DNA Methylation In Cervical Cancer Research Articles

Detection of DNA Methylation in Gene Loci ASTN1, DLX1, ITGA4, RXFP3, SOX17, and ZNF671 for Diagnosis of Cervical Cancer.

To evaluate the diagnostic value of DNA methylation detection of multiple gene loci in cervical cancer. A total of 61 cases requiring cervical biopsy were selected from the outpatient clinic of Maternal and Child Health Hospital of Hubei Province between January 2018 and December 2019. The patients were divided into four groups based on histopathologic diagnosis: cervical cancer (CC) group, high-grade squamous intraepithelial lesion (HSIL) group, low-grade squamous intraepithelial lesion (LSIL) group, and control group. HPV examination, liquid-based cytology examination, and DNA methylation detection at multiple gene sites were performed. The positive rate of DNA methylation, sensitivity, specificity, area under the curve (AUC), and other efficacy indexes were calculated to evaluate the diagnostic value of DNA methylation detection at multiple gene loci in cervical cancer. The positive rates of DNA methylation in CC, HSIL, LSIL, and control groups were 100%, 88%, 83% and 17%, respectively. The ZNF671 gene had the highest positive rate among the cervical lesion group, with rates of 57%, 76%, and 100% in LSIL, HSIL, and CC groups respectively. The combination of DNA methylation detection at multiple gene loci showed the highest diagnostic efficacy for HSIL and cervical cancer, with AUC value of 0.850 (95% CI:0.746-0.954), a Youden index of 0.654, and a sensitivity and specificity of 85% and 85.4%, respectively. The diagnostic efficacy of the combined detection was significantly higher than that of HPV examination and liquid-based cytology examination (P < 0.05). DNA methylation detection at multiple gene loci is highly effective and diagnostic tool for cervical cancer, and has potential application value in clinical practice.

Abstract 4288: Predicting DNA methylation in cervical cancer using somatic mutations in a classified mixed model prediction

Abstract In cervical cancer, the promoter CpG islands of several tumor suppressor genes have been found with abnormal DNA methylation (DNAm) levels, which results in transcriptional silencing. Genetic databases from tumor samples are available without the corresponding DNAm profile. To fulfill this gap and contribute to deciphering the link between genetic variants and DNAm, we performed this study to find a good statistical model for predicting DNAm using genetic data. To address this, we downloaded from the TCGA dataset the genes with significant somatic mutations, as reported by the BROAD Institute, and the DNAm beta values, in known CpG sites, from 307 Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (CESC) samples. Clinical data were also downloaded from patients, including race, age, gender, and cancer stage. We tested five mixed models containing both fixed and random effects to include the unmeasured source of variations in DNAm, for which we used the clustering of samples based on DNAm patterns. Models tested were: Classified mixed model prediction (CMMP), Linear regression model (LM), High dimensional shrinkage estimator based on the elastic net (ENET), a combination of CMMP - ENET, and Random Forest prediction (RF). Besides the significantly mutated genes, the clinical variables were also included as covariates to predict DNAm. We used shared random effects to borrow strength across racial groups, which improves predictive accuracy. Models were enhanced by combining other types of cancers to increase data heterogeneity and the number of samples. Lung Adenocarcinoma (LUAD) and Liver Hepatocellular Carcinoma (LIHC) were selected using Gini and Gap statistics for optimal clustering. Model fitting was evaluated using the average mean squared prediction error (MSPE). Results revealed that the CMMP model with CESC LIHC and LUAD data combined showed the best prediction results (lowest MSPE). The plot of the averaged estimated ENET coefficients indicated that the most important-significantly mutated genes to predict DNAm were CTNNB1, DMD, XIRP2, and PIK3CA. SNPs in these genes linked to cervical cancer include rs121913396, rs121913403 (CTNNB1), rs867262025, and rs121913279 (PIK3CA).In summary, we developed a mixed-effects model for accurately predicting DNAm levels in cervical cancer, using genes with significant somatic mutations (SNVs and INDELs). These results also align with growing evidence suggesting that genetic variation plays a role in DNAm. Citation Format: Jairo D. Ramos, J. Sunil Rao. Predicting DNA methylation in cervical cancer using somatic mutations in a classified mixed model prediction. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4288.

MRVI1 and NTRK3 Are Potential Tumor Suppressor Genes Commonly Inactivated by DNA Methylation in Cervical Cancer.

The abnormally methylated tumor suppressor genes (TSGs) associated with cervical cancer are unclear. DNA methylation data, RNA-seq expression profiles, and overall survival data were downloaded from TCGA CESC database. DMGs and DEGs were obtained through CHAMP and DESeq packages, respectively. TSGs were downloaded from TSGene 2.0. Candidate hypermethylated/down-regulated TSGs were further evaluated and pyrosequencing was used to confirm their difference in methylation levels of selected TSGs in cervical cancer patients. A total of 25946 differentially methylated CpGs corresponding to 2686 hypermethylated genes and 4898 hypomethylated genes between cervical cancer and adjacent normal cervical tissues were found in this study. Besides, 693 DEGs (109 up-regulated and 584 down-regulated) were discovered in cervical cancer tissues. Then, 192 hypermethylated/down-regulated genes were obtained in cervical cancer compared to adjacent tissues. Interestingly, 26 TSGs were found in hypermethylated/down-regulated genes. Among these genes, low expression of MRVI1 and NTRK3 was associated with poor overall survival in cervical cancer. Moreover, GEO data showed that MRVI1 and NTRK3 were significantly decreased in cervical cancer tissues. The expression levels of MRVI1 and NTRK3 were negatively correlated with the methylation levels of their promoter CpG sites. Additionally, elevated methylation levels of MRVI1 and NTRK3 promoter were further verified in cervical cancer tissues by pyrosequencing experiments. Finally, the ROC results showed that the promoter methylation levels of MRVI1 and NTRK3 had the ability to discriminate cervical cancer from healthy samples. The study contributes to our understanding of the roles of MRVI1 and NTRK3 in cervical cancer.

Predicting DNA methylation from genetic data lacking racial diversity using shared classified random effects

Public genomic repositories are notoriously lacking in racially and ethnically diverse samples. This limits the reaches of exploration and has in fact been one of the driving factors for the initiation of the All of Us project. Our particular focus here is to provide a model-based framework for accurately predicting DNA methylation from genetic data using racially sparse public repository data. Epigenetic alterations are of great interest in cancer research but public repository data is limited in the information it provides. However, genetic data is more plentiful. Our phenotype of interest is cervical cancer in The Cancer Genome Atlas (TCGA) repository. Being able to generate such predictions would nicely complement other work that has generated gene-level predictions of gene expression for normal samples.We develop a new prediction approach which uses shared random effects from a nested error mixed effects regression model. The sharing of random effects allows borrowing of strength across racial groups greatly improving predictive accuracy. Additionally, we show how to further borrow strength by combining data from different cancers in TCGA even though the focus of our predictions is DNA methylation in cervical cancer. We compare our methodology against other popular approaches including the elastic net shrinkage estimator and random forest prediction. Results are very encouraging with the shared classified random effects approach uniformly producing more accurate predictions – overall and for each racial group.

Studies on the Role of hTERT – a Telomerase Regulator of DNA Methylation in Cervical Cancer

MJCRS is aimed to encourage the publication of the latest information by providing a platform of writing distinctive, rare and unusual cases that augment our understanding of disease process and its diagnosis, supervision and clinico-pathologic connections.

MiR-23b as a potential tumor suppressor and its regulation by DNA methylation in cervical cancer.

BackgroundThe aberrant expression of miR-23b is involved in the development and progression of cancer. The aim of this study was to evaluate the potential role of methylation in the silencing of miR-23b in cervical cancer cell lines and to determine its expression in stages of malignant progression and in cervical cancer tissues HPV16-positive.MethodsThe methylation of the miR-23b promoter was determined in HeLa, SiHa, CaSki and C33A cells using a Human Cancer miRNA EpiTectMethyl II Signature PCR Array®. The cells were treated with 5-Aza-2′-deoxycytidine, and the expression of miR-23b, uPa, c-Met and Zeb1 was determined by qRT-PCR. miR-92a and GAPDH were used as controls. The expression of miR-23b was determined in cervical scrapes and biopsies of women without squamous intraepithelial lesions, with precursor lesions and with cervical cancer, all were HPV16-positive. The Fisher exact and Mann–Whitney tests were used to compare the differences of the expression of miR-23b, uPa, c-Met and Zeb1 among cell groups, and the difference among patients, respectively. The association between the expression of miR-23b and cervical cancer was determined by logistic regression with a confidence level of 95 %. A value of p < 0.05 was considered statistically significant.ResultsIn C33A, HeLa and CaSki cells, methylation was associated with decreased expression of miR-23b. After treatment with 5-Aza-CdR, the expression of miR-23b increased in all cell lines and the expression of c-Met decreased in HeLa cells, while uPa and Zeb1 decreased in C33A and CaSki cells. In SiHa cells the expression of uPa, c-Met and Zeb1 increased. The expression of miR-23b decreased in relation to the increase in the severity of the lesion and was significantly lower in cervical cancer. In women with premalignant lesions HPV16-positive, decreased levels of miR-23b increased the risk of cervical cancer (OR = 36, 95 % CI = 6.7-192.6, p < 0.05).ConclusionsThe results suggest that the expression of miR-23b is regulated by the methylation of its promoter and is possible that this microRNA influence the expression of uPa, c-Met and Zeb1 in cervical cancer cells lines. In women with premalignant lesions and cervical cancer infected with HPV16, the expression level of miR-23b agree with a tumor suppressor gene.

Identification of differentially-expressed genes by DNA methylation in cervical cancer.

To identify novel cervical cancer-related genes that are regulated by DNA methylation, integrated analyses of genome-wide DNA methylation and RNA expression profiles were performed using the normal and tumor regions of tissues from four patients; two with cervical cancer and two with pre-invasive cancer. The present study identified 19 novel cervical cancer-related genes showing differential RNA expression by DNA methylation. A number of the identified genes were novel cervical cancer-related genes and their differential expression was confirmed in a publicly available database. Among the candidate genes, the epigenetic regulation and expression of three genes, CAMK2N1, ALDH1A3 and PPP1R3C, was validated in HeLa cells treated with a demethylating reagent using methylation-specific polymerase chain reaction (PCR) and quantitative PCR, respectively. From these results, the expression of the CAMK2N1, ALDH1A3 and PPP1R3C genes are were shown to be suppressed in cervical cancers by DNA methylation. These genes may be involved in the progression or initiation of cervical cancer.

Epigenetic regulation of double c2 like domain beta (Doc2b) in cervical cancer.

Associations of genetic changes and aneuploidy with tumor growth are traditionally attributed to alterations in DNA sequence manifested as mutations, deletions and amplifications. Inactive tumor suppressor genes could serve as drivers of tumor progression due to not only altered or lack of protein function but may also contribute to phenotypic changes that may provide distinct growth advantage in a hostile environment in the host. Human variation is also due to epigenetic alterations and heritable change that leads to altered gene expression; the functional consequence of which may contribute to definitive trait. A number of key regulatory genes associated with epigenetic silencing due to DNA methylation in cervical cancer have been reported. Elucidation of differentially methylated genes may identify new targets and further strengthen our understanding of molecular mechanism governing pathogenesis of cervical cancer. Thus, to identify DNA methylation regulated genes in cervical cancer, we have employed DMH based microarray experiments in pre-malignant and malignant cervical sample. Microarray data analysis and validation using bisulfite genomic sequencing lead to the identification of several CpG island as altered during cervical carcinogenesis and showed the potential for early screening of cervical cancer. One of the candidate gene identified was Double C2 like Domain beta (DOC2B), a key calcium regulator protein whose alteration has never been linked to cancer. We provide evidence that DOC2B is depressed in cervical cancer due to promoter hypermethylation and act as a novel tumor suppressor gene by regulating multiple pathways in cervical cancer.

DNA methylation in cervical intraepithelial neoplasia and invasive cervical cancer

The relationship between DNA methylation and tumor development gets more and more at-tention. It has been recently found that aberrant promoter methylation of various of genes may be associated with cervical intraepithelial neoplasia(CIN) and invasive cervical cancer. Now we review the research progress of DNA methylation in CIN andeervieal carcinoma. Key words: Cervical intTaepithelial neoplasia; Cervix neoplasms; DNA methylation

Identification of novel DNA methylation markers in cervical cancer

Testing for DNA methylation has potential in cancer screening. Most previous studies of DNA methylation in cervical cancer used a candidate gene approach. The aim our study was to identify novel genes that are methylated in cervical cancers and to test their potential in clinical applications. We did a differential methylation hybridization using a CpG island (CGI) microarray containing 8640 CGI tags to uncover methylated genes in squamous cell carcinomas (SCC) of the uterine cervix. Pooled DNA from cancer tissues and normal cervical swabs were used for comparison. Methylation-specific polymerase chain reaction, bisulfite sequencing and reverse transcription polymerase chain reaction were used to confirm the methylation status in cell lines, normal cervices (n = 45), low-grade lesions (n = 45), high-grade lesions (HSIL; n = 58) and invasive squamous cell carcinomas (SCC; n = 22 from swabs and n = 109 from tissues). Human papillomavirus (HPV) was detected using reverse line blots. We reported 6 genes (SOX1, PAX1, LMX1A, NKX6-1, WT1 and ONECUT1) more frequently methylated in SCC tissues (81.5, 94.4, 89.9, 80.4, 77.8 and 20.4%, respectively) than in their normal controls (2.2, 0, 6.7, 11.9, 11.1 and 0%, respectively; p < 0.0001). Parallel testing of HPV and PAX1 methylation in cervical swabs confers an improved sensitivity than HPV testing alone (80% vs. 66%) without compromising specificity (63% vs. 64%) for HSIL/SCC. Testing PAX1 methylation marker alone, the specificity for HSIL/SCC is 99%. The analysis of these novel DNA methylations may be a promising approach for the screening of cervical cancers.

E-cadherin expression is silenced by DNA methylation in cervical cancer cell lines and tumours

A previous study showed E-cadherin expression was lost in some cervical cancer cell lines and tumours. This study was designed to clarify the significance of DNA methylation in silencing E-cadherin expression. We examined promoter methylation of E-cadherin in five cervical cancer cell lines and 20 cervical cancer tissues using methylation-specific PCR (MSP) and bisulphite DNA sequencing. The correlation of E-cadherin methylation and expression together with methyltransferase ( DNMT1) were further studied. We found that hypermethylation of E-cadherin was involved in five cervical cancer cell lines and 40% (8/20) of cervical cancer tissues. E-cadherin protein was lost in 6/8 (75%) samples and 3/5 (60%) cell lines with promoter methylation. E-cadherin methylation was significantly correlated with increased DNMT1. Using an antisense DNMT1 oligo to transfect into SiHa HeLa C33A cell line, E-cadherin protein was re-expressed. We concluded that loss of E-cadherin expression was in part correlated with DNA methylation and DNMT1 expression in cervical cancer.