Article Data

  • Views 364
  • Dowloads 112

Original Research

Open Access

Identification of ferroptosis-related risk signature and correlation with the overall survival of ovarian cancer

  • Yibin Liu1,†
  • Xin Xu2,†
  • Jianlei Wu3,†
  • Zhongkang Li1
  • Ye Zhang4
  • Xiaoxiao Zhang4
  • Shike Shui4
  • Hui Li4
  • Tiantian Wang4
  • Juan Zhai4
  • Ruixia Guo4,*,
  • Yanpeng Tian4,*,

1Department of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, 050000 Shijiazhuang, Hebei, China

2Department of Gynecological Endocrinology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, 100026 Beijing, China

3Department of Gynecological Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, 250021 Jinan, Shandong, China

4Department of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, 450000 Zhengzhou, Henan, China

DOI: 10.22514/ejgo.2023.023 Vol.44,Issue 2,April 2023 pp.58-66

Submitted: 20 May 2022 Accepted: 10 June 2022

Published: 15 April 2023

*Corresponding Author(s): Ruixia Guo E-mail:
*Corresponding Author(s): Yanpeng Tian E-mail:

† These authors contributed equally.


Ovarian cancer is a lethal female reproductive system malignancy. However, the physiological roles of ferroptosis in ovarian cancer remains unclear. In this study, biological information databases were screened to characterize and examine the differentially expressed ferroptosis-related genes between ovarian cancer and normal ovarian tissue, and to further investigate a novel risk signature for predicting the prognosis of ovarian cancer. Molecular and clinical data were retrieved from The Cancer Genome Atlas (TCGA) database. Based on these data, we identified differentially expressed ferroptosis-related genes, and construct a multigene risk signature by least absolute shrinkage and celection operator (LASSO) Cox regression to predict the prognosis of ovarian cancer. Univariate and multivariate Cox regression analysis were used to verify the prognostic value of the signature. We constructed a risk signature for ovarian cancer based on differentially expressed ferroptosis-related genes between normal ovarian samples and ovarian cancer samples. Referring to median risk score, patients were divided into high-risk group and low-risk group. We performed Cox regression analysis, principal component analysis (PCA), t-distributed stochastic neighbor embedding (t-SNE) analysis, Kaplan-Meier Survival analysis and receiver operating characteristic (ROC) curve to verify the accuracy of the predicted value of the risk signature. The overall survival rates in low-risk group was significantly higher than that in high-risk group. In addition, the area under the curve (AUC) of the ROC curve reached 0.684 at 1 year, 0.682 at 2 years and 0.661 at 3 years. Functional analysis indicated differentially expressed ferroptosis-related genes were enriched in immune-related cells. The ferroptosis-related genes signature could predict the prognosis of ovarian cancer. These genes might be potential therapeutic targets.


Ovarian cancer; Ferroptosis; Risk signature; Prognosis; Overall survival

Cite and Share

Yibin Liu,Xin Xu,Jianlei Wu,Zhongkang Li,Ye Zhang,Xiaoxiao Zhang,Shike Shui,Hui Li,Tiantian Wang,Juan Zhai,Ruixia Guo,Yanpeng Tian. Identification of ferroptosis-related risk signature and correlation with the overall survival of ovarian cancer. European Journal of Gynaecological Oncology. 2023. 44(2);58-66.


[1] Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians. 2021; 71: 209–249.

[2] Feng P, Ge Z, Guo Z, Lin L, Yu Q. A comprehensive analysis of the downregulation of miRNA-1827 and its prognostic significance by targeting SPTBN2 and BCL2L1 in ovarian cancer. Frontiers in Molecular Biosciences. 2021; 8: 687576.

[3] Lu KH. Screening for ovarian cancer in asymptomatic women. JAMA. 2018; 319: 557.

[4] Choi P, Bahrampour A, Ng S, Liu SK, Qiu W, Xie F, et al. Characterization of miR-200 family members as blood biomarkers for human and laying hen ovarian cancer. Scientific Reports. 2020; 10: 20071.

[5] Liu R, Zeng Y, Zhou C, Wang Y, Li X, Liu Z, et al. Long noncoding RNA expression signature to predict platinum-based chemotherapeutic sensitivity of ovarian cancer patients. Scientific Reports. 2017; 7: 18.

[6] Feng Z, Wen H, Jiang Z, Liu S, Ju X, Chen X, et al. A triage strategy in advanced ovarian cancer management based on multiple predictive models for R0 resection: a prospective cohort study. Journal of Gynecologic Oncology. 2018; 29: e65.

[7] Laios A, Gryparis A, DeJong D, Hutson R, Theophilou G, Leach C. Predicting complete cytoreduction for advanced ovarian cancer patients using nearest-neighbor models. Journal of Ovarian Research. 2020; 13: 117.

[8] Hong T, Lei G, Chen X, Li H, Zhang X, Wu N, et al. PARP inhibition promotes ferroptosis via repressing SLC7a11 and synergizes with ferroptosis inducers in BRCA-proficient ovarian cancer. Redox Biology. 2021; 42: 101928.

[9] Wan C, Keany MP, Dong H, Al-Alem LF, Pandya UM, Lazo S, et al. Enhanced efficacy of simultaneous PD-1 and PD-L1 immune checkpoint blockade in high-grade serous ovarian cancer. Cancer Research. 2021; 81: 158–173.

[10] Farkkila A, Gulhan DC, Casado J, Jacobson CA, Nguyen H, Kochupu-rakkal B, et al. Immunogenomic profiling determines responses to combined PARP and PD-1 inhibition in ovarian cancer. Nature Commu-nications. 2020; 11: 1459.

[11] Hirschhorn T, Stockwell BR. The development of the concept of ferroptosis. Free Radical Biology and Medicine. 2019; 133: 130–143.

[12] Basuli D, Tesfay L, Deng Z, Paul B, Yamamoto Y, Ning G, et al. Iron addiction: a novel therapeutic target in ovarian cancer. Oncogene. 2017; 36: 4089–4099.

[13] Liang J, Wang D, Lin H, Chen X, Yang H, Zheng Y, et al. A novel ferroptosis-related gene signature for overall survival prediction in patients with hepatocellular carcinoma. International Journal of Biological Sciences. 2020; 16: 2430–2441.

[14] Jiang L, Kon N, Li T, Wang S, Su T, Hibshoosh H, et al. Ferroptosis as a p53-mediated activity during tumour suppression. Nature. 2015; 520: 57–62.

[15] Lang X, Green MD, Wang W, Yu J, Choi JE, Jiang L, et al. Radiotherapy and immunotherapy promote tumoral lipid oxidation and ferroptosis via synergistic repression of SLC7a11. Cancer Discovery. 2019; 9: 1673–1685.

[16] Friedmann Angeli JP, Krysko DV, Conrad M. Ferroptosis at the crossroads of cancer-acquired drug resistance and immune evasion. Nature Reviews Cancer. 2019; 19: 405–414.

[17] You Y, Fan Q, Huang J, Wu Y, Lin H, Zhang Q. Ferroptosis-related gene signature promotes ovarian cancer by influencing immune infiltration and invasion. Journal of Oncology. 2021; 2021: 1–16.

[18] Yang L, Tian S, Chen Y, Miao C, Zhao Y, Wang R, et al. Ferroptosis-related gene model to predict overall survival of ovarian carcinoma. Journal of Oncology. 2021; 2021: 1–14.

[19] Hassannia B, Vandenabeele P, Vanden Berghe T. Targeting ferroptosis to iron out cancer. Cancer Cell. 2019; 35: 830–849.

[20] Yimit A, Adebali O, Sancar A, Jiang Y. Differential damage and repair of DNA-adducts induced by anti-cancer drug cisplatin across mouse organs. Nature Communications. 2019; 10: 309.

[21] Zheng Z, Li Y, Jin G, Huang T, Zou M, Duan S. The biological role of arachidonic acid 12-lipoxygenase (ALOX12) in various human diseases. Biomedicine & Pharmacotherapy. 2020; 129: 110354.

[22] Ye Y, Dai Q, Li S, He J, Qi H. A novel defined risk signature of the ferroptosis-related genes for predicting the prognosis of ovarian cancer. Frontiers in Molecular Biosciences. 2021; 8: 645845.

[23] Goji T, Takahara K, Negishi M, Katoh H. Cystine uptake through the cystine/glutamate antiporter xCT triggers glioblastoma cell death under glucose deprivation. Journal of Biological Chemistry. 2017; 292: 19721–19732.

[24] Chu B, Kon N, Chen D, Li T, Liu T, Jiang L, et al. ALOX12 is required for p53-mediated tumour suppression through a distinct ferroptosis pathway. Nature Cell Biology. 2019; 21: 579–591.

[25] Chajes V, Cambot M, Moreau K, Lenoir GM, Joulin V. Acetyl-CoA carboxylase alpha is essential to breast cancer cell survival. Cancer Research. 2006; 66: 5287–5294.

[26] Fang W, Cui H, Yu D, Chen Y, Wang J, Yu G. Increased expression of phospho-acetyl-CoA carboxylase protein is an independent prognostic factor for human gastric cancer without lymph node metastasis. Medical Oncology. 2014; 31: 15.

[27] Liang C, Zhang X, Yang M, Dong X. Recent progress in ferroptosis inducers for cancer therapy. Advanced Materials. 2019; 31: 1904197.

[28] Yu Z, He H, Chen Y, Ji Q, Sun M. A novel ferroptosis related gene signature is associated with prognosis in patients with ovarian serous cystadenocarcinoma. Scientific Reports. 2021; 11: 11486.

Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,500 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Biological Abstracts Easily discover critical journal coverage of the life sciences with Biological Abstracts, produced by the Web of Science Group, with topics ranging from botany to microbiology to pharmacology. Including BIOSIS indexing and MeSH terms, specialized indexing in Biological Abstracts helps you to discover more accurate, context-sensitive results.

Google Scholar Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.

JournalSeek Genamics JournalSeek is the largest completely categorized database of freely available journal information available on the internet. The database presently contains 39226 titles. Journal information includes the description (aims and scope), journal abbreviation, journal homepage link, subject category and ISSN.

Current Contents - Clinical Medicine Current Contents - Clinical Medicine provides easy access to complete tables of contents, abstracts, bibliographic information and all other significant items in recently published issues from over 1,000 leading journals in clinical medicine.

BIOSIS Previews BIOSIS Previews is an English-language, bibliographic database service, with abstracts and citation indexing. It is part of Clarivate Analytics Web of Science suite. BIOSIS Previews indexes data from 1926 to the present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Submission Turnaround Time