DNA Methylation Subtypes for Ovarian Cancer Prognosis

Overview

Journal FEBS Open Bio

Specialty Biology

Date 2020 Dec 5

PMID 33278864

Citations 7

Authors

Lili Yin

Ningning Zhang

Qing Yang

Affiliations

Soon will be listed here.

Abstract

Ovarian cancer is one of three major malignancies of the female reproductive system. DNA methylation (MET) is closely related to ovarian cancer occurrence and development, and as such, elucidation of effective MET subtype markers may guide individualized treatment and improve ovarian cancer prognosis. To identify potential markers, we downloaded a total of 571 ovarian cancer MET samples from The Cancer Genome Atlas (TCGA), and established a Cox proportional hazards model using the MET spectrum and clinical pathological parameters. A total of 250 prognosis-related MET loci were obtained by Cox regression, and six molecular subtypes were screened by consensus clustering of CpG loci with a significant difference in both univariate and multivariate analyses. There was a remarkable MET difference between most subtypes. Cluster 2 had the highest MET level and demonstrated the best prognosis, while Clusters 4 and 5 had MET levels significantly lower than those of the other subtypes and demonstrated very poor prognosis. All Cluster 5 samples were at a high grade, while the percentage of stage IV samples in Cluster 4 was greater than in the other subtypes. We obtained five CpG loci using a coexpression network: cg27625732, cg00431050, cg22197830, cg03152385, and cg22809047. Our cluster analysis showed that prognosis in patients with hypomethylation was significantly worse than in patients with hypermethylation. These MET molecular subtypes can be used not only to evaluate ovarian cancer prognosis, but also to fully distinguish the tumor stage and histological grade in patients with ovarian cancer.

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References

Haq R, Fisher D . Biology and clinical relevance of the micropthalmia family of transcription factors in human cancer. J Clin Oncol. 2011; 29(25):3474-82. DOI: 10.1200/JCO.2010.32.6223. View

Wu S, Cooper B, Bu F, Bowman C, Killian J, Serrano J . DNA Methylation-Based Classifier for Accurate Molecular Diagnosis of Bone Sarcomas. JCO Precis Oncol. 2018; 2017. PMC: 5772901. DOI: 10.1200/PO.17.00031. View

Kommoss S, Schmidt D, Kommoss F, Hedderich J, Harter P, Pfisterer J . Histological grading in a large series of advanced stage ovarian carcinomas by three widely used grading systems: consistent lack of prognostic significance. A translational research subprotocol of a prospective randomized phase III study (AGO-OVAR.... Virchows Arch. 2009; 454(3):249-56. DOI: 10.1007/s00428-009-0725-y. View

Petrocca F, Iliopoulos D, Qin H, Nicoloso M, Yendamuri S, E Wojcik S . Alterations of the tumor suppressor gene ARLTS1 in ovarian cancer. Cancer Res. 2006; 66(21):10287-91. DOI: 10.1158/0008-5472.CAN-06-2289. View

Kommoss S, Winterhoff B, Oberg A, Konecny G, Wang C, Riska S . Bevacizumab May Differentially Improve Ovarian Cancer Outcome in Patients with Proliferative and Mesenchymal Molecular Subtypes. Clin Cancer Res. 2017; 23(14):3794-3801. PMC: 5661884. DOI: 10.1158/1078-0432.CCR-16-2196. View

Roode S, Rotroff D, Avery A, Suter S, Bienzle D, Schiffman J . Genome-wide assessment of recurrent genomic imbalances in canine leukemia identifies evolutionarily conserved regions for subtype differentiation. Chromosome Res. 2015; 23(4):681-708. DOI: 10.1007/s10577-015-9475-7. View

Miller J, Kotecha R, Ahluwalia M, Mohammadi A, Chao S, Barnett G . Overall survival and the response to radiotherapy among molecular subtypes of breast cancer brain metastases treated with targeted therapies. Cancer. 2017; 123(12):2283-2293. DOI: 10.1002/cncr.30616. View

Reimand J, Arak T, Adler P, Kolberg L, Reisberg S, Peterson H . g:Profiler-a web server for functional interpretation of gene lists (2016 update). Nucleic Acids Res. 2016; 44(W1):W83-9. PMC: 4987867. DOI: 10.1093/nar/gkw199. View

Tothill R, Tinker A, George J, Brown R, Fox S, Lade S . Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome. Clin Cancer Res. 2008; 14(16):5198-208. DOI: 10.1158/1078-0432.CCR-08-0196. View

10.

Esteller M, Silva J, Dominguez G, Bonilla F, Matias-Guiu X, Lerma E . Promoter hypermethylation and BRCA1 inactivation in sporadic breast and ovarian tumors. J Natl Cancer Inst. 2000; 92(7):564-9. DOI: 10.1093/jnci/92.7.564. View

11.

Shih I, Kurman R . Ovarian tumorigenesis: a proposed model based on morphological and molecular genetic analysis. Am J Pathol. 2004; 164(5):1511-8. PMC: 1615664. DOI: 10.1016/s0002-9440(10)63708-x. View

12.

Horak P, Pils D, Haller G, Pribill I, Roessler M, Tomek S . Contribution of epigenetic silencing of tumor necrosis factor-related apoptosis inducing ligand receptor 1 (DR4) to TRAIL resistance and ovarian cancer. Mol Cancer Res. 2005; 3(6):335-43. DOI: 10.1158/1541-7786.MCR-04-0136. View

13.

Maruyama Y, Miyazaki T, Ikeda K, Okumura T, Sato W, Horie-Inoue K . Short hairpin RNA library-based functional screening identified ribosomal protein L31 that modulates prostate cancer cell growth via p53 pathway. PLoS One. 2014; 9(10):e108743. PMC: 4186824. DOI: 10.1371/journal.pone.0108743. View

14.

Kang Y, Yoon J, Long N, Koo G, Noh H, Oh S . Spheroid-Induced Epithelial-Mesenchymal Transition Provokes Global Alterations of Breast Cancer Lipidome: A Multi-Layered Omics Analysis. Front Oncol. 2019; 9:145. PMC: 6437068. DOI: 10.3389/fonc.2019.00145. View

15.

Aran D, Hellman A . DNA methylation of transcriptional enhancers and cancer predisposition. Cell. 2013; 154(1):11-3. DOI: 10.1016/j.cell.2013.06.018. View

16.

Baylin S, Ohm J . Epigenetic gene silencing in cancer - a mechanism for early oncogenic pathway addiction?. Nat Rev Cancer. 2006; 6(2):107-16. DOI: 10.1038/nrc1799. View

17.

Wilkerson M, Hayes D . ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking. Bioinformatics. 2010; 26(12):1572-3. PMC: 2881355. DOI: 10.1093/bioinformatics/btq170. View

18.

Zhang Z, Huang K, Gu C, Zhao L, Wang N, Wang X . Molecular Subtyping of Serous Ovarian Cancer Based on Multi-omics Data. Sci Rep. 2016; 6:26001. PMC: 4868982. DOI: 10.1038/srep26001. View

19.

. Integrated genomic analyses of ovarian carcinoma. Nature. 2011; 474(7353):609-15. PMC: 3163504. DOI: 10.1038/nature10166. View

20.

Sung P, Chang Y, Chao K, Chuang C . Global distribution pattern of histological subtypes of epithelial ovarian cancer: a database analysis and systematic review. Gynecol Oncol. 2014; 133(2):147-54. DOI: 10.1016/j.ygyno.2014.02.016. View