Background. Ferroptosis is a recently described form of intentional cellular damage that is iron-dependent and separate from apoptosis, cellular necrosis, and autophagy. It has been demonstrated to be adequately regulated by long noncoding RNAs (lncRNAs) in various cancers. However, the predictive profile of ferroptosis-related lncRNAs (FRLs) in endometrial carcinoma (EC) is unknown. Herein, FRLs associated with uterine corpus endometrial carcinoma (UCEC) prognosis were screened to predict treatment response in EC. Methods. Samples of EC and adjacent normal tissues were obtained from The Cancer Genome Atlas (TCGA) dataset repository. Limma and survival packages in R software were used to screen FRLs associated with the prognosis of EC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) chord and circle plots of FRLs were also plotted. Next, FRLs screened by the least absolute shrinkage and selection operator (LASSO) method were applied to construct and validate a multivariate Cox proportional risk regression model. Nomogram plots were created to forecast the outcome of UCEC patients, and gene set enrichment analysis (GSEA), principal component analysis (PCA), and immunoassays were performed on the prognostic models. Finally, limma, ggpubr, pRRophetic, and ggplot2 programs were used for drug sensitivity analysis of the prognostic models. Results. A signature based on nine FRLs (CFAP58-DT, LINC00443, EMSLR, HYI-AS1, ADIRF-AS1, LINC02474, CDKN2B-AS1, LINC01629, and LINC00942) was constructed. The developed FRL prognostic model effectively discriminated UCEC patients into low-risk and high-risk groups. Immunological checkpoints CD80 and CD40 were strongly expressed in the high-risk group. In addition, the nine FRLs were all more expressed in the high-risk group compared to the low-risk group. Conclusion. These findings significantly contribute to the understanding of the function of FRLs in UCEC and provide promising therapeutic strategies for UCEC.

Background Signal transducer and activator of transcription (STAT) is a unique protein family that binds to DNA and plays a vital role in regulating major physiological cellular processes. Seven STAT genes have been identified in the human genome. Several studies suggest STAT family members to be involved in cancer development, progression, and metastasis. However, the predictive relationship between STAT family expression and immune cell infiltration in endometrial cancer remains unknown. Methods We explored STAT family expression and prognosis in endometrial cancer using various databases. The STRING, GeneMANIA, and DAVID databases, along with GO and KEGG analyses, were used to construct a protein interaction network of related genes. Finally, the TIMER database and ssGSEA immune infiltration algorithm were used to investigate the correlation of STAT family expression with the immune infiltration level in uterine corpus endometrial carcinoma (UCEC). Results Our study showed that different STAT family members are differentially expressed in UCEC. STAT1 and STAT2 expression increased at various stages of UCEC, and STAT5A, STAT5B, and STAT6 levels were decreased. STAT3 and STAT4 expression was not significantly different between UCEC and normal tissues. High STAT1 expression may be a prognostic disadvantage of UCEC, and high STAT6 expression may improve UCEC patient prognosis. The STAT family‐associated genes were significantly enriched in signal transduction, protein binding, DNA binding, and ATP binding upon GO analysis. Related genes in the KEGG analysis were mainly enriched in pathways in cancer, viral carcinogenesis, chemokine signaling pathway, JAK/STAT signaling pathway, and regulation of the actin cytoskeleton. In terms of immune infiltration, STAT1 and STAT2 were positively correlated with B, CD8+ T, CD4+ T, and dendritic cells, and neutrophils (p < 0.05). All STAT family members were positively correlated with neutrophils and dendritic cells (p < 0.05). STAT1 and STAT2 showed similar correlations with all immune cell types, whereas STAT1 and STAT6 showed opposite correlations. Conclusion These findings suggest that the STAT family is a prognostic marker, and the immune infiltration level, a therapeutic target, for endometrial cancer.

Background N6‐methyladenosine (m6A) has been identified as the most common, abundant, and conserved internal transcriptional modification. Long noncoding RNAs (lncRNAs) are noncoding RNAs consisting of more than 200 nucleotides, and the expression of various lncRNAs may affect cancer prognosis. The impact of m6A‐associated lncRNAs on uterine corpus endometrial carcinoma (UCEC) prognosis is unknown. Methods In this study, UCEC prognosis‐related m6A lncRNAs were screened, bioinformatics analysis was performed, and experimental validation was conducted. Endometrial carcinoma (EC) and normal tissue samples were obtained from The Cancer Genome Atlas. The prognosis‐related m6A lncRNAs screened by the least absolute shrinkage and selection operator method were used for multivariate Cox proportional risk regression modeling. Principal component analysis and Gene Ontology, immune function difference, and drug sensitivity analyses of the prognostic models were performed. Prognostic analysis was conducted for m6A‐associated lncRNAs. The immune infiltration relationship of m6A‐associated lncRNAs in EC was identified using the ssGSEA immune infiltration algorithm. A competing endogenouse RNA network was constructed using the LncACTdb database. Finally, quantitative real‐time polymerase chain reaction (qRT‐PCR) assays were used to validate the differences in m6A‐related lncRNA expression in normal and EC cells. Results CDKN2B‐AS1 and MIR924HG were found to be risk factors for EC. RAB11B‐AS1 was a protective factor in EC patients. MIR924HG expression was upregulated in KLE and RL95‐2 endometrial cancer cell lines. Prognostic models involved RAB11B‐AS1, LINC01812, HM13‐IT1, TPM1‐AS, SLC16A1‐AS1, LINC01936, and CDKN2B‐AS1. The high‐risk group was more sensitive to five compounds (ABT.263, ABT.888, AP.24534, ATRA, and AZD.0530) than the low‐risk group. Conclusion These findings contribute to understanding of the function of m6A‐related lncRNAs in UCEC and provide promising therapeutic strategies for UCEC.