Epigenome-based cancer risk prediction: rationale, opportunities and challenges

Dietary Restriction and Rapamycin Affect Brain Aging in Mice by Attenuating Age-Related DNA Methylation Changes

The fact that dietary restriction (DR) and long-term rapamycin treatment (RALL) can ameliorate the aging process has been reported by many researchers. As the interface between external and genetic factors, epigenetic modification such as DNA methylation may have latent effects on the aging rate at the molecular level. To understand the mechanism behind the impacts of dietary restriction and rapamycin on aging, DNA methylation and gene expression changes were measured in the hippocampi of different-aged mice. Examining the single-base resolution of DNA methylation, we discovered that both dietary restriction and rapamycin treatment can maintain DNA methylation in a younger state compared to normal-aged mice. Through functional enrichment analysis of genes in which DNA methylation or gene expression can be affected by DR/RALL, we found that DR/RALL may retard aging through a relationship in which DNA methylation and gene expression work together not only in the same gene but also in the same biological process. This study is instructive for understanding the maintenance of DNA methylation by DR/RALL in the aging process, as well as the role of DR and RALL in the amelioration of aging.

Ethical implications of epigenetics in the era of personalized medicine

Given the increasing research activity on epigenetics to monitor human diseases and its connection with lifestyle and environmental expositions, the field of epigenetics has attracted a great deal of interest also at the ethical and societal level. In this review, we will identify and discuss current ethical, legal and social issues of epigenetics research in the context of personalized medicine. The review covers ethical aspects such as how epigenetic information should impact patient autonomy and the ability to generate an intentional and voluntary decision, the measures of data protection related to privacy and confidentiality derived from epigenome studies (e.g., risk of discrimination, patient re-identification and unexpected findings) or the debate in the distribution of responsibilities for health (i.e., personal versus public responsibilities). We pay special attention to the risk of social discrimination and stigmatization as a consequence of inferring information related to lifestyle and environmental exposures potentially contained in epigenetic data. Furthermore, as exposures to the environment and individual habits do not affect all populations equally, the violation of the principle of distributive justice in the access to the benefits of clinical epigenetics is discussed. In this regard, epigenetics represents a great opportunity for the integration of public policy measures aimed to create healthier living environments. Whether these public policies will coexist or, in contrast, compete with strategies reinforcing the personalized medicine interventions needs to be considered. The review ends with a reflection on the main challenges in epigenetic research, some of them in a technical dimension (e.g., assessing causality or establishing reference epigenomes) but also in the ethical and social sphere (e.g., risk to add an epigenetic determinism on top of the current genetic one). In sum, integration into life science investigation of social experiences such as exposure to risk, nutritional habits, prejudice and stigma, is imperative to understand epigenetic variation in disease. This pragmatic approach is required to locate clinical epigenetics out of the experimental laboratories and facilitate its implementation into society.

A novel DNA methylation signature associated with lymph node metastasis status in early gastric cancer

Background

Lymph node metastasis (LNM) is an important factor for both treatment and prognosis of early gastric cancer (EGC). Current methods are insufficient to evaluate LNM in EGC due to suboptimal accuracy. Herein, we aim to identify methylation signatures for LNM of EGC, facilitate precision diagnosis, and guide treatment modalities.

Methods

For marker discovery, genome-wide methylation sequencing was performed in a cohort (marker discovery) using 47 fresh frozen (FF) tissue samples. The identified signatures were subsequently characterized for model development using formalin-fixed paraffin-embedded (FFPE) samples by qPCR assay in a second cohort (model development cohort, n = 302, training set: n = 151, test set: n = 151). The performance of the established model was further validated using FFPE samples in a third cohorts (validation cohort, n = 130) and compared with image-based diagnostics, conventional clinicopathology-based model (conventional model), and current standard workups.

Results

Fifty LNM-specific methylation signatures were identified de novo and technically validated. A derived 3-marker methylation model for LNM diagnosis was established that achieved an AUC of 0.87 and 0.88, corresponding to the specificity of 80.9% and 85.7%, sensitivity of 80.6% and 78.1%, and accuracy of 80.8% and 83.8% in the test set of model development cohort and validation cohort, respectively. Notably, this methylation model outperformed computed tomography (CT)-based imaging with a superior AUC (0.88 vs. 0.57, p < 0.0001) and individual clinicopathological features in the validation cohort. The model integrated with clinicopathological features demonstrated further enhanced AUCs of 0.89 in the same cohort. The 3-marker methylation model and integrated model reduced 39.4% and 41.5% overtreatment as compared to standard workups, respectively.

Conclusions

A novel 3-marker methylation model was established and validated that shows diagnostic potential to identify LNM in EGC patients and thus reduce unnecessary gastrectomy in EGC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01219-x.

The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

Genetic and non-genetic factors contribute to breast cancer development. An epigenome-based signature capturing these components in easily accessible samples could identify women at risk. Here, we analyse the DNA methylome in 2,818 cervical, 357 and 227 matched buccal and blood samples respectively, and 42 breast tissue samples from women with and without breast cancer. Utilising cervical liquid-based cytology samples, we develop the DNA methylation-based Women’s risk IDentification for Breast Cancer index (WID-BC-index) that identifies women with breast cancer with an AUROC (Area Under the Receiver Operator Characteristic) of 0.84 (95% CI: 0.80–0.88) and 0.81 (95% CI: 0.76–0.86) in internal and external validation sets, respectively. CpGs at progesterone receptor binding sites hypomethylated in normal breast tissue of women with breast cancer or in BRCA mutation carriers are also hypomethylated in cervical samples of women with poor prognostic breast cancer. Our data indicate that a systemic epigenetic programming defect is highly prevalent in women who develop breast cancer. Further studies validating the WID-BC-index may enable clinical implementation for monitoring breast cancer risk.

Breast cancer is most commonly diagnosed via a needle biopsy. In this study, the authors show that cervical samples from women with breast cancer have a methylation signature different to that of healthy controls.

The DNA methylome of cervical cells can predict the presence of ovarian cancer

The vast majority of epithelial ovarian cancer arises from tissues that are embryologically derived from the Müllerian Duct. Here, we demonstrate that a DNA methylation signature in easy-to-access Müllerian Duct-derived cervical cells from women with and without ovarian cancer (i.e. referred to as the Women's risk IDentification for Ovarian Cancer index or WID-OC-index) is capable of identifying women with an ovarian cancer in the absence of tumour DNA with an AUC of 0.76 and women with an endometrial cancer with an AUC of 0.81. This and the observation that the cervical cell WID-OC-index mimics the epigenetic program of those cells at risk of becoming cancerous in BRCA1/2 germline mutation carriers (i.e. mammary epithelium, fallopian tube fimbriae, prostate) further suggest that the epigenetic misprogramming of cervical cells is an indicator for cancer predisposition. This concept has the potential to advance the field of risk-stratified cancer screening and prevention.

Hypermethylated PCDHGB7 as a Biomarker for Early Detection of Endometrial Cancer in Endometrial Brush Samples and Cervical Scrapings

Endometrial cancer (EC) is one of the most common gynecologic cancers in developed countries. Presently, it is imperative to develop a reliable, noninvasive, or minimally invasive detection method for EC. We explored the possibility of using DNA methylation marker from endometrial brush samples (with a “Tao brush”) and cervical scrapes (with a “Pap brush”) for early detection of EC. We analyzed the methylation data of EC and normal endometrial tissues from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. An optimized methylation-sensitive restriction enzyme combined with real-time fluorescent quantitative PCR (MSRE-qPCR) was used for methylation detection. Included in the training set were 143 endometrial tissues, 103 Tao, and 109 Pap brush samples. The validation set included 110 Tao and 112 Pap brush samples. PCDHGB7 was significantly hypermethylated in EC compared with normal endometrial tissues in the TCGA and GEO data sets (AUC >0.95), which was verified in clinical samples. In the Pap brush samples, the AUC was 0.86 with 80.65% sensitivity and 82.81% specificity, whereas the Tao brush samples exhibited higher specificity (95.31%). The combination of Tao and Pap brush samples significantly increased the sensitivity to 90.32%. In the validation set, the final model yielded a sensitivity of 98.61%, specificity of 60.53%, positive predictive value of 82.56%, and negative predictive value of 95.83%. These results demonstrate the potential application of the novel methylation marker, hypermethylated PCDHGB7, in cervical scrapings and endometrial brush, which provides a viable, noninvasive, or minimally invasive method for early endometrial cancer detection across different clinical features and histologies to supplement current hysteroscopy diagnosis.

A Prognostic Model for Breast Cancer Based on Cancer Incidence-Related DNA Methylation Pattern

Breast cancer (BC) is the most diagnosed cancer and the leading cause of cancer-related deaths in women. The purpose of this study was to develop a prognostic model based on BC-related DNA methylation pattern. A total of 361 BC incidence-related probes (BCIPs) were differentially methylated in blood samples from women at high risk of BC and BC tissues. Twenty-nine of the 361 BCIPs that significantly correlated with BC outcomes were selected to establish the BCIP score. BCIP scores based on BC-related DNA methylation pattern were developed to evaluate the mortality risk of BC. The correlation between overall survival and BCIP scores was assessed using Kaplan-Meier, univariate, and multivariate analyses. In BC, the BCIP score was significantly correlated with malignant BC characteristics and poor outcomes. Furthermore, we assessed the BCIP score-related gene expression profile and observed that genes with expressions associated with the BCIP score were involved in the process of cancer immunity according to GO and KEGG analyses. Using the ESTIMATE and CIBERSORT algorithms, we discovered that BCIP scores were negatively correlated with both T cell infiltration and immune checkpoint inhibitor response markers in BC tissues. Finally, a nomogram comprising the BCIP score and BC prognostic factors was used to establish a prognostic model for patients with BC, while C-index and calibration curves were used to evaluate the effectiveness of the nomogram. A nomogram comprising the BCIP score, tumor size, lymph node status, and molecular subtype was developed to quantify the survival probability of patients with BC. Collectively, our study developed the BCIP score, which correlated with poor outcomes in BC, to portray the variation in DNA methylation pattern related to BC incidence.

Exploring the Ethics of Implementation of Epigenomics Technologies in Cancer Screening: A Focus Group Study

New epigenomics technologies are being developed and used for the detection and prediction of various types of cancer. By allowing for timely intervention or preventive measures, epigenomics technologies show promise for public health, notably in population screening. In order to assess whether implementation of epigenomics technologies in population screening may be morally acceptable, it is important to understand – in an early stage of development – ethical and societal issues that may arise. We held 3 focus groups with experts in science and technology studies (STS) (n = 13) in the Netherlands, on 3 potential future applications of epigenomic technologies in screening programmes of increasing scope: cervical cancer, female cancers and ‘global’ cancer. On the basis of these discussions, this paper identifies ethical issues pertinent to epigenomics-based population screening, such as risk communication, trust and public acceptance; personal responsibility, stigmatisation and societal pressure, and data protection and data governance. It also points out how features of epigenomics (eg, modifiability) and changing concepts (eg, of cancer) may challenge the existing evaluative framework for screening programmes. This paper aims to anticipate and prepare for future ethical challenges when epigenomics technologies can be tested and introduced in public health settings.

Value of Plasma Methylated SFRP2 in Prognosis of Gastric Cancer

BACKGROUND

Secreted frizzled-related protein 2 (SFRP2) in circulating tumor DNA (ctDNA) is related to gastric cancer (GC) proliferation. However, whether methylated SFRP2 in ctDNA serves as the biomarker in GC patients remains unknown.

AIMS

To investigate the relationship between methylated SFRP2 and the clinical outcomes of GC patients.

METHODS

One hundred and forty-eight GC patients receiving systemic chemotherapy were collected during 2015-2017. Aberrant SFRP2 methylation was detected before and after chemotherapy by digital PCR-based technologies.

RESULTS

Baseline SFRP2 methylation positively correlated with lymph node status (P < 0.001), distant metastasis (P < 0.001) and TNM stage (P = 0.005). The top 50% methylated SFRP2 had shorter progression-free survival (PFS) and overall survival (OS) than those with bottom 50% in stage III GC patients (median PFS, 11.0 vs. NR months; HR 13.05; 95% CI 3.05-55.95; median OS 17.0 vs. NR months; HR 7.80; 95% CI 1.81-33.60) and stage IV GC patients (median PFS, 4.0 vs. 7.0 months; HR 2.74; 95% CI 1.58-4.78; median OS 12.0 vs. 16.0 months; HR 3.14; 95% CI 1.67-5.92). Besides, the increased methylated SFPR2 from baseline to post-treatment was related to the worse PFS and OS among stage IV patients (median PFS, 5.0 vs. 7.0 months; HR 2.17; 95% CI 1.25-3.76; median OS 12.0 vs. 15.5 months; HR 3.51; 95% CI 1.94-6.35), but not to stage III patients.

CONCLUSIONS

SFRP2 methylation and dynamic change are associated with GC prognosis. Our findings provide potential biomarker detection approach in ctDNA for prognosis prediction and dynamic monitoring among GC patients.

DNA methylation in lung cancer patients: Opening a "window of life" under precision medicine

DNA methylation is a work of adding a methyl group to the 5th carbon atom of cytosine in DNA sequence under the catalysis of DNA methyltransferase (DNMT) to produce 5-methyl cytosine. Some current studies have elucidated the mechanism of lung cancer occurrence and causes of lung cancer progression and metastasis from the perspective of DNA methylation. Moreover, many studies have shown that smoking can change the methylation status of some gene loci, leading to the occurrence of lung cancer, especially central lung cancer. This review mainly introduces the role of DNA methylation in the pathogenesis, early diagnosis and screening, progression and metastasis, treatment, and prognosis of lung cancer, as well as the latest progress. We point out that methylation markers, sample tests, and methylation detection limit the clinical application of DNA methylation. If the liquid biopsy is to become the main force in lung cancer diagnosis, it must make efficient use of limited samples and improve the sensitivity and specificity of the tests. In addition, we also put forward our views on the future development direction of DNA methylation.

Discovery and validation of methylation signatures in circulating cell-free DNA for early detection of esophageal cancer: a case-control study

BACKGROUND

Plasma cell-free DNA (cfDNA) methylation has shown promising results in the early detection of multiple cancers recently. Here, we conducted a study to investigate the performance of cfDNA methylation in the early detection of esophageal cancer (ESCA).

METHODS

Specific methylation markers for ESCA were identified and optimized based on esophageal tumor and paired adjacent tissues (n = 24). Age-matched participants with ESCA (n = 85), benign esophageal diseases (n = 10), and healthy controls (n = 125) were randomized into the training and test sets to develop a classifier to differentiate ESCA from healthy controls and benign esophageal disease. The classifier was further validated in an independent plasma cohort of ESCA patients (n = 83) and healthy controls (n = 98).

RESULTS

In total, 921 differentially methylated regions (DMRs) between tumor and adjacent tissues were identified. The early detection classifier based on those DMRs was first developed and tested in plasma samples, discriminating ESCA patients from benign and healthy controls with a sensitivity of 76.2% (60.5-87.9%) and a specificity of 94.1% (85.7-98.4%) in the test set. The performance of the classifier was consistent irrespective of sex, age, and pathological diagnosis (P > 0.05). In the independent plasma validation cohort, similar performance was observed with a sensitivity of 74.7% (64.0-83.6%) and a specificity of 95.9% (89.9-98.9%). Sensitivity for stage 0-II was 58.8% (44.2-72.4%).

CONCLUSION

We demonstrated that the cfDNA methylation patterns could distinguish ESCAs from healthy individuals and benign esophageal diseases with promising sensitivity and specificity. Further prospective evaluation of the classifier in the early detection of ESCAs in high-risk individuals is warranted.

Inferring Functional Epigenetic Modules by Integrative Analysis of Multiple Heterogeneous Networks

Gene expression and methylation are critical biological processes for cells, and how to integrate these heterogeneous data has been extensively investigated, which is the foundation for revealing the underlying patterns of cancers. The vast majority of the current algorithms fuse gene methylation and expression into a network, failing to fully explore the relations and heterogeneity of them. To resolve these problems, in this study we define the epigenetic modules as a gene set whose members are co-methylated and co-expressed. To address the heterogeneity of data, we construct gene co-expression and co-methylation networks, respectively. In this case, the epigenetic module is characterized as a common module in multiple networks. Then, a non-negative matrix factorization-based algorithm that jointly clusters the co-expression and co-methylation networks is proposed for discovering the epigenetic modules (called Ep-jNMF). Ep-jNMF is more accurate than the baselines on the artificial data. Moreover, Ep-jNMF identifies more biologically meaningful modules. And the modules can predict the subtypes of cancers. These results indicate that Ep-jNMF is efficient for the integration of expression and methylation data.

ramr: an R/Bioconductor package for detection of rare aberrantly methylated regions

MOTIVATION

With recent advances in the field of epigenetics, the focus is widening from large and frequent disease- or phenotype-related methylation signatures to rare alterations transmitted mitotically or transgenerationally (constitutional epimutations). Merging evidence indicate that such constitutional alterations, albeit occurring at a low mosaic level, may confer risk of disease later in life. Given their inherently low incidence rate and mosaic nature, there is a need for bioinformatic tools specifically designed to analyze such events.

RESULTS

We have developed a method (ramr) to identify aberrantly methylated DNA regions (AMRs). ramr can be applied to methylation data obtained by array or next-generation sequencing techniques to discover AMRs being associated with elevated risk of cancer as well as other diseases. We assessed accuracy and performance metrics of ramr and confirmed its applicability for analysis of large public datasets. Using ramr we identified aberrantly methylated regions that are known or may potentially be associated with development of colorectal cancer and provided functional annotation of AMRs that arise at early developmental stages.

AVAILABILITY AND IMPLEMENTATION

The R package is freely available at https://github.com/BBCG/ramr and https://bioconductor.org/packages/ramr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Of Screening, Stratification, and Scores

Technological innovations including risk-stratification algorithms and large databases of longitudinal population health data and genetic data are allowing us to develop a deeper understanding how individual behaviors, characteristics, and genetics are related to health risk. The clinical implementation of risk-stratified screening programmes that utilise risk scores to allocate patients into tiers of health risk is foreseeable in the future. Legal and ethical challenges associated with risk-stratified cancer care must, however, be addressed. Obtaining access to the rich health data that are required to perform risk-stratification, ensuring equitable access to risk-stratified care, ensuring that algorithms that perform risk-scoring are representative of human genetic diversity, and determining the appropriate follow-up to be provided to stratification participants to alert them to changes in their risk score are among the principal ethical and legal challenges. Accounting for the great burden that regulatory requirements could impose on access to risk-scoring technologies is another critical consideration.

Histone methyltransferase SETD1A participates in lung cancer progression

Lung cancer is the leading cause of cancer‐related death worldwide, with an estimated 1.2 million deaths each year. Despite advances in lung cancer treatment, 5‐year survival rates are lower than ~15%, which is attributes to diagnosis limitations and current clinical drug resistance. Recently, more evidence has suggested that epigenome dysregulation is associated with the initiation and progress of cancer, and targeting epigenome‐related molecules improves cancer symptoms. Interestingly, some groups reported that the level of methylation of histone 3 lysine 4 (H3K4me3) was increased in lung tumors and participated in abnormal transcriptional regulation. However, a mechanistic analysis is not available. In this report, we found that the SET domain containing 1A (SETD1A), the enzyme for H3K4me3, was elevated in lung cancer tissue compared to normal lung tissue. Knockdown of SETD1A in A549 and H1299 cells led to defects in cell proliferation and epithelial‐mesenchymal transition (EMT), as evidenced by inhibited WNT and transforming growth factor β (TGFβ) pathways, compared with the control group. Xenograft assays also revealed a decreased tumor growth and EMT in the SETD1A silenced group compared with the control group. Mechanistic analysis suggested that SETD1A might regulate tumor progression via several critical oncogenes, which exhibited enhanced H3K4me3 levels around transcriptional start sites in lung cancer. This study illustrates the important role of SETD1A in lung cancer and provides a potential drug target for treatment.

Epigenetic Silencing of MicroRNA-126 Promotes Cell Growth in Marek's Disease

During latency, herpesvirus infection results in the establishment of a dormant state in which a restricted set of viral genes are expressed. Together with alterations of the viral genome, several host genes undergo epigenetic silencing during latency. These epigenetic dysregulations of cellular genes might be involved in the development of cancer. In this context, Gallid alphaherpesvirus 2 (GaHV-2), causing Marek’s disease (MD) in susceptible chicken, was shown to impair the expression of several cellular microRNAs (miRNAs). We decided to focus on gga-miR-126, a host miRNA considered a tumor suppressor through signaling pathways controlling cell proliferation. Our objectives were to analyze the cause and the impact of miR-126 silencing during GaHV-2 infection. This cellular miRNA was found to be repressed at crucial steps of the viral infection. In order to determine whether miR-126 low expression level was associated with specific epigenetic signatures, DNA methylation patterns were established in the miR-126 gene promoter. Repression was associated with hypermethylation at a CpG island located in the miR-126 host gene epidermal growth factor like-7 (EGFL-7). A strategy was developed to conditionally overexpress miR-126 and control miRNAs in transformed CD4+ T cells propagated from Marek’s disease (MD) lymphoma. This functional assay showed that miR-126 restoration specifically diminishes cell proliferation. We identified CT10 regulator of kinase (CRK), an adaptor protein dysregulated in several human malignancies, as a candidate target gene. Indeed, CRK protein levels were markedly reduced by the miR-126 restoration.

Toward a Population-Based Breast Cancer Risk Stratification Approach? The Needs and Concerns of Healthcare Providers

Given the expanding knowledge base in cancer genomics, risk-based screening is among the promising avenues to improve breast cancer (BC) prevention and early detection at the population level. Semi-structured interviews were conducted to explore the perceptions of healthcare professionals (HPs) regarding the implementation of such an approach and identify tools that can support HPs. After undertaking an in-depth thematic content analysis of the responses, 11 themes were identified. These were embedded into a logical model to distinguish the potential eligible participants (who?), the main clinical activities (how?) and associated tools (what?), the key factors of acceptability (which?), and the expected effects of the strategy (why?). Overall, it was found that the respondents positively welcomed the implementation of this strategy and agreed on some of the benefits that could accrue to women from tailored risk-based screening. Some important elements, however, deserve clarification. The results also highlight three main conditions that should be met to foster the acceptability of BC risk stratification: respecting the principle of equity, paying special attention to knowledge management, and rethinking human resources to capitalize on the strengths of the current workforce. Because the functioning of BC risk-based screening is not yet well defined, important planning work is required before advancing this organizational innovation, and outstanding issues must be resolved to get HPs on board.

Detection and relevance of epigenetic markers on ctDNA: recent advances and future outlook

Liquid biopsy, a minimally invasive approach, is a highly powerful clinical tool for the real-time follow-up of cancer and overcomes many limitations of tissue biopsies. Epigenetic alterations have a high potential to provide a valuable source of innovative biomarkers for cancer, owing to their stability, frequency, and noninvasive accessibility in bodily fluids. Numerous DNA methylation markers are now tested in circulating tumor DNA (ctDNA) as potential biomarkers, in various types of cancer. DNA methylation in combination with liquid biopsy is very powerful in identifying circulating epigenetic biomarkers of clinical importance. Blood-based epigenetic biomarkers have a high potential for early detection of cancer since DNA methylation in plasma can be detected early during cancer pathogenesis. In this review, we summarize the latest findings on DNA methylation markers in ctDNA for early detection, prognosis, minimal residual disease, risk of relapse, treatment selection, and resistance, for breast, prostate, lung, and colorectal cancer.

Leveraging Genetic Reports and Electronic Health Records for the Prediction of Primary Cancers: Algorithm Development and Validation Study

BACKGROUND

Precision oncology has the potential to leverage clinical and genomic data in advancing disease prevention, diagnosis, and treatment. A key research area focuses on the early detection of primary cancers and potential prediction of cancers of unknown primary in order to facilitate optimal treatment decisions.

OBJECTIVE

This study presents a methodology to harmonize phenotypic and genetic data features to classify primary cancer types and predict cancers of unknown primaries.

METHODS

We extracted genetic data elements from oncology genetic reports of 1011 patients with cancer and their corresponding phenotypical data from Mayo Clinic's electronic health records. We modeled both genetic and electronic health record data with HL7 Fast Healthcare Interoperability Resources. The semantic web Resource Description Framework was employed to generate the network-based data representation (ie, patient-phenotypic-genetic network). Based on the Resource Description Framework data graph, Node2vec graph-embedding algorithm was applied to generate features. Multiple machine learning and deep learning backbone models were compared for cancer prediction performance.

RESULTS

With 6 machine learning tasks designed in the experiment, we demonstrated the proposed method achieved favorable results in classifying primary cancer types (area under the receiver operating characteristic curve [AUROC] 96.56% for all 9 cancer predictions on average based on the cross-validation) and predicting unknown primaries (AUROC 80.77% for all 8 cancer predictions on average for real-patient validation). To demonstrate the interpretability, 17 phenotypic and genetic features that contributed the most to the prediction of each cancer were identified and validated based on a literature review.

CONCLUSIONS

Accurate prediction of cancer types can be achieved with existing electronic health record data with satisfactory precision. The integration of genetic reports improves prediction, illustrating the translational values of incorporating genetic tests early at the diagnosis stage for patients with cancer.

Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood

BACKGROUND

DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development.

METHODS

In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status.

RESULTS

We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls.

CONCLUSION

The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.

Differential DNA Methylation by Hispanic Ethnicity Among Firefighters in the United States

Firefighters are exposed to a variety of environmental hazards and are at increased risk for multiple cancers. There is evidence that risks differ by ethnicity, yet the biological or environmental differences underlying these differences are not known. DNA methylation is one type of epigenetic regulation that is altered in cancers. In this pilot study, we profiled DNA methylation with the Infinium MethylationEPIC in blood leukocytes from 31 Hispanic white and 163 non-Hispanic white firefighters. We compared DNA methylation (1) at 12 xenobiotic metabolizing genes and (2) at all loci on the array (>740 000), adjusting for confounders. Five of the xenobiotic metabolizing genes were differentially methylated at a raw P-value <.05 when comparing the 2 ethnic groups, yet were not statistically significant at a 5% false discovery rate (q-value <.05). In the epigenome-wide analysis, 76 loci exhibited DNA methylation differences at q < .05. Among these, 3 CpG sites in the promoter region of the biotransformation gene SULT1C2 had lower methylation in Hispanic compared to non-Hispanic firefighters. Other differentially methylated loci included genes that have been implicated in carcinogenesis in published studies (FOXK2, GYLTL1B, ZBTB16, ARHGEF10, and more). In this pilot study, we report differential DNA methylation between Hispanic and non-Hispanic firefighters in xenobiotic metabolism genes and other genes with functions related to cancer. Epigenetic susceptibility by ethnicity merits further study as this may alter risk for cancers linked to toxic exposures.

OPCML Methylation and the Risk of Ovarian Cancer: A Meta and Bioinformatics Analysis

Background: The association of opioid binding protein cell adhesion molecule-like (OPCML) gene methylation with ovarian cancer risk remains unclear. Methods: We identified eligible studies by searching the PubMed, Web of Science, ScienceDirect, and Wanfang databases. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to determine the association of OPCML methylation with ovarian cancer risk. Meta-regression and subgroup analysis were used to assess the sources of heterogeneity. Additionally, we analyzed the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets to validate our findings. Results: Our study included 476 ovarian cancer patients and 385 controls from eight eligible studies. The pooled OR was 33.47 (95% CI = 12.43-90.16) in the cancer group vs. the control group under the random-effects model. The association was still significant in subgroups according to sample type, control type, methods, and sample sizes (all P < 0.05). Sensitivity analysis showed that the finding was robust. No publication bias was observed in Begg's (P = 0.458) and Egger's tests (P = 0.261). We further found that OPCML methylation was related to III/IV (OR = 4.20, 95% CI = 1.59-11.14) and poorly differentiated grade (OR = 4.37; 95% CI = 1.14-16.78). Based on GSE146552 and GSE155760, we validated that three CpG sites (cg16639665, cg23236270, cg15964611) in OPCML promoter region were significantly higher in cancer tissues compared to normal tissues. However, we did not observe the associations of OPCML methylation with clinicopathological parameters and overall survival based on TCGA ovarian cancer data. Conclusion: Our findings support that OPCML methylation is associated with an increased risk of ovarian cancer.

Blueprint for cancer research: Critical gaps and opportunities

We are experiencing a revolution in cancer. Advances in screening, targeted and immune therapies, big data, computational methodologies, and significant new knowledge of cancer biology are transforming the ways in which we prevent, detect, diagnose, treat, and survive cancer. These advances are enabling durable progress in the goal to achieve personalized cancer care. Despite these gains, more work is needed to develop better tools and strategies to limit cancer as a major health concern. One persistent gap is the inconsistent coordination among researchers and caregivers to implement evidence-based programs that rely on a fuller understanding of the molecular, cellular, and systems biology mechanisms underpinning different types of cancer. Here, the authors integrate conversations with over 90 leading cancer experts to highlight current challenges, encourage a robust and diverse national research portfolio, and capture timely opportunities to advance evidence-based approaches for all patients with cancer and for all communities.

Long non-coding RNA Lnc-LALC facilitates colorectal cancer liver metastasis via epigenetically silencing LZTS1

Colorectal cancer (CRC) is one of the most common cancers around the world and endangers human health seriously. Liver metastasis is an important factor affecting the long-term prognosis of CRC and the specific mechanism of CRLM (colorectal cancer with liver metastasis) is not fully understood. LZTS1 has been found dysregulated in many cancers, especially in CRC. Theories suggested that hypermethylation of the promoter regions of LZTS1 was responsible for LZTS1 abnormal expression in multiple malignant tumors. Although the role of LZTS1 in CRC cell proliferation has been reported, its role in CRLM remains unclear. Numerous studies reported Long non-coding RNA (lncRNA) could regulate the gene expression level by regulating gene methylation status in many tumors. However, whether there were lncRNAs could change the methylation status of LZTS1 or not in CRLM was unknown. In this study, we aimed to investigate whether there are lncRNAs can regulate the expression of LZTS1 through affecting DNA methylation in CRLM. We found that upregulated Lnc-LALC in CRC was negatively correlated with LZTS1 expression, and Lnc-LALC could regulate LZTS1 expression in both mRNA and protein level in our study. Functionally, Lnc-LALC enhanced the CRC cells metastasis ability in vitro and vivo through inhibiting the expression of LZTS1. Furthermore, the precise mechanisms exploration showed that lnc-LALC could recruit DNA methyltransferases (DNMTs) to the LZTS1 promoter by combining with Enhancer of zeste homolog 2(EZH2) and then altered the expression of LZTS1 via DNMTs-mediated DNA methylation. Collectively, our data demonstrated the important role of Lnc-LALC/ LZTS1 axis in CRLM development.

The MHC Class-I Transactivator NLRC5: Implications to Cancer Immunology and Potential Applications to Cancer Immunotherapy

The immune system constantly monitors the emergence of cancerous cells and eliminates them. CD8⁺ cytotoxic T lymphocytes (CTLs), which kill tumor cells and provide antitumor immunity, select their targets by recognizing tumor antigenic peptides presented by MHC class-I (MHC-I) molecules. Cancer cells circumvent immune surveillance using diverse strategies. A key mechanism of cancer immune evasion is downregulation of MHC-I and key proteins of the antigen processing and presentation machinery (APM). Even though impaired MHC-I expression in cancers is well-known, reversing the MHC-I defects remains the least advanced area of tumor immunology. The discoveries that NLRC5 is the key transcriptional activator of MHC-I and APM genes, and genetic lesions and epigenetic modifications of NLRC5 are the most common cause of MHC-I defects in cancers, have raised the hopes for restoring MHC-I expression. Here, we provide an overview of cancer immunity mediated by CD8⁺ T cells and the functions of NLRC5 in MHC-I antigen presentation pathways. We describe the impressive advances made in understanding the regulation of NLRC5 expression, the data supporting the antitumor functions of NLRC5 and a few reports that argue for a pro-tumorigenic role. Finally, we explore the possible avenues of exploiting NLRC5 for cancer immunotherapy.

Integrated analysis of microRNA and mRNA expression profiling identifies BAIAP3 as a novel target of dysregulated hsa-miR-1972 in age-related white matter lesions

White matter lesions known as leukoaraiosis (LA) are cerebral white matter hyperintensities observed in elderly individuals. Currently, no reliable molecular biomarkers are available for monitoring their progression over time. To identify biomarkers for the onset and progression of LA, we analyzed whole blood-based, microRNA expression profiles of leukoaraiosis, validated those exhibiting significant microRNA changes in clinical subjects by means of quantitative real-time polymerase chain reactions and determined the function of miRNA in cell lines by means of microRNA mimic transfection assays. A total of seven microRNAs were found to be significantly down-regulated in leukoaraiosis. Among the microRNAs, hsa-miR-1972 was downregulated during the early onset phase of leukoaraiosis, as confirmed in independent patients, and it was found to target leukoaraiosis-dependent BAIAP3, decreasing its expression in 293T cell lines. Functional enrichment analysis revealed that significantly dysregulated miRNAs-mRNAs changes associated with the onset of leukoaraiosis were involved in neurogenesis, neuronal development, and differentiation. Taken together, the study identified a set of candidate microRNA biomarkers that may usefully monitor the onset and progression of leukoaraiosis. Given the enrichment of leukoaraiosis-associated microRNAs and mRNAs in neuron part and membrane system, BAIAP3 could potentially represent a novel target of hsa-miR-1972 in leukoaraiosis through which microRNAs are involved in the pathogenesis of white matter lesions.

Integrative Analysis of DNA Methylation and Gene Expression to Determine Specific Diagnostic Biomarkers and Prognostic Biomarkers of Breast Cancer

Background: DNA methylation is a common event in the early development of various tumors, including breast cancer (BRCA), which has been studies as potential tumor biomarkers. Although previous studies have reported a cluster of aberrant promoter methylation changes in BRCA, none of these research groups have proved the specificity of these DNA methylation changes. Here we aimed to identify specific DNA methylation signatures in BRCA which can be used as diagnostic and prognostic markers.

Methods: Differentially methylated sites were identified using the Cancer Genome Atlas (TCGA) BRCA data set. We screened for BRCA-differential methylation by comparing methylation profiles of BRCA patients, healthy breast biopsies and blood samples. These differential methylated sites were compared to nine main cancer samples to identify BRCA specific methylated sites. A BayesNet model was built to distinguish BRCA patients from healthy donors. The model was validated using three Gene Expression Omnibus (GEO) independent data sets. In addition, we also carried out the Cox regression analysis to identify DNA methylation markers which are significantly related to the overall survival (OS) rate of BRCA patients and verified them in the validation cohort.

Results: We identified seven differentially methylated sites (DMSs) that were highly correlated with cell cycle as potential specific diagnostic biomarkers for BRCA patients. The combination of 7 DMSs achieved ~94% sensitivity in predicting BRCA, ~95% specificity comparing healthy vs. cancer samples, and ~88% specificity in excluding other cancers. The 7 DMSs were highly correlated with cell cycle. We also identified 6 methylation sites that are highly correlated with the OS of BRCA patients and can be used to accurately predict the survival of BRCA patients (training cohort: likelihood ratio = 70.25, p = 3.633 × 10⁻¹³, area under the curve (AUC) = 0.784; validation cohort: AUC = 0.734). Stratification analysis by age, clinical stage, Tumor types, and chemotherapy retained statistical significance.

Conclusion: In summary, our study demonstrated the role of methylation profiles in the diagnosis and prognosis of BRCA. This signature is superior to currently published methylation markers for diagnosis and prognosis for BRCA patients. It can be used as promising biomarkers for early diagnosis and prognosis of BRCA.

DNA methylation signatures to predict the cervicovaginal microbiome status

Background

The composition of the microbiome plays an important role in human health and disease. Whether there is a direct association between the cervicovaginal microbiome and the host’s epigenome is largely unexplored.

Results

Here we analyzed a total of 448 cervicovaginal smear samples and studied both the DNA methylome of the host and the microbiome using the Illumina EPIC array and next-generation sequencing, respectively. We found that those CpGs that are hypo-methylated in samples with non-lactobacilli (O-type) dominating communities are strongly associated with gastrointestinal differentiation and that a signature consisting of 819 CpGs was able to discriminate lactobacilli-dominating (L-type) from O-type samples with an area under the receiver operator characteristic curve (AUC) of 0.84 (95% CI = 0.77–0.90) in an independent validation set. The performance found in samples with more than 50% epithelial cells was further improved (AUC 0.87) and in women younger than 50 years of age was even higher (AUC 0.91). In a subset of 96 women, the buccal but not the blood cell DNA showed the same trend as the cervicovaginal samples in discriminating women with L- from O-type cervicovaginal communities.

Conclusions

These findings strongly support the view that the epithelial epigenome plays an essential role in hosting specific microbial communities.

Prevention in the age of personal responsibility: epigenetic risk-predictive screening for female cancers as a case study

Epigenetic markers could potentially be used for risk assessment in risk-stratified population-based cancer screening programmes. Whereas current screening programmes generally aim to detect existing cancer, epigenetic markers could be used to provide risk estimates for not-yet-existing cancers. Epigenetic risk-predictive tests may thus allow for new opportunities for risk assessment for developing cancer in the future. Since epigenetic changes are presumed to be modifiable, preventive measures, such as lifestyle modification, could be used to reduce the risk of cancer. Moreover, epigenetic markers might be used to monitor the response to risk-reducing interventions. In this article, we address ethical concerns related to personal responsibility raised by epigenetic risk-predictive tests in cancer population screening. Will individuals increasingly be held responsible for their health, that is, will they be held accountable for bad health outcomes? Will they be blamed or subject to moral sanctions? We will illustrate these ethical concerns by means of a Europe-wide research programme that develops an epigenetic risk-predictive test for female cancers. Subsequently, we investigate when we can hold someone responsible for her actions. We argue that the standard conception of personal responsibility does not provide an appropriate framework to address these concerns. A different, prospective account of responsibility meets part of our concerns, that is, concerns about inequality of opportunities, but does not meet all our concerns about personal responsibility. We argue that even if someone is responsible on grounds of a negative and/or prospective account of responsibility, there may be moral and practical reasons to abstain from moral sanctions.

Epigenetic landscape of small cell lung cancer: small image of a giant recalcitrant disease

Small cell lung cancer (SCLC) is a particular subtype of lung cancer with high mortality. Recent advances in understanding SCLC genomics and breakthroughs of immunotherapy have substantially expanded existing knowledge and treatment modalities. However, challenges associated with SCLC remain enigmatic and elusive. Most of the conventional drug discovery approaches targeting altered signaling pathways in SCLC end up in the 'grave-yard of drug discovery', which mandates exploring novel approaches beyond inhibiting cell signaling pathways. Epigenetic modifications have long been documented as the key contributors to the tumorigenesis of almost all types of cancer, including SCLC. The last decade witnessed an exponential increase in our understanding of epigenetic modifications for SCLC. The present review highlights the central role of epigenetic regulations in acquiring neoplastic phenotype, metastasis, aggressiveness, resistance to chemotherapy, and immunotherapeutic approaches of SCLC. Different types of epigenetic modifications (DNA/histone methylation or acetylation) that can serve as predictive biomarkers for prognostication, treatment stratification, neuroendocrine lineage determination, and development of potential SCLC therapies are also discussed. We also review the utility of epigenetic targets/epidrugs in combination with first-line chemotherapy and immunotherapy that are currently under investigation in preclinical and clinical studies. Altogether, the information presents the inclusive landscape of SCLC epigenetics and epidrugs that will help to improve SCLC outcomes.

Personalized early detection and prevention of breast cancer: ENVISION consensus statement

The European Collaborative on Personalized Early Detection and Prevention of Breast Cancer (ENVISION) brings together several international research consortia working on different aspects of the personalized early detection and prevention of breast cancer. In a consensus conference held in 2019, the members of this network identified research areas requiring development to enable evidence-based personalized interventions that might improve the benefits and reduce the harms of existing breast cancer screening and prevention programmes. The priority areas identified were: 1) breast cancer subtype-specific risk assessment tools applicable to women of all ancestries; 2) intermediate surrogate markers of response to preventive measures; 3) novel non-surgical preventive measures to reduce the incidence of breast cancer of poor prognosis; and 4) hybrid effectiveness-implementation research combined with modelling studies to evaluate the long-term population outcomes of risk-based early detection strategies. The implementation of such programmes would require health-care systems to be open to learning and adapting, the engagement of a diverse range of stakeholders and tailoring to societal norms and values, while also addressing the ethical and legal issues. In this Consensus Statement, we discuss the current state of breast cancer risk prediction, risk-stratified prevention and early detection strategies, and their implementation. Throughout, we highlight priorities for advancing each of these areas.

Hypomethylation of GDNF family receptor alpha 1 promotes epithelial-mesenchymal transition and predicts metastasis of colorectal cancer

Tumor metastasis is the major cause of poor prognosis and mortality in colorectal cancer (CRC). However, early diagnosis of highly metastatic CRC is currently difficult. In the present study, we screened for a novel biomarker, GDNF family receptor alpha 1 (GFRA1) based on the expression and methylation data in CRC patients from The Cancer Genome Altlas (TCGA), followed by further analysis of the correlation between the GFRA1 expression, methylation, and prognosis of patients. Our results show DNA hypomethylation-mediated upregulation of GFRA1 in invasive CRC, and it was found to be correlated with poor prognosis of CRC patients. Furthermore, GFRA1 methylation-modified sequences were found to have potential as methylation diagnostic markers of highly metastatic CRC. The targeted demethylation of GFRA1 by dCas9-TET1CD and gRNA promoted CRC metastasis in vivo and in vitro. Mechanistically, demethylation of GFRA1 induces epithelial-mesenchymal transition (EMT) by promoting AKT phosphorylation and increasing c-Jun expression in CRC cells. Collectively, our findings indicate that GFRA1 hypomethylation can promote CRC invasion via inducing EMT, and thus, GFRA1 methylation can be used as a biomarker for the early diagnosis of highly metastasis CRC.

Machine learning analysis of DNA methylation in a hypoxia-immune model of oral squamous cell carcinoma

BACKGROUND

Hypoxia status and immunity are related with the development and prognosis of oral squamous cell carcinoma (OSCC). Here, we constructed a hypoxia-immune model to explore its upstream mechanism and identify potential CpG sites.

METHODS

The hypoxia-immune model was developed and validated by the iCluster algorithm. The LASSO, SVM-RFE and GA-ANN were performed to screen CpG sites correlated to the hypoxia-immune microenvironment.

RESULTS

We found seven hypoxia-immune related CpG sites. Lasso had the best classification performance among three machine learning algorithms.

CONCLUSION

We explored the clinical significance of the hypoxia-immune model and found seven hypoxia-immune related CpG sites by multiple machine learning algorithms. This model and candidate CpG sites may have clinical applications to predict the hypoxia-immune microenvironment.

An overview of advances in multi-omics analysis in prostate cancer

Prostate cancer (PCa) is a deadly disease for men, and studies of all types of omics data are necessary to promote precision medicine. The maturity of sequencing technology, the improvements of computer processing power, and the progress achieved in omics analysis methods have improved research efficiency and saved research costs. The occurrence and development of PCa is due to multisystem and multilevel pathological changes. Although omics research at a single level is important, this approach often has limitations. In contrast, the combined analysis of multiple types of omics data can better analyze PCa changes as a whole, thus ensuring the validity of research results to the greatest extent. This paper introduces the applications of single omics in PCa and then summarizes research progress in the combined analysis of two or more types of omics data, so as to systematically and comprehensively analyze the necessity of combined analysis of multiple omics data in PCa.

Criteria for evaluating risk prediction of multiple outcomes

Risk prediction models have been developed in many contexts to classify individuals according to a single outcome, such as risk of a disease. Emerging “-omic” biomarkers provide panels of features that can simultaneously predict multiple outcomes from a single biological sample, creating issues of multiplicity reminiscent of exploratory hypothesis testing. Here I propose definitions of some basic criteria for evaluating prediction models of multiple outcomes. I define calibration in the multivariate setting and then distinguish between outcome-wise and individual-wise prediction, and within the latter between joint and panel-wise prediction. I give examples such as screening and early detection in which different senses of prediction may be more appropriate. In each case I propose definitions of sensitivity, specificity, concordance, positive and negative predictive value and relative utility. I link the definitions through a multivariate probit model, showing that the accuracy of a multivariate prediction model can be summarised by its covariance with a liability vector. I illustrate the concepts on a biomarker panel for early detection of eight cancers, and on polygenic risk scores for six common diseases.

Identifying epigenetic biomarkers of established prognostic factors and survival in a clinical cohort of individuals with oropharyngeal cancer

BACKGROUND

Smoking status, alcohol consumption and HPV infection (acquired through sexual activity) are the predominant risk factors for oropharyngeal cancer and are thought to alter the prognosis of the disease. Here, we conducted single-site and differentially methylated region (DMR) epigenome-wide association studies (EWAS) of these factors, in addition to ∼ 3-year survival, using Illumina Methylation EPIC DNA methylation profiles from whole blood in 409 individuals as part of the Head and Neck 5000 (HN5000) study. Overlapping sites between each factor and survival were then assessed using two-step Mendelian randomization to assess whether methylation at these positions causally affected survival.

RESULTS

Using the MethylationEPIC array in an OPC dataset, we found novel CpG associations with smoking, alcohol consumption and ~ 3-year survival. We found no CpG associations below our multiple testing threshold associated with HPV16 E6 serological response (used as a proxy for HPV infection). CpG site associations below our multiple-testing threshold (PBonferroni < 0.05) for both a prognostic factor and survival were observed at four gene regions: SPEG (smoking), GFI1 (smoking), PPT2 (smoking) and KHDC3L (alcohol consumption). Evidence for a causal effect of DNA methylation on survival was only observed in the SPEG gene region (HR per SD increase in methylation score 1.28, 95% CI 1.14 to 1.43, P 2.12 × 10-05).

CONCLUSIONS

Part of the effect of smoking on survival in those with oropharyngeal cancer may be mediated by methylation at the SPEG gene locus. Replication in data from independent datasets and data from HN5000 with longer follow-up times is needed to confirm these findings.

Prognostic Value of a Three-DNA Methylation Biomarker in Patients with Soft Tissue Sarcoma

Soft tissue sarcomas (STS) are a highly aggressive and heterogeneous group of malignant mesenchymal tumors. The prognosis of patients with advanced or metastatic STS remains poor, and the main therapy of STS patients combines primary surgery, radiotherapy, and chemotherapy. Aberrant DNA methylation shows close association with the pathogenesis and tumor progression. Therefore, DNA methylation biomarkers might have the potential in accurately predicting the survival of STS patients. In order to identify a prognostic biomarker based on DNA methylation sites, a comprehensive analysis of the DNA methylation profile of STS patients in the Cancer Genome Atlas (TCGA) database was performed. All samples were randomly divided into training and testing datasets. Cox proportional hazards regression analysis was performed to identify a prognostic biomarker that contains three DNA methylation sites. The Kaplan-Meier analysis demonstrated that the 3-DNA methylation biomarker discriminated patients into high-risk and low-risk groups, both in the training and in the testing datasets, and the area under the receiver operating characteristic curve values (AUCs) were 0.844 (P < 0.001, 95% CI: 0.740-0.948) and 0.710 (P = 0.002, 95% CI: 0.595-0.823), respectively. Besides, this biomarker presented superior prognostic performance in STS patients with different age, sex, tissue of origin, therapy, and histologic subtypes. Compared with other prognostic biomarkers, this biomarker tended to be a more precise prognostic factor in STS patients. Moreover, methylation sites in this biomarker might provide a new way for clinicians to make decisions regarding the intervention and assess the effectiveness of an individual therapeutic strategy.

A Systematic Review on Cost-effectiveness Studies Evaluating Ovarian Cancer Early Detection and Prevention Strategies

Ovarian cancer imposes a substantial health and economic burden. We systematically reviewed current health-economic evidence for ovarian cancer early detection or prevention strategies. Accordingly, we searched relevant databases for cost-effectiveness studies evaluating ovarian cancer early detection or prevention strategies. Study characteristics and results including quality-adjusted life years (QALY), and incremental cost-effectiveness ratios (ICER) were summarized in standardized evidence tables. Economic results were transformed into 2017 Euros. The included studies (N = 33) evaluated ovarian cancer screening, risk-reducing interventions in women with heterogeneous cancer risks and genetic testing followed by risk-reducing interventions for mutation carriers. Multimodal screening with a risk-adjusted algorithm in postmenopausal women achieved ICERs of 9,800-81,400 Euros/QALY, depending on assumptions on mortality data extrapolation, costs, test performance, and screening frequency. Cost-effectiveness of risk-reducing surgery in mutation carriers ranged from cost-saving to 59,000 Euros/QALY. Genetic testing plus risk-reducing interventions for mutation carriers ranged from cost-saving to 54,000 Euros/QALY in women at increased mutation risk. Our findings suggest that preventive surgery and genetic testing plus preventive surgery in women at high risk for ovarian cancer can be considered effective and cost-effective. In postmenopausal women from the general population, multimodal screening using a risk-adjusted algorithm may be cost-effective.

Ethical Issues in Research and Development of Epigenome-wide Technologies

To date, few scholarly discussions on ethical implications of epigenetics and epigenomics technologies have focused on the current phase of research and development, in which researchers are confronted with real and practical ethical dilemmas. In this article, a responsible research and innovation approach, using interviews and an expert meeting, is applied to a case of epigenomic test development for cervical cancer screening. This article provides an overview of ethical issues presently facing epigenomics researchers and test developers, and discusses 3 sets of issues in depth: (1) informed consent; (2) communication with donors and/or research participants, and (3) privacy and publication of data and research results. Although these issues are familiar to research ethics, some aspects are new and most require reinterpretation in the context of epigenomics technologies. With this article, we aim to start a discussion of the practical ethical issues rising in research and development of epigenomic technologies and to offer guidance for researchers working in the field of epigenetic and epigenomic technology.

Non-Surgical Cancer Risk Reduction in BRCA1 Mutation Carriers: Disabling the Remote Control

Women-specific cancers are a major health issue, particularly those associated with the BRCA1 germline mutation carrier state, which include triple-negative basal breast carcinomas and high-grade serous ovarian carcinomas (referred to as extra-uterine Müllerian carcinomas). Whereas many chronic diseases can currently be prevented (e.g., cardiovascular diseases), no recent tangible progress was made in cancer prevention of BRCA1 mutation carriers apart from surgical resections of at-risk organs. This lack of progress is largely due to (1) poor understanding of the initiating events triggered by known risk factors in the development of these cancers, (2) the fact that current preventive measures rely on evidence obtained from adjuvant breast cancer treatment that fail to protect against poor prognostic cancers, and (3) problems with using cancer incidence in high-risk women as an ethically justifiable endpoint in cancer prevention trials. Here, we propose that cancer predisposition in BRCA1 mutation carriers is driven, at least in part, by cell-nonautonomous mechanisms (i.e., driven by consequences of this carrier state on hormonal and other systemic factors controlled in organs other than those that are cancer-prone) and that biomarkers of epigenomic reprogramming, hypothesized to be a direct consequence of such cell-nonautonomous mechanisms, are attractive as intermediate surrogate endpoints to assess the efficacy of cancer risk-reducing strategies targeting these mechanisms.

Demethylation of the Cosmc Promoter Alleviates the Progression of Breast Cancer Through Downregulation of the Tn and Sialyl-Tn Antigens

Background

Aberrant gene methylation in breast cancer is associated with an unfavorable prognosis. Besides, abnormal Cosmc can induce the expression of Tn and STn antigens. The present study aimed to investigate the roles of Cosmc promoter methylation in breast cancer through the regulation of Tn and STn antigens.

Methods

The expression patterns of Cosmc and the Tn and STn antigens in breast cancer cell lines were determined. Cosmc was overexpressed to explore the effects of Cosmc on cell behavior, including the growth, migration, invasion, and apoptosis of breast cancer cells and tumor growth with in vitro and in vivo experiments. Afterwards, a methyltransferase and a methyltransferase inhibitor were used to alter the methylation status of Cosmc to explore the mechanisms related to Cosmc promoter methylation.

Results

Cosmc was poorly expressed in breast cancer cells. Cosmc overexpression inhibited cell growth, migration, and invasion while promoting apoptosis in breast cancer cells in vitro and restraining tumor growth in vivo. Cosmc promoter methylation was found to decrease the levels of Cosmc and increased the expression of the Tn and STn antigens in breast cancer.

Conclusion

In conclusion, the demethylation of Cosmc mitigates breast cancer progression through the repression of the Tn and STn antigens, which provides evidence for therapeutic considerations for a novel target against breast cancer.

Cell and tissue type independent age-associated DNA methylation changes are not rare but common

Age-associated DNA methylation changes have been widely reported across many different tissue and cell types. Epigenetic ‘clocks’ that can predict chronological age with a surprisingly high degree of accuracy appear to do so independently of tissue and cell-type, suggesting that a component of epigenetic drift is cell-type independent. However, the relative amount of age-associated DNAm changes that are specific to a cell or tissue type versus the amount that occurs independently of cell or tissue type is unclear and a matter of debate, with a recent study concluding that most epigenetic drift is tissue-specific. Here, we perform a novel comprehensive statistical analysis, including matched multi cell-type and multi-tissue DNA methylation profiles from the same individuals and adjusting for cell-type heterogeneity, demonstrating that a substantial amount of epigenetic drift, possibly over 70%, is shared between significant numbers of different tissue/cell types. We further show that ELOVL2 is not unique and that many other CpG sites, some mapping to genes in the Wnt and glutamate receptor signaling pathways, are altered with age across at least 10 different cell/tissue types. We propose that while most age-associated DNAm changes are shared between cell-types that the putative functional effect is likely to be tissue-specific.

Epigenetics and gestational diabetes: a review of epigenetic epidemiology studies and their use to explore epigenetic mediation and improve prediction

Epigenetics encapsulates a group of molecular mechanisms including DNA methylation, histone modification and microRNAs (miRNAs). Gestational diabetes (GDM) increases the risk of adverse perinatal outcomes and is associated with future offspring risk of obesity and type 2 diabetes. It has been hypothesised that epigenetic mechanisms mediate an effect of GDM on offspring adiposity and type 2 diabetes and this could provide a modifiable mechanism to reduce type 2 diabetes in the next generation. Evidence for this hypothesis is lacking. Epigenetic epidemiology could also contribute to reducing type 2 diabetes by identifying biomarkers that accurately predict risk of GDM and its associated future adverse outcomes. We reviewed published human studies that explored associations between any of maternal GDM, type 2 diabetes, gestational fasting or post-load glucose and any epigenetic marker (DNA methylation, histone modification or miRNA). Of the 81 relevant studies we identified, most focused on the potential role of epigenetic mechanisms in mediating intrauterine effects of GDM on offspring outcomes. Studies were small (median total number of participants 58; median number of GDM cases 27) and most did not attempt replication. The most common epigenetic measure analysed was DNA methylation. Most studies that aimed to explore epigenetic mediation examined associations of in utero exposure to GDM with offspring cord or infant blood/placenta DNA methylation. Exploration of any causal effect, or effect on downstream offspring outcomes, was lacking. There is a need for more robust methods to explore the role of epigenetic mechanisms as possible mediators of effects of exposure to GDM on future risk of obesity and type 2 diabetes. Research to identify epigenetic biomarkers to improve identification of women at risk of GDM and its associated adverse (maternal and offspring) outcomes is currently rare but could contribute to future tools for accurate risk stratification.

Targeting the undruggable: exploiting neomorphic features of fusion oncoproteins in childhood sarcomas for innovative therapies

While sarcomas account for approximately 1% of malignant tumors of adults, they are particularly more common in children and adolescents affected by cancer. In contrast to malignancies that occur in later stages of life, childhood tumors, including sarcoma, are characterized by a striking paucity of somatic mutations. However, entity-defining fusion oncogenes acting as the main oncogenic driver mutations are frequently found in pediatric bone and soft-tissue sarcomas such as Ewing sarcoma (EWSR1-FLI1), alveolar rhabdomyosarcoma (PAX3/7-FOXO1), and synovial sarcoma (SS18-SSX1/2/4). Since strong oncogene-dependency has been demonstrated in these entities, direct pharmacological targeting of these fusion oncogenes has been excessively attempted, thus far, with limited success. Despite apparent challenges, our increasing understanding of the neomorphic features of these fusion oncogenes in conjunction with rapid technological advances will likely enable the development of new strategies to therapeutically exploit these neomorphic features and to ultimately turn the "undruggable" into first-line target structures. In this review, we provide a broad overview of the current literature on targeting neomorphic features of fusion oncogenes found in Ewing sarcoma, alveolar rhabdomyosarcoma, and synovial sarcoma, and give a perspective for future developments. Graphical abstract Scheme depicting the different targeting strategies of fusion oncogenes in pediatric fusion-driven sarcomas. Fusion oncogenes can be targeted on their DNA level (1), RNA level (2), protein level (3), and by targeting downstream functions and interaction partners (4).

Cell-Free DNA Methylation Profiling Analysis-Technologies and Bioinformatics

Analysis of circulating nucleic acids in bodily fluids, referred to as “liquid biopsies”, is rapidly gaining prominence. Studies have shown that cell-free DNA (cfDNA) has great potential in characterizing tumor status and heterogeneity, as well as the response to therapy and tumor recurrence. DNA methylation is an epigenetic modification that plays an important role in a broad range of biological processes and diseases. It is well known that aberrant DNA methylation is generalizable across various samples and occurs early during the pathogenesis of cancer. Methylation patterns of cfDNA are also consistent with their originated cells or tissues. Systemic analysis of cfDNA methylation profiles has emerged as a promising approach for cancer detection and origin determination. In this review, we will summarize the technologies for DNA methylation analysis and discuss their feasibility for liquid biopsy applications. We will also provide a brief overview of the bioinformatic approaches for analysis of DNA methylation sequencing data. Overall, this review provides informative guidance for the selection of experimental and computational methods in cfDNA methylation-based studies.

ZNF382: A transcription inhibitor down-regulated in multiple tumors due to promoter methylation

Zinc finger protein 382 (ZNF382), a member of the Krüppel-associated box zinc finger proteins (KRAB-ZFPs) family, plays critical roles in regulating certain downstream genes expression as a transcription inhibitor. ZNF382 is downregulated in multiple tumors due to hypermethylation of its promoter, to be more specific, methylation of promoter CpG island may contributes to inhibition of gene expression as found in many studies. With application of DNA methyltransferase inhibitors (DNMTi) 5-azacytidine and 5-aza-2'-deoxycytidine, hypomethylation of ZNF382 gene may contribute to anti-tumor effects. This review summerized the structure, biological functions, expression and the roles of ZNF382 in multiple cancers, and, expression of ZNF382 regulated by promoter methylation was further discussed to show the possibilities of DNA hypomethylation treatment as a potential treatment in clinical applications.

Hypomethylation of 111 Probes Predicts Poor Prognosis for Glioblastoma

Glioblastoma (GBM) is a complicated brain tumor with heterogeneous outcome. Identification of effective biomarkers is an urgent need for the treatment decision-making and precise evaluation of prognosis. Based on a relatively large dataset of genome-wide methylation (138 glioblastoma patients), a joint-score of 111 methyl-probes was found to be of statistical significance for prognostic evaluation. Low joint-score were significantly associated with adverse outcomes (OS: P < 0.001, PFS: P = 0.03). Multivariable analyses adjusted for known risk factors confirmed the low joint-score of 111 methyl-probes as a high risk factor. The prognostic value of the methylated joint-score was further validated in another dataset of glioblastoma patients (OS: P = 0.006). Additionally, variance analysis revealed that aberrant genetic and epigenetic alterations were significantly associated with the joint-score of those methyl-probes. In conclusion, our results supported the joint-score of 111 methyl-probes as a potential prognosticator for the precision treatment of glioblastoma.

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

New technologies have enabled the investigation of biology and human health at an unprecedented scale and in multiple dimensions. These dimensions include myriad properties describing genome, epigenome, transcriptome, microbiome, phenotype, and lifestyle. No single data type, however, can capture the complexity of all the factors relevant to understanding a phenomenon such as a disease. Integrative methods that combine data from multiple technologies have thus emerged as critical statistical and computational approaches. The key challenge in developing such approaches is the identification of effective models to provide a comprehensive and relevant systems view. An ideal method can answer a biological or medical question, identifying important features and predicting outcomes, by harnessing heterogeneous data across several dimensions of biological variation. In this Review, we describe the principles of data integration and discuss current methods and available implementations. We provide examples of successful data integration in biology and medicine. Finally, we discuss current challenges in biomedical integrative methods and our perspective on the future development of the field.

Up-regulation of SPC25 promotes breast cancer

In this study, expression of the SPC25 gene was characterized in breast cancer (BC), and its effects on BC development and progression, functions in BC cells, and potential underlying mechanisms were examined. Data from TCGAportal and FIREBROWSE indicated that SPC25 was upregulated in BC tissues compared to normal tissues, and CANCERTOOL indicated that higher SPC25 mRNA levels were associated with increased probability of recurrence and poorer survival in BC patients. BC patients with higher SPC25 expression displayed shorter distant metastasis-free survival, relapse-free survival, and overall survival. Colony formation and CCK-8 experiments confirmed that SPC25 promoted proliferation of BC cells. Single-cell analysis indicated that SPC25 is associated with cell cycle regulation, DNA damage and repair, and BC cell proliferation. SPC25 knockdown suppressed proliferation of BC cells. MiRNAs, circRNAs, RNA-binding proteins, transcription factors, and immune factors that might interact with SPC25 mRNA to promote BC were also identified. These findings suggest that SPC25 levels are higher in more malignant BC subtypes and are associated with poor prognosis in BC patients. In addition, DNA methyltransferase inhibitor and transcription factors inhibitor treatments targeting SPC25 might improve survival in BC patients.

The Cancer Research UK - Ludwig Cancer Research Nutrition and Cancer Prevention Collaborative Group. Current opportunities to catalyze research in nutrition and cancer prevention - an interdisciplinary perspective

Cancer Research UK and Ludwig Cancer Research convened an inaugural international Cancer Prevention and Nutrition Conference in London on December 3-4, 2018. Much of the discussion focused on the need for systematic, interdisciplinary approaches to better understand the relationships of nutrition, exercise, obesity and metabolic dysfunction with cancer development. Scientists at the meeting underscored the importance of studying the temporal natural history of exposures that may cumulatively impact cancer risk later in life.A robust dialogue identified obesity as a major risk for cancer, and the food environment, especially high energy and low nutrient processed foods, as strong and prevalent risk factors for obesity. Further engagement highlighted challenges in the post-diagnostic setting, where similar opportunities to understand the complex interplay of nutrition, physical activity, and weight will inform better health outcomes.Going forward, holistic research approaches, encompassing insights from multiple disciplines and perspectives, will catalyze progress urgently needed to prevent cancer and improve public health.