Methylation and ovarian cancer: Can DNA methylation be of diagnostic use? (Review)

Hentze, Julie L.; Høgdall, Claus; Høgdall, Estrid

doi:10.3892/mco.2019.1800

Cited by 32 publications

(39 citation statements)

References 107 publications

(102 reference statements)

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“…Dysregulation of DNMT activity, and subsequent hypermethylation of promoter regions, has been identified as a key component in acute myeloid leukemia initiation and progression (Yang et al, 2019). Furthermore, hypermethylation of promoter regions has also been observed in 56% of breast and 15-30% ovarian cancers (de Almeida et al, 2019;Hentze et al, 2019).…”

Section: Parp Inhibitors and Drugs Targeting Epigenetic Modificationsmentioning

confidence: 99%

PARP Inhibitors: Clinical Relevance, Mechanisms of Action and Tumor Resistance

Rose

Burgess

O’Byrne

et al. 2020

Front. Cell Dev. Biol.

438

296

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The Poly (ADP-ribose) polymerase (PARP) family has many essential functions in cellular processes, including the regulation of transcription, apoptosis and the DNA damage response. PARP1 possesses Poly (ADP-ribose) activity and when activated by DNA damage, adds branched PAR chains to facilitate the recruitment of other repair proteins to promote the repair of DNA single-strand breaks. PARP inhibitors (PARPi) were the first approved cancer drugs that specifically targeted the DNA damage response in BRCA1/2 mutated breast and ovarian cancers. Since then, there has been significant advances in our understanding of the mechanisms behind sensitization of tumors to PARP inhibitors and expansion of the use of PARPi to treat several other cancer types. Here, we review the recent advances in the proposed mechanisms of action of PARPi, biomarkers of the tumor response to PARPi, clinical advances in PARPi therapy, including the potential of combination therapies and mechanisms of tumor resistance.

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Section: Parp Inhibitors and Drugs Targeting Epigenetic Modificationsmentioning

confidence: 99%

PARP Inhibitors: Clinical Relevance, Mechanisms of Action and Tumor Resistance

Rose

Burgess

O’Byrne

et al. 2020

Front. Cell Dev. Biol.

438

296

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“…The most notable methylation changes in solid OT are in the BRCA1 [29,55], OPCML [56], HOXA9 [33] and P16 INK4α genes [57]. BRCA1 is methylated in up to 30% [29,55] of these tumours and OPCML is methylated in over 80% of OT [56]. Interestingly, RASSF1 A is the major RASSF1 gene isoform and this has been repeatedly analysed for methylation changes in both OC tissues and plasma samples.…”

Section: Discussionmentioning

confidence: 99%

“…However, no statistically significant differences were established between particular CpGs or mean methylation indices. Importantly, although these differences proved insignificant, they can indicate wide methylation changes in RASSF1 gene regulating sequences and the important role of methylation in silencing this gene in OC development as is generally suggested [29].…”

Section: Discussionmentioning

confidence: 99%

“…Finally, changes in DNA methylation were repeatedly noted in OC and these affected the activity of variable genes, and therefore contributed to the tumorigenesis of variable histotypes. Furthermore, methylation changes in OC can be prognostic for shorter progression-free survival (PFS) and chemotherapy resistance [29,30,31]. Importantly for this study, all four selected genes have previously been observed to be abnormally methylated in primary OC tumours [25,32,33,34,35,36,37,38,39,40].…”

Section: Introductionmentioning

confidence: 99%

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Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples

Dvorska

Braný

Nagy

et al. 2019

IJMS

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Ovarian cancer is a highly heterogeneous disease and its formation is affected by many epidemiological factors. It has typical lack of early signs and symptoms, and almost 70% of ovarian cancers are diagnosed in advanced stages. Robust, early and non-invasive ovarian cancer diagnosis will certainly be beneficial. Herein we analysed the regulatory sequence methylation profiles of the RASSF1, PTEN, CDH1 and PAX1 tumour suppressor genes by pyrosequencing in healthy, benign and malignant ovarian tissues, and corresponding plasma samples. We recorded statistically significant higher methylation levels (p < 0.05) in the CDH1 and PAX1 genes in malignant tissues than in controls (39.06 ± 18.78 versus 24.22 ± 6.93; 13.55 ± 10.65 versus 5.73 ± 2.19). Higher values in the CDH1 gene were also found in plasma samples (22.25 ± 14.13 versus 46.42 ± 20.91). A similar methylation pattern with positive correlation between plasma and benign lesions was noted in the CDH1 gene (r = 0.886, p = 0.019) and malignant lesions in the PAX1 gene (r = 0.771, p < 0.001). The random forest algorithm combining methylation indices of all four genes and age determined 0.932 AUC (area under the receiver operating characteristic (ROC) curve) prediction power in the model classifying malignant lesions and controls. Our study results indicate the effects of methylation changes in ovarian cancer development and suggest that the CDH1 gene is a potential candidate for non-invasive diagnosis of ovarian cancer.

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“…Several promising prognostic OC biomarkers have been recently discovered such as; VEGF, HE4, mesothelin, M-CSF, osteopontin, kallikrein(s), bikunin, EphA2, and soluble EGF receptor [4]. With the development of multi-omics, numerous genomic variations, miRNAs, lncRNAs, and metabolites have been suggested to serve as prognostic biomarkers [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

Liu

et al. 2020

Preprint

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BackgroundOvarian cancer (OC) is one of the most lethal gynecological cancer globally. Serous ovarian cancer (SOC) is most common pathological type of ovarian cancer. Growing evidence suggests that transcription factors (TFs) play vital roles in serous ovarian cancer (SOC). In the present study, we aimed to develop a transcription factors-related prognostic signature to better predict the survival in patients with SOC.Materials and methodsThe TFs mRNA expression profiles of 564 SOC subjects in the TCGA database, and 70 SOC subjects in the GEO database were screened. Lasso cox regression and consensus clustering analysis were utilized to construct a novel TFs related signature and cluster model, respectively. Genomic alternative analysis was used to elaborate on the association between the TFs related prognostic signature and genomic aberrations. GSEA analysis was applied to identify the biological functional difference between high risk-score group and low-risk score group.ResultsA 17-TFs related prognostic signature was constructed using lasso cox regression and validated in the TCGA and GEO cohorts. Consensus clustering analysis was applied to establish a cluster model. The 17-TFs related prognostic signature, risk score, and cluster models were effective at accurately distinguishing the prognosis of SOC. The GSEA assay results suggested that there was a significant difference in the inflammatory and immune response pathways between the high-risk and low-risk score groups. Immune infiltration, immunotherapy, and chemotherapy responses were analyzed due to the significant difference in the regulation of lymphocyte migration and T cell-mediated cytotoxicity between the two groups; indicating that patients with low-risk score were more likely to respond anti-PD-1, etoposide, paclitaxel, and veliparib but not to gemcitabine, doxorubicin, docetaxel, and cisplatin. Also, the prognostic nomogram model revealed that the risk score was a good prognostic indicator for SOC patients.ConclusionsIn conclusion, we explored the prognostic values of TFs in SOC and developed a 17-TFs related prognostic signature to predict the survival of SOC patients.

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Methylation and ovarian cancer: Can DNA methylation be of diagnostic use? (Review)

Cited by 32 publications

References 107 publications

PARP Inhibitors: Clinical Relevance, Mechanisms of Action and Tumor Resistance

PARP Inhibitors: Clinical Relevance, Mechanisms of Action and Tumor Resistance

Aberrant Methylation Status of Tumour Suppressor Genes in Ovarian Cancer Tissue and Paired Plasma Samples

Development of a novel transcription factors-related prognostic signature for serous ovarian cancer

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