

Objective: Endometrial cancer is one of the most common tumors of the female reproductive system, and the existing treatment options for advanced and metastatic endometrial cancer have certain limitations. The antitumor activity of luteolin has been gradually discovered. The purpose of this study was to predict the potential of luteolin in the treatment of endometrial cancer and to provide reference for future clinical drug use.

Methods: The target gene database of luteolin and differential gene dataset of uterine corpus endometrial carcinoma (UCEC) have been constructed to obtain the differential genes (DR-DEGs) for luteolin and UCEC. The Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis are performed at the same time. Genes associated with prognosis in DR-DEGs were screened and validated using univariate and multivariate COX risk regression analysis so as to construct a prognostic model. Genes are divided into high-risk and low-risk groups according to risk scores for survival analysis and the predictive effect of the model is evaluated. The role of immune function in UCEC is investigated by immune infiltration and immune checkpoint analysis Finally, Transwell experiment was conducted to investigate the effect of luteolin on the migration ability of endometrial cancer cells, and the expression changes of MMP1, IL-17 and VEGF were detected by q-PCR.

Results: Through the GO, KEGG and GSEA enrichment analysis, we have found a significant enrichment in "IL 17 signaling (IL-17) pathway", "oxidative stress response" and "HOMOLOGOUS_RECOMBINATION". Through multivariate COX risk regression analysis, four genes associated with the prognosis are harvested, including "PRSS1, MMP1, ERBB2 and NUF2" which belong to high-risk genes. Kaplan-Meier analysis shows that the survival rate in the high risk group is lower than that in the low risk group, and the receiver operating characteristic (ROC) curve reveals that the predictive effect of the model is good and stable (area under 1-year curve (AUC) 0.569, two-year AUC 0.628 and three-year AUC 0.653). Immune infiltration and immune checkpoint analysis suggest that "CD40", "T cells regulatory (Tregs)", "dendritic cells resting" and "dendritic cells activated" are correlated with survival and prognosis in UCEC patients. In in vitro experiments, we found that the migration ability of endometrial cancer cells was significantly reduced after luteolin treatment, and the expressions of MMP1, IL-17 and VEGF were all decreased.

Conclusion: Through bioinformatic analysis, we found that luteolin could slow down the progression of UCEC by inhibiting the production of inflammatory mediators such as IL-17 and oxidative stress, and constructed genetic prognostic models associated with them: PRSS1, MMP1, ERBB2 and NUF2, respectively. In addition, we found that luteolin has an inhibitory effect on the migration of endometrial cancer cells and can reduce the expressions of MMP1, IL-17 and VEGF, thus easing the progression of endometrial cancer.

Keywords: Luteolin; UCEC; bioinformatics analysis; experimental verification; treatment.