DNA methylation marker to estimate the breast cancer cell fraction in DNA samples

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic β-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature's applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

DNA methylation marker to estimate ovarian cancer cell fraction

Evaluation of a cancer cell fraction is important for accurate molecular analysis, and pathological analysis is the gold standard for evaluation. Despite the potential convenience, no established molecular markers for evaluation are available. In this study, we aimed to identify ovarian cancer cell fraction markers using DNA methylation highly specific to ovarian cancer cells. Using genome-wide DNA methylation data, we screened candidate marker genes methylated in 30 ovarian cancer FFPE samples and 12 high-grade serous ovarian cancer cell lines, and unmethylated in two female leucocytes and two normal fallopian epithelial cell samples. Methylation levels of two genes, SIM1, and ZNF154, showed high correlation with pathological cancer cell fractions among the 30 ovarian cancer FFPE samples (R = 0.61 for SIM1, 0.71 for ZNF154). For cost-effective analysis of FFPE samples, pyrosequencing primers were designed, and successfully established for SIM1 and ZNF154. Correlation between a pathological cancer cell fraction and methylation levels obtained by pyrosequencing was confirmed to be high (R = 0.53 for SIM1, 0.64 for ZNF154). Finally, an independent validation cohort of 29 ovarian cancer FFPE samples was analyzed. ZNF154 methylation showed a high correlation with the pathological cancer cell fraction (R = 0.77, P < 0.0001). Therefore, the ZNF154 methylation level was considered to be useful for the estimation of ovarian cancer cell fraction, and is expected to help accurate molecular analysis.

The Effects of Exercise Duration and Intensity on Breast Cancer-Related DNA Methylation: A Randomized Controlled Trial

Emerging research suggests that one mechanism through which physical activity may decrease cancer risk is through its influence on the methylation of genes associated with cancer. The purpose of the current study was to prospectively test, using a rigorous experimental design, whether aerobic exercise affects DNA methylation in genes associated with breast cancer, as well as whether quantity of exercise completed affects change in DNA methylation in a dose-response manner. 276 women (M age = 37.25, SD = 4.64) were recruited from the Denver metro area for a randomized controlled trial in which participants were assigned to a supervised aerobic exercise program varying in a fully crossed design by intensity (55-65% versus 75-85% of VO2max) and duration (40 versus 20 min per session). DNA methylation was assessed via blood samples provided at baseline, after completing a 16-week supervised exercise intervention, and six months after the intervention. 137 participants completed the intervention, and 81 had viable pre-post methylation data. Contrary to our hypotheses, total exercise volume completed in kcal/kg/week was not associated with methylation from baseline to post-intervention for any of the genes of interest. An increase in VO2max over the course of the intervention, however, was associated with decreased post-intervention methylation of BRCA1, p = 0.01. Higher levels of self-reported exercise during the follow-up period were associated with lower levels of GALNT9 methylation at the six-month follow-up. This study provides hypothesis-generating evidence that increased exercise behavior and or increased fitness might affect methylation of some genes associated with breast cancer to reduce risk.

Screening and identification of Theileria annulata subtelomere-encoded variable secreted protein-950454 (SVSP454) interacting proteins from bovine B cells

BACKGROUND

Theileria annulata is a protozoan parasite that can infect and transform bovine B cells, macrophages, and dendritic cells. The mechanism of the transformation is still not well understood, and some parasite molecules have been identified, which contribute to cell proliferation by regulating host signaling pathways. Subtelomeric variable secreted proteins (SVSPs) of Theileria might affect the host cell phenotype, but its function is still not clear. Therefore, in the present study, we explored the interactions of SVSP454 with host cell proteins to investigate the molecular mechanism of T. annulata interaction with host cells.

METHODS

The transcription level of an SVSP protein from T. annulata, SVSP454, was analyzed between different life stages and transformed cell passages using qRT-PCR. Then, SVSP454 was used as a bait to screen its interacting proteins from the bovine B cell cDNA library using a yeast two-hybrid (Y2H) system. The potential interacting proteins of host cells with SVSP454 were further identified by using a coimmunoprecipitation (Co-IP) and bimolecular fluorescence complementation (BiFC) assays.

RESULTS

SVSP454 was transcribed in all three life stages of T. annulata but had the highest transcription during the schizont stage. However, the transcription level of SVSP454 continuously decreased as the cultures passaged. Two proteins, Bos Taurus coiled-coil domain 181 (CCDC181) and Bos Taurus mitochondrial ribosomal protein L30 (MRPL30), were screened. The proteins CCDC181 and MRPL30 of the host were further identified to directly interact with SVSP454.

CONCLUSION

In the present study, SVSP454 was used as a bait plasmid, and its prey proteins CCDC181 and MRPL30 were screened out by using a Y2H system. Then, we demonstrated that SVSP454 directly interacted with both CCDC181 and MRPL30 by Co-IP and BiFC assays. Therefore, we speculate that SVSP454-CCDC181/SVSP454MRPL30 is an interacting axis that regulates the microtubule network and translation process of the host by some vital signaling molecules. Identification of the interaction of SVSP454 with CCDC181 and MRPL30 will help illustrate the transformation mechanisms induced by T. annulata.

Automatic Detection of the Circulating Cell-Free Methylated DNA Pattern of GCM2, ITPRIPL1 and CCDC181 for Detection of Early Breast Cancer and Surgical Treatment Response

The early detection of cancer can reduce cancer-related mortality. There is no clinically useful noninvasive biomarker for early detection of breast cancer. The aim of this study was to develop accurate and precise early detection biomarkers and a dynamic monitoring system following treatment. We analyzed a genome-wide methylation array in Taiwanese and The Cancer Genome Atlas (TCGA) breast cancer (BC) patients. Most breast cancer-specific circulating methylated CCDC181, GCM2 and ITPRIPL1 biomarkers were found in the plasma. An automatic analysis process of methylated ccfDNA was established. A combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was performed in R using Recursive Partitioning and Regression Trees to establish a new prediction model. Combined analysis of CCDC181, GCM2 and ITPRIPL1 (CGIm) was found to have a sensitivity level of 97% and an area under the curve (AUC) of 0.955 in the training set, and a sensitivity level of 100% and an AUC of 0.961 in the test set. The circulating methylated CCDC181, GCM2 and ITPRIPL1 was also significantly decreased after surgery (all p < 0.001). The aberrant methylation patterns of the CCDC181, GCM2 and ITPRIPL1 genes means that they are potential biomarkers for the detection of early BC and can be combined with breast imaging data to achieve higher accuracy, sensitivity and specificity, facilitating breast cancer detection. They may also be applied to monitor the surgical treatment response.

ARHI overexpression inhibits proliferation and invasion and promotes apoptosis of gastric carcinoma MKN28 cells

BACKGROUND

ARHI has been proved to be associated with tumorigenesis and progression. However, it is not clear whether ARHI gene overexpression can inhibit the proliferation of gastric cancer (GC). In this study, we investigated the effect of ARHI gene overexpression on cell proliferation, invasion, and apoptosis in GC cell line MKN28.

AIM

To investigate the effect of ARHI overexpression on the proliferation, invasion, and apoptosis of gastric carcinoma MKN28 cells and to explore the possible mechanisms involved.

METHODS

The pcDNA 3.1-ARHI plasmid was constructed and used to transfect MKN28 cells. Meanwhile, a blank control group and a negative control mock group were set. Cell proliferation was detected by MTT assay. Cell scratch wound assay was used to detect the ability of cell migration. Transwell method was used to detect cell invasion ability. Flow cytometry was used to detect cell apoptosis. Western blot was used for detection of related protein expression.

RESULTS

Compared with blank control MKN28 cells (1.257% ± 0.006%), the proliferation rates at 48 h after transfection in the mock group was comparable (1.257% ± 0.006% vs 1.163% ± 0.003%, P > 0.05), while that of the ARHI overexpression group was significantly decreased (1.257% ± 0.006% vs 0.826% ± 0.005%, P < 0.05); the migration ability in the mock group was not significantly changed (19.918% ± 0.233% vs 18.295% ± 0.534%, P > 0.05), while that of the ARHI overexpression group was significantly decreased (19.918% ± 0.233% vs 4.299% ± 1.572 %, P < 0.05); the invasion ability in the mock group was not significantly changed (234 ± 3.61 vs 235 ± 4.51, P > 0.05), while that of the ARHI overexpression group was significantly decreased (234 ± 3.61 vs 93.3 ± 2.08, P < 0.05); the total apoptosis rate in the mock group was not significantly changed (3.513% ± 0.015% vs 3.597% ± 0.25%, P > 0.05), while that of the ARHI overexpression group was significantly increased (3.513% ± 0.015% vs 14.133% ± 0.032%, P < 0.05). Western blot results showed that, compared with blank control MKN28 cells, the relative expression of ARHI protein (1.037 ± 0.003), vascular endothelial growth factor (VEGF) (1.026 ± 0.008), B-cell lymphoma-2 (Bcl-2) (1.014 ± 0.010), protein kinase B (AKT) (1.001 ± 0.005), and p-AKT protein (0.977 ± 0.003) was not significantly changed (P > 0.05), while the expression of ARHI protein (2.088 ± 0.007) was significantly up-regulated (P < 0.05), that of VEGF protein (0.456 ± 0.004), Bcl-2 protein (0.468 ± 0.005), and p-AKT protein (0.502 ± 0.001) was significantly down-regulated (P < 0.05), and that of AKT protein was not significantly changed (P > 0.05).

CONCLUSION

Excessive expression of ARHI gene can inhibit the proliferation of MKN28 cells and promote their apoptosis, which may be related to the reduction of VEGF and p-AKT protein expression.

Combined Analysis of the Aberrant Epigenetic Alteration of Pancreatic Ductal Adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most fatal malignancies due to its high morbidity and mortality. DNA methylation exerts a vital part in the development of PDAC. However, a mechanistic role of mutual interactions between DNA methylation and mRNA as epigenetic regulators on transcriptomic alterations and its correlation with clinical outcomes such as survival have remained largely uncovered in cancer. Therefore, elucidation of aberrant epigenetic alteration in the development of PDAC is an urgent problem to be solved. In this work, we conduct an integrative epigenetic analysis of PDAC to identify aberrant DNA methylation-driven cancer genes during the occurrence of cancer.

METHODS

DNA methylation matrix and mRNA profile were obtained from the TCGA database. The integration of methylation and gene expression datasets was analyzed using an R package MethylMix. The genes with hypomethylation/hypermethylation were further validated in the Kaplan-Meier analysis. The correlation analysis of gene expression and aberrant DNA methylation was also conducted. We performed a pathway analysis on aberrant DNG methylation genes identified by MethylMix criteria using ConsensusPathDB.

RESULTS

188 patients with both methylation data and mRNA data were considered eligible. A mixture model was constructed, and differential methylation genes in normal and tumor groups using the Wilcoxon rank test was performed. With the inclusion criteria, 95 differential methylation genes were detected. Among these genes, 74 hypermethylation and 21 hypomethylation genes were found. The pathway analysis revealed an increase in hypermethylation of genes involved in ATP-sensitive potassium channels, Robo4, and VEGF signaling pathways crosstalk, and generic transcription pathway.

CONCLUSION

Integrated analysis of the aberrant epigenetic alteration in pancreatic ductal adenocarcinoma indicated that differentially methylated genes could play a vital role in the occurrence of PDAC by bioinformatics analysis. The present work can help clinicians to elaborate on the function of differentially methylated expressed genes and pathways in PDAC. CDO1, GJD2, ID4, NOL4, PAX6, TRIM58, and ZNF382 might act as aberrantly DNA-methylated biomarkers for early screening and therapy of PDAC in the future.