DNA Methylation Identifies Loci Distinguishing Hereditary Nonpolyposis Colorectal Cancer Without Germ-Line MLH1/MSH2 Mutation from Sporadic Colorectal Cancer

Novel methylated DNA markers accurately discriminate Lynch syndrome associated colorectal neoplasia

Aim:

Acquired molecular changes in Lynch syndrome (LS) colorectal tumors have been largely unstudied. We identified methylated DNA markers (MDMs) for discrimination of colorectal neoplasia in LS and determined if these MDMs were comparably discriminant in sporadic patients.

Patients & methods:

For LS discovery, we evaluated DNA from 53 colorectal case and control tissues using next generation sequencing. For validation, blinded methylation-specific PCR assays to the selected MDMs were performed on 197 cases and controls.

Results:

OPLAH was the most discriminant MDM with areas under the receiver operating characteristic curve ≥0.97 for colorectal neoplasia in LS and sporadic tissues. ALKBH5, was uniquely hypermethylated in LS neoplasms.

Conclusion:

Highly discriminant MDMs for colorectal neoplasia in LS were identified with potential use in screening and surveillance.

A FITM1-Related Methylation Signature Predicts the Prognosis of Patients With Non-Viral Hepatocellular Carcinoma

Although great progress has been made in treatment against hepatitis virus infection, the prognosis of hepatocellular carcinoma (HCC) remains unsatisfied. Therefore, there is an unmet need to explore biomarkers or prognostic models for monitoring non-viral hepatocellular carcinoma. Accumulating evidence indicates that DNA methylation participates in carcinogenesis of malignancies. In the present study, we analyzed 101 non-viral HCC patients from TCGA database to figure out methylation-driven genes (MDGs) that might get involved in non-viral HCC pathogenesis using MethyMix algorithm. Then we picked out 8 key genes out of 137 MDGs that could affect the overall survival (OS) of both methylation and expression level. Using PCA, Uni-variate, Multi-variate, and LASSO cox regression analyses, we confirmed the potential prognostic value of these eight epigenetic genes. Ultimately, combined with immunohistochemistry (IHC), ROC, OS, and GSEA analyses, fat storage-inducing transmembrane protein1 (FITM1) was identified as a novel tumor suppressor gene in non-viral HCC and an applicable FITM1-methylation-based signature was built in a training set and validated in a testing set. Briefly, our work provides several potential biomarkers, especially FITM1, as well as a new method for disease surveillance and treatment strategy development.

Hereditary Nonpolyposis Colorectal Cancer and Cancer Syndromes: Recent Basic and Clinical Discoveries

Approximately one-third of individuals diagnosed with colorectal cancer have a family history of cancer, suggesting that CRCs may result from a heritable component. Despite the availability of current gene-identification techniques, only 5% of all CRCs emerge from well-identifiable inherited causes for predisposition, including polyposis and nonpolyposis syndromes. Hereditary nonpolyposis colorectal cancer represents a large proportion of cases, and robustly affected patients are at increased risk for early onset, synchronous, and metachronous colorectal malignancies and extracolonic malignancies. HNPCC encompasses several cancer syndromes, such as Lynch syndrome, Lynch-like syndrome, and familial colorectal cancer type X, which have remarkable clinical presentations and overlapping genetic profiles that make clinical diagnosis a challenging task. Therefore, distinguishing between the HNPCC disorders is crucial for physicians as an approach to tailor different recommendations for patients and their at-risk family members according to the risks for colonic and extracolonic cancer associated with each syndrome. Identification of these potential patients through epidemiological characteristics and new genetic testing can estimate the individual risk, which informs appropriate cancer screening, surveillance, and/or treatment strategies. In the past three years, many appealing and important advances have been made in our understanding of the relationship between HNPCC and CRC-associated syndromes. The knowledge from the genetic profile of cancer syndromes and unique genotype-phenotype profiles in the different syndromes has changed our cognition. Therefore, this review presents and discusses HNPCC and several common nonpolyposis syndromes with respect to molecular phenotype, histopathologic features, and clinical presentation.

Targeted bisulfite sequencing identified a panel of DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC)

Background

DNA methylation has been implicated as a promising biomarker for precise cancer diagnosis. However, limited DNA methylation-based biomarkers have been described in esophageal squamous cell carcinoma (ESCC).

Methods

A high-throughput DNA methylation dataset (100 samples) of ESCC from The Cancer Genome Atlas (TCGA) project was analyzed and validated along with another independent dataset (12 samples) from the Gene Expression Omnibus (GEO) database. The methylation status of peripheral blood mononuclear cells and peripheral blood leukocytes from healthy controls was also utilized for biomarker selection. The candidate CpG sites as well as their adjacent regions were further validated in 94 pairs of ESCC tumor and adjacent normal tissues from the Chinese Han population using the targeted bisulfite sequencing method. Logistic regression and several machine learning methods were applied for evaluation of the diagnostic ability of our panel.

Results

In the discovery stage, five hyper-methylated CpG sites were selected as candidate biomarkers for further analysis as shown below: cg15830431, P = 2.20 × 10⁻⁴; cg19396867, P = 3.60 × 10⁻⁴; cg20655070, P = 3.60 × 10⁻⁴; cg26671652, P = 5.77 × 10⁻⁴; and cg27062795, P = 3.60 × 10⁻⁴. In the validation stage, the methylation status of both the five CpG sites and their adjacent genomic regions were tested. The diagnostic model based on the combination of these five genomic regions yielded a robust performance (sensitivity = 0.75, specificity = 0.88, AUC = 0.85). Eight statistical models along with five-fold cross-validation were further applied, in which the SVM model reached the best accuracy in both training and test dataset (accuracy = 0.82 and 0.80, respectively). In addition, subgroup analyses revealed a significant difference in diagnostic performance between the alcohol use and non-alcohol use subgroups.

Conclusions

Methylation profiles of the five genomic regions covering cg15830431 (STK3), cg19396867, cg20655070, cg26671652 (ZNF418), and cg27062795 (ZNF542) can be used for effective methylation-based testing for ESCC diagnosis.

Electronic supplementary material

The online version of this article (10.1186/s13148-017-0430-7) contains supplementary material, which is available to authorized users.