Systematic CpG islands methylation profiling of genes in the wnt pathway in epithelial ovarian cancer identifies biomarkers of progression-free survival

Evolving landscape of detection and targeting miRNA/epigenetics for therapeutic strategies in ovarian cancer

Ovarian cancer (OC) accounts for the highest mortality rates among all gynecologic malignancies. The high mortality of OC is often associated with delayed detection, prolonged latency, enhanced metastatic potential, acquired drug resistance, and frequent recurrence. This review comprehensively explores key aspects of OC, including cancer diagnosis, mechanisms of disease resistance, and the pivotal role of epigenetic regulation, particularly by microRNAs (miRs) in cancer progression. We highlight the intricate regulatory mechanisms governing miR expression within the context of OC and the current status of epigenetic advancement in the therapeutic development and clinical trial progression. Through network analysis we elucidate the regulatory interactions between dysregulated miRs in OC and their targets which are involved in different signaling pathways. By exploring these interconnected facets and critical analysis, we endeavor to provide a nuanced understanding of the molecular dynamics underlying OC, its detection and shedding light on potential avenues for miRs and epigenetics-based therapeutic intervention and management strategies.

Epigenetic regulation in ovarian cancer

Ovarian cancer is one of the diseases that have the highest mortality rate for women, especially women over 50 years old. In the future, incidence and mortality rates are predicted to extend in countries with low HDI. Instability in the structure and function of genetic factors has long been known as a cause of cancer, including ovarian cancer. Besides understanding gene mutations, epigenetic alterations have emerged as another aspect leading to the pathogenesis of ovarian neoplasm. The development and progression of this fatal disease have been found to be associated with abnormalities of epigenetic regulation. DNA methylation, histone modification, and non-coding RNAs-based gene silencing are processes of interest in developing ovarian carcinoma and are also new targets for cancer detection or treatment.

Identification of a CpG-based signature coupled with gene expression as prognostic indicators for melanoma: a preliminary study

DNA methylation is an important part of the genomic biology, which recently allowed the identification of key biomarkers for a variety of cancers, including cutaneous melanoma. Despite the current knowledge in cutaneous melanoma, there is a clear need for new efficient biomarkers in clinical application of detection. We use The Cancer Genome Atlas data as a training set and a multi-stage screening strategy to identify prognostic characteristics of melanoma based on DNA methylation. Three DNA methylation CpG sites were identified to be related to the overall survival in the skin cutaneous melanoma cohort. This signature was validated in two independent datasets from Gene Expression Omnibus. The stratified analysis by clinical stage, age, gender, and grade retained the statistical significance. The methylation signature was significantly correlated with immune cells and anti-tumor immune response. Moreover, gene expression corresponding to the candidate CpG locus was also significantly correlated with the survival rate of the patient. About 49% of the prognostic effects of methylation are mediated by affecting the expression of the corresponding genes. The prognostic characteristics of DNA methylation combined with clinical information provide a better prediction value tool for melanoma patients than the clinical information alone. However, more experiments are required to validate these findings. Overall, this signature presents a prospect of novel and wide-ranging applications for appropriate clinical adjuvant trails.

Therapeutic targeting of DNA damage repair pathways guided by homologous recombination deficiency scoring in ovarian cancers

The susceptibility of cells to DNA damage and their DNA repair ability are crucial for cancer therapy. Homologous recombination is one of the major repairing mechanisms for DNA double-strand breaks. Approximately half of ovarian cancer (OvCa) cells harbor homologous recombination deficiency (HRD). Considering that HRD is a major hallmark of OvCas, scholars proposed HRD scoring to evaluate the HRD degree and guide the choice of therapeutic strategies for OvCas. In the last decade, synthetic lethal strategy by targeting poly (ADP-ribose) polymerase (PARP) in HR-deficient OvCas has attracted considerable attention in view of its favorable clinical effort. We therefore suggested that the uses of other DNA damage/repair-targeted drugs in HR-deficient OvCas might also offer better clinical outcome. Here, we reviewed the current small molecule compounds that targeted DNA damage/repair pathways and discussed the HRD scoring system to guide their clinical uses.

IntOMICS: A Bayesian Framework for Reconstructing Regulatory Networks Using Multi-Omics Data

Integration of multi-omics data can provide a more complex view of the biological system consisting of different interconnected molecular components. We present a new comprehensive R/Bioconductor-package, IntOMICS, which implements a Bayesian framework for multi-omics data integration. IntOMICS adopts a Markov Chain Monte Carlo sampling scheme to systematically analyze gene expression, copy number variation, DNA methylation, and biological prior knowledge to infer regulatory networks. The unique feature of IntOMICS is an empirical biological knowledge estimation from the available experimental data, which complements the missing biological prior knowledge. IntOMICS has the potential to be a powerful resource for exploratory systems biology.

Clinical Significance of NKD Inhibitor of WNT Signaling Pathway 1 (NKD1) in Glioblastoma

Introduction. As the most malignant type of gliomas, glioblastoma is characterized with disappointing prognosis. Here, we aimed to investigate expression and function of NKD inhibitor of Wnt signaling pathway 1 (NKD1), an antagonist of Wnt-beta-catenin signaling pathways, in glioblastoma. Methods. The mRNA level of NKD1 was firstly retrieved from TCGA glioma dataset to evaluate its correlation with clinical characteristics and its value in prognosis prediction. Then, its protein expression level in glioblastoma was tested by immunohistochemistry staining in a retrospectively cohort collected from our medical center (n = 66). Univariate and multivariate survival analyses were conducted to assess its effect on glioma prognosis. Two glioblastoma cell lines, U87 and U251, were used to further investigate the tumor-related role of NKD1 through overexpression strategy in combination with cell proliferation assays. Immune cell enrichment in glioblastoma and its correlation with NKD1 level was finally assessed using bioinformatics analyses. Results. NKD1 shows a lower expression level in glioblastoma compared to that in the normal brain or other glioma subtypes, which is independently correlated to a worse prognosis in both the TCGA cohort and our retrospective cohort. Overexpressing NKD1 in glioblastoma cell lines can significantly attenuate cell proliferation. In addition, expression of NKD1 in glioblastoma is negatively correlated to the T cell infiltration, indicating it may have crosstalk with the tumor immune microenvironment. Conclusions. NKD1 inhibits glioblastoma progression and its downregulated expression indicates a poor prognosis.

A novel DNA methylation signature to improve survival prediction of progression-free survival for testicular germ cell tumors

This study aimed to develop a nomogram for predicting the progression-free survival (PFS) of testicular germ cell tumors (TGCT) patients based on DNA methylation signature and clinicopathological characteristics. The DNA methylation profiles, transcriptome data, and clinical information of TGCT patients were obtained from the Cancer Genome Atlas (TCGA) database. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a prognostic CpG sites-derived risk signature. Differential expression analysis, functional enrichment analysis, immunoinfiltration analysis, chemotherapy sensitivity analysis, and clinical feature correlation analysis were performed to elucidate the differences among risk groups. A prognostic nomogram integrating CpG sites-derived risk signature and clinicopathological features was further established and evaluated likewise. A risk score model based on 7 CpG sites was developed and found to exhibit significant differences among different survival, staging, radiotherapy, and chemotherapy subgroups. There were 1452 differentially expressed genes between the high- and low-risk groups, with 666 being higher expressed and 786 being lower expressed. Genes highly expressed were significantly enriched in immune-related biological processes and related to T-cell differentiation pathways; meanwhile, down-regulated genes were significantly enriched in extracellular matrix tissue organization-related biological processes and involved in multiple signaling pathways such as PI3K-AKT. As compared with the low-risk group, patients in the high-risk group had decreased lymphocyte infiltration (including T-cell and B-cell) and increased macrophage infiltration (M2 macrophages). They also showed decreased sensitivity to etoposide and bleomycin chemotherapy. Three clusters were obtained by consensus clustering analysis based on the 7 CpG sites and showed distinct prognostic features, and the risk scores in each cluster were significantly different. Multivariate Cox regression analysis found that the risk scores, age, chemotherapy, and staging were independent prognostic factors of PFS of TGCT, and the results were used to formulate a nomogram model that was validated to have a C-index of 0.812. Decision curve analysis showed that the nomogram model was superior to other strategies in the prediction of PFS of TGCT. In this study, we successfully established CpG sites-derived risk signature, which might serve as a useful tool in the prediction of PFS, immunoinfiltration, and chemotherapy sensitivity for TGCT patients.

Construction of DNA methylation-based nomogram for predicting biochemical-recurrence-free survival in prostate cancer

This study aimed to develop a DNA methylation-based nomogram for predicting biochemical recurrence in patients with prostate cancer. A DNA methylation signature was obtained via univariate, lasso, and stepwise multivariate Cox regression models. A 11-DNA methylation signature yielded a high evaluative performance for biochemical-recurrence-free survival. Cox regression analysis indicated that 11-DNA methylation signature and Gleason score served as independent risk factors. A nomogram was constructed based on the 11-DNA methylation signature and Gleason score, and C-index as well as the calibration plots demonstrated good performance and clinical application of the nomogram. A DNA methylation-associated nomogram serve as a prognosis stratification tool to predict the biochemical recurrence of prostate cancer patients after radical prostatectomy.

Decrease of FZD4 exon 1 methylation in probands from FZD4-associated FEVR family of phenotypic heterogeneity

Familial exudative vitreoretinopathy (FEVR) is an important cause of childhood blindness and is clinically characterized by phenotypic heterogeneity. FEVR patients harboring the same genetic mutation vary widely in disease severity. The purpose of this study was to explore non-genetic factors that regulate FEVR phenotypic heterogeneity. We detected methylation levels of 21 CpG sites located at the FZD4 exon 1 region of 11 probands, 12 asymptomatic/paucisymptomatic carriers and 11 non-carriers from 10 unrelated FZD4-associated FEVR families using bisulfite amplicon sequencing (BSAS). Our results showed reduced methylation level of FZD4 exon 1 in probands, suggesting that FZD4 exon 1 methylation level may be negatively linked with FEVR disease severity. It provided a new research direction for follow-up research, helping us better understand the complexity of the FEVR-causing mechanism.

Tackling drug resistance in ovarian cancer with epigenetic targeted drugs

Epigenetic dysregulation plays a crucial role in the development and progression of ovarian cancer. Since the first experiment conducted on resistant ovarian cancer cells using demethylating drugs, multiple clinical trials have revealed that epigenetic targeted drugs combined with chemotherapy, molecular-targeted drugs, or even immunotherapy could enhance tumor sensitivity and reverse acquired resistances. Here, we summarized the combination strategies of epigenetic targeted drugs with other treatment strategies of ovarian cancer and discussed the principles of combination therapy. Finally, we enumerated several reasonable clinical trial designs as well as future drug development strategies, which may provide promising ideas for the application of epigenetic drugs to ovarian cancer.

Chemotherapy resistance in epithelial ovarian cancer: Mechanisms and emerging treatments

Ovarian cancer (OC) remains a fatal malignancy because most patients experience recurrent disease, which is resistant to chemotherapy. The outcomes for patients with platinum-resistant OC are poor, response rates to further chemotherapy are low and median survival is lower than 12 months. The complexity of platinum-resistant OC, which comprises a heterogeneous spectrum of diseases, is indeed far from being completely understood. Therefore, comprehending tumors' biological behaviour to identify reliable biomarkers, which may predict responses to therapies, is a demanding challenge to improve OC management. In the age of precision medicine, efforts to overcome platinum resistance in OC represent a dynamic and vast field in which innovative drugs and clinical trials rapidly develop. This review will present the exceptional biochemical environment implicated in OC and highlights mechanisms of chemoresistance. Furthermore, innovative molecules and new therapeutic opportunities are presented, along with currently available therapies and ongoing clinical trials.

Identification of 4-methylation driven genes based prognostic signature in thyroid cancer: an integrative analysis based on the methylmix algorithm

Thyroid cancer (TC) is known with a high rate of persistence and recurrence. We aimed to develop a prognostic signature to monitor and assess the survival of TC patients. mRNA expression and methylation data were downloaded from the TCGA database. Then, R package methylmix was applied to construct a mixed model was used to identify methylation-driven genes (MDGs) according to the methylation levels. Furthermore, an MDGs based prognostic signature and predictive nomogram were constructed according to the analysis of univariate and multivariate Cox regression. Totally 62 methylation-driven genes that were mainly enriched in substrate-dependent cell migration, cellular response to mechanical stimulus, et al. were found in TC tissues. aldolase C (AldoC), C14orf62, dishevelled 1 (DVL1), and protein tyrosine phosphatase receptor type C (PTPRC) were identified to be significantly related to patients' survival, and may serve as independent prognostic biomarkers for TC. Additionally, the prognostic methylation signature and a novel prognostic, predictive nomogram was established based on the methylation level of 4 MDGs. In this study, we developed a 4-MDGs based prognostic model, which might be the potential predictors for the survival rate of TC patients, and this findings might provide a novel sight for accurate monitoring and prognosis assessment.

A High Epigenetic Risk Score Shapes the Non-Inflamed Tumor Microenvironment in Breast Cancer

Background: Epigenetic dysregulation via aberrant DNA methylation has gradually become recognized as an efficacious signature for predicting tumor prognosis and response to therapeutic targets. However, reliable DNA methylation biomarkers describing tumorigenesis remain to be comprehensively explored regarding their prognostic and therapeutic potential in breast cancer (BC). Methods: Whole-genome methylation datasets integrated from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database were profiled (n = 1,268). A three-stage selection procedure (discovery, training, and external validation) was utilized to screen out the prominent biomarkers and establish a robust risk score from more than 300,000 CpG sites after quality control, rigorous filtering, and reducing dimension. Moreover, gene set enrichment analyses guided us to systematically correlate this epigenetic risk score with immunological characteristics, including immunomodulators, anti-cancer immunity cycle, immune checkpoints, tumor-infiltrating immune cells and a series of signatures upon modulating components within BC tumor microenvironment (TME). Multi-omics data analyses were performed to decipher specific genomic alterations in low- and high-risk patients. Additionally, we also analyzed the role of risk score in predicting response to several treatment options. Results: A 10-CpG-based prognostic signature which could significantly and independently categorize BC patients into distinct prognoses was established and sufficiently validated. And we hypothesize that this signature designs a non-inflamed TME in BC based on the evidence that the derived risk score is negatively correlated with tumor-associated infiltrating immune cells, anti-cancer immunity cycle, immune checkpoints, immune cytolytic activity, T cell inflamed score, immunophenoscore, and the vast majority of immunomodulators. The identified high-risk patients were characterized by upregulation of immune inhibited oncogenic pathways, higher TP53 mutation and copy number burden, but lower response to cancer immunotherapy and chemotherapy. Conclusion: Our work highlights the complementary roles of 10-CpG-based signature in estimating overall survival in BC patients, shedding new light on investigating failed events concerning immunotherapy at present.

A DNA methylation-associated nomogram predicts the overall survival of osteosarcoma

Numerous reports have demonstrated that DNA methylation may be underlying prognostic biomarkers of cancer. However, few studies indicated that DNA methylation was independent biomarker for osteosarcoma prognosis. We aimed to discover and validate a novel DNA methylation signature for prediction of osteosarcoma patients' overall survival (OS).The DNA methylation data of osteosarcoma patients was researched from The Cancer Genome Atlas (TCGA) database. Overall, 80 samples with 485,577 DNA methylation sites were enrolled in our study. The 80 samples were randomly allocated into training dataset (first two-thirds) and validation dataset (remaining one-third). Initially, the univariate Cox proportional hazard analysis was performed in the training dataset to determine methylation sites significantly (P < .05) relevant to osteosarcoma patients' OS as underlying indicators. Subsequently, the underlying indicators were employed to carry out the least absolute shrinkage and selection operator (LASSO) Cox regression analysis for further selecting the candidate methylation sites. Then, the selected candidate methylation sites were employed as covariates to perform multivariate Cox proportional hazard model for identifying the predictor of OS in osteosarcoma patients. The validation dataset was used to validate the predictive accuracy by receiver operating characteristic (ROC) analysis and Kaplan-Meier survival analysis.We discovered a 7-DNA methylation signature closely relevant to OS of osteosarcoma patients. AUC at 1, 3, 5 years in training dataset (0.951, 0.922, 0.925, respectively), testing dataset (0.952, 0.918, 0.925, respectively), and entire dataset (0.952, 0.968, 0.968, respectively). Suggesting high predictive values for OS of osteosarcoma patients. In addition, a methylation-associated nomogram suggested good predictive value and clinical application.We discovered and validated a novel 7-DNA methylation-associated nomogram for predicting OS of osteosarcoma patients.

Methylation biomarkers with discriminating ability are potential therapeutic targets in lung adenocarcinoma

Aims: Given the reversibility of methylation, biomarkers with discriminating ability are of great interest for targeted therapeutic sites. Materials & methods: Methylation array data of 461 lung adenocarcinoma (LUAD) patients comprising of 458 tumor and 32 LUAD paracancerous samples were compared using partial least squares discrimination analysis and receiver operating characteristics analysis. Results: A six-DNA methylation signature (corresponding to five genes) was found to significantly discriminate normal and LUAD samples. Kyoto Encyclopedia of Genes and Genomes analysis indicated enrichment of methylation sites in the Wnt pathway in LUAD compared with controls. Conclusion: This six-DNA methylation signature demonstrated potential as a novel biomarker for diagnosis and therapeutic targets. Further, inhibition of Wnt signaling pathway may be an important step in LUAD progression.

The Development of Three-DNA Methylation Signature as a Novel Prognostic Biomarker in Patients with Colorectal Cancer

Aims

The prognosis of colorectal cancer (CRC) remains poor. This study aimed to develop and validate DNA methylation-based signature model to predict overall survival of CRC patients.

Methods

The methylation array data of CRC patients were retrieved from The Cancer Genome Atlas (TCGA) database. These patients were divided into training and validation datasets. A risk score model was established based on Kaplan-Meier and multivariate Cox regression analysis of training cohort and tested in validation cohort.

Results

Among total 14,626 DNA methylation candidate markers, we found that a three-DNA methylation signature (NR1H2, SCRIB, and UACA) was significantly associated with overall survival of CRC patients. Subgroup analysis indicated that this signature could predict overall survival of CRC patients regardless of age and gender.

Conclusions

We established a prognostic model consisted of 3-DNA methylation sites, which could be used as potential biomarker to evaluate the prognosis of CRC patients.

Colon cancer-specific diagnostic and prognostic biomarkers based on genome-wide abnormal DNA methylation

Abnormal DNA methylation is a major early contributor to colon cancer (COAD) development. We conducted a cohort-based systematic investigation of genome-wide DNA methylation using 299 COAD and 38 normal tissue samples from TCGA. Through conditional screening and machine learning with a training cohort, we identified one hypomethylated and nine hypermethylated differentially methylated CpG sites as potential diagnostic biomarkers, and used them to construct a COAD-specific diagnostic model. Unlike previous models, our model precisely distinguished COAD from nine other cancer types (e.g., breast cancer and liver cancer; error rate ≤ 0.05) and from normal tissues in the training cohort (AUC = 1). The diagnostic model was verified using a validation cohort from The Cancer Genome Atlas (AUC = 1) and five independent cohorts from the Gene Expression Omnibus (AUC ≥ 0.951). Using Cox regression analyses, we established a prognostic model based on six CpG sites in the training cohort, and verified the model in the validation cohort. The prognostic model sensitively predicted patients’ survival (p ≤ 0.00011, AUC ≥ 0.792) independently of important clinicopathological characteristics of COAD (e.g., gender and age). Thus, our DNA methylation analysis provided precise biomarkers and models for the early diagnosis and prognostic evaluation of COAD.

E-Cadherin, NFATC3, and PLP2 Are Differentially Methylated in Multiple Cancers

It is well documented that cancer cells have abnormal methylation patterns often caused by faulty methylating machinery. Specifically, E-cadherin, NFATC3, and PLP2 are 3 genes known to be aberrantly methylated in cancer cells. These genes are well documented for their role in signaling pathways involved with cell proliferation, adhesion, migration, and other signs of tumor progression. Therefore, changes in gene expression of CDH1, NFATC3, and PLP2 due to aberrant methylation can lead to profound changes in cellular function and tumor formation. In order to ensure that previous in vitro and in vivo methylation studies match what is observed in the clinic, we utilized a bioinformatics approach to complete an extensive analysis of methylation patterns of these 3 genes, analyzing over 5000 patient samples, across all cancers for which both normal and tumor tissues were available. Specifically, we analyzed overall and site-specific methylation patterns, at CpG islands and shores, of all 3 genes across 14 cancer types. Furthermore, we compared these methylation levels in normal and tumor samples of both matched and unmatched patient samples in order to determine any differences between groups. Finally, we examined whether an aberrant DNA methyltransferase, DNMT3B7, known to be expressed in cancer cells and to alter methylation patterns in vitro correlated with altered overall and site-specific methylation of CDH1, NFATC3, and PLP2 in these patient samples. Our results indicate that methylation patterns of CDH1 and NFATC3 were unexpectedly varied across tumors, contrary to previous studies performed in vitro, while PLP2 showed the expected hypomethylation pattern in tumor tissues. We also observed some correlation between DNMT3B7 expression and methylation patterns of these genes, but patterns were inconsistent. Taken together, these results emphasize the necessity for in vivo and patient studies rather than a complete reliance on in vitro data and provide multiple areas of future research.

Frizzled Receptors in Tumors, Focusing on Signaling, Roles, Modulation Mechanisms, and Targeted Therapies

Wnt molecules play crucial roles in development and adult homeostasis through their receptors Frizzled proteins (Fzds). Fzds mediate canonical β-catenin pathway and various noncanonical β-catenin-independent pathways. Aberrant Fzd signaling is involved in many diseases including cancer. Wnt/β-catenin is a well-established oncogenic pathway involved in almost every aspect of tumor development. However, Fzd-mediated noncanonical Wnt pathways function as both tumor promoters and tumor suppressors depending on cellular context. Fzd-targeted therapies have proven to be effective on cultured tumor cells, tumor cell xenografts, mouse tumor models, and patient-derived xenografts (PDX). Moreover, Fzd-targeted therapies synergize with chemotherapy in preclinical models. However, the occurrence of fragility fractures in patients treated with Fzd-targeted agents such as OMP-54F28 and OMP-18R5 limits the development of this combination. Along with new insights on signaling, roles, and modulation mechanisms of Fzds in human tumors, more Fzd-related therapeutic targets will be developed.

Negative Regulation of Serine Threonine Kinase 11 (STK11) through miR-100 in Head and Neck Cancer

BACKGROUND

Serine Threonine Kinase 11 (STK11), also known as LKB1, is a tumor suppressor gene that regulates several biological processes such as apoptosis, energetic metabolism, proliferation, invasion, and migration. During malignant progression, different types of cancer inhibit STK11 function by mutation or epigenetic inactivation. In Head and Neck Cancer, it is unclear what mechanism is involved in decreasing STK11 levels. Thus, the present work aims to determine whether STK11 expression might be regulated through epigenetic or post-translational mechanisms.

METHODS

Expression levels and methylation status for STK11 were analyzed in 59 cases of head and neck cancer and 10 healthy tissue counterparts. Afterward, we sought to identify candidate miRNAs exerting post-transcriptional regulation of STK11. Then, we assessed a luciferase gene reporter assay to know if miRNAs directly target STK11 mRNA. The expression levels of the clinical significance of mir-100-3p, -5p, and STK11 in 495 HNC specimens obtained from the TCGA database were further analyzed. Finally, the Kaplan-Meier method was used to estimate the prognostic significance of the miRNAs for Overall Survival, and survival curves were compared through the log-rank test.

RESULTS

STK11 was under-expressed, and its promoter region was demethylated or partially methylated. miR-17-5p, miR-106a-5p, miR-100-3p, and miR-100-5p could be negative regulators of STK11. Our experimental data suggested evidence that miR-100-3p and -5p were over-expressed in analyzed tumor patient samples. Luciferase gene reporter assay experiments showed that miR-100-3p targets and down-regulates STK11 mRNA directly. With respect to overall survival, STK11 expression level was significant for predicting clinical outcomes.

CONCLUSION

This is, to our knowledge, the first report of miR-100-3p targeting STK11 in HNC. Together, these findings may support the importance of regulation of STK11 through post-transcriptional regulation in HNC and the possible contribution to the carcinogenesis process in this neoplasia.

A methylomics-associated nomogram predicts recurrence-free survival of thyroid papillary carcinoma

Background

Thyroid papillary carcinoma (TPC) is the most common type of thyroid cancer (TC). The prognosis of TPC patients with tumor‐cell metastasis is poor. Therefore, this study aims to develop a model for predicting TPC patients' recurrence‐free survival (RFS).

Methods

We included 546 TPC patients who were clinically and pathologically diagnosed with TPC. The methylation biomarkers that associate with RFS were explored. These 546 samples were divided into training dataset (first 70%) and validation dataset (remaining 30%) randomly. The training dataset was used to identify prognostic biomarkers and construct risk prediction model, in addition, the validation dataset was used to verify the predictive performance of the model. We used Cox proportional hazard analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to identify the significant predictive biomarkers, and establish the relapse risk prediction model from the identified biomarkers.

Results

A 6‐DNA methylation signature yielded a high evaluative performance for RFS. The Kaplan‐Meier analysis indicated that the 6‐DNA methylation signature could significantly distinguish the high‐ and low‐risk patients in training, validation and entire sets. In addition, a nomogram was constructed based on risk score, metastasis status and residual tumor status, and C‐index, receiver operating characteristic (ROC) and the calibration plots analysis which demonstrated the good performance and clinical utility of the nomogram.

Conclusions

The results suggested that the 6‐DNA methylation signature is the independent prognostic marker for RFS and functioned as a significant tool for guiding the clinical treatment of TPC patients.

A prognostic 11-DNA methylation signature for lung squamous cell carcinoma

Background

Lung squamous cell carcinoma (LUSC), as the second frequent subtype of lung cancer, causes lots of mortalities primarily due to a lack of precise prognostic markers and timely treatment intervention. Previous studies have constructed several risk prognostic models based on DNA methylation sites in multiple tumors, whereas, DNA methylation signature of LUSC remains to be built, and its predictive value need to be evaluated.

Methods

The genome-wide DNA methylation data of LUSC samples was obtained from The Cancer Genome Atlas dataset. Univariate Cox analysis and the least absolute shrinkage and selection operator (LASSO) were implemented to identify DNA methylation sites related to overall survival of LUSC patients. Thus, we performed multivariate Cox regression to establish a DNA methylation signature. The Kaplan-Meier (K-M) survival curves and time-dependent receiver operating characteristic (ROC) curves were plotted to estimate the prognostic power of the signature. Comparison with other known prognostic biomarkers, our DNA methylation signature showed higher predictive specificity and sensitivity. In addition, multivariate Cox regression screened out independent prognostic factors and constructed a nomogram.

Results

Several statistical methods were performed to construct an 11-DNA methylation signature. LUSC patients were divided into low- and high-risk group based on risk score, and high-risk group had a shorter survival time. According to the results of K-M and ROC analyses, the 11-DNA methylation signature showed significant sensitivity and specificity in predicting the LUSC patients’ overall survival. Finally, we integrated some independent prognostic factors (risk score, metastasis stage, and tobacco smoking history) to construct a nomogram, which has excellent prognostic power and may provide guidance for the therapeutic strategies.

Conclusions

We constructed the first risk prognosis model based on DNA methylation site in LUSC, which showed better predictive ability. In addition, a nomogram integrating the DNA methylation signature, metastasis stage, and tobacco smoking history was developed.

Prognostic and predictive value of a five-molecule panel in resected pancreatic ductal adenocarcinoma: A multicentre study

Background

Pancreatic ductal adenocarcinoma (PDAC) has a devastating prognosis. The performance of clinicopathologic parameters and molecules as prognostic factors remains limited and inconsistent. The present study aimed to construct a multi-molecule biomarker panel to more accurately predict post-resectional prognosis of PDAC patients.

Methods

Firstly, a novel computational strategy integrating prognostic evidence from omics and literature on the basis of bioinformatics prediction (CIPHER) to generate the network, was designed to systematically identify potential high-confidence PDAC-related prognostic candidates. After specimens from 605 resected PDAC patients were retrospectively collected, 23 candidates were detected immunohistochemically in tissue-microarrays for the development cohort to construct a multi-molecule panel. Lastly, the panel was validated in two independent cohorts.

Findings

According to the constructed five-molecule panel, disease-specific survival (DSS) was significantly poorer in high-risk patients than in low-risk ones in development cohort (HR 2.15, 95%CI 1.51–3.05, P<0.0001; AUC 0.67). In two validation cohorts, similar significant differences between the two groups were also observed (HR 3.18 and 3.31, 95%CI 1.89–5.37 and 1.78–6.16, All P<0.0001; AUC 0.72 and 0.73). In multivariate analyses, this panel was the sole prognosticator that was significant in each cohort. Furthermore, its predictive power for long-term survival, higher than its individual constituents, could be largely enhanced by combination with traditional clinicopathological variables. Finally, adjuvant chemotherapy (ACT) correlated with better DSS only in high-risk patients, uni- and multi-variately, in all the cohorts.

Interpretation

The novel prognostic panel developed by a systematically network-based strategy presents strong ability in prediction of post-resectional survival of PDAC patients. Furthermore, panel-defined high-risk patients might benefit more from ACT.

DNA methylation profiling to predict overall survival risk in gastric cancer: development and validation of a nomogram to optimize clinical management

DNA methylation has been reported to serve an important role in the carcinogenesis and development of gastric cancer. Our aim was to systematically develop an individualized prediction model of the survival risk combing clinical and methylation factors in gastric cancer. A univariate Cox proportional risk regression analysis was used to identify the prognosis-associated methylation sites based on the differentially expressed methylation sites between early and advanced gastric cancer group, then we applied least absolute shrinkage and selection operator (LASSO) Cox regression model to screen candidate methylation sites. Subsequently, multivariate Cox proportional risk regression analysis was conducted to identify predictive signature according to the candidate sites. Relative operating characteristic curve (ROC) analysis manifested that an 11-methylation signature exhibited great predictive efficiency for 1-, 3-, 5-year survival events. Patients in the low-risk group classified according to 11-methylation signature-based risk score yield significantly better survival than that in high-risk group. Moreover, Cox regression analysis combing methylation-based risk score and other clinical factors indicated that 11-methylation signature served as an independent risk factor. The predictive value of risk score was validated in the testing dataset. In addition, a nomogram was constructed and the ROC as well as calibration plots analysis demonstrated the good performance and clinical application of the nomogram. In conclusion, the result suggested the 11-DNA methylation signature may be potentially independent prognostic marker and functioned as a significant tool for guiding the clinical prediction of gastric cancer patients' overall survival.

Expression of Wnt pathway molecules is associated with disease outcome in metastatic high-grade serous carcinoma

The objective of this study was to analyze the expression and clinical role of Wnt pathway molecules in metastatic high-grade serous carcinoma (HGSC). mRNA expression by qPCR of 20 molecules related to Wnt signaling (WNT1, WNT2, WNT3, WNT4, WNT5A, WNT6, WNT7, WNT11, FZD1, FZD4, FZD5, FZD6, FZD7, FZD8, FZD10, LRP5, LRP6, DKK, CCND, RUNX2) was analyzed in 87 HGSC effusions. Thirty-nine surgical specimens (19 ovarian, 20 from other intra-abdominal sites) were analyzed for comparative purposes. Protein expression of YAP and LRP and their phosphorylated forms by western blotting were analyzed in 52 tumors. Significant differences in mRNA expression as a function of the anatomic site were observed for WNT3 (p = 0.005), WNT5A (p = 0.008), WNT7 (p < 0.001), FRZ5 (p = 0.04), and FRZ6 (p < 0.001). YAP and LRP and their phosphorylated forms were detected in HGSC specimens. FZD10 was overexpressed in effusions from patients who had complete response to chemotherapy compared with those with less favorable response (p = 0.037). WNT4 (p = 0.005), WNT7 (p = 0.047), RUNX2 (p = 0.038), LRP5 (p = 0.022), LRP6 (p = 0.011), FZD6 (p = 0.036), FZD7 (p = 0.004), and FZD10 (p = 0.015) levels were inversely related to primary chemoresistance. High FZD5 levels in pre-chemotherapy effusions tapped at diagnosis and high WNT2 levels in post-chemotherapy disease recurrence effusions were related to shorter overall survival (p = 0.018 and p = 0.011, respectively), whereas high RUNX2 (p = 0.031) and FZD1 (p = 0.029) in post-chemotherapy effusions were associated with longer overall survival. In multivariate analysis of post-chemotherapy cases, WNT2 (p = 0.002), RUNX2 (p = 0.017), FZD1 (p = 0.036), and FZD4 (p = 0.013) were independent prognosticators. In conclusion, expression of Wnt pathway molecules is anatomic site dependent. In HGSC effusions, it is informative of chemoresponse and survival.

A Two-DNA Methylation Signature to Improve Prognosis Prediction of Clear Cell Renal Cell Carcinoma

PURPOSE

Effective biomarkers and models are needed to improve the prognostic prospects of clear cell renal cell carcinoma (ccRCC). The purpose of this work was to identify DNA methylation biomarkers and to evaluate the utility of DNA methylation analysis for ccRCC prognosis.

MATERIALS AND METHODS

An overview of genome-wide methylation of ccRCC tissues derived from The Cancer Genome Atlas (TCGA) database was download for analysis. DNA methylation signatures were identified using Cox regression methods. The potential clinical significance of methylation biomarkers acting as a novel prognostic markers was analyzed using the Kaplan-Meier method and receiver operating characteristic (ROC) curves.

RESULTS

This study analyzed data for 215 patients with information on 23171 DNA methylation sites and identified a two-DNA methylation signature (cg18034859, cg24199834) with the help of a step-wise multivariable Cox regression model. The area under the curve of ROCs for the two-DNA methylation signature was 0.819. The study samples were stratified into low- and high-risk classifications based on an optimal threshold, and the two groups showed markedly different survival rates. Moreover, the two-DNA methylation marker was suitable for patients of varying ages, sex, stages (I and IV), and histologic grade (G2).

CONCLUSION

The two-DNA methylation signature was deemed to be a potential novel prognostic biomarker of use in increasing the accuracy of predicting overall survival of ccRCC patients.

Epigenetic Biomarkers in the Management of Ovarian Cancer: Current Prospectives

Ovarian cancer (OC) causes significant morbidity and mortality as neither detection nor screening of OC is currently feasible at an early stage. Difficulty to promptly diagnose OC in its early stage remains challenging due to non-specific symptoms in the early-stage of the disease, their presentation at an advanced stage and poor survival. Therefore, improved detection methods are urgently needed. In this article, we summarize the potential clinical utility of epigenetic signatures like DNA methylation, histone modifications, and microRNA dysregulation, which play important role in ovarian carcinogenesis and discuss its application in development of diagnostic, prognostic, and predictive biomarkers. Molecular characterization of epigenetic modification (methylation) in circulating cell free tumor DNA in body fluids offers novel, non-invasive approach for identification of potential promising cancer biomarkers, which can be performed at multiple time points and probably better reflects the prevailing molecular profile of cancer. Current status of epigenetic research in diagnosis of early OC and its management are discussed here with main focus on potential diagnostic biomarkers in tissue and body fluids. Rapid and point of care diagnostic applications of DNA methylation in liquid biopsy has been precluded as a result of cumbersome sample preparation with complicated conventional methods of isolation. New technologies which allow rapid identification of methylation signatures directly from blood will facilitate sample-to answer solutions thereby enabling next-generation point of care molecular diagnostics. To date, not a single epigenetic biomarker which could accurately detect ovarian cancer at an early stage in either tissue or body fluid has been reported. Taken together, the methodological drawbacks, heterogeneity associated with ovarian cancer and non-validation of the clinical utility of reported potential biomarkers in larger ovarian cancer populations has impeded the transition of epigenetic biomarkers from lab to clinical settings. Until addressed, clinical implementation as a diagnostic measure is a far way to go.

A four-DNA methylation biomarker is a superior predictor of survival of patients with cutaneous melanoma

Cutaneous melanoma (CM) is a life-threatening form of skin cancer. Prognostic biomarkers can reliably stratify patients at initial melanoma diagnosis according to risk, and may inform clinical decisions. Here, we performed a retrospective, cohort-based study analyzing genome-wide DNA methylation of 461 patients with CM from the TCGA database. Cox regression analyses were conducted to establish a four-DNA methylation signature that was significantly associated with the overall survival (OS) of patients with CM, and that was validated in an independent cohort. Corresponding Kaplan-Meier analysis displayed a distinct separation in OS. The ROC analysis confirmed that the predictive signature performed well. Notably, this signature exhibited much higher predictive accuracy in comparison with known biomarkers. This signature was significantly correlated with immune checkpoint blockade (ICB) immunotherapy-related signatures, and may have potential as a guide for measures of responsiveness to ICB immunotherapy.

Hypermethylation of tumor suppressor genes is a risk factor for poor prognosis in ovarian cancer: A meta-analysis

OBJECTIVE

DNA methylation is the earliest and most studied epigenetic modification in cancer. The literature reported that the abnormal methylation level of multiple genes was associated with poor prognosis in ovarian cancer. However, due to a small sample size, the results reported in the literature vary widely. In this study, the correlation between aberrant methylation level of genes and poor prognosis of ovarian cancer was reviewed in order to clarify the role of DNA methylation in the prognosis of ovarian cancer.

METHODS

A systematic research of PubMed, EMbase, Cochrane Library, China Biology Medicine disc (CBMdisc), China National Knowledge Infrastructure (CNKI), Wanfang databases, and EMBASE was performed, and calculated the hazard ratio (HR) of overall survival (OS) and progression-free survival (PFS) and its 95% confidence interval.

RESULTS

HR of the OS obtained of target genes was 2.32 (95% CI: 1.54-3.48, P = .000); HR of the PFS obtained of target genes was 1.318 (95% CI: 0.848-2.050, P = .220). HR of OS achieved by tumor suppressor genes was 3.09 (95% CI 1.80 - 5.30, P = .000).

CONCLUSION

Hypermethylation of tumor suppressor genes indicate poor prognosis of ovarian cancer.

A five-DNA methylation signature act as a novel prognostic biomarker in patients with ovarian serous cystadenocarcinoma

Background

Ovarian cancer is the most fatal tumor of the female reproductive system and the fifth leading cause of cancer death among women in the USA. The prognosis is poor due to the lack of biomarkers for treatment options.

Results

The methylation array data of 551 patients with ovarian serous cystadenocarcinoma (OSC) in The Cancer Genome Atlas (TCGA) database were assessed in this study to explore the methylation biomarkers associated with prognosis and improve the prognosis of patients. These patients were divided into training (first two thirds) and validation datasets (remaining one third). A five-DNA methylation signature was found to be significantly associated with the overall survival of patients with OSC using the Cox regression analysis in the training dataset. The Kaplan–Meier analysis showed that the five-DNA methylation signature could significantly distinguish the high- and low-risk patients in both training and validation sets. The receiver operating characteristic (ROC) analysis further confirmed that the five-DNA methylation signature exhibited high sensitivity and specificity to predict the prognostic survival of patients. Also, the five-DNA methylation signature was not only applicable in patients of different ages, stages, histologic grade, and size of residual tumor after surgery but also more accurate in predicting OSC prognosis compared with known biomarkers.

Conclusions

This five-DNA methylation signature demonstrated the potential of being a novel independent prognostic indicator and served as an important tool for guiding the clinical treatment of OSC to improve outcome prediction and management for patients. Hence, the findings of this study might have potential clinical significance.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0574-0) contains supplementary material, which is available to authorized users.

LogLoss-BERAF: An ensemble-based machine learning model for constructing highly accurate diagnostic sets of methylation sites accounting for heterogeneity in prostate cancer

Although modern methods of whole genome DNA methylation analysis have a wide range of applications, they are not suitable for clinical diagnostics due to their high cost and complexity and due to the large amount of sample DNA required for the analysis. Therefore, it is crucial to be able to identify a relatively small number of methylation sites that provide high precision and sensitivity for the diagnosis of pathological states. We propose an algorithm for constructing limited subsamples from high-dimensional data to form diagnostic panels. We have developed a tool that utilizes different methods of selection to find an optimal, minimum necessary combination of factors using cross-entropy loss metrics (LogLoss) to identify a subset of methylation sites. We show that the algorithm can work effectively with different genome methylation patterns using ensemble-based machine learning methods. Algorithm efficiency, precision and robustness were evaluated using five genome-wide DNA methylation datasets (totaling 626 samples), and each dataset was classified into tumor and non-tumor samples. The algorithm produced an AUC of 0.97 (95% CI: 0.94-0.99, 9 sites) for prostate adenocarcinoma and an AUC of 1.0 (from 2 to 6 sites) for urothelial bladder carcinoma, two types of kidney carcinoma and colorectal carcinoma. For prostate adenocarcinoma we showed that identified differential variability methylation patterns distinguish cluster of samples with higher recurrence rate (hazard ratio for recurrence = 0.48, 95% CI: 0.05-0.92; log-rank test, p-value < 0.03). We also identified several clusters of correlated interchangeable methylation sites that can be used for the elaboration of biological interpretation of the resulting models and for further selection of the sites most suitable for designing diagnostic panels. LogLoss-BERAF is implemented as a standalone python code and open-source code is freely available from https://github.com/bioinformatics-IBCH/logloss-beraf along with the models described in this article.

Epigenetic loss of heparan sulfate 3-O-sulfation sensitizes ovarian carcinoma to oncogenic signals and predicts prognosis

Precision medicine requires markers for therapeutic guidance. The purpose of this study was to determine whether epithelial ovarian cancer (EOC) epigenetics can lead to the identification of biomarkers for precision medicine. Through integrative methylomics, we discovered and validated the epigenetic signature of NEFH and HS3ST2 as an independent prognostic factor for type II EOC in our dataset (n = 84), and two independent methylomics datasets (total n = 467). Integrated transcriptomics dataset (n = 1147) and tissue microarrays (n = 54) of HS3ST2 also related to high-methylation statuses and the EOC prognosis. Mechanistic explorations of HS3ST2 have assessed responses to oncogenic stimulations such as IL-6, EGF, and FGF2 in cancer cells. The combination of HS3ST2 and various oncogenic ligands also confers the worse outcome. 3-O-sulfation of heparan sulfate by HS3ST2 makes ovarian cancer cells intrinsically sensitive to oncogenic signals, which sheds new light on the application of HS3ST2 as a companion diagnostic for targeted therapy using kinase inhibitors or therapeutic antibodies.

Methylation and expression of PTPN22 in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a fatal disease contributed by both genetic and epigenetic factors. The epigenetic alteration of protein tyrosine phosphatase non-receptor type 22 (PTPN22) and its clinical significance in ESCC were still not yet clarified. A quantitative methylation study of PTPN22 and its expression were conducted in 121 and 31 paired tumor and adjacent normal tissue (ANT), respectively. Moreover, the association between PTPN22 methylation and clinicopathological parameters was evaluated. We found that the methylation level of PTPN22 was significantly elevated in tumor tissues (66.3%) relative to ANT (62.1%) (p=0.005). The methylation level of non-smoking ANT (59.1%) was significant lower than smoking ESCC tissue (65.8%) (p=0.03); similarly, the methylation levels in ANT with no lymph node invasion (57.6%) were significant lower than tumor tissues with lymph node invasion (67.5%) (p=0.001). PTPN22 expression in ESCC was lower than normal tissues, however the difference was not statistically significant (p=0.55). Lower expression was more frequently occurred in N_1-3 and III stage patients, while higher expression was more likely to occur in N₀ and I-II stage patients. Lower expression of PTPN22 was associated with poor overall survival (p=0.04). Taken together, PTPN22 was hypermethylationed in ESCC. Hypermethylation was associated with lymph node invasion. The PTPN22 expression may act as a prognostic biomarker to identify patients at risk of high grade.

Activation of the ROCK1/MMP-9 pathway is associated with the invasion and poor prognosis in papillary thyroid carcinoma

Rho-associated protein kinase 1 (ROCK1), a serine/threonine kinase, has previously been shown to be over-expressed in various types of human malignant tumors and to play an important role in cancer development and progression. Although ROCK1 has gained growing prominence as an important protein kinase in cancer biology, its potential as a predictive biomarker and a therapeutic target in papillary thyroid carcinoma (PTC) remains unknown. In the present study, ROCK1 expression was examined in 356 formalin-fixed, paraffin-embedded papillary thyroid carcinoma tissues using immunohistochemistry, and its clinical implications and prognostic significance were analyzed. Our results showed that ROCK1 expression was significantly increased in PTC compared with normal tissues, and was significantly associated with tumor size, lymphatic metastasis, distant organ metastasis, extrathyroid invasion, vascular invasion and tumor, node and metastasis (TNM) stage. Patients with strong ROCK1 expression had lower overall survival, disease-free survival, lymph node recurrence-free survival and distant recurrence-free survival rates than those with weak expression. Furthermore, overexpression of ROCK1 in papillary thyroid carcinoma cells was found to increase their invasiveness. Silencing ROCK1 by siRNA, however, caused an inhibition of cell invasion. Knockdown of ROCK1 decreased the volume and weight of the xenograft tumors, while overexpression of ROCK1 showed a proliferative tendency with significantly greater tumor volume and weight in vivo. Moreover, the upregulation of ROCK1 increased the expression of MMP-9, and levels of MMP-9 positively correlated with the ROCK1 levels in PTC tissues, implicating that MMP-9 may be involved in the mechanism of ROCK1 in the development and progression of PTC. These data suggest that ROCK1 might be a potential prognostic marker and therapeutic target for the treatment of PTC.

Methylome analysis of extreme chemoresponsive patients identifies novel markers of platinum sensitivity in high-grade serous ovarian cancer

BACKGROUND

Despite an early response to platinum-based chemotherapy in advanced stage high-grade serous ovarian cancer (HGSOC), the majority of patients will relapse with drug-resistant disease. Aberrant epigenetic alterations like DNA methylation are common in HGSOC. Differences in DNA methylation are associated with chemoresponse in these patients. The objective of this study was to identify and validate novel epigenetic markers of chemoresponse using genome-wide analysis of DNA methylation in extreme chemoresponsive HGSOC patients.

METHODS

Genome-wide next-generation sequencing was performed on methylation-enriched tumor DNA of two HGSOC patient groups with residual disease, extreme responders (≥18 months progression-free survival (PFS), n = 8) and non-responders (≤6 months PFS, n = 10) to platinum-based chemotherapy. DNA methylation and expression data of the same patients were integrated to create a gene list. Genes were validated on an independent cohort of extreme responders (n = 21) and non-responders (n = 31) using pyrosequencing and qRT-PCR. In silico validation was performed using publicly available DNA methylation (n = 91) and expression (n = 208) datasets of unselected advanced stage HGSOC patients. Functional validation of FZD10 on chemosensitivity was carried out in ovarian cancer cell lines using siRNA-mediated silencing.

RESULTS

Integrated genome-wide methylome and expression analysis identified 45 significantly differentially methylated and expressed genes between two chemoresponse groups. Four genes FZD10, FAM83A, MYO18B, and MKX were successfully validated in an external set of extreme chemoresponsive HGSOC patients. High FZD10 and MKX methylation were related with extreme responders and high FAM83A and MYO18B methylation with non-responders. In publicly available advanced stage HGSOC datasets, FZD10 and MKX methylation levels were associated with PFS. High FZD10 methylation was strongly associated with improved PFS in univariate analysis (hazard ratio (HR) = 0.43; 95% CI, 0.27-0.71; P = 0.001) and multivariate analysis (HR = 0.39; 95% CI, 0.23-0.65; P = 0.003). Consistently, low FZD10 expression was associated with improved PFS (HR = 1.36; 95% CI, 0.99-1.88; P = 0.058). FZD10 silencing caused significant sensitization towards cisplatin treatment in survival assays and apoptosis assays.

CONCLUSIONS

By applying genome-wide integrated methylome analysis on extreme chemoresponsive HGSOC patients, we identified novel clinically relevant, epigenetically-regulated markers of platinum-sensitivity in HGSOC patients. The clinical potential of these markers in predictive and therapeutic approaches has to be further validated in prospective studies.

An epigenetic signature of adhesion molecules predicts poor prognosis of ovarian cancer patients

DNA methylation is a promising biomarker for cancer. The epigenetic effects of cell adhesion molecules may affect the therapeutic outcome and the present study examined their effects on survival in ovarian cancer. We integrated methylomics and genomics datasets in The Cancer Genome Atlas (n = 391) and identified 106 highly methylated adhesion-related genes in ovarian cancer tissues. Univariate analysis revealed the methylation status of eight genes related to progression-free survival. In multivariate Cox regression analysis, four highly methylated genes (CD97, CTNNA1, DLC1, HAPLN2) and three genes (LAMA4, LPP, MFAP4) with low methylation were significantly associated with poor progression-free survival. Low methylation of VTN was an independent poor prognostic factor for overall survival after adjustment for age and stage. Patients who carried any two of CTNNA1, DLC1 or MFAP4 were significantly associated with poor progression-free survival (hazard ratio: 1.59; 95% confidence interval: 1.23, 2.05). This prognostic methylation signature was validated in a methylomics dataset generated in our lab (n = 37, hazard ratio: 16.64; 95% confidence interval: 2.68, 103.14) and in another from the Australian Ovarian Cancer Study (n = 91, hazard ratio: 2.43; 95% confidence interval: 1.11, 5.36). Epigenetics of cell adhesion molecules is related to ovarian cancer prognosis. A more comprehensive methylomics of cell adhesion molecules is needed and may advance personalized treatment with adhesion molecule-related drugs.

Methylation of MYLK3 gene promoter region: a biomarker to stratify surgical care in ovarian cancer in a multicentre study

BACKGROUND

Survival benefit from surgical debulking of ovarian cancer (OC) is well established, but some women, despite total macroscopic clearance of disease, still have poor prognosis. We aimed to identify biomarkers to predict benefit from conventional surgery.

METHODS

Clinical data from women debulked for high-stage OC were analysed (Hammersmith Hospital, London, UK; 2001-2014). Infinium's HumanMethylation27 array interrogated tumour DNA for differentially methylated CpG sites, correlated to survival, in patients with the least residual disease (RD; Hammersmith Array). Validation was performed using bisulphite pyrosequencing (Charité Hospital, Berlin, Germany cohort) and The Cancer Genome Atlas' (TCGA) methylation data set. Kaplan-Meier curves and Cox models tested survival.

RESULTS

Altogether 803 women with serous OC were studied. No RD was associated with significantly improved overall survival (OS; hazard ratio (HR) 1.25, 95% CI 1.06-1.47; P=0.0076) and progression-free survival (PFS; HR 1.23, 95% CI 1.05-1.43; P=0.012; Hammersmith database n=430). Differentially methylated loci within FGF4, FGF21, MYLK2, MYLK3, MYL7, and ITGAE associated with survival. Patients with the least RD had significantly better OS with higher methylation of MYLK3 (Hammersmith (HR 0.51, 95% CI 0.31-0.84; P=0.01), Charité (HR 0.46, 95% CI 0.21-1.01; P=0.05), and TCGA (HR 0.64, 95% CI 0.44-0.93; P=0.02)).

CONCLUSIONS

MYLK3 methylation is associated with improved OS in patients with the least RD, which could potentially be used to determine response to surgery.

The expression of SFRP1, SFRP3, DVL1, and DVL2 proteins in testicular germ cell tumors

Germ cell tumors of the testis are a heterogeneous group of neoplasms that affect male adolescents and young adults. Wnt signaling pathway components have been shown to be actively involved in normal and malignant germ cell differentiation and progression. In this study, we aimed to explore the expression patterns of the secreted frizzled-related protein (SFRP) and Disheveled protein family (DVL) in a subset of testicular germ cell tumors. Eighty-five formalin-fixed, paraffin-embedded tissue samples of the primary germ cell tumors of the testis were stained against SFRP1, SFRP3, DVL1, and DVL2 proteins using immunohistochemistry. SFRP1 and SFRP3 exhibited lower expression in both seminomas and mixed/non-seminomatous tumors, compared with atrophic/benign tissue (p < 0.001). SFRP3 expression was lower than SFRP1 expression within the seminoma group (p = 0.004), but not within the mixed/non-seminomatous group (p = 0.409). The majority of the tested cases (27/28, 96%) exhibited low DVL1 protein expression (median 0%, range 0-90%). In contrast, 20 out of 22 tested cases (91%) exhibited strong expression of DVL2 protein (median 80%, range 0-100%). No significant difference in DVL1 and DVL2 protein expression was observed between seminomas and mixed/non-seminomatous tumors (p = 0.68 and 0.29). The secreted frizzled-related protein and disheveled protein family members appear to be actively involved in the pathogenesis of primary testicular germ cell tumors.

Predictive and Prognostic Value of sPRR in Patients with Primary Epithelial Ovarian Cancer

Aim. The purpose of the present study was to analyze the predictive and prognostic role of soluble (pro)renin receptor (sPRR) as a biomarker for clinicopathological outcome in patients with primary epithelial ovarian cancer (EOC). As part of the renin-angiotensin system (RAS) whose activity is known to increase in ovarian cancer patients, the relation of sPRR and ovarian cancer should be further investigated. Patients and Methods. In this study 197 patients with primary EOC in our institution from 2000 to 2011 were included. sPRR was determined by enzyme-linked immunosorbent assay (ELISA) in preoperative taken blood sera. Associations with clinicopathological outcome were analyzed and serum levels of sPRR in patients have been compared to those in healthy specimen. Kaplan-Meier and logistic/Cox regression assessed the impact of the markers on progression-free survival (PFS) and overall survival (OS). Results. There have been no correlations proved of sPRR levels with neither clinicopathological factors nor prognostic data. Also the distribution of sPRR in patients and controls was normal. Conclusion. sPRR seems to have no predictive, prognostic, or diagnostic value in EOC. As several factors of the RAS which might indicate cancer events have been shown, sPRR seems not to be affected.

WNT5A and Its Receptors in the Bone-Cancer Dialogue

Wnt signaling is critical for tumorigenesis and skeletal remodeling. However, its contribution to the formation of metastatic bone lesions remains poorly defined. One major challenge of unraveling its role in cancer progression is the high complexity of Wnt signaling, which includes numerous ligands, receptors, and inhibitors, with intricate biological effects and specific signaling pathways depending on the cellular context. In this perspective, we summarize the role of the noncanonical Wnt ligand WNT5A in the development and metastatic process of osteotropic cancer entities. We focus on its tumor-suppressive function in breast cancer, tumor promoting effects in melanoma, and ambiguous role in prostate cancer, and discuss potential challenges and opportunities that may be associated with targeting Wnt signaling for cancer therapy and treatment of bone metastases. © 2016 American Society for Bone and Mineral Research.

Genomic/Epigenomic Alterations in Ovarian Carcinoma: Translational Insight into Clinical Practice

Ovarian carcinoma is the most lethal gynecological malignancy worldwide. Recent advance in genomic/epigenomic researches will impact on our prevention, detection and intervention on ovarian carcinoma. Detection of germline mutations in BRCA1/BRCA2, mismatch repair genes, and other genes in the homologous recombination/DNA repair pathway propelled the genetic surveillance of most hereditary ovarian carcinomas. Germline or somatic mutations in SMARCA4 in familial and sporadic small cell carcinoma of the ovary, hypercalcemia type, lead to our recognition on this rare aggressive tumor as a new entity of the atypical teratoma/rhaboid tumor family. Genome-wide association studies have identified many genetic variants that will contribute to the evaluation of ovarian carcinoma risk and prognostic prediction. Whole exome sequencing and whole genome sequencing discovered rare mutations in other drive mutations except p53, but demonstrated the presence of high genomic heterogeneity and adaptability in the genetic evolution of high grade ovarian serous carcinomas that occurs in cancer progression and chemotherapy. Gene mutations, copy number aberrations and DNA methylations provided promising biomarkers for the detection, diagnosis, prognosis, therapy response and targets of ovarian cancer. These findings underscore the necessity to translate these potential biomarkers into clinical practice.

Biological markers of prognosis, response to therapy and outcome in ovarian carcinoma

INTRODUCTION

Ovarian cancer (OvCa) is among the most common types of cancer and is the leading cause of death from gynecological malignancies in western countries. Cancer biomarkers have a potential for improving the management of OvCa patients at every point from screening and detection, diagnosis, prognosis, follow up, response to therapy and outcome.

AREAS COVERED

The literature search has indicated a number of candidate biomarkers have recently emerged that could facilitate the molecular definition of OvCa, providing information about prognosis and predicting response to therapy. These potentially promising biomarkers include immune cells and their products, tumor-derived exosomes, nucleic acids and epigenetic biomarkers. Expert commentary: Although most of the biomarkers available today require prospective validation, the development of noninvasive liquid biopsy-based monitoring promises to improve their utility for evaluations of prognosis, response to therapy and outcome in OvCa.

The NKD1/Rac1 feedback loop regulates the invasion and migration ability of hepatocarcinoma cells

Hepatocellular carcinoma (HCC) is complicated by aggressive migration and invasion, which contribute to the increased mortality of HCC patients. The NKD1 protein is abnormally expressed in many neoplasms and plays an important role in tumor progression. However, the regulation and underlying molecular mechanisms of NKD1 in HCC cell invasion and migration remain poorly understood. In the present study, ectopic expression of NKD1 in HCC cells attenuated migration and invasion in vitro and in vivo by down-regulating Rac1 expression level and activity, which affected the HCC cell cytoskeleton and E-cadherin expression. Mechanistic studies showed that NKD1 interacted with Rac1 in the cytoplasm and promoted its degradation by the ubiquitin-proteasome pathway. Over-expression of Rac1 enhanced the transcription of the NKD1 gene and protein expression conversely owing to its negative regulation of EZH2. Analysis of clinical samples showed that abnormal expression of NKD1 and Rac1 was associated with the poor prognosis of HCC patients. In summary, our data indicate a new role for NKD1 as a regulator of HCC cell invasion and migration via a feedback loop involving Rac1.

Developmental DNA methyltransferase inhibitors in the treatment of gynecologic cancers

INTRODUCTION

DNA methylation has become an attractive target for the treatment of cancer. DNA methyltransferase inhibitors have proven useful for the treatment of myelodysplastic syndrome and are being evaluated in gynecological neoplasias.

AREAS COVERED

We provide an overview of the current knowledge on DNA methylation and cancer and the role of DNA methylation in cervical, ovarian and endometrial carcinomas. The results of recent clinical trials with demethylating agents for cervical and ovarian cancer treatment are also discussed.

EXPERT OPINION

There are few studies of DNA demethylating agents for cervical and ovarian cancer treatment; nevertheless, the results are promising. To accelerate these advances, there are at least two actions that can be simultaneously pursued. One is to greatly increase the number of small clinical exploratory trials with existing demethylating drugs and using methylome analyses to identify predictive factors for response and/or toxicity. The second is finding out epigenetic 'drivers' unique to gynecological cancers and their subtypes, and then proceed to clinical trials in a highly selected population of patients. It is expected that in the future, DNA demethylation could have a role in the treatment of gynecologic cancers.

Aberrant methylation of the TERT promoter in esophageal squamous cell carcinoma

A recent study indicated that upstream of the transcription start site (UTSS) hypermethylation of the telomerase reverse transcriptase (TERT) gene was associated with tumor progression and poor prognosis in pediatric brain tumors. The potential for methylation-mediated regulation of the UTSS region of the TERT gene in esophageal squamous cell carcinoma (ESCC) has not yet been investigated. Here, TERT methylation was investigated in tumor and paired adjacent non-cancerous tissues (ANT) from 185 ESCC patients, and the expression of TERT was investigated in 26 tumors paired with ANTs selected from the same cohort. The methylation level of TERT was analyzed in three different regions: region 1, region 2, and the UTSS region. Comparison and correlation of methylation level and clinical features were analyzed in the abovementioned regions. The results showed that the methylation level of TERT was significantly elevated in the tumor relative to the ANT in ESCC. TERT RNA expression was significantly reduced in primary tumors. Tumor stage was the major determinant of survival. The UTSS region may not be an accessible biomarker for ESCC.

Evaluation of Epigenetic Drug Targeting of Heterogenous Tumor Cell Fractions Using Potential Biomarkers of Response in Ovarian Cancer

PURPOSE

Resolution of aberrant epigenetic changes leading to altered gene expression during transformation and tumor progression is pertinent for mechanistic understanding of disrupted pathways in cancer. Such changes provide for biomarkers that can be applied in drug screening and improved disease management.

EXPERIMENTAL DESIGN

Genome-wide profiling and analyses of promoter DNA methylation, histone modifications, and gene expression of an in vitro progression model of serous ovarian adenocarcinoma were carried out. Similar in silico analyses and comparison of methylation and gene expression of early- and late-grade ovarian cancer samples in The Cancer Genome Atlas assigned a clinical relevance to our study. Candidate biomarkers were evaluated for epigenetic drug treatments in experimental animal models on a background of differing tumor cell responses arising from intratumor heterogeneity.

RESULTS

Differentially regulated genes during tumor progression were identified through the previously mentioned analyses as candidate biomarkers. In examining the tumor suppressor PTGIS as a potential biomarker for treatment with either 5-Aza-dC or TSA, 5-Aza-dC effectively stabilized cell cycling, restricted genetic instability, and derepressed PTGIS expression, while TSA led to emergence of drug-resistant progenitors lacking PTGIS expression. Profiling MEST and RXRγ for curcumin and CBB1007, respectively, indicated an inability of curcumin and CBB1007 in restricting residual tumor regenerative capabilities.

CONCLUSIONS

Our study provides novel insights into epigenetic regulation in ovarian cancer progression and potential biomarkers for evaluating efficacy of epigenetic drugs in restricting residual tumor regeneration. Such approaches may assign a new functional interpretation of drug efficacy and cell tumor responses in ovarian cancer.

Methylation Profiling of Multiple Tumor Suppressor Genes in Hepatocellular Carcinoma and the Epigenetic Mechanism of 3OST2 Regulation

DNA methylation is considered as a significant mechanism that silences tumor suppressor genes (TSGs) and could be used in the early diagnosis of cancer. Histone modifications often work together with DNA methylation; however, how these epigenetic alterations regulate TSGs remains unclear. Here, we determined the methylation status of ten TSGs (3OST2, ppENK, CHFR, LKB1, THBS1, HIC1, SLIT2, EDNRB, COX2, and CLDN7) in hepatocellular carcinoma (HCC) and corresponding noncancerous tissues. Methylation profiling revealed that four genes had very high frequencies of methylation in HCCs, but interestingly, similar high frequencies were also detected in corresponding noncancerous tissues (97.9% vs 95.8% for SLIT2, 93.8% vs 81.3% for EDNRB, 66.7% vs 85.4% for HIC1, and 56.3% vs 56.3% for ppENK, P > 0.05). Only the 3OST2 gene was frequently methylated in HCCs and there was significant difference between HCCs and corresponding noncancerous tissues (68.8% vs 37.5%, P < 0.05). 5-aza-2'-deoxycytidine (5-Aza-CdR) or trichostatin A (TSA) alone could partially reverse 3OST2 methylation, and their combination resulted in complete reversal. UHRF1 and histone H3R8me2s were both enriched on the hypermethylated 3OST2 promoter, but H3R8me2a was not. After 5-Aza-CdR or TSA treatment, the UHRF1 and H3R8me2s enrichment was decreased, while H3R8me2a enrichment increased. We demonstrated that 3OST2 methylation may play a critical role in the earliest steps of hepatocarcinogenesis and is directly regulated by UHRF1. Furthermore, H3R8me2s acted as a repressive mark, while H3R8me2a was correlated with 3OST2 transcriptional activity.

A 10-gene expression signature of Notch pathway predicts recurrence in ovarian carcinoma

Patients with ovarian carcinoma are at high risk of tumor recurrence. In the present study, 81 Notch pathway genes were selected to find recurrence-related genes in The Cancer Genome Atlas dataset. A 10-gene signature (FZD4, HES1, PSEN2, JAG2, PPARG, FOS, HEY1, CDC16, MFNG, and EP300) was identified and validated that is associated with recurrence-free survival time, but not with overall survival time, in the TCGA dataset and in other two independent datasets, GSE9891 and GSE30161. This gene signature gave a significant performance in discriminating patients at high risk of recurrence from those at low risk, as measured by the area under the receiver operating characteristic curve. Cox proportional hazards regression analyses demonstrated that the prognostic value of this 10-gene set is independent of other clinical variables in all three datasets. The potential as a biomarker for predicting high- and low-risk subgroups for recurrence in ovarian cancer patients deserves further investigation in prospective patient cohorts in the future.