The Effectiveness of a Ferroptosis-Related lncRNA Model Based on CFAP58-DT for Predicting Prognosis in Endometrial Cancer

A group of researchers recently investigated the use of a prognostic ferroptosis-related long noncoding RNA (lncRNA) model based on the RNA gene CFAP58-DT for predicting the survival time of patients with endometrial cancer (EC) and to help guide their treatment. (Ann Transl Med. 2023; 11[3]:151. doi:10.21037/atm-22-6659.)

Ferroptosis is involved in different cancer processes, including diagnosis, prognosis, carcinogenesis, cancer resistance, antitumor immunity, and more. Previous studies have shown that lncRNAs play an important role in various tumors and in the tumor microenvironment (TME).

For their study, Aijun Qin, MD, Biopharmaceutical Co, Ltd, Shanghai, China, and colleagues collected the data of pathologically diagnosed patients with uterine corpus endometrial carcinoma (UCEC) up to October 24, 2022. They obtained the patients’ clinical data and transcriptome profiling, including messenger RNA (mRNA) expression, using The Cancer Genome Atlas (TCGA) database. A total of 526 UCEC patients and 23 patients with normal endometrial tissues were included in the study.

The researchers then downloaded the gene transfer format files from the Ensembl website to distinguish mRNAs and lncRNAs. The FerrDb database delivered a total of 382 ferroptosis-related genes for the coexpression analysis of the ferroptosis-related lncRNAs (gene correlation coefficients > 0.4 and P < .001).

Following a Cox regression analysis, 1,731 ferroptosis-related lncRNA were screened. The analysis confirmed 9 DEFerlncRNAs, and the researchers then used machine learning methods to construct a 9-related lncRNA prognostic model. With univariate and multivariate Cox analyses, they investigated the selected lncRNAs and then classified the patients as high and low risk according to their expression spectrum. According to the Kaplan-Meier analyses used in the study, the prognosis of low-risk patients was poor.

The enriched pathways among the high- and low-risk groups were determined using a gene set enrichment analysis, and the researchers evaluated the immune-infiltrating conditions to help improve immune therapy. In addition, they performed cytological studies on the model’s most important indicators.

“Operating characteristic curves, decision curve analysis, and a nomogram suggested the model could independently guide prognostic evaluation, with higher sensitivity, specificity, and efficiency than other common clinical characteristics,” wrote Dr Qin and colleagues.

However, the researchers acknowledged that the study had a few limitations, including that they were confined to using the only open database with EC-related clinical and survival information. They suggest that further efforts to study EC are needed. In addition, they indicated that more experiments are necessary to investigate the immune conditions and risk score differences in EC.

Overall, the researchers found that it is possible to predict immune-infiltrating conditions and prognosis for patients with EC using a ferroptosis-related lncRNA model based on CFAP58-DT.

“The clinicopathological characteristics were significantly correlated and had a positive relationship with the risk score. Thus, our model can predict the diagnosis to some degree,” added Dr Qin and colleagues.

The potential oncogenic role of CFAP58-DT can further guide immunotherapy and chemotherapy, according to the researchers. Overall, further examination of the role of ferroptosis in EC is still needed outside of its known effect on cancer cell progression. They suggest that the mechanism and relationship between lncRNAs should also be studied further.