Ferroptosis-Related Gene Model to Predict Overall Survival of Ovarian Carcinoma

Abstract

Background. Ovarian cancer (OC) is the eighth most common cause of cancer death and the second cause of gynecologic cancer death in women around the world. Ferroptosis, an iron-dependent regulated cell death, plays a vital role in the development of many cancers. Applying expression of ferroptosis-related gene to forecast the cancer progression is helpful for cancer treatment. However, the relationship between ferroptosis-related genes and OC patient prognosis is still vastly unknown, making it still a challenge for developing ferroptosis therapy for OC. Methods. The Cancer Genome Atlas (TCGA) data of OC were obtained and the datasets were randomly divided into training and test datasets. A novel ferroptosis-related gene signature associated with overall survival (OS) was constructed according to the training cohort. The test dataset and ICGC dataset were used to validate this signature. Results. We constructed a model containing nine ferroptosis-related genes, namely, LPCAT3, ACSL3, CRYAB, PTGS2, ALOX12, HSBP1, SLC1A5, SLC7A11, and ZEB1, and predicted the OS of OC in TCGA. At a suitable cutoff, patients were divided into low risk and high risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics (ROCs) were as high as 0.664, respectively. Then, the test dataset and the ICGC dataset were used to evaluate our model, and the ROCs of test dataset were 0.667 and 0.777, respectively. In addition, functional analysis and correlation analysis showed that immune-related pathways were significantly enriched. Meanwhile, we also integrated with other clinical factors and we found the synthesized clinical factors and ferroptosis-related gene signature improved prognostic accuracy relative to the ferroptosis-related gene signature alone. Conclusion. The ferroptosis-related gene signature could predict the OS of OC patients and improve therapeutic decision-making.

Identification of a glycolysis‐related gene signature for survival prediction of ovarian cancer patients

“…In our study, the AUCs of the signatures at 3, and 5 years were 0.709, 0.762, respectively, which were significantly higher than those of most hallmark predictive models. Table 4 shows that the AUCs of the other three prognostic signatures, namely, the 21 immune‐related gene signature, 35 17 immune‐related gene signature (0.754 at 3 years, 0.824 at 5 years) 36 and 17 transcription factor ‐related gene signature (0.803 at 5 years), 37 were comparable to the predictive capabilities of our predictive model and distinctly higher than those of other signatures, such as the epithelial‐mesenchymal transition related gene signature, 38 TME‐related gene signature, 39,40 RNA‐binding protein‐related gene signature, 41 energy metabolism‐related gene signature, 42 autophagy‐related gene signature, 43,44 ferroptosis‐related gene signature, 45 protein‐coding gene signature, 46 and DNA methylated gene signatures 47 . The larger the AUC value of a biomarker, the better was the predictive ability of the signature, indicating that our gene signature outperformed most of the other signatures in predicting OV prognosis.…”

“…The included studies 11,35–47,54–61 used models built based on the TCGA cohort and involved all types of breast cancer. The final results showed that our signature and three other prognostic signatures, namely, a 21 immune‐related gene signature, 35 17 immune‐related gene signature 36 and 17 TF‐related gene signature 37 performed better than the other hallmark signatures in the prediction of OS in patients with OV 11,35,38–47,54–61 . Additionally, Yu et al has constructed a five GRG signature (ANGPTL4, PYGB, ISG20, SEH1L and IRS2) for patients with OV 62 .…”

Table_7.XLSX

“…be a feasible treatment of pancreatic cancer. Similar research results can also be found in lung adenocarcinoma, ovarian carcinoma, and uveal melanoma (Gao et al, 2021;Luo and Ma, 2021;Yang L. et al, 2021). However, no studies have attempted to construct a ferroptosis-related prognostic model of PCa.…”

Identification of the Prognostic Signature Associated With Tumor Immune Microenvironment of Uterine Corpus Endometrial Carcinoma Based on Ferroptosis-Related Genes

“…As shown in Figure 4, the AUC for this signature was 0.705, which was higher than the existing ferroptosis-related signatures. This result revealed that our established signature was superior to other signatures in predicting patient's survival information (Yu et al, 2015;Liu et al, 2021;Yang et al, 2021;Zhu et al, 2021).…”