Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk

Genetic effects on the skin methylome in healthy older twins

Whole-skin DNA methylation variation has been implicated in several diseases, including melanoma, but its genetic basis has not yet been fully characterized. Using bulk skin tissue samples from 414 healthy female UK twins, we performed twin-based heritability and methylation quantitative trait loci (meQTL) analyses for >400,000 DNA methylation sites. We find that the human skin DNA methylome is on average less heritable than previously estimated in blood and other tissues (mean heritability: 10.02%). meQTL analysis identified local genetic effects influencing DNA methylation at 18.8% (76,442) of tested CpG sites, as well as 1,775 CpG sites associated with at least one distal genetic variant. As a functional follow-up, we performed skin expression QTL (eQTL) analyses in a partially overlapping sample of 604 female twins. Colocalization analysis identified over 3,500 shared genetic effects affecting thousands of CpG sites (10,067) and genes (4,475). Mediation analysis of putative colocalized gene-CpG pairs identified 114 genes with evidence for eQTL effects being mediated by DNA methylation in skin, including in genes implicating skin disease such as ALOX12 and CSPG4. We further explored the relevance of skin meQTLs to skin disease and found that skin meQTLs and CpGs under genetic influence were enriched for multiple skin-related genome-wide and epigenome-wide association signals, including for melanoma and psoriasis. Our findings give insights into the regulatory landscape of epigenomic variation in skin.

Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk

The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the Genotype-Tissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P < 0.05, we identify 4248 CpGs that are significantly associated with cancer risk, of which 95.4% (4052) are specific to a particular cancer type. Notably, 92 CpGs within 55 putative novel loci retain significant associations with cancer risk after conditioning on proximal signals identified by genome-wide association studies. Integrative multi-omics analyses reveal 854 CpG-gene-cancer trios, suggesting that DNA methylation at 309 distinct CpGs might influence cancer risk through regulating the expression of 205 unique cis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.

Current data and future perspectives on DNA methylation in ovarian cancer (Review)

Ovarian cancer (OC) represents the most prevalent malignancy of the female reproductive system. Its distinguishing features include a high aggressiveness, substantial morbidity and mortality, and a lack of apparent symptoms, which collectively pose significant challenges for early detection. Given that aberrant DNA methylation events leading to altered gene expression are characteristic of numerous tumor types, there has been extensive research into epigenetic mechanisms, particularly DNA methylation, in human cancers. In the context of OC, DNA methylation is often associated with the regulation of critical genes, such as BRCA1/2 and Ras‑association domain family 1A. Methylation modifications within the promoter regions of these genes not only contribute to the pathogenesis of OC, but also induce medication resistance and influence the prognosis of patients with OC. As such, a more in‑depth understanding of DNA methylation underpinning carcinogenesis could potentially facilitate the development of more effective therapeutic approaches for this intricate disease. The present review focuses on classical tumor suppressor genes, oncogenes, signaling pathways and associated microRNAs in an aim to elucidate the influence of DNA methylation on the development and progression of OC. The advantages and limitations of employing DNA methylation in the diagnosis, treatment and prevention of OC are also discussed. On the whole, the present literature review indicates that the DNA methylation of specific genes could potentially serve as a prognostic biomarker for OC and a therapeutic target for personalized treatment strategies. Further investigations in this field may yield more efficacious diagnostic and therapeutic alternatives for patients with OC.

DNA methylation marker identification and poly-methylation risk score in prediction of healthspan termination

Aim: To elucidate the epigenetic consequences of DNA methylation in healthspan termination (HST), considering the current limited understanding. Materials & methods: Genetically predicted DNA methylation models were established (n = 2478). These models were applied to genome-wide association study data on HST. Then, a poly-methylation risk score (PMRS) was established in 241,008 individuals from the UK Biobank. Results: Of the 63,046 CpGs from the prediction models, 13 novel CpGs were associated with HST. Furthermore, people with high PMRSs showed higher HST risk (hazard ratio: 1.18; 95% CI: 1.13-1.25). Conclusion: The study indicates that DNA methylation may influence HST by regulating the expression of genes (e.g., PRMT6, CTSK). PMRSs have a promising application in discriminating subpopulations to facilitate early prevention.

Epigenetic biomarkers for disease susceptibility and preventative medicine

The development of molecular biomarkers for disease makes it possible for preventative medicine approaches to be considered. Therefore, therapeutics, treatments, or clinical management can be used to delay or prevent disease development. The problem with genetic mutations as biomarkers is the low frequency with genome-wide association studies (GWASs), generally at best a 1% association of the patients with the disease. In contrast, epigenetic alterations have a high-frequency association of greater than 90%-95% of individuals with pathology in epigenome-wide association studies (EWASs). A wide variety of human diseases have been shown to have epigenetic biomarkers that are disease specific and that detect pathology susceptibility. This review is focused on the epigenetic biomarkers for disease susceptibility, and it distinct from the large literature on epigenetics of disease etiology or progression. The development of efficient epigenetic biomarkers for disease susceptibility will facilitate a paradigm shift from reactionary medicine to preventative medicine.

Dietary sources of branched-chain fatty acids and their biosynthesis, distribution, and nutritional properties

Branched-chain fatty acids (BCFAs) consist of a wide variety of fatty acids with alkyl branching of methyl group. The most common BCFAs are the types with one methyl group (mmBCFA) on the penultimate carbon (iBCFA) or the antepenultimate carbon (aiBCFA). Long-chain mmBCFAs are widely existing in animal fats, milks and are mostly derived from bacteria in the diet or animal digestive system. Recent studies show that BCFAs benefit human intestinal health and immune homeostasis, but the connection between their content, distribution in the human and their nutritional functions are not well established. In this paper, we reviewed BCFAs from various dietary sources focused on their molecular species. The BCFAs biosynthesis in bacteria, Caenorhabditis elegans, mammals and their distribution in human tissues are summarized. This paper also discusses the nutritional properties of BCFAs including influences on intestinal health, immunoregulatory effects, anti-carcinoma, and anti-obesity activities, by highlighting the most recent research progress.

Effect of Primary Versus Revisional One Anastomosis Gastric Bypass (OAGB) on Fatty Acid Profile

INTRODUCTION

One anastomosis gastric bypass (OAGB) is one option of a revisional procedure for failed sleeve gastrectomy. Moreover, it can be used as a primary bariatric procedure, and is an effective surgery resulting in significant weight loss and the resolution or improvement of obesity-associated medical problems, accompanied by low perioperative complications. However, as with any therapy, OAGB has its limitations, including micronutrient deficiency or malnutrition. In our study, we compared the fatty acid (FA) profile in serum of patients after both primary OAGB (pOAGB) and revisional OAGB (rOAGB) to identify potential postsurgical FA alterations.

METHODS

This is a retrospective study on patients with obesity who underwent OAGB procedures (pOAGB n=68; rOAGB n=17), conducted from 2016 to 2018. In blood, we analyzed a series of biochemical parameters, and in the serum, the FA profile was determined using gas chromatography-mass spectrometry.

RESULTS

The percentage of excess BMI loss (% EBMIL) after pOAGB was 73.5 ± 2.47% in comparison to 45.9 ± 4.15% in the rOAGB group (p<0.001). In contrast to the lack of effect of rOAGB on most polyunsaturated FAs, in the pOAGB group, there was a decrease in eicosapentaenoic acid, and eicosatetraenoic and docosahexaenoic acid levels (p<0.001). We also found a decrease in very long-chain FAs (VLCFAs) and an increase in branched-chain FAs (BCFAs) after both types of OAGB procedure.

CONCLUSIONS

Both OAGB procedures improved the profile of most FAs, leading to a decrease in VLCFAs, which are considered harmful, and an improvement in BCFAs, which are considered to be beneficial. There is a need to further investigate the possibility of n-3 polyunsaturated FA supplementation after pOAGB, due to the large decrease in these FAs after pOAGB.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Cytological DNA methylation for cervical cancer screening: a validation set

Background

In a previous training set with a case-controlled design, cutoff values for host EPB41L3 and JAM3 gene methylation were obtained for the detection of cervical intraepithelial neoplasia (CIN) 2 or more severe lesions (CIN2+). This validation trial was conducted to evaluate the role of DNA methylation in screening for CIN2+ by cervical cytology among unselected participants.

Methods

From June 1, 2019, to September 1, 2019, in our study center, we collected liquid-based samples from cervical swabs for methylation assays and hrHPV testing in eligible patients. The primary endpoint was the diagnostic accuracy of DNA methylation and hrHPV genotyping for CIN2+ according to confirmed histology results.

Results

Among 307 participants, compared with hrHPV testing, the methylation assay for CIN2+ had lower sensitivity (68.7% versus 86.1%, p=0.002) but higher specificity (96.7% versus 0.696, p<0.001). The methylation assay also had favorable sensitivity and specificity in patients with negative hrHPV testing (56.3% and 96.9%) and in patients with cervical adenocarcinoma (73.7% and 92.7%). DNA methylation had higher specificity than the hrHPV assay (100.0% versus 44.4%, p<0.001) for identifying residual CIN2+ in patients without residual lesions. Positive cervical DNA methylation was associated with a diagnostic probability of endometrial carcinoma (odds ratio 15.5 [95% confidence interval 4.1-58.6]) but not of ovarian epithelial carcinoma (1.4 [0.3-6.5]).

Conclusions

The host EPB41L3 and JAM3 gene methylation assay in cervical cytology had favorable diagnostic accuracy for CIN2+ and was highly specific for residual CIN2+ lesions The methylation assay is a promising triage tool in hrHPV+ women, or even an independent tool for cervical cancer screening. The methylation status in cervical cytology could also serve as a prognostic biomarker. Its role in detecting endometrial carcinomas is worthy of further exploration.

Tumor Markers and Their Diagnostic Significance in Ovarian Cancer

Ovarian cancer (OC) is characterized by silent progression and late-stage diagnosis. It is critical to detect and accurately diagnose the disease early to improve survival rates. Tumor markers have emerged as valuable tools in the diagnosis and management of OC, offering non-invasive and cost-effective options for screening, monitoring, and prognosis.

PURPOSE

This paper explores the diagnostic importance of various tumor markers including CA-125, CA15-3, CA 19-9, HE4,hCG, inhibin, AFP, and LDH, and their impact on disease monitoring and treatment response assessment.

METHODS

Article searches were performed on PubMed, Scopus, and Google Scholar. Keywords used for the searching process were "Ovarian cancer", "Cancer biomarkers", "Early detection", "Cancer diagnosis", "CA-125","CA 15-3","CA 19-9", "HE4","hCG", "inhibin", "AFP", "LDH", and others.

RESULTS

HE4, when combined with CA-125, shows improved sensitivity and specificity, particularly in early-stage detection. Additionally, hCG holds promise as a prognostic marker, aiding treatment response prediction and outcome assessment. Novel markers like microRNAs, DNA methylation patterns, and circulating tumor cells offer potential for enhanced diagnostic accuracy and personalized management. Integrating these markers into a comprehensive panel may improve sensitivity and specificity in ovarian cancer diagnosis. However, careful interpretation of tumor marker results is necessary, considering factors such as age, menopausal status, and comorbidities. Further research is needed to validate and refine diagnostic algorithms, optimizing the clinical significance of tumor markers in ovarian cancer management. In conclusion, tumor markers such as CA-125, CA15-3, CA 19-9, HE4, and hCG provide valuable insights into ovarian cancer diagnosis, monitoring, and prognosis, with the potential to enhance early detection.

Characterization of global research trends and prospects on platinum-resistant ovarian cancer: a bibliometric analysis

Background

In the last decades, growing attention has been focused on identifying effective therapeutic strategies in the orphan clinical setting of women with platinum-resistant ovarian cancer (PROC), generating thousands of original articles. However, the literature involving bibliometric analysis of PROC has not been published yet.

Objective

This study hopes to gain a better understanding of the hot spots and trends in PROC by conducting a bibliometric analysis, as well as identify potential new research directions.

Methods

We searched the Web of Science Core Collection (WOSCC) for PROC-related articles published between 1990 and 2022. CiteSpace 6.1.R2 and VOS viewer 1.6.18.0 were primarily utilized to evaluate the contribution and co-occurrence relationships of various countries and regions, institutes, and journals and to identify research hotspots and promising future trends in this research field.

Results

A total of 3,462 Web of Science publications were retrieved that were published in 671 academic journals by 1135 authors from 844 organizations in 75 countries and regions. The United States was the leading contributor in this field, and the University of Texas MD Anderson Cancer Center was the most productive institution. Gynecologic Oncology was the most productive journal, while the Journal of Clinical Oncology was the most cited and influential. Co-citation cluster labels revealed the characteristics of seven major clusters, including synthetic lethality, salvage treatment, human ovarian-carcinoma cell line, PARP inhibitor resistance, antitumor complexes, folate receptor, and targeting platinum-resistant disease. Keywords and references burst detection indicated that biomarkers, genetic and phenotypic changes, immunotherapy, and targeted therapy were the most recent and most significant aspects of PROC research.

Conclusion

This study conducted a comprehensive review of PROC research using bibliometric and visual techniques. Understanding the immunological landscape of PROC and identifying the population that can benefit from immunotherapy, especially in combination with other therapeutic options (such as chemotherapy and targeted therapy), will continue to be the focal point of research.

RASAL2 Deficiency Attenuates Hepatic Steatosis by Promoting Hepatic VLDL Secretion via the AKT/TET1/MTTP Axis

BACKGROUND AND AIMS

RAS protein activator like 2 (RASAL2) is a newly discovered metabolic regulator involved in energy homeostasis and adipogenesis. However, whether RASAL2 is involved in hepatic lipid metabolism remains undetermined. This study explored the function of RASAL2 and elucidated its potential mechanisms in nonalcoholic fatty liver disease (NAFLD).

METHODS

NAFLD models were established either by feeding mice a high-fat diet or by incubation of hepatocytes with 1 mM free fatty acids (oleic acid:palmitic acid=2:1). Pathological changes were observed by hematoxylin and eosin staining. Lipid accumulation was assessed by Oil Red O staining, BODIPY493/503 staining, and triglyceride quantification. The in vivo secretion rate of very low-density lipoprotein was determined by intravenous injection of tyloxapol. Gene regulation was analyzed by chromatin immunoprecipitation assays and hydroxymethylated DNA immunoprecipitation combined with real-time polymerase chain reaction.

RESULTS

RASAL2 deficiency ameliorated hepatic steatosis both in vivo and in vitro. Mechanistically, RASAL2 deficiency upregulated hepatic TET1 expression by activating the AKT signaling pathway and thereby promoted MTTP expression by DNA hydroxymethylation, leading to increased production and secretion of very low-density lipoprotein, which is the major carrier of triglycerides exported from the liver to distal tissues.

CONCLUSIONS

Our study reports the first evidence that RASAL2 deficiency ameliorates hepatic steatosis by regulating lipid metabolism through the AKT/TET1/MTTP axis. These findings will help understand the pathogenesis of NAFLD and highlight the potency of RASAL2 as a new molecular target for NAFLD.

Hepatic and serum branched-chain fatty acid profile in patients with nonalcoholic fatty liver disease: A case-control study

OBJECTIVE

Alterations in the hepatic lipidome are a crucial factor involved in the pathophysiology of nonalcoholic fatty liver disease (NAFLD). The aim of this study was to evaluate the serum and hepatic profile of branched-chain fatty acids (BCFAs) in patients with different stages of NAFLD.

METHODS

This was a case-control study performed in 27 patients without NAFLD, 49 patients with nonalcoholic fatty liver, and 17 patients with nonalcoholic steatohepatitis, defined by liver biopsies. Serum and hepatic levels of BCFAs were analyzed by gas chromatography-mass spectrometry. The hepatic expression of genes involved in the endogenous synthesis of BCFAs was analyzed by real-time quantitative polymerase chain reaction (RT-qPCR).

RESULTS

A significant increase in hepatic BCFAs was found in subjects with NAFLD compared with those without NAFLD; no differences were observed in serum BCFAs between study groups. Trimethyl BCFAs, iso-BCFAs, and anteiso-BCFAs were increased in subjects with NAFLD (either nonalcoholic fatty liver or nonalcoholic steatohepatitis) compared with those without NAFLD. Correlation analysis showed a relationship between hepatic BCFAs and the histopathological diagnosis of NAFLD, as well as other histological and biochemical parameters related to this disease. Gene expression analysis in liver showed that the mRNA levels of BCAT1, BCAT2, and BCKDHA were upregulated in patients with NAFLD.

CONCLUSIONS

These results suggest that the increased production of liver BCFAs might be related to NAFLD development and progression.

A novel subtype to predict prognosis and treatment response with DNA driver methylation-transcription in ovarian cancer

Aims: To identify a novel subtype with DNA driver methylation-transcriptomic multiomics and predict prognosis and therapy response in serous ovarian cancer (SOC). Methods: SOC cohorts with both mRNA and methylation were collected, and DNA driver methylation (DNAme) was identified with the MithSig method. A novel prognostic subtype was developed by integrating the information on DNAme and prognosis-regulated DNAme-associated mRNA by similarity network fusion. Results: 43 overlapped DNAme were identified in three independent cohorts. SOC patients were categorized into three distinct subtypes by integrated multiomics. There were differences in prognosis, tumor microenvironment and response to therapy among the subtypes. Conclusion: This study identified 43 DNAmes and proposes a novel subtype toward personalized chemotherapy and immunotherapy for SOC patients based on multiomics.

Integrative multi-omic analysis identifies genetically influenced DNA methylation biomarkers for breast and prostate cancers

Aberrant DNA methylation has emerged as a hallmark in several cancers and contributes to risk, oncogenesis, progression, and prognosis. In this study, we performed imputation-based and conventional methylome-wide association analyses for breast cancer (BrCa) and prostate cancer (PrCa). The imputation-based approach identified DNA methylation at cytosine-phosphate-guanine sites (CpGs) associated with BrCa and PrCa risk utilising genome-wide association summary statistics (N_BrCa = 228,951, N_PrCa = 140,254) and prebuilt methylation prediction models, while the conventional approach identified CpG associations utilising TCGA and GEO experimental methylation data (N_BrCa = 621, N_PrCa = 241). Enrichment analysis of the association results implicated 77 and 81 genetically influenced CpGs for BrCa and PrCa, respectively. Furthermore, analysis of differential gene expression around these CpGs suggests a genome-epigenome-transcriptome mechanistic relationship. Conditional analyses identified multiple independent secondary SNP associations (P_cond < 0.05) around 28 BrCa and 22 PrCa CpGs. Cross-cancer analysis identified eight common CpGs, including a strong therapeutic target in SREBF1 (17p11.2)—a key player in lipid metabolism. These findings highlight the utility of integrative analysis of multi-omic cancer data to identify robust biomarkers and understand their regulatory effects on cancer risk.

Methylome-wide association studies identify genetically-influenced CpGs associated with breast and prostate cancer risk and (epi)genome-transcriptome mechanistic relationships, with lipid metabolism genes implicated as potential therapeutic targets.

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.

Identification of Prognostic Biomarkers for Bladder Cancer Based on DNA Methylation Profile

Background: DNA methylation is an important epigenetic modification, which plays an important role in regulating gene expression at the transcriptional level. In tumor research, it has been found that the change of DNA methylation leads to the abnormality of gene structure and function, which can provide early warning for tumorigenesis. Our study aims to explore the relationship between the occurrence and development of tumor and the level of DNA methylation. Moreover, this study will provide a set of prognostic biomarkers, which can more accurately predict the survival and health of patients after treatment.

Methods: Datasets of bladder cancer patients and control samples were collected from TCGA database, differential analysis was employed to obtain genes with differential DNA methylation levels between tumor samples and normal samples. Then the protein-protein interaction network was constructed, and the potential tumor markers were further obtained by extracting Hub genes from subnet. Cox proportional hazard regression model and survival analysis were used to construct the prognostic model and screen out the prognostic markers of bladder cancer, so as to provide reference for tumor prognosis monitoring and improvement of treatment plan.

Results: In this study, we found that DNA methylation was indeed related with the occurrence of bladder cancer. Genes with differential DNA methylation could serve as potential biomarkers for bladder cancer. Through univariate and multivariate Cox proportional hazard regression analysis, we concluded that FASLG and PRKCZ can be used as prognostic biomarkers for bladder cancer. Patients can be classified into high or low risk group by using this two-gene prognostic model. By detecting the methylation status of these genes, we can evaluate the survival of patients.

Conclusion: The analysis in our study indicates that the methylation status of tumor-related genes can be used as prognostic biomarkers of bladder cancer.

Integrating Genome and Methylome Data to Identify Candidate DNA Methylation Biomarkers for Pancreatic Cancer Risk

BACKGROUND

The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.

METHODS

Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.

RESULTS

We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.

CONCLUSIONS

We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.

IMPACT

A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

The blood transcriptome prior to ovarian cancer diagnosis: A case-control study in the NOWAC postgenome cohort

Epithelial ovarian cancer (EOC) has a 5-year relative survival of 50%, partly because markers of early-stage disease are not available in current clinical diagnostics. The aim of the present study was to investigate whether EOC is associated with transcriptional profiles in blood collected up to 7 years before diagnosis. For this, we used RNA-stabilized whole blood, which contains circulating immune cells, from a sample of EOC cases from the population-based Norwegian Women and Cancer (NOWAC) postgenome cohort. We explored case-control differences in gene expression in all EOC (66 case-control pairs), as well as associations between gene expression and metastatic EOC (56 pairs), serous EOC (45 pairs, 44 of which were metastatic), and interval from blood sample collection to diagnosis (≤3 or >3 years; 34 and 31 pairs, respectively). Lastly, we assessed differential expression of genes associated with EOC in published functional genomics studies that used blood samples collected from newly diagnosed women. After adjustment for multiple testing, this nested case-control study revealed no significant case-control differences in gene expression in all EOC (false discovery rate q>0.96). With the exception of a few probes, the log₂ fold change values obtained in gene-wise linear models were below ±0.2. P-values were lowest in analyses of metastatic EOC (80% of which were serous EOC). No common transcriptional profile was indicated by interval to diagnosis; when comparing the 100 genes with the lowest p-values in gene-wise tests in samples collected ≤3 and >3 years before EOC diagnosis, no overlap in these genes was observed. Among 86 genes linked to ovarian cancer in previous publications, our data contained expression values for 42, and of these, tests of LIME1, GPR162, STAB1, and SKAP1, resulted in unadjusted p<0.05. Although limited by sample size, our findings indicated less variation in blood gene expression between women with similar tumor characteristics.

An integrative multiomics analysis identifies putative causal genes for COVID-19 severity

Purpose

It is critical to identify putative causal targets for SARS coronavirus 2, which may guide drug repurposing options to reduce the public health burden of COVID-19.

Methods

We applied complementary methods and multiphased design to pinpoint the most likely causal genes for COVID-19 severity. First, we applied cross-methylome omnibus (CMO) test and leveraged data from the COVID-19 Host Genetics Initiative (HGI) comparing 9,986 hospitalized COVID-19 patients and 1,877,672 population controls. Second, we evaluated associations using the complementary S-PrediXcan method and leveraging blood and lung tissue gene expression prediction models. Third, we assessed associations of the identified genes with another COVID-19 phenotype, comparing very severe respiratory confirmed COVID versus population controls. Finally, we applied a fine-mapping method, fine-mapping of gene sets (FOGS), to prioritize putative causal genes.

Results

Through analyses of the COVID-19 HGI using complementary CMO and S-PrediXcan methods along with fine-mapping, XCR1, CCR2, SACM1L, OAS3, NSF, WNT3, NAPSA, and IFNAR2 are identified as putative causal genes for COVID-19 severity.

Conclusion

We identified eight genes at five genomic loci as putative causal genes for COVID-19 severity.

Prostate cancer risk variants of the HOXB genetic locus

The G84E germline mutation of HOXB13 predisposes to prostate cancer and is clinically tested for familial cancer care. We investigated the HOXB locus to define a potentially broader contribution to prostate cancer heritability. We sought HOXB locus germline variants altering prostate cancer risk in three European-ancestry case-control study populations (combined 7812 cases and 5047 controls): the International Consortium for Prostate Cancer Genetics Study; the Nashville Familial Prostate Cancer Study; and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Multiple rare genetic variants had concordant and strong risk effects in these study populations and exceeded genome-wide significance. Independent risk signals were best detected by sentinel variants rs559612720 within SKAP1 (OR = 8.1, P = 2E-9) and rs138213197 (G84E) within HOXB13 (OR = 5.6, P = 2E-11), separated by 567 kb. Half of carriers inherited both risk alleles, while others inherited either alone. Under mutual adjustment, the variants separately carried 3.6- and 3.1-fold risk, respectively, while joint inheritance carried 11.3-fold risk. These risks were further accentuated among men meeting criteria for hereditary prostate cancer, and further still for those with early-onset or aggressive disease. Among hereditary prostate cancer cases diagnosed under age 60 and with aggressive disease, joint inheritance carried a risk of OR = 27.7 relative to controls, P = 2E-8. The HOXB sentinel variant pair more fully captured genetic risk for prostate cancer within the study populations than either variant alone.

Artificial Intelligence in Epigenetic Studies: Shedding Light on Rare Diseases

More than 7,000 rare diseases (RDs) exist worldwide, affecting approximately 350 million people, out of which only 5% have treatment. The development of novel genome sequencing techniques has accelerated the discovery and diagnosis in RDs. However, most patients remain undiagnosed. Epigenetics has emerged as a promise for diagnosis and therapies in common disorders (e.g., cancer) with several epimarkers and epidrugs already approved and used in clinical practice. Hence, it may also become an opportunity to uncover new disease mechanisms and therapeutic targets in RDs. In this “big data” age, the amount of information generated, collected, and managed in (bio)medicine is increasing, leading to the need for its rapid and efficient collection, analysis, and characterization. Artificial intelligence (AI), particularly deep learning, is already being successfully applied to analyze genomic information in basic research, diagnosis, and drug discovery and is gaining momentum in the epigenetic field. The application of deep learning to epigenomic studies in RDs could significantly boost discovery and therapy development. This review aims to collect and summarize the application of AI tools in the epigenomic field of RDs. The lower number of studies found, specific for RDs, indicate that this is a field open to expansion, following the results obtained for other more common disorders.

The Prognostic Value of DNA Methylation, Post-Translational Modifications and Correlated with Immune Infiltrates in Gynecologic Cancers

Background

To depict the prognostic landscape of gynecological cancers from the perspective of DNA methylation, alternative splicing (AS) and polyadenylation (APA) events and investigate their correlation with immune infiltrates.

Methods

Methylation and RNA-seq data and corresponding clinical information regarding gynecologic cancers were used to explore the relationships between changes in DNA methylation, AS and APA events and gynecologic cancer prognosis. QRT-PCR and multiple bioinformatics tools were employed to construct a gene interaction network and explore immune infiltrates.

Results

Only the mRNA levels of CIRBP and INPP5K were simultaneously significantly decreased in gynecologic cancers and negatively associated with overall survival, which verified by qrt-PCR. We also identified that CIRBP or INPP5K DNA methylation, AS and APA events are prognostic indicators of gynecologic cancers. The activation of T cells might be the main signaling pathway by which these genes modulate cancer progression. CIRBP/INPP5K expression is positively associated with immune infiltration and is a major risk factor of survival, especially among uterine corpus endometrial carcinoma (UCEC) patients.

Conclusion

According to these findings, the DNA methylation, AS and APA events of CIRBP and INPP5K may serve as important prognostic biomarkers and targets in gynecological cancers by modulating T cell infiltration.

Point-of-care DNA testing by automatically and sequentially performing extraction, amplification and identification in a closed-type cassette

Nucleic acid detection is important for clinical diagnostics; however, it is challenging to perform genetic testing at the point-of-care due to the tedious steps involved in DNA extraction and the risk of cross-contamination from amplicons. To achieve a fully-automated and contamination-free nucleic acid detection, we propose a closed-type cassette system which enables the following steps to be operated automatically and sequentially: sample preparation based on magnetic beads, target amplification using multiplex polymerase chain reaction, and colorimetric detection of amplicons using a serial invasive reaction coupled with the aggregation of gold nanoparticle probes. The cassette was designed to be round and closed, and 10 targets in a sample could be simultaneously detected by the naked eye or using a spectrophotometer in the system. In addition, a cassette-driven device was fabricated to transfer reagents between wells, to control the temperature of each reaction, and to sense the colour in the detection wells. The cassette system was sensitive enough to detect 10 genotypes at 5 single nucleotide polymorphism sites related to the anticoagulant's usage, by using a 0.5 μL blood sample. The accuracy of the system was evaluated by detecting 12 whole blood samples, and the results obtained were consistent with those obtained using pyrosequencing. The cassette is airtight and the whole system is fully automatic; the only manual operation is the addition of the sample to the cassette, performing point-of-care genetic testing in a sample-in/answer-out way.

DNA Methylation in Ovarian Cancer Susceptibility

Epigenetic alterations are somatically acquired over the lifetime and during neoplastic transformation but may also be inherited as widespread 'constitutional' alterations in normal tissues that can cause cancer predisposition. Epithelial ovarian cancer (EOC) has an established genetic susceptibility and mounting epidemiological evidence demonstrates that DNA methylation (DNAm) intermediates as well as independently contributes to risk. Targeted studies of known EOC susceptibility genes (CSGs) indicate rare, constitutional BRCA1 promoter methylation increases familial and sporadic EOC risk. Blood-based epigenome-wide association studies (EWAS) for EOC have detected a total of 2846 differentially methylated probes (DMPs) with 71 genes replicated across studies despite significant heterogeneity. While EWAS detect both symptomatic and etiologic DMPs, adjustments and analytic techniques may enrich risk associations, as evidenced by the detection of dysregulated methylation of BNC2-a known CSG identified by genome-wide associations studies (GWAS). Integrative genetic-epigenetic approaches have mapped methylation quantitative trait loci (meQTL) to EOC risk, revealing DNAm variations that are associated with nine GWAS loci and, further, one novel risk locus. Increasing efforts to mapping epigenome variation across populations and cell types will be key to decoding both the genomic and epigenomic causal pathways to EOC.

An integrative multi-omics network-based approach identifies key regulators for breast cancer

Although genome-wide association studies (GWASs) have successfully identified thousands of risk variants for human complex diseases, understanding the biological function and molecular mechanisms of the associated SNPs involved in complex diseases is challenging. Here we developed a framework named integrative multi-omics network-based approach (IMNA), aiming to identify potential key genes in regulatory networks by integrating molecular interactions across multiple biological scales, including GWAS signals, gene expression-based signatures, chromatin interactions and protein interactions from the network topology. We applied this approach to breast cancer, and prioritized key genes involved in regulatory networks. We also developed an abnormal gene expression score (AGES) signature based on the gene expression deviation of the top 20 rank-ordered genes in breast cancer. The AGES values are associated with genetic variants, tumor properties and patient survival outcomes. Among the top 20 genes, RNASEH2A was identified as a new candidate gene for breast cancer. Thus, our integrative network-based approach provides a genetic-driven framework to unveil tissue-specific interactions from multiple biological scales and reveal potential key regulatory genes for breast cancer. This approach can also be applied in other complex diseases such as ovarian cancer to unravel underlying mechanisms and help for developing therapeutic targets.

An integrative multi-omics analysis to identify candidate DNA methylation biomarkers related to prostate cancer risk

It remains elusive whether some of the associations identified in genome-wide association studies of prostate cancer (PrCa) may be due to regulatory effects of genetic variants on CpG sites, which may further influence expression of PrCa target genes. To search for CpG sites associated with PrCa risk, here we establish genetic models to predict methylation (N = 1,595) and conduct association analyses with PrCa risk (79,194 cases and 61,112 controls). We identify 759 CpG sites showing an association, including 15 located at novel loci. Among those 759 CpG sites, methylation of 42 is associated with expression of 28 adjacent genes. Among 22 genes, 18 show an association with PrCa risk. Overall, 25 CpG sites show consistent association directions for the methylation-gene expression-PrCa pathway. We identify DNA methylation biomarkers associated with PrCa, and our findings suggest that specific CpG sites may influence PrCa via regulating expression of candidate PrCa target genes.

Methylation in HOX Clusters and Its Applications in Cancer Therapy

HOX genes are commonly known for their role in embryonic development, defining the positional identity of most structures along the anterior–posterior axis. In postembryonic life, HOX gene aberrant expression can affect several processes involved in tumorigenesis such as proliferation, apoptosis, migration and invasion. Epigenetic modifications are implicated in gene expression deregulation, and it is accepted that methylation events affecting HOX gene expression play crucial roles in tumorigenesis. In fact, specific methylation profiles in the HOX gene sequence or in HOX-associated histones are recognized as potential biomarkers in several cancers, helping in the prediction of disease outcomes and adding information for decisions regarding the patient’s treatment. The methylation of some HOX genes can be associated with chemotherapy resistance, and its identification may suggest the use of other treatment options. The use of epigenetic drugs affecting generalized or specific DNA methylation profiles, an approach that now deserves much attention, seems likely to be a promising weapon in cancer therapy in the near future. In this review, we summarize these topics, focusing particularly on how the regulation of epigenetic processes may be used in cancer therapy.

Challenge-comet assay, a functional and genomic biomarker for precision risk assessment and disease prevention among exposed workers

Advancements in genomic technologies have ushered application of innovative changes into biomedical sciences and clinical medicine. Consequently, these changes have created enormous opportunities to implement precision population/occupational disease prevention and target-specific disease intervention (or personalized medicine). To capture the opportunities, however, it is necessary is to develop novel, especially genomic-based, biomarkers which can provide precise and individualized health risk assessment. In this review, development of the Challenge-comet assay is used as an example to demonstrate how assays need to be validated for its sensitivity, specificity, and functional and quantitative features, and how assays can be used to provide individualized health risk assessment for precision prevention and intervention. Other examples of genomic-based novel biomarkers will also be discussed. Furthermore, no biomarkers can be used alone therefore their integrated usage with other biomarkers and with personal data bases will be discussed.

EMP1 Promotes the Proliferation and Invasion of Ovarian Cancer Cells Through Activating the MAPK Pathway

Introduction

Epithelial membrane protein 1 (EMP1), a member of the EMP family, is overexpressed in a large number of tumors and is thought to be a cellular connexin on the cell membrane and is involved in proliferation, invasion, metastasis of tumor cells, and epithelial-mesenchymal transition (EMT). Nevertheless, its biomedical function in ovarian cancer is still unclear.

Methods

EMP1 was detected in ovarian cancer cell lines by whole transcriptome resequencing. The mRNA of EMP1 was examined by qRT-PCR. The relationship between expression of EMP1 and clinical classification, metastasis, and shortened survival time in ovarian cancer specimens was analysed by immunohistochemical (IHC). The mechanism of EMP1 enhanced proliferation and invasion of ovarian cancer cells was determined by siRNA interference, colony formation, migration and invasion experiments, and Western blot.

Results

EMP1 was up-regulated in ovarian cancer cell lines and ovarian cancer tissues in comparison with non-cancerous ovarian specimens. High expression of EMP1 in ovarian cancer specimens was obviously related to high clinical classification, metastasis, and shortened survival time. High expressed EMP1 facilitates cell proliferation, invasion and EMT in ovarian cancer cells. Over-expressed EMP1 increased the protein levels of RAS/RAF/MAPK/c-JUN.

Conclusion

Over-expressed EMP1 in ovarian cancer promotes tumor cell proliferation, invasion, and EMT by the MAPK signaling pathway.

Novel Epigenetic Biomarkers in Pregnancy-Related Disorders and Cancers

As the majority of cancers and gestational diseases are prognostically stage- and grade-dependent, the ultimate goal of ongoing studies in precision medicine is to provide early and timely diagnosis of such disorders. These studies have enabled the development of various new diagnostic biomarkers, such as free circulating nucleic acids, and detection of their epigenetic changes. Recently, extracellular vesicles including exosomes, microvesicles, oncosomes, and apoptotic bodies have been recognized as powerful diagnostic tools. Extracellular vesicles carry specific proteins, lipids, DNAs, mRNAs, and miRNAs of the cells that produced them, thus reflecting the function of these cells. It is believed that exosomes, in particular, may be the optimal biomarkers of pathological pregnancies and cancers, especially those that are frequently diagnosed at an advanced stage, such as ovarian cancer. In the present review, we survey and critically appraise novel epigenetic biomarkers related to free circulating nucleic acids and extracellular vesicles, focusing especially on their status in trophoblasts (pregnancy) and neoplastic cells (cancers).

Bioinformatics and functional analyses of key genes in smoking-associated lung adenocarcinoma

Smoking is one of the most important factors associated with the development of lung cancer. However, the signaling pathways and driver genes in smoking-associated lung adenocarcinoma remain unknown. The present study analyzed 433 samples of smoking-associated lung adenocarcinoma and 75 samples of non-smoking lung adenocarcinoma from the Cancer Genome Atlas database. Gene Ontology (GO) analysis was performed using the Database for Annotation, Visualization and Integrated Discovery and the ggplot2 R/Bioconductor package. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the R packages RSQLite and org.Hs.eg.db. Multivariate Cox regression analysis was performed to screen factors associated with patient survival. Kaplan-Meier and receiver operating characteristic curves were used to analyze the potential clinical significance of the identified biomarkers as molecular prognostic markers for the five-year overall survival time. A total of 373 differentially expressed genes (DEGs; |log2-fold change|≥2.0 and P<0.01) were identified, of which 71 were downregulated and 302 were upregulated. These DEGs were associated with 28 significant GO functions and 11 significant KEGG pathways (false discovery rate <0.05). Two hundred thirty-eight proteins were associated with the 373 differentially expressed genes, and a protein-protein interaction network was constructed. Multivariate regression analysis revealed that 7 mRNAs, cytochrome P450 family 17 subfamily A member 1, PKHD1 like 1, retinoid isomerohydrolase RPE65, neurotensin receptor 1, fetuin B, insulin-like growth factor binding protein 1 and glucose-6-phosphatase catalytic subunit, significantly distinguished between non-smoking and smoking-associated adenocarcinomas. Kaplan-Meier analysis demonstrated that patients in the 7 mRNAs-high-risk group had a significantly worse prognosis than those of the low-risk group. The data obtained in the current study suggested that these genes may serve as potential novel prognostic biomarkers of smoking-associated lung adenocarcinoma.

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk

Several blood protein biomarkers have been associated with prostate cancer risk. However, most studies assessed only a small number of biomarkers and/or included a small sample size. To identify novel protein biomarkers of prostate cancer risk, we studied 79,194 cases and 61,112 controls of European ancestry, included in the PRACTICAL/ELLIPSE consortia, using genetic instruments of protein quantitative trait loci for 1,478 plasma proteins. A total of 31 proteins were associated with prostate cancer risk including proteins encoded by GSTP1, whose methylation level was shown previously to be associated with prostate cancer risk, and MSMB, SPINT2, IGF2R, and CTSS, which were previously implicated as potential target genes of prostate cancer risk variants identified in genome-wide association studies. A total of 18 proteins inversely correlated and 13 positively correlated with prostate cancer risk. For 28 of the identified proteins, gene somatic changes of short indels, splice site, nonsense, or missense mutations were detected in patients with prostate cancer in The Cancer Genome Atlas. Pathway enrichment analysis showed that relevant genes were significantly enriched in cancer-related pathways. In conclusion, this study identifies 31 candidates of protein biomarkers for prostate cancer risk and provides new insights into the biology and genetics of prostate tumorigenesis. SIGNIFICANCE: Integration of genomics and proteomics data identifies biomarkers associated with prostate cancer risk.

Doxycycline, salinomycin, monensin and ivermectin repositioned as cancer drugs

Chemotherapy is one of the standard methods for the treatment of malignant tumors. It aims to cause lethal damage to cellular structures, mainly DNA. Noteworthy, in recent years discoveries of novel anticancer agents from well-known antibiotics have opened up new treatment pathways for several cancer diseases. The aim of this review article is to describe new applications for the following antibiotics: doxycycline (DOX), salinomycin (SAL), monensin (MON) and ivermectin (IVR) as they are known to show anti-tumor activity, but have not yet been introduced into standard oncological therapy. To date, these agents have been used for the treatment of a broad-spectrum of bacterial and parasitic infectious diseases and are widely available, which is why they were selected. The data presented here clearly show that the antibiotics mentioned above should be recognised in the near future as novel agents able to eradicate cancer cells and cancer stem cells (CSCs) across several cancer types.