Differential involvement of RASSF2 hypermethylation in breast cancer subtypes and their prognosis

ZEB1 hypermethylation is associated with better prognosis in patients with colon cancer

BACKGROUND

Colon cancer (CC) is a heterogeneous disease that is categorized into four Consensus Molecular Subtypes (CMS) according to gene expression. Patients with loco-regional CC (stages II/III) lack prognostic factors, making it essential to analyze new molecular markers that can delineate more aggressive tumors. Aberrant methylation of genes that are essential in crucial mechanisms such as epithelial mesenchymal transition (EMT) contributes to tumor progression in CC. We evaluate the presence of hyper- and hypomethylation in subrogate IHC markers used for CMS classification (CDX2, FRMD6, HTR2B, ZEB1) of 144 stage II/III patients and CC cell lines by pyrosequencing. ZEB1 expression was also studied in control and shRNA-silenced CC cell lines and in paired normal tissue/tumors by quantitative PCR. The pattern of ZEB1 staining was also analyzed in methylated/unmethylated tumors by immunohistochemistry.

RESULTS

We describe for the first time the hypermethylation of ZEB1 gene and the hypomethylation of the FRMD6 gene in 32.6% and 50.9% of tumors, respectively. Additionally, we confirm the ZEB1 re-expression by epigenetic drugs in methylated cell lines. ZEB1 hypermethylation was more frequent in CMS1 patients and, more importantly, was a good prognostic factor related to disease-free survival (p = 0.015) and overall survival (p = 0.006) in our patient series, independently of other significant clinical parameters such as patient age, stage, lymph node involvement, and blood vessel and perineural invasion.

CONCLUSIONS

Aberrant methylation is present in the subrogate genes used for CMS classification. Our results are the first evidence that ZEB1 is hypermethylated in CC and that this alteration is an independent factor of good prognosis.

Network and pathway-based analysis of genes associated with esophageal squamous cell carcinoma

Background

Although diagnostic methods and treatments have improved over the last few years, the 5-year survival rate of esophageal squamous cell carcinoma (ESCC) patients remains generally poor. The development of high-throughput technology has facilitated great achievements in localization of ESCC-related genes. To take a further step toward a thorough understanding of ESCC at a molecular level, the potential pathogenesis of ESCC needs to be deciphered.

Methods

The interaction of ESCC-related genes was explored by collecting genes associated with ESCC and then performing gene enrichment assays, pathway enrichment assays, pathway crosstalk analysis, and extraction of ESCC-specific subnetwork to describe the relevant biochemical processes.

Results

Through Gene Ontology (GO) enrichment analysis, many molecular functions related to response to chemical, cellular response to stimulus, and cell proliferation were found to be significantly enriched in ESCC-related genes. The results of pathway and pathway crosstalk analysis showed that pathways associated with multiple malignant tumors, the immune system, and metabolic processes were significantly enriched in ESCC-related genes. Through the analysis of specific subnetworks, we obtained some novel ESCC-related potential genes, such as MUC13, GSTO1, FIN, GRB2, CDC25C, and others.

Conclusions

The molecular mechanism of ESCC is extremely complex. Some inducing factors change the expression status of many genes. The abnormal expression of genes mediates the biological processes involved in immunity and metabolism, apoptosis, and cell proliferation, leading to the occurrence of tumors. The genes MUC13, RYK, and FIN may be potential prognostic indicators of ESCC; GRB2 and CDC25C may be potential targets of ESCC in proliferation. Our work may provide valuable information for further understanding the molecular mechanisms for the development of ESCC.

High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer

Background

Although notable therapeutic and prognostic benefits of compound kushen injection (CKI) have been found when it was used alone or in combination with chemotherapy or radiotherapy for triple-negative breast cancer (TNBC) treatment, the effects of CKI on TNBC microenvironment remain largely unclear. This study aims to construct and validate a predictive immunotherapy signature of CKI on TNBC.

Methods

The UPLC-Q-TOF-MS technology was firstly used to investigate major constituents of CKI. RNA sequencing data of CKI-perturbed TNBC cells were analyzed to detect differential expression genes (DEGs), and the GSVA algorithm was applied to explore significantly changed pathways regulated by CKI. Additionally, the ssGSEA algorithm was used to quantify immune cell abundance in TNBC patients, and these patients were classified into distinct immune infiltration subgroups by unsupervised clustering. Then, prognosis-related genes were screened from DEGs among these subgroups and were further overlapped with the DEGs regulated by CKI. Finally, a predictive immunotherapy signature of CKI on TNBC was constructed based on the LASSO regression algorithm to predict mortality risks of TNBC patients, and the signature was also validated in another TNBC cohort.

Results

Twenty-three chemical components in CKI were identified by UPLC-Q-TOF-MS analysis. A total of 3692 DEGs were detected in CKI-treated versus control groups, and CKI significantly activated biological processes associated with activation of T, natural killer and natural killer T cells. Three immune cell infiltration subgroups with 1593 DEGs were identified in TNBC patients. Then, two genes that can be down-regulated by CKI with hazard ratio (HR) > 1 and 26 genes that can be up-regulated by CKI with HR < 1 were selected as key immune- and prognosis-related genes regulated by CKI. Lastly, a five-gene prognostic signature comprising two risky genes (MARVELD2 and DYNC2I2) that can be down-regulated by CKI and three protective genes (RASSF2, FERMT3 and RASSF5) that can be up-regulated by CKI was developed, and it showed a good performance in both training and test sets.

Conclusions

This study proposes a predictive immunotherapy signature of CKI on TNBC, which would provide more evidence for survival prediction and treatment guidance in TNBC as well as a paradigm for exploring immunotherapy biomarkers in compound medicines.

Automated and rapid detection of cancer in suspicious axillary lymph nodes in patients with breast cancer

Preoperative staging of suspicious axillary lymph nodes (ALNs) allows patients to be triaged to ALN dissection or to sentinel lymph node biopsy (SLNB). Ultrasound-guided fine needle aspiration (FNA) and cytology of ALN is moderately sensitive but its clinical utility relies heavily on the cytologist's experience. We proposed that the 5-h automated GeneXpert system-based prototype breast cancer detection assay (BCDA) that quantitatively measures DNA methylation in ten tumor-specific gene markers could provide a facile, accurate test for detecting cancer in FNA of enlarged lymph nodes. We validated the assay in ALN-FNA samples from a prospective study of patients (N = 230) undergoing SLNB. In a blinded analysis of 218 evaluable LN-FNAs from 108 malignant and 110 benign LNs by histology, BCDA displayed a sensitivity of 90.7% and specificity of 99.1%, achieving an area under the ROC curve, AUC of 0.958 (95% CI: 0.928-0.989; P < 0.0001). Next, we conducted a study of archival FNAs of ipsilateral palpable LNs (malignant, N = 72, benign, N = 53 by cytology) collected in the outpatient setting prior to neoadjuvant chemotherapy (NAC). Using the ROC-threshold determined in the prospective study, compared to cytology, BCDA achieved a sensitivity of 94.4% and a specificity of 92.5% with a ROC-AUC = 0.977 (95% CI: 0.953-1.000; P < 0.0001). Our study shows that the automated assay detects cancer in suspicious lymph nodes with a high level of accuracy within 5 h. This cancer detection assay, scalable for analysis to scores of LN FNAs, could assist in determining eligibility of patients to different treatment regimens.

A Risk Score System Based on the Methylation Levels of 15 RNAs in Breast Cancer

Background: Breast cancer (BC) occurs in the epithelial tissues of the breast gland, which is the most common cancer in women. This study is implemented to construct a risk score system for BC. Methods: The methylation data of BC from The Cancer Genome Atlas database (the training set) and GSE37754 from Gene Expression Omnibus database (the validation set) were downloaded. The differentially methylated RNAs (DMRs) between BC and normal samples were screened by limma package, and the correlations between the expression levels and methylation levels of the DMRs were analyzed to calculate their Pearson correlation coefficients (PCCs) using the cor.test function. To build the risk score system, the optimal RNAs were identified by penalized package. Subsequently, the nomogram survival model was established using the rms package. The lncRNA-mRNA comethylation network was constructed by Cytoscape software, and then enrichment analysis was performed using DAVID tool. Results: From the 1170 DMRs between BC and normal samples, 800 DMRs with significant negative PCCs were screened. For building the risk score system, the 15 optimal RNAs were selected. Afterward, the nomogram survival model based on four independent clinical prognostic factors (including age, radiation therapy, tumor recurrence, and RS model status) was constructed. In the comethylation network, the long noncoding RNA (lncRNA) PRNT was comethylated with FAM19A5 and RBM24. For the mRNAs in the comethylation network, angiogenesis and pathways in cancer were enriched. Conclusion: The risk score system and the nomogram survival model might be of great importance for the prognosis prediction of BC patients.

Prognostic DNA methylation markers for hormone receptor breast cancer: a systematic review

BACKGROUND

In patients with hormone receptor-positive breast cancer, differentiating between patients with a low and a high risk of recurrence is an ongoing challenge. In current practice, prognostic clinical parameters are used for risk prediction. DNA methylation markers have been proven to be of additional prognostic value in several cancer types. Numerous prognostic DNA methylation markers for breast cancer have been published in the literature. However, to date, none of these markers are used in clinical practice.

METHODS

We conducted a systematic review of PubMed and EMBASE to assess the number and level of evidence of published DNA methylation markers for hormone receptor-positive breast cancer. To obtain an overview of the reporting quality of the included studies, all were scored according to the REMARK criteria that were established as reporting guidelines for prognostic biomarker studies.

RESULTS

A total of 74 studies were identified reporting on 87 different DNA methylation markers. Assessment of the REMARK criteria showed variation in reporting quality of the studies. Eighteen single markers and one marker panel were studied in multiple independent populations. Hypermethylation of the markers RASSF1, BRCA, PITX2, CDH1, RARB, PCDH10 and PGR, and the marker panel GSTP1, RASSF1 and RARB showed a statistically significant correlation with poor disease outcome that was confirmed in at least one other, independent study.

CONCLUSION

This systematic review provides an overview on published prognostic DNA methylation markers for hormone receptor-positive breast cancer and identifies eight markers that have been independently validated. Analysis of the reporting quality of included studies suggests that future research on this topic would benefit from standardised reporting guidelines.

DNA methylation of SFRP1, SFRP2, and WIF1 and prognosis of postoperative colorectal cancer patients

Background

As biomarkers, DNA methylation is used to detect colorectal cancer (CRC) and make assessment of CRC prognosis. The published findings showed the association between the methylation of SFRP1, SFRP2, and WIF1, located in the Wnt signaling pathway, and the prognosis of CRC were not consistent. Our study aimed to explore the potential possibility of SFRP1, SFRP2, and WIF1 concomitant promoter methylation as prognostic biomarkers of postoperative CRC patients.

Methods

As a total of 307 sporadic postoperative CRC patients were followed up, we detected SFRP1, SFRP2, and WIF1 methylation obtained from tumor tissues and adjacent non-tumor tissues respectively on the basis of methylation-sensitive high resolution melting analysis. Univariate and multivariate Cox regressions were carried out so as to assess the potential possibility of SFRP1, SFRP2, and WIF1 promoter methylation as predictors of prognosis. Confounders in our study were controlled by Propensity Score (PS) analysis.

Results

The SFRP1, SFRP2, and WIF1 methylation levels in tumor tissues were significantly higher than that in adjacent non-tumor tissues (P < 0.001). SFRP2 hypermethylation was significantly associated with a favorable clinical outcome at the hazard ratio (HR) of 0.343 [95% confidence intervals (CI): 0.164–0.718, P = 0.005] and 0.410 (95% CI: 0.200–0.842, P = 0.015) in multivariate Cox regression and PS analysis, respectively. Co-hypermethylation of SFRP1 and SFRP2 was significantly associated with a favorable clinical outcome at the HR of 0.333 (95% CI: 0.159–0.694, P = 0.003) and 0.398 (95% CI: 0.192–0.821, P = 0.013) in multivariate Cox regression and PS analysis, respectively. Co-hypermethylation of SFRP1, SFRP2 and WIF1 was significantly associated with a favorable clinical outcome at the HR of 0.326 (95% CI: 0.117–0.908, P = 0.032) and 0.401 (95% CI: 0.146–1.106, P = 0.077) in multivariate Cox regression and PS analysis, respectively.

Conclusions

SFRP1, SFRP2, and WIF1 were frequently hypermethylated in CRC tumor tissues. It was apparent that the promoter hypermethylation of SFRP2 and co-hypermethylation of SFRP1 and SFRP2 might be considered as independent prognostic predictors for survival advantage of postoperative CRC patients.

Incorporating genetic networks into case-control association studies with high-dimensional DNA methylation data

Background

In human genetic association studies with high-dimensional gene expression data, it has been well known that statistical selection methods utilizing prior biological network knowledge such as genetic pathways and signaling pathways can outperform other methods that ignore genetic network structures in terms of true positive selection. In recent epigenetic research on case-control association studies, relatively many statistical methods have been proposed to identify cancer-related CpG sites and their corresponding genes from high-dimensional DNA methylation array data. However, most of existing methods are not designed to utilize genetic network information although methylation levels between linked genes in the genetic networks tend to be highly correlated with each other.

Results

We propose new approach that combines data dimension reduction techniques with network-based regularization to identify outcome-related genes for analysis of high-dimensional DNA methylation data. In simulation studies, we demonstrated that the proposed approach overwhelms other statistical methods that do not utilize genetic network information in terms of true positive selection. We also applied it to the 450K DNA methylation array data of the four breast invasive carcinoma cancer subtypes from The Cancer Genome Atlas (TCGA) project.

Conclusions

The proposed variable selection approach can utilize prior biological network information for analysis of high-dimensional DNA methylation array data. It first captures gene level signals from multiple CpG sites using data a dimension reduction technique and then performs network-based regularization based on biological network graph information. It can select potentially cancer-related genes and genetic pathways that were missed by the existing methods.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-3040-x) contains supplementary material, which is available to authorized users.

Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data

Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide and causing significant impact on their quality of life and economic burden. Neither a definitive clinical symptom nor a minimally invasive diagnostic method is available, thus leading to an average of 4 to 11 years of diagnostic latency. Discovery of relevant biological patterns from microarray expression or next generation sequencing (NGS) data has been advanced over the last several decades by applying various machine learning tools. We performed machine learning analysis using 38 RNA-seq and 80 enrichment-based DNA methylation (MBD-seq) datasets. We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine, and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: a) implication of three different normalization techniques and b) implication of differential analysis using the generalized linear model (GLM). Several candidate biomarker genes were identified by multiple machine learning experiments including NOTCH3, SNAPC2, B4GALNT1, SMAP2, DDB2, GTF3C5, and PTOV1 from the transcriptomics data analysis and TRPM6, RASSF2, TNIP2, RP3-522J7.6, FGD3, and MFSD14B from the methylomics data analysis. We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.

Association Between RASSF2 Methylation and Gastric Cancer: A PRISMA-Compliant Systematic Review and Meta-Analysis

RASSF2 is a tumor suppressor gene closely related to gastric cancer. This meta-analysis was designed to assess the quality in the previous studies and establish the value of RASSF2 methylation in the prediction and prognosis of gastric cancer. The eligible literatures with publication deadline of May 3, 2019 were collected from PubMed, EMBASE, CNKI, Wanfang, and CNVIP databases. The correlation between RASSF2 methylation level and gastric cancer was estimated by odds ratio and 95% confidence interval (OR and 95% CI) values. A total of eight articles were included in the study. A total of 517 gastric cancer tissue samples and 517 adjacent nontumor tissue samples were included. The results of the analysis showed that RASSF2 had a significantly higher level of methylation in gastric cancer (OR = 17.56, 95% CI = 7.11-43.35, p-value = 0.009). Meanwhile, we tested whether there was association of RASSF2 methylation with tumor metastasis, and we also analyzed whether there was a gender difference in RASSF2 methylation. However, our results showed no statistical significance of the two aforementioned tests (p > 0.1). Our study suggested that RASSF2 methylation could predict the risk of gastric cancer. However, it might not be feasible for the prediction of tumor metastasis.

Epigenetic silencing of triple negative breast cancer hallmarks by Withaferin A

Triple negative breast cancer (TNBC) is characterized by poor prognosis and a DNA hypomethylation profile. Withaferin A (WA) is a plant derived steroidal lactone which holds promise as a therapeutic agent for treatment of breast cancer (BC). We determined genome-wide DNA methylation changes in weakly-metastatic and aggressive, metastatic BC cell lines, following 72h treatment to a sub-cytotoxic concentration of WA. In contrast to the DNA demethylating agent 5-aza-2'-deoxycytidine (DAC), WA treatment of MDA-MB-231 cells rather tackles an epigenetic cancer network through gene-specific DNA hypermethylation of tumor promoting genes including ADAM metallopeptidase domain 8 (ADAM8), urokinase-type plasminogen activator (PLAU), tumor necrosis factor (ligand) superfamily, member 12 (TNFSF12), and genes related to detoxification (glutathione S-transferase mu 1, GSTM1), or mitochondrial metabolism (malic enzyme 3, ME3). Gene expression and pathway enrichment analysis further reveals epigenetic suppression of multiple cancer hallmarks associated with cell cycle regulation, cell death, cancer cell metabolism, cell motility and metastasis. Remarkably, DNA hypermethylation of corresponding CpG sites in PLAU, ADAM8, TNSF12, GSTM1 and ME3 genes correlates with receptor tyrosine-protein kinase erbB-2 amplification (HER2)/estrogen receptor (ESR)/progesterone receptor (PR) status in primary BC tumors. Moreover, upon comparing differentially methylated WA responsive target genes with DNA methylation changes in different clinical subtypes of breast cancer patients in the cancer genome atlas (TCGA), we found that WA silences HER2/PR/ESR-dependent gene expression programs to suppress aggressive TNBC characteristics in favor of luminal BC hallmarks, with an improved therapeutic sensitivity. In this respect, WA may represent a novel and attractive phyto-pharmaceutical for TNBC treatment.

CHL1 hypermethylation as a potential biomarker of poor prognosis in breast cancer

The CHL1 gene encodes a cell-adhesion molecule proposed as being a putative tumour-suppressor gene in breast cancer (BC). However, neither the underlying molecular mechanisms nor the clinical value of CHL1 downregulation in BC has been explored. The methylation status of three CpG sites in the CHL1 promoter was analysed by pyrosequencing in neoplastic biopsies from 142 patients with invasive BC and compared with that of non-neoplastic tissues. We found higher CHL1 methylation levels in breast tumours than in non-neoplastic tissues, either from mammoplasties or adjacent-to-tumour, which correlated with lower levels of protein expression in tumours measured by immunohistochemistry. A panel of five BC cell lines was treated with two epigenetic drugs, and restoration of CHL1 expression was observed, indicating in vitro dynamic epigenetic regulation. CHL1 was silenced by shRNA in immortalized but non-neoplastic mammary cells, and enhanced cell proliferation and migration, but not invasion, were found by real-time cell analysis. The prognostic value of CHL1 hypermethylation was assessed by the log-rank test and fitted in a Cox regression model. Importantly, CHL1 hypermethylation was very significantly associated with shorter progression-free survival in our BC patient series, independent of age and stage (p = 0.001). In conclusion, our results indicate that CHL1 is downregulated by hypermethylation and that this epigenetic alteration is an independent prognostic factor in BC.

Prognostic and predictive role of COX-2, XRCC1 and RASSF1 expression in patients with esophageal squamous cell carcinoma receiving radiotherapy

Identification of biomarkers for predicting radiosensitivity would be useful for administering individualized radiotherapy (RT) to patients with esophageal cancer. The aim of the present study was to evaluate the association between cyclooxygenase-2 (COX-2), X-ray repair cross complementing group 1 (XRCC1), ras association domain family 1 (RASSF1) protein expression, clinicopathological characteristics, radiosensitivity and survival rate in 76 patients with esophageal squamous cell carcinoma (ESCC) who were treated with RT. Positive expression of COX-2, XRCC1 and RASSF1 was identified by immunohistochemistry in 81.6, 52.6 and 59.2% of ESCC cases, respectively. Negative COX-2 expression was associated with tumor (T) stage, node (N) stage, clinical stage and complete response (P<0.05), but not with gender, age, tumor location, differentiation degree, lesion length, progression-free survival (PFS) or overall survival (OS; P>0.05). XRCC1 expression was not associated with the clinicopathological features of ESCC, response to RT, PFS or OS. Positive RASSF1 expression was associated with the clinical stage, response to RT, PFS and OS (P<0.05), but not with gender, age, tumor location, T stage, N stage, differentiation degree or the lesion length (P>0.05). In the subgroup analysis, RASSF1 positive/XRCC1 negative expression was correlated with a longer median OS and PFS (P<0.05). Multivariate analyses revealed that the tumor response and RASSF1 expression were significant prognostic factors. Therefore, positive RASSF1 expression is associated with ESCC RT sensitivity, and may be a useful independent prognostic factor for ESCC.

DNA methylation in endometriosis (Review)

Endometriosis is defined by the presence and growth of functional endometrial tissue, outside the uterine cavity, primarily in the ovaries, pelvic peritoneum and rectovaginal septum. Although it is a benign disease, it presents with malignant characteristics, such as invasion to surrounding tissues, metastasis to distant locations and recurrence following treatment. Accumulating evidence suggests that various epigenetic aberrations may play an essential role in the pathogenesis of endometriosis. Aberrant DNA methylation represents a possible mechanism repsonsible for this disease, linking gene expression alterations observed in endometriosis with hormonal and environmental factors. Several lines of evidence indicate that endometriosis may partially be due to selective epigenetic deregulations influenced by extrinsic factors. Previous studies have shed light into the epigenetic component of endometriosis, reporting variations in the epigenetic patterns of genes known to be involved in the aberrant hormonal, immunologic and inflammatory status of endometriosis. Although recent studies, utilizing advanced molecular techniques, have allowed us to further elucidate the possible association of DNA methylation with altered gene expression, whether these molecular changes represent the cause or merely the consequence of the disease is a question which remains to be answered. This review provides an overview of the current literature on the role of DNA methylation in the pathophysiology and malignant evolution of endometriosis. We also provide insight into the mechanisms through which DNA methylation-modifying agents may be the next step in the research of the pharmaceutical treatment of endometriosis.

Proteomics Analysis Reveals Novel RASSF2 Interaction Partners

RASSF2 is a tumor suppressor that shares homology with other Ras-association domain (RASSF) family members. It is a powerful pro-apoptotic K-Ras effector that is frequently inactivated in many human tumors. The exact mechanism by which RASSF2 functions is not clearly defined, but it likely acts as a scaffolding protein, modulating the activity of other pro-apoptotic effectors, thereby regulating and integrating tumor suppressor pathways. However, only a limited number of RASSF2 interacting partners have been identified to date. We used a proteomics based approach to identify additional RASSF2 interactions, and thereby gain a better insight into the mechanism of action of RASSF2. We identified several proteins, including C1QBP, Vimentin, Protein phosphatase 1G and Ribonuclease inhibitor that function in diverse biological processes, including protein post-translational modifications, epithelial-mesenchymal transition, cell migration and redox homeostasis, which have not previously been reported to interact with RASSF2. We independently validated two of these novel interactions, C1QBP and Vimentin and found that the interaction with C1QBP was enhanced by K-Ras whereas, interestingly, the Vimentin interaction was reduced by K-Ras. Additionally, RASSF2/K-Ras regulated the acetylation of Vimentin. Our data thus reveal novel mechanisms by which RASSF2 may exert its functions, several of which may be Ras-regulated.

Differential role of gene hypermethylation in adenocarcinomas, squamous cell carcinomas and cervical intraepithelial lesions of the uterine cervix

Cervical cancer is the third most common cancer in women worldwide. The hypermethylation of P16, TSLC-1 and TSP-1 genes was analyzed in squamous cell carcinomas (SCC), cervical intraepithelial lesions (CIN) and adenocarcinomas (ADC) of the uterine cervix (total 181 lesions). Additionally human papillomavirus (HPV) type, EPB41L3, RASSF1 and RASSF2 hypermethylation were tested in ADC and the results were compared with those obtained previously by our group in SCC. P16, TSLC-1 and TSP-1 hypermethylation was more frequent in SCCs than in CINs. These percentages and the corresponding ones for EPB41L3, RASSF1 and RASSF2 genes were also higher in SCCs than in ADCs, except for P16. The presence of HPV in ADCs was lower than reported previously in SCC and CIN. Patients with RASSF1A hypermethylation showed significantly longer disease-free survival (P = 0.015) and overall survival periods (P = 0.009) in ADC patients. To our knowledge, this is the first description of the EPB41L3 and RASSF2 hypermethylation in ADCs. These results suggest that the involvement of DNA hypermethylation in cervical cancer varies depending on the histological type, which might contribute to explaining the different prognosis of patients with these types of tumors.