Genome-wide screening of genes regulated by DNA methylation in colon cancer development

Differential gene expression analysis supports dysregulation of mitochondrial activity as a new perspective for glioblastoma's aggressiveness

Brain cancer is considered one of the most aggressive and lethal types of cancer, including primary tumors, being subdivided into milder forms such as low-grade gliomas and glioblastoma, considered the most aggressive form with higher invasion. Among the hallmarks of glioblastoma, the deregulation of mitochondrial metabolism has not yet been fully elucidated. Therefore, the search for mitochondrial biomarkers that can be used as indicators of the progression of this type of cancer is necessary. The aim of this study was to investigate the difference in gene expression between astrocytoma-type gliomas and glioblastomas, and how genes involved in mitochondrial metabolism can influence the proliferative cascade and be associated with tumor invasion. From the differential analysis of glioblastoma expression when compared to the milder form, 11 differentially expressed genes (DEGs) were found in our study, six of which were upregulated (ATP5MGL, C15orf48, MCUB, TERT, AGXT and CYP27B1) and four downregulated (SLC2A4, GK2, SLC25A48, ETNPPL and HMGCS2). To validate the findings, we used other independent bulk RNA-seq datasets and evaluated the number of normalized counts of the DEGs founded. Among these genes, we highlight that none of them had been reported in glioblastoma until this research, and we suggest these genes as possible biomarkers to be further explored, since they are associated with essential pathways for the tumor, such as glucose metabolization, gluconeogenesis, calcium and vitamin D metabolism, tumor progression and activation of the invasion cascade.

Revelation of comprehensive cell profiling of primary and metastatic tumour ecosystems in oral squamous cell carcinoma by single-cell transcriptomic analysis

Background: The analysis of single-cell transcriptome profiling of tumour tissue isolates helps to identify heterogeneous tumour cells, neighbouring stromal cells and immune cells. Local metastasis of lymph nodes is the most dominant and influential biological behaviors of oral squamous cell carcinoma (OSCC) in terms of treatment prognosis. Understanding metastasis initiation and progression is important for the discovery of new treatments for OSCC and prediction of clinical responses to immunotherapy. However, the identity of metastasis-initiating cells in human OSCC remains elusive, and whether metastases are hierarchically organized is unknown. Therefore, this study was conducted to understand the cellular origins and gene expression signature of OSCC at the single-cell level. Methods: Single-cell RNA sequencing (scRNA-seq) was used to analyze cells from tissue of para-carcinoma (PCA: adjacent normal tissue not less than 2 cm from the tumour), carcinoma (CA), lymph node metastasis (LNM) from patients with OSCC and PCA and CA tissue from patients with second primary OSCC (SPOSCC) after radiotherapy of nasopharyngeal carcinoma (NPC). The cell types and their underlying functions were classified. The comparisons were then conducted between the homology and heterogeneity from cell types and both conservative and heterogeneous aspects of evolution were identified. Immunohistochemistry was performed to verify the makers of cell clusters and the expression level of novel genes. Results: A single-cell transcriptomic map of OSCC was created, including 16 clusters of PCA cells, 17 clusters of CA cells, 14 clusters of left LNM cells, and 14 clusters of right LNM cells. We also discovered two novel types of cells including CD1C-CD141-dendritic cells and CD1C+_B dendritic cells. Most of the non-cancer cells are immune cells, with two distinct clusters of T lymphocytes, B lymphocytes, CD1C-CD141-dendritic cells+ and CD1C+_B dendritic cells. We also classified cells into 15 clusters for SPOSCC after radiotherapy of NPC. Determining the upregulated expression levels of IL1RN and C15orf48 as novel markers using immunohistochemistry facilitated the correct classification of OSCC including SPOSCC after radiotherapy of NPC and the prediction of their prognosis. Conclusions: The findings provided an unprecedented and valuable view of the functional states and heterogeneity of cell populations in LNM of OSCC and SPOSCC after radiotherapy of NPC at single-cell genomic resolution. Moreover, this transcriptomic map discovered new cell types in mouth, and novel tumour cell-specific markers/oncogene.

Deoxycholic acid inducing chronic atrophic gastritis with colonic mucosal lesion correlated to mucosal immune dysfunction in rats

The present study aimed to explore the underlying mechanism of bile reflux-inducing chronic atrophic gastritis (CAG) with colonic mucosal lesion. The rat model of CAG with colonic mucosal lesion was induced by free-drinking 20 mmol/L sodium deoxycholate to simulate bile reflux and 2% cold sodium salicylate for 12 weeks. In comparison to the control group, the model rats had increased abundances of Bacteroidetes and Firmicutes but had decreased abundances of Proteobacteria and Fusobacterium. Several gut bacteria with bile acids transformation ability were enriched in the model group, such as Blautia, Phascolarctobacter, and Enterococcus. The cytotoxic deoxycholic acid and lithocholic acid were significantly increased in the model group. Transcriptome analysis of colonic tissues presented that the down-regulated genes enriched in T cell receptor signaling pathway, antigen processing and presentation, Th17 cell differentiation, Th1 and Th2 cell differentiation, and intestinal immune network for IgA production in the model group. These results suggest that bile reflux-inducing CAG with colonic mucosal lesion accompanied by gut dysbacteriosis, mucosal immunocompromise, and increased gene expressions related to repair of intestinal mucosal injury.

Early results of the integrative epigenomic-transcriptomic landscape of colorectal adenoma and cancer

BACKGROUND

Aberrant methylation is common during the initiation and progression of colorectal cancer (CRC), and detecting these changes that occur during early adenoma (ADE) formation and CRC progression has clinical value.

AIM

To identify potential DNA methylation markers specific to ADE and CRC.

METHODS

Here, we performed SeqCap targeted bisulfite sequencing and RNA-seq analysis of colorectal ADE and CRC samples to profile the epigenomic-transcriptomic landscape.

RESULTS

Comparing 22 CRC and 25 ADE samples, global methylation was higher in the former, but both showed similar methylation patterns regarding differentially methylated gene positions, chromatin signatures, and repeated elements. High-grade CRC tended to exhibit elevated methylation levels in gene promoter regions compared to those in low-grade CRC. Combined with RNA-seq gene expression data, we identified 14 methylation-regulated differentially expressed genes, of which only AGTR1 and NECAB1 methylation had prognostic significance.

CONCLUSION

Our results suggest that genome-wide alterations in DNA methylation occur during the early stages of CRC and demonstrate the methylation signatures associated with colorectal ADEs and CRC, suggesting prognostic biomarkers for CRC.

Role of epigenetics and the transcription factor Sp1 in the expression of the D prostanoid receptor 1 in human cartilage

D prostanoid receptor 1 (DP1), a prostaglandin D2 receptor, plays a central role in the modulation of inflammation and cartilage metabolism. We have previously shown that activation of DP1 signaling downregulated catabolic responses in cultured chondrocytes and was protective in mouse osteoarthritis (OA). However, the mechanisms underlying its transcriptional regulation in cartilage remained poorly understood. In the present study, we aimed to characterize the human DP1 promoter and the role of DNA methylation in DP1 expression in chondrocytes. In addition, we analyzed the expression level and methylation status of the DP1 gene promoter in normal and OA cartilage. Deletion and site-directed mutagenesis analyses identified a minimal promoter region (-250/-120) containing three binding sites for specificity protein 1 (Sp1). Binding of Sp1 to the DP1 promoter was confirmed using electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP) assays. Treatment with the Sp1 inhibitor mithramycin A reduced DP1 promoter activity and DP1 mRNA expression. Inhibition of DNA methylation by 5-Aza-2'-deoxycytidine upregulated DP1 expression, and in vitro methylation reduced the DP1 promoter activity. Neither the methylation status of the DP1 promoter nor the DP1 expression level were different between normal and OA cartilage. In conclusion, our results suggest that the transcription factor Sp1 and DNA methylation are important determinants of DP1 transcription regulation. They also suggest that the methylation status and expression level of DP1 are not altered in OA cartilage. These findings will improve our understanding of the regulatory mechanisms of DP1 transcription and may facilitate the development of intervention strategies involving DP1.

Multiomics dynamic learning enables personalized diagnosis and prognosis for pancancer and cancer subtypes

Artificial intelligence (AI) approaches in cancer analysis typically utilize a 'one-size-fits-all' methodology characterizing average patient responses. This manner neglects the diverse conditions in the pancancer and cancer subtypes of individual patients, resulting in suboptimal outcomes in diagnosis and treatment. To overcome this limitation, we shift from a blanket application of statistics to a focus on the explicit recognition of patient-specific abnormalities. Our objective is to use multiomics data to empower clinicians with personalized molecular descriptions that allow for customized diagnosis and interventions. Here, we propose a highly trustworthy multiomics learning (HTML) framework that employs multiomics self-adaptive dynamic learning to process each sample with data-dependent architectures and computational flows, ensuring personalized and trustworthy patient-centering of cancer diagnosis and prognosis. Extensive testing on a 33-type pancancer dataset and 12 cancer subtype datasets underscored the superior performance of HTML compared with static-architecture-based methods. Our findings also highlighting the potential of HTML in elucidating complex biological pathogenesis and paving the way for improved patient-specific care in cancer treatment.

Whole-genome DNA methylation profiling reveals epigenetic signatures in developing muscle in Tan and Hu sheep and their offspring

Introduction

The Tan sheep is a popular local breed in China because of its tenderness and flavor. The Hu sheep breed is also famous for its high litter size, and its muscle growth rate is faster than that of Tan sheep. However, the epigenetic mechanism behind these muscle-related phenotypes is unknown.

Methods

In this study, the longissimus dorsi tissue from 18 6 month-old Tan sheep, Hu sheep, and Tan-Hu F2 generation (6 sheep per population) were collected. After genomic DNA extraction, whole-genome bisulfite sequencing (WGBS) and bioinformatics analysis were performed to construct genome-wide DNA methylome maps for the Tan sheep, Hu sheep and their Tan-Hu F2 generation.

Results

Distinct genome-wide DNA methylation patterns were observed between Tan sheep and Hu sheep. Moreover, DNA methylated regions were significantly increased in the skeletal muscle from Tan sheep vs. the F2 generation compared to the Hu sheep vs. F2 generation and the Tan sheep vs. Hu sheep. Compared with Hu sheep, the methylation levels of actin alpha 1 (ACTA1), myosin heavy chain 11 (MYH11), Wiskott-Aldrich syndrome protein (WAS), vav guanine nucleotide exchange factor 1 (VAV1), fibronectin 1 (FN1) and Rho-associated protein kinase 2 (ROCK2) genes were markedly distinct in the Tan sheep. Furthermore, Gene Ontology analysis indicated that these genes were involved in myotube differentiation, myotube cell development, smooth muscle cell differentiation and striated muscle cell differentiation.

Conclusion

The findings from this study, in addition to data from previous research, demonstrated that the ACTA1, MYH11, WAS, VAV1, FN1, and ROCK2 genes may exert regulatory effects on muscle development.

Single-cell transcriptomic analysis of normal and pathological tissues from the same patient uncovers colon cancer progression

The aim of the present study was to elucidate the evolutionary trajectory of colon cells from normal colon mucosa, to adenoma, then to carcinoma in the same microenvironment. Normal colon, adenoma and carcinoma tissues from the same patient were analyzed by single-cell sequencing, which perfectly simulated the process of time-dependent colon cancer due to the same microenvironment. A total of 22 cell types were identified. Results suggest the presence of dominant clones of same cells including C2 goblet cell, epithelial cell subtype 1 (Epi1), enterocyte cell subset 0 (Entero0), and Entero5 in carcinoma. Epi1 and Entero0 were Co-enriched in antibacterial and IL-17 signaling, Entero5 was enriched in immune response and mucin-type O-glycan biosynthesis. We discovered new colon cancer related genes including AC007952.4, NEK8, CHRM3, ANO7, B3GNT6, NEURL1, ODC1 and KCNMA1. The function of TBC1D4, LTB, C2CD4A, AND GBP4/5 in T cells needs to be clarified. We used colon samples from the same person, which provide new information for colon cancer therapy.

The prognostic and immune significance of C15orf48 in pan-cancer and its relationship with proliferation and apoptosis of thyroid carcinoma

Background

C15orf48 was recently identified as an inflammatory response-related gene; however there is limited information on its function in tumors. In this study, we aimed to elucidate the function and potential mechanism of action of C15orf48 in cancer.

Methods

We evaluated the pan-cancer expression, methylation, and mutation data of C15orf48 to analyze its clinical prognostic value. In addition, we explored the pan-cancer immunological characteristics of C15orf48, especially in thyroid cancer (THCA), by correlation analysis. Additionally, we conducted a THCA subtype analysis of C15orf48 to determine its subtype-specific expression and immunological characteristics. Lastly, we evaluated the effects of C15orf48 knockdown on the THCA cell line, BHT101, by in vitro experimentation.

Results

The results of our study revealed that C15orf48 is differentially expressed in different cancer types and that it can serve as an independent prognostic factor for glioma. Additionally, we found that the epigenetic alterations of C15orf48 are highly heterogeneous in several cancers and that its aberrant methylation and copy number variation are associated with poor prognosis in multiple cancers. Immunoassays elucidated that C15orf48 was significantly associated with macrophage immune infiltration and multiple immune checkpoints in THCA, and was a potential biomarker for PTC. In addition, cell experiments showed that the knockdown of C15orf48 could reduce the proliferation, migration, and apoptosis abilities of THCA cells.

Conclusions

The results of this study indicate that C15orf48 is a potential tumor prognostic biomarker and immunotherapy target, and plays an essential role in the proliferation, migration, and apoptosis of THCA cells.

High DAPK1 Expression Promotes Tumor Metastasis of Gastric Cancer

Gastric cancer (GC) is a common upper gastrointestinal tumor. Death-associated protein kinase (DAPK1) was found to participate in the development of various malignant tumors. However, there are few reports on DAPK1 in gastric cancer. In this study, the TCGA and GEO datasets were used to explore the expression and role of DAPK1 in gastric cancer. The functions of DAPK1 in gastric cancer were determined by proliferation, migration and invasion assays. In addition, genes co-expressed with DAPK1 in gastric cancer were estimated through the WGCNA and correlation analysis. A DAPK1-related gene prognostic model was constructed using the Cox regression and lasso analyses. The expression of DAPK1 was significantly up-regulated in gastric cancer tissues. Kaplan-Meier analysis showed that low expression of DAPK1 was a favorable prognostic factor of overall survival and disease-free survival for gastric cancer patients. Functional experiments demonstrated that DAPK1 can promote the migration and invasion of gastric cancer cells. WGCNA, correlation analysis, Cox regression, and lasso analyses were applied to construct the DAPK1-related prognostic model. The prognostic value of this prognostic model of DAPK1-related genes was further successfully validated in an independent database. Our results indicated that DAPK1 can promote gastric cancer cell migration and invasion and established four DAPK1-related signature genes for gastric cancer that could independently predict the survival of GC patients.

Evaluating the tumor immune profile based on a three-gene prognostic risk model in HER2 positive breast cancer

To date, there have not been great breakthroughs in immunotherapy for HER2 positive breast cancer (HPBC). This study aimed to build a risk model that might contribute to predicting prognosis and discriminating the immune landscape in patients with HPBC. We analyzed the tumor immune profile of HPBC patients from the TCGA using the ESTIMATE algorithm. Thirty survival-related differentially expressed genes were selected according to the ImmuneScore and StromalScore. A prognostic risk model consisting of PTGDR, PNOC and CCL23 was established by LASSO analysis, and all patients were classified into the high- and low-risk score groups according to the risk scores. Subsequently, the risk model was proven to be efficient and reliable. Immune related pathways were the dominantly enriched category. ssGSEA showed stronger immune infiltration in the low-risk score group, including the infiltration of TILs, CD8 T cells, NK cells, DCs, and so on. Moreover, we found that the expression of immune checkpoint genes, including PD-L1, CTLA-4, TIGIT, TIM-3 and LAG-3, was significantly upregulated in the low-risk score group. All the results were validated with corresponding data from the GEO database. In summary, our investigation indicated that the risk model composed of PTGDR, PNOC and CCL23 has potential to predict prognosis and evaluate the tumor immune microenvironment in HPBC patients. More importantly, HPBC patients with a low-risk scores are likely to benefit from immune treatment.

STAT3/HIF1A and EMT specific transcription factors regulated genes: Novel predictors of breast cancer metastasis

Metastasis, the fatal hallmark of breast cancer (BC), is a serious hurdle for therapy. Current prognostic approaches are not sufficient to predict the metastasis risk for BC patients. Therefore, in the present study, we analyzed gene expression data from GSE139038 and TCGA database to develop predictive markers for BC metastasis. Initially, the data from GSE139038 which contained 65 samples consisting of 41 breast tumor tissues, 18 paired morphologically normal tissues and 6 from non-malignant breast tissues were analyzed for differentially expressed genes (DEGs). DEGs were obtained from three different comparisons: paired morphologically normal (MN) versus tumor samples (C), apparently normal (AN) versus tumor samples (C), and paired morphologically normal (MN) versus apparently normal samples (AN). Multiple bioinformatic methods were employed to evaluate metastasis, EMT and triple negative breast cancer (TNBC) specific genes. Further, regulation of gene expression, clinicopathological factors and DNA methylation patterns of DEGs in BC were validated with TCGA datasets. Our bioinformatic analysis showed that 40 genes were upregulated and 294 were found to be downregulated between AN vs C; 124 were upregulated and 760 genes were downregulated between MN vs C; 4 were upregulated and 13 were downregulated between MN vs AN. Analysis using TCGA dataset revealed 18 genes were significantly altered in nodal positive BC patients compared to nodal negative BC patients. Our study showed novel candidate genes as predictive markers for BC metastasis which can also be used for therapeutic targets for BC treatment.

The Regulatory Role of Neuropeptide Gene Glucagon in Colorectal Cancer: A Comprehensive Bioinformatic Analysis

Background

Colorectal cancer is highly prevalent and causes high global mortality, and glucagon axis has been implicated in colon cancer. The present study is aimed at investigating the regulating mechanisms of glucagon involvement in colorectal cancer.

Methods

Publicly available data from the TCGA database was utilized to explore the expression pattern and regulating role of glucagon (GCG) in colorectal cancer (COADREAD) including colon adenocarcinomas (COAD) and rectum adenocarcinomas (READ). Statistical analyses were performed using the R software packages and public web servers. The expression pattern and prognostic significance of GCG gene in pan-cancer and TCGA-COADREAD data were investigated by performing unpaired and paired sample analyses. The association of GCG expression with clinical characteristics was investigated using logistic regression analysis. Univariate cox regression analysis was performed to test the prognostic value of GCG expression for overall survival in COADREAD patients. GCG-significantly correlated genes were obtained. Biological functions and signaling pathways were identified by performing functional enrichment analysis and Gene Set Enrichment Analysis (GSEA). Additionally, the potential involvement of GCG in tumor immunity was researched by investigating the correlation between GCG expression and 24 tumor infiltrating immune cells.

Results

GCG was found to be significantly downregulated in COADREAD tumor samples compared with healthy control samples. GCG gene was shown to be associated with the prognostic outcomes of COADREAD, whereby its upregulation predicted improved survival outcomes. Functional enrichment analysis showed that the top 100 positively and top 100 negatively GCG-correlated genes were mainly enriched in three signaling pathways including ribosome, nitrogen metabolism, and proximal tubule bicarbonate reclamation. The GSEA showed that GCG-significantly correlated genes were mainly enriched in cell cycle-related pathways (reactome cell cycle, reactome cell cycle mitotic, reactome cell cycle checkpoints, reactome M phase, Reactome G2 M DNA damage checkpoint, and Reactome G2 M checkpoints), neuropeptide ligand receptor interaction, RHO GTPases signaling, WNT signaling, RUNX1 signaling, NOTCH signaling, ESR signaling, HCMV infection, and oxidative stress-related signaling. GCG was positively correlated with Th17 cells, pDC, macrophages, TFH cells, iDC, Tem, B cells, dendritic cells, neutrophils, mast cells, and eosinophils and was negatively associated with NK cells.

Conclusions

GCG dysregulation with high prognostic value in COADREAD was noted. Several tumor progression-related pathways and tumor immune-modulatory cells were linked to GCG expression in COADREAD. Therefore, GCG may be regarded as a potential therapeutic target for treating colorectal cancer.

Identification of key regulators in parathyroid adenoma using an integrative gene network analysis

Parathyroid adenoma (PA) is marked by a certain benign outgrowth in the surface of parathyroid glands. The transcriptome analysis of parathyroid adenomas can provide a deep insight into actively expressed genes and transcripts. Hence, we analyzed and compared the gene expression profiles of parathyroid adenomas and healthy parathyroid gland tissues from Gene Expression Omnibus (GEO) database. We identified a total of 280 differentially expressed genes (196 up-regulated, 84 down-regulated), which are involved in a wide array of biological processes. We further constructed a gene interaction network and analyzed its topological properties to know the network structure and its hidden mechanism. This will help to understand the molecular mechanisms underlying parathyroid adenoma development. We thus identified 13 key regulators (PRPF19, SMC3, POSTN, SNIP1, EBF1, MEIS2, PAX9, SCUBE2, WNT4, ARHGAP10, DOCK5, CAV1 and VSIR), which are deep-rooted from top to bottom in the gene interaction network forming a backbone for the network. The structural features of the network are probably maintained by crosstalk between important genes within the network along with associated functional modules.Thus, gene-expression profiling and network approach could be used to provide an independent platform to glen insights from available clinical data.

Application of weighted gene co‑expression network analysis to explore the potential diagnostic biomarkers for colorectal cancer

Colorectal cancer (CRC) is one of the most common malignant diseases in the world. Although mechanistic studies have been conducted on the pathogenesis of CRC, the molecular mechanism of CRC tumorigenesis remains unclear. In the present study, the weighted gene co-expression network analysis was performed for the Gene Expression Omnibus (GEO) dataset GSE87211, in order to analyze the key modules involved in the pathogenesis of CRC. Next, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on the key module genes to analyze the functional pathways involved. The hub genes were screened using the Cytoscape platform and verified by a second GEO dataset, GSE21510. Finally, 10 hub genes were identified in 2 key modules (the green and brown modules) as the genes most significantly associated with the tumorigenesis of CRC. The 5 hub genes from the green module included collagen type I α1 chain, collagen type XII α1 chain, collagen triple helix repeat containing 1, inhibin subunit βa (INHBA) and chromobox 2 (CBX2), while the 5 hub genes from the brown module included bestrophin 2 (BEST2), carbonic anhydrase 2, glucagon, solute carrier family 4 member 4 and gliomedin. The 2 key modules with the 10 hub genes identified may regulate the occurrence and development of CRC through the extracellular matrix pathway, PI3K-Akt and chemokine signaling pathways, thus providing a reference for understanding the complex mechanism of tumorigenesis in CRC. Of note, few studies have reported the pathogenesis of CRC with the 3 identified hub genes, INHBA, CBX2 and BEST2. Further investigation of the molecular mechanism of these genes in CRC is recommended.

Layered Bayesian nonparametric regression for DNA methylation rates

DNA methylation rate is one of key indicators that may show the association of a set of genes with a specific disease. However, DNA methylation rates usually follow a skewed distribution with a large amount of variance depending on the sample and genetic site. Using the functional data analysis to investigate differentially methylated genetic regions, it is desirable to utilize a regression methodology that is robust for errors with skewed distribution and large variance. To this purpose, we propose a novel regression method that fits the regression functions on the decomposed several layers of categorical responses and a layer of continuous responses and aggregates all fitted functions together. We carried out simulation studies to evaluate the performance of the proposed method under different amounts of error variances and skewed distributions. We also applied the proposed method in a functional data analysis to identify differentially methylated genetic regions within a chromosome by using data from sample tissues of patients with lung adenocarcinoma.

Integrated analysis of DNA methylation profiling and gene expression profiling identifies novel markers in lung cancer in Xuanwei, China

BACKGROUND

Aberrant DNA methylation occurs frequently in cancer. The aim of this study was to identify novel methylation markers in lung cancer in Xuanwei, China, through integrated genome-wide DNA methylation and gene expression studies.

METHODS

Differentially methylated regions (DMRs) and differentially expressed genes (DEGs) were detected on 10 paired lung cancer tissues and noncancerous lung tissues by methylated DNA immunoprecipitation combined with microarray (MeDIP-chip) and gene expression microarray analyses, respectively. Integrated analysis of DMRs and DEGs was performed to screen out candidate methylation-related genes. Both methylation and expression changes of the candidate genes were further validated and analyzed.

RESULTS

Compared with normal lung tissues, lung cancer tissues expressed a total of 6,899 DMRs, including 5,788 hypermethylated regions and 1,111 hypomethylated regions. Integrated analysis of DMRs and DEGs identified 45 tumor-specific candidate genes: 38 genes whose DMRs were hypermethylated and expression was downregulated, and 7 genes whose DMRs were hypomethylated and expression was upregulated. The methylation and expression validation results identified 4 candidate genes (STXBP6, BCL6B, FZD10, and HSPB6) that were significantly hypermethylated and downregulated in most of the tumor tissues compared with the noncancerous lung tissues.

CONCLUSIONS

This integrated analysis of genome-wide DNA methylation and gene expression in lung cancer in Xuanwei revealed several genes regulated by promoter methylation that have not been described in lung cancer before. These results provide new insight into the carcinogenesis of lung cancer in Xuanwei and represent promising new diagnostic and therapeutic targets.

Hypermethylation of normal mucosa of esophagus-specific 1 is associated with an unfavorable prognosis in patients with non-small cell lung cancer

Lung cancer is the leading cause of cancer-associated mortality due to high incidence and poor survival rates, irrespective of global variations in its biology and treatment. Changes in DNA methylation are frequent in cancer and constitute an important mechanism in tumorigenesis. Normal mucosa of esophagus-specific 1 (NMES1) is expressed in epithelial tissue and is believed to be a tumor suppressor gene. The present study investigated the methylation status of the NMES1 promoter in 178 cases of primary non-small cell lung cancer (NSCLC) by pyrosequencing and evaluated the prognostic value of this methylation. NMES1 methylation-positive tumors above the background threshold for non-malignant tissue were found in 15 cases (8.4%) and were detected exclusively in malignant tissues. In addition, univariate and multivariate analyses showed that methylation-positive patients experienced worse overall survival rate (OSR) compared with methylation-negative patients (adjusted hazard ratio, 2.62; 95% confidence interval, 1.20-5.69; P=0.02). Notably, within the methylation-positive group, patients with strong methylation tended to experience worse OSR compared with those with weak methylation (adjusted hazard ratio, 2.45 vs. 3.05; P_trend=0.02). These findings suggest that NMES1 may serve an important role in lung cancer pathogenesis, and its methylation could be considered a prognostic marker for NSCLC. Further studies with large numbers of samples are required to confirm this conclusion.

Analysis of potential genes and pathways associated with the colorectal normal mucosa-adenoma-carcinoma sequence

This study aimed to identify differentially expressed genes (DEGs) related to the colorectal normal mucosa-adenoma-carcinoma sequence using bioinformatics analysis. Raw data files were downloaded from Gene Expression Omnibus (GEO) and underwent quality assessment and preprocessing. DEGs were analyzed by the limma package in R software (R version 3.3.2). Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed with the DAVID online tool. In a comparison of colorectal adenoma (n = 20) and colorectal cancer (CRC) stage I (n = 31), II (n = 38), III (n = 45), and IV (n = 62) with normal colorectal mucosa (n = 19), we identified 336 common DEGs. Among them, seven DEGs were associated with patient prognosis. Five (HEPACAM2, ITLN1, LGALS2, MUC12, and NXPE1) of the seven genes presented a sequentially descending trend in expression with tumor progression. In contrast, TIMP1 showed a sequentially ascending trend. GCG was constantly downregulated compared with the gene expression level in normal mucosa. The significantly enriched GO terms included extracellular region, extracellular space, protein binding, and carbohydrate binding. The KEGG categories included HIF-1 signaling pathway, insulin secretion, and glucagon signaling pathway. We discovered seven DEGs in the normal colorectal mucosa-adenoma-carcinoma sequence that was associated with CRC patient prognosis. Monitoring changes in these gene expression levels may be a strategy to assess disease progression, evaluate treatment efficacy, and predict prognosis.

Transcriptome Analysis Reveals Neuroprotective aspects of Human Reactive Astrocytes induced by Interleukin 1β

Reactive astrogliosis is a critical process in neuropathological conditions and neurotrauma. Although it has been suggested that it confers neuroprotective effects, the exact genomic mechanism has not been explored. The prevailing dogma of the role of astrogliosis in inhibition of axonal regeneration has been challenged by recent findings in rodent model’s spinal cord injury, demonstrating its neuroprotection and axonal regeneration properties. We examined whether their neuroprotective and axonal regeneration potentials can be identify in human spinal cord reactive astrocytes in vitro. Here, reactive astrogliosis was induced with IL1β. Within 24 hours of IL1β induction, astrocytes acquired reactive characteristics. Transcriptome analysis of over 40000 transcripts of genes and analysis with PFSnet subnetwork revealed upregulation of chemokines and axonal permissive factors including FGF2, BDNF, and NGF. In addition, most genes regulating axonal inhibitory molecules, including ROBO1 and ROBO2 were downregulated. There was no increase in the gene expression of “Chondroitin Sulfate Proteoglycans” (CSPGs’) clusters. This suggests that reactive astrocytes may not be the main CSPG contributory factor in glial scar. PFSnet analysis also indicated an upregulation of “Axonal Guidance Signaling” pathway. Our result suggests that human spinal cord reactive astrocytes is potentially neuroprotective at an early onset of reactive astrogliosis.

FcGBP was upregulated by HPV infection and correlated to longer survival time of HNSCC patients

FcGBP was normally found in intestinal and colonic epithelia, gallbladder, cystic duct, bronchus, submandibular gland, cervix uteri and in fluids secreted by these cells in humans, and was down-regulated during colon carcinogenesis. We found FcGBP gene expression was decreased in HNSCC tissues compared to surgical safety border tissues while TGF-β expression level increased in HNSCC tissues, and higher FcGBP expression level was correlated to longer OS time of HNSCC patients. FcGBP expression level was higher in HPV-positive HNSCC tissues compared to HPV-negative HNSCC tissues, while TGF-β expression level was lower in HPV-positive HNSCC tissues. Gene expression level of FcGBP and TGF-β was negatively correlated in HNSCC tissues. FcGBP expression level increased after HPV E6 overexpression in HPV-negative HNSCC cells, and TGF-β could inhibit the up-regulation of FcGBP after HPV E6 or FcGBP overexpression in HPV-negative HNSCC cells. The migration capability was inhibited after FcGBP overexpression, and TGF-β could counteract the inhibition of migration caused by FcGBP overexpression. FcGBP gene expression level was correlated to the expression levels of EMT markers. In conclusion, FCGBP expression was upregulated by HPV infection while inhibited by TGF-β, and was correlated to the prognosis of HNSCC patients.

Transcriptome analysis of human colorectal cancer biopsies reveals extensive expression correlations among genes related to cell proliferation, lipid metabolism, immune response and collagen catabolism

Precise characterization of biological processes critical to proliferation and metastasis of colorectal cancer should facilitate the development of diagnostic and prognostic biomarkers as well as novel treatments. Using mRNA-Seq, we examined the protein coding messenger RNA (mRNA) expression profiles across different histologically defined stages of primary colon cancers and compared them to their patient matched normal tissue controls. In comparing 79 colorectal cancers to their matched normal mucosa, tumors were distinguished from normal non-malignant tissues not only in the upregulation of biological processes pertaining to cell proliferation, inflammation, and tissue remodeling, but even more strikingly, in downregulated biological processes including fatty acid beta oxidization for ATP production and epithelial cell differentiation and function. A network analysis of deregulated genes revealed newly described cancer networks and putative hub genes.

Taken together, our findings suggest that, within an inflammatory microenvironment, invasive, dedifferentiated and rapidly dividing tumor cells divert the oxidation of fatty acids and lipids from energy production into lipid components of cell membranes and organelles to support tumor proliferation. A gene co-expression network analysis provides a clear and broad picture of biological pathways in tumors that may significantly enhance or supplant current histopathologic studies.

Genome-wide profiling of DNA methylation and gene expression in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is the leading cause of cancer-related death worldwide. Previous studies have suggested that DNA methylation involved in the development of ESCC. However, the precise mechanisms underlying the regulation and maintenance of the methylome as well as their relationship with ESCC remain poorly understood. Herein, we used methylated DNA immunoprecipitation sequencing (MeDIP-Seq) and RNA-Seq to investigate whole-genome DNA methylation patterns and the genome expression profiles in ESCC samples. The results of MeDIP-Seq analyses identified differentially methylated regions (DMRs) covering almost the entire genome with sufficient depth and high resolution. The gene ontology (GO) analysis showed that the DMRs related genes belonged to several different ontological domains, such as cell cycle, adhesion, proliferation and apoptosis. The RNA-Seq analysis identified a total of 6150 differentially expressed genes (3423 up-regulated and 2727 down-regulated). The significant GO terms showed that these genes belonged to several molecular functions and biological pathways. Moreover, the bisulfite-sequencing of genes MLH1, CDH5, TWIST1 and CDX1 confirmed the methylation status identified by MeDIP-Seq. And the mRNA expression levels of MLH1, TWIST1 and CDX1 were consistent with their DNA methylation profiles. The DMR region of MLH1 was found to correlate with survival. The identification of whole-genome DNA methylation patterns and gene expression profiles in ESCC provides new insight into the carcinogenesis of ESCC and represents a promising avenue through which to investigate novel therapeutic targets.

Transcriptome analysis of equine sarcoids

Equine sarcoids are the most commonly detected skin tumours in Equidae. In the present research, a comparative transcriptomic analysis was performed which aimed at looking inside a tumour biology and identification of the expression profile as a potential source of cancer specific genes useful as biomarkers. We have used Horse Gene Expression Microarray data from matched equine sarcoids and tumour-distant skin samples. In total, 901 significantly differentially expressed genes (DEGs) between lesional and healthy skin samples have been identified (fold change ≥ 2; P < 0.05). The large subset of DEGs, with decreased expression, was associated with a suppression of malignant transformation, whereas several overexpressed genes were involved in the processes associated with growth and progression of a tumour or immune system activity. Our results, as a first to date, showed comprehensive transcriptome analysis of skin tumour in horses and pinpointed significant pathways and genes related with oncogenesis processes.

Aberrant DNA methylation of WNT pathway genes in the development and progression of CIMP-negative colorectal cancer

The WNT signaling pathway has an essential role in colorectal carcinogenesis and progression, which involves a cascade of genetic and epigenetic changes. We aimed to analyze DNA methylation affecting the WNT pathway genes in colorectal carcinogenesis in promoter and gene body regions using whole methylome analysis in 9 colorectal cancer, 15 adenoma, and 6 normal tumor adjacent tissue (NAT) samples by methyl capture sequencing. Functional methylation was confirmed on 5-aza-2'-deoxycytidine-treated colorectal cancer cell line datasets. In parallel with the DNA methylation analysis, mutations of WNT pathway genes (APC, β-catenin/CTNNB1) were analyzed by 454 sequencing on GS Junior platform. Most differentially methylated CpG sites were localized in gene body regions (95% of WNT pathway genes). In the promoter regions, 33 of the 160 analyzed WNT pathway genes were differentially methylated in colorectal cancer vs. normal, including hypermethylated AXIN2, CHP1, PRICKLE1, SFRP1, SFRP2, SOX17, and hypomethylated CACYBP, CTNNB1, MYC; 44 genes in adenoma vs. NAT; and 41 genes in colorectal cancer vs. adenoma comparisons. Hypermethylation of AXIN2, DKK1, VANGL1, and WNT5A gene promoters was higher, while those of SOX17, PRICKLE1, DAAM2, and MYC was lower in colon carcinoma compared to adenoma. Inverse correlation between expression and methylation was confirmed in 23 genes, including APC, CHP1, PRICKLE1, PSEN1, and SFRP1. Differential methylation affected both canonical and noncanonical WNT pathway genes in colorectal normal-adenoma-carcinoma sequence. Aberrant DNA methylation appears already in adenomas as an early event of colorectal carcinogenesis.

Identification of metastasis-associated genes in colorectal cancer using metaDE and survival analysis

The aim of the present study was to detect the candidate genes involved in the metastasis of colorectal cancer (CRC). Gene expression profiles of primary and metastatic CRC samples in the GSE14297 and GSE49355 datasets were downloaded from the Gene Expression Omnibus database. Subsequent to processing, Fishers exact test and the metaDE package in R language were applied to screen the differentially expressed genes (DEGs) between primary and metastatic CRC samples. In addition, function and pathway enrichment analysis was performed using online tools in the Database for Annotation, Visualization, and Integrated Discovery resource and common DEGs in GSE14297 and GSE49355 were identified. Their expression values in another dataset, GSE29621, were then collected in order to screen the genes with high standard deviations between primary and metastatic samples, which were considered as candidate metastasis-associated genes. Candidate genes were finally verified by performing survival analysis via the log-rank test. A total of 370 DEGs were screened in GSE14297 and GSE49355, and 77 common DEGs were identified. Upregulated DEGs were mainly enriched in the immune, energy metabolism and drug metabolism-associated functions. Downregulated DEGs were mainly enriched in cell adhesion-associated functions. A total of 12 genes, including the carbonic anhydrase II (CA2), carcinoembryonic antigen-related cell adhesion molecule 7 (CEACAM7), Fc fragment of immunoglobulin G binding protein (FCGBP), and placenta-specific 8 (PLAC8), were the candidate metastasis-associated genes, among which FCGBP expression significantly decreased the overall survival time of patients. The selected candidate metastasis-associated gene, FCGBP, may be used as a potential therapeutic target in patients with metastatic CRC.

DNA hypermethylation and decreased mRNA expression of MAL, PRIMA1, PTGDR and SFRP1 in colorectal adenoma and cancer

BACKGROUND

Colorectal cancer (CRC) development is accompanied by changes in expression for several genes; but the details of the underlying regulatory procesess remain unknown. Our aims were to assess the role of epigenetic processes in tumour formation and to identify characteristic DNA methylation and miRNA alterations in the colorectal adenoma-carcinoma sequence.

METHODS

Whole genome expression profiling was performed on colonic biopsy samples (49 healthy normal, 49 colorectal adenoma (AD), 49 CRC); on laser capture microdissected (LCM) epithelial and stromal cells from 6 CRC-normal adjacent tissue (NAT) samples pairs, and on demethylated human CRC cell lines using HGU133 Plus 2.0 microarrays (Affymetrix). Methylation status of genes with gradually altering expression along the AD-CRC sequence was further analysed on 10-10 macrodissected and 5-5 LCM samples from healthy colon, from adenoma and from CRC biopsy samples using bisulfite-sequencing PCR (BS-PCR) followed by pyrosequencing. In silico miRNA prediction for the selected genes was performed with miRWALK algorithm, miRNA expression was analysed on 3 CRC-NAT sample pairs and 3 adenoma tissue samples using the Human Panel I + II (Exiqon). SFRP1 immunohistochemistry experiments were performed.

RESULTS

A set of transcripts (18 genes including MAL, SFRP1, SULT1A1, PRIMA1, PTGDR) showed decreasing expression (p < 0.01) in the biopsy samples along the adenoma-carcinoma sequence. Three of those (COL1A2, SFRP2, SOCS3) showed hypermethylation and THBS2 showed hypomethylation both in AD and in CRC samples compared to NAT, while BCL2, PRIMA1 and PTGDR showed hypermethylation only in the CRC group. miR-21 was found to be significantly (p < 0.01) upregulated in adenoma and tumour samples compared to the healthy colonic tissue controls and could explain the altered expression of genes for which DNA methylation changes do not appear to play role (e.g. BCL2, MAL, PTGS2). Demethylation treatment could upregulate gene expression of genes that were found to be hypermethylated in human CRC tissue samples. Decreasing protein levels of SFRP1 was also observed along the adenoma-carcinoma sequence.

CONCLUSION

Hypermethylation of the selected markers (MAL, PRIMA1, PTGDR and SFRP1) can result in reduced gene expression and may contribute to the formation of colorectal cancer.

Comprehensive DNA Methylation Analysis Reveals a Common Ten-Gene Methylation Signature in Colorectal Adenomas and Carcinomas

Microarray analysis of promoter hypermethylation provides insight into the role and extent of DNA methylation in the development of colorectal cancer (CRC) and may be co-monitored with the appearance of driver mutations. Colonic biopsy samples were obtained endoscopically from 10 normal, 23 adenoma (17 low-grade (LGD) and 6 high-grade dysplasia (HGD)), and 8 ulcerative colitis (UC) patients (4 active and 4 inactive). CRC samples were obtained from 24 patients (17 primary, 7 metastatic (MCRC)), 7 of them with synchronous LGD. Field effects were analyzed in tissues 1 cm (n = 5) and 10 cm (n = 5) from the margin of CRC. Tissue materials were studied for DNA methylation status using a 96 gene panel and for KRAS and BRAF mutations. Expression levels were assayed using whole genomic mRNA arrays. SFRP1 was further examined by immunohistochemistry. HT29 cells were treated with 5-aza-2' deoxycytidine to analyze the reversal possibility of DNA methylation. More than 85% of tumor samples showed hypermethylation in 10 genes (SFRP1, SST, BNC1, MAL, SLIT2, SFRP2, SLIT3, ALDH1A3, TMEFF2, WIF1), whereas the frequency of examined mutations were below 25%. These genes distinguished precancerous and cancerous lesions from inflamed and healthy tissue. The mRNA alterations that might be caused by systematic methylation could be partly reversed by demethylation treatment. Systematic changes in methylation patterns were observed early in CRC carcinogenesis, occuring in precursor lesions and CRC. Thus we conclude that DNA hypermethylation is an early and systematic event in colorectal carcinogenesis, and it could be potentially reversed by systematic demethylation therapy, but it would need more in vitro and in vivo experiments to support this theory.

Myofibroblast-derived SFRP1 as potential inhibitor of colorectal carcinoma field effect

Epigenetic changes of stromal-epithelial interactions are of key importance in the regulation of colorectal carcinoma (CRC) cells and morphologically normal, but genetically and epigenetically altered epithelium in normal adjacent tumor (NAT) areas. Here we demonstrated retained protein expression of well-known Wnt inhibitor, secreted frizzled-related protein 1 (SFRP1) in stromal myofibroblasts and decreasing epithelial expression from NAT tissues towards the tumor. SFRP1 was unmethylated in laser microdissected myofibroblasts and partially hypermethylated in epithelial cells in these areas. In contrast, we found epigenetically silenced myofibroblast-derived SFRP1 in CRC stroma. Our results suggest that the myofibroblast-derived SFRP1 protein might be a paracrine inhibitor of epithelial proliferation in NAT areas and loss of this signal may support tumor proliferation in CRC.

Proteomics, genomics and transcriptomics: their emerging roles in the discovery and validation of colorectal cancer biomarkers

Colorectal cancer (CRC) is the second most common cancer in females and the third in males. Since CRC is often diagnosed at an advanced stage when prognosis is poor, identification of biomarkers for early diagnosis is urgently required. Recent advances in proteomics, genomics and transcriptomics have facilitated high-throughput profiling of data generated from CRC-related genes and proteins, providing a window of information for biomarker discovery and validation. However, transfer of candidate biomarkers from bench to bedside remains a dilemma. In this review, we will discuss emerging proteomic technologies and highlight various sample types utilized for proteomics-based identification of CRC biomarkers. Moreover, recent breakthroughs in genomics and transcriptomics for the identification of CRC biomarkers, with particular emphasis on the merits of emerging methylomic and miRNAomic strategies, will be discussed. Integration of proteomics, genomics and transcriptomics will facilitate the discovery and validation of CRC biomarkers leading to the emergence of personalized medicine.

Genetic and epigenetic biomarkers for diagnosis, prognosis and treatment of colorectal cancer

Colorectal cancer (CRC) is one of the most common cancer worldwide and results from the accumulation of mutations and epimutations in colonic mucosa cells ultimately leading to cell proliferation and metastasis. Unfortunately, CRC prognosis is still poor and the search of novel diagnostic and prognostic biomarkers is highly desired to prevent CRC-related deaths. The present article aims to summarize the most recent findings concerning the use of either genetic or epigenetic (mainly related to DNA methylation) biomarkers for CRC diagnosis, prognosis, and response to treatment. Recent large-scale DNA methylation studies suggest that CRC can be divided into several subtypes according to the frequency of DNA methylation and those of mutations in key CRC genes, and that this is reflected by different prognostic outcomes. Increasing evidence suggests that the analysis of DNA methylation in blood or fecal specimens could represent a valuable non-invasive diagnostic tool for CRC. Moreover, a broad spectrum of studies indicates that the inter-individual response to chemotherapeutic treatments depends on both epigenetic modifications and genetic mutations occurring in colorectal cancer cells, thereby opening the way for a personalized medicine. Overall, combining genetic and epigenetic data might represent the most promising tool for a proper diagnostic, prognostic and therapeutic approach.

FAM161A, a novel centrosomal-ciliary protein implicated in autosomal recessive retinitis pigmentosa

Retinitis pigmentosa (RP) is an inherited disease of the retina leading to vision impairment due to progressive photoreceptor cell death. Homozygous and compound heterozygous null mutations in the CRX-regulated FAM161A gene of unknown function were identified as a cause for autosomal recessive RP (RP28) in patients from India, Germany, Israel, the Palestinian territories, and the USA. The FAM161A protein has been found to be localized to the connecting cilium, the basal body, and the adjacent centriole in mammalian photoreceptors and was also present in synaptic layers and ganglion cells of the retina. In addition, FAM161A was shown to be part of microtubule-organizing centers in cultured cells and associates with the intracellular microtubule network. Moreover, FAM161A directly binds to microtubules and increases the acetylation of α-tubulin. An evolutionary highly conserved, C-terminal protein domain (UPF0564) of FAM161A was shown to mediate microtubule association, homo- and heterotypic interaction among UPF0564-containing proteins and binding to several ciliopathy-associated proteins. In summary, FAM161A is a novel centrosomal-ciliary protein that likely is implicated in the regulation of microtubule-based cellular processes in the retina.

Systems biology approach to stage-wise characterization of epigenetic genes in lung adenocarcinoma

Background

Epigenetics refers to the reversible functional modifications of the genome that do not correlate to changes in the DNA sequence. The aim of this study is to understand DNA methylation patterns across different stages of lung adenocarcinoma (LUAD).

Results

Our study identified 72, 93 and 170 significant DNA methylated genes in Stages I, II and III respectively. A set of common 34 significant DNA methylated genes located in the promoter section of the true CpG islands were found across stages, and these were: HOX genes, FOXG1, GRIK3, HAND2, PRKCB, etc. Of the total significant DNA methylated genes, 65 correlated with transcription function. The epigenetic analysis identified the following novel genes across all stages: PTGDR, TLX3, and POU4F2. The stage-wise analysis observed the appearance of NEUROG1 gene in Stage I and its re-appearance in Stage III. The analysis showed similar epigenetic pattern across Stage I and Stage III. Pathway analysis revealed important signaling and metabolic pathways of LUAD to correlate with epigenetics. Epigenetic subnetwork analysis identified a set of seven conserved genes across all stages: UBC, KRAS, PIK3CA, PIK3R3, RAF1, BRAF, and RAP1A. A detailed literature analysis elucidated epigenetic genes like FOXG1, HLA-G, and NKX6-2 to be known as prognostic targets.

Conclusion

Integrating epigenetic information for genes with expression data can be useful for comprehending in-depth disease mechanism and for the ultimate goal of better target identification.

Genome-wide methylation analysis shows similar patterns in Barrett's esophagus and esophageal adenocarcinoma

Barrett's esophagus (BE) is a precursor of esophageal adenocarcinoma (EAC). To identify novel tumor suppressors involved in esophageal carcinogenesis and potential biomarkers for the malignant progression of BE, we performed a genome-wide methylation profiling of BE and EAC tissues. Using Illumina's Infinium HumanMethylation27 BeadChip microarray, we examined the methylation status of 27 578 CpG sites in 94 normal esophageal (NE), 77 BE and 117 EAC tissue samples. The overall methylation of CpG sites within the CpG islands was higher, but outside of the CpG islands was lower in BE and EAC tissues than in NE tissues. Hierarchical clustering analysis showed an excellent separation of NE tissues from BE and EAC tissues; however, the clustering of BE and EAC tissues was less clear, suggesting that methylation occurs early during the progression of EAC. We confirmed many previously reported hypermethylated genes and identified a large number of novel hypermethylated genes in BE and EAC tissues, particularly genes encoding ADAM (A Disintegrin And Metalloproteinase) peptidase proteins, cadherins and protocadherins, and potassium voltage-gated channels. Pathway analysis showed that a number of channel and transporter activities were enriched for hypermethylated genes. We used pyrosequencing to validate selected candidate genes and found high correlations between the array and pyrosequencing data (rho > 0.8 for each validated gene). The differentially methylated genes and pathways may provide biological insights into the development and progression of BE and become potential biomarkers for the prediction and early detection of EAC.

Epigenetic analysis of laser capture microdissected fetal epithelia

Laser capture microdissection (LCM) is a superior method for nondestructive collection of specific cell populations from tissue sections. Although DNA, RNA, and protein have been analyzed from LCM-procured samples, epigenetic analyses, particularly of fetal, highly hydrated tissue, have not been attempted. A standardized protocol with quality assurance measures was established to procure cells by LCM of the medial edge epithelia (MEE) of the fetal palatal processes for isolation of intact microRNA for expression analyses and genomic DNA (gDNA) for CpG methylation analyses. MicroRNA preparations, obtained using the RNAqueous Micro kit (Life Technologies), exhibited better yields and higher quality than those obtained using the Arcturus PicoPure RNA Isolation kit (Life Technologies). The approach was validated using real-time polymerase chain reaction (PCR) to determine expression of selected microRNAs (miR-99a and miR-200b) and pyrosequencing to determine CpG methylation status of selected genes (Aph1a and Dkk4) in the MEE. These studies describe an optimized approach for employing LCM of epithelial cells from fresh frozen fetal tissue that enables quantitative analyses of microRNA expression levels and CpG methylation.

A method to detect differentially methylated loci with next-generation sequencing

Epigenetic changes, especially DNA methylation at CpG loci have important implications in cancer and other complex diseases. With the development of next-generation sequencing (NGS), it is feasible to generate data to interrogate the difference in methylation status for genome-wide loci using case-control design. However, a proper and efficient statistical test is lacking. There are several challenges. First, unlike methylation experiments using microarrays, where there is one measure of methylation for one individual at a particular CpG site, here we have the counts of methylation allele and unmethylation allele for each individual. Second, due to the nature of sample preparation, the measured methylation reflects the methylation status of a mixture of cells involved in sample preparation. Therefore, the underlying distribution of the measured methylation level is unknown, and a robust test is more desirable than parametric approach. Third, currently NGS measures methylation at over 2 million CpG sites. Any statistical tests have to be computationally efficient in order to be applied to the NGS data. Taking these challenges into account, we propose a test for differential methylation based on clustered data analysis by modeling the methylation counts. We performed simulations to show that it is robust under several distributions for the measured methylation levels. It has good power and is computationally efficient. Finally, we apply the test to our NGS data on chronic lymphocytic leukemia. The results indicate that it is a promising and practical test.

Double restriction-enzyme digestion improves the coverage and accuracy of genome-wide CpG methylation profiling by reduced representation bisulfite sequencing

BACKGROUND

Reduced representation bisulfite sequencing (RRBS) was developed to measure DNA methylation of high-CG regions at single base-pair resolution, and has been widely used because of its minimal DNA requirements and cost efficacy; however, the CpG coverage of genomic regions is restricted and important regions with low-CG will be ignored in DNA methylation profiling. This method could be improved to generate a more comprehensive representation.

RESULTS

Based on in silico simulation of enzyme digestion of human and mouse genomes, we have optimized the current single-enzyme RRBS by applying double enzyme digestion in the library construction to interrogate more representative regions. CpG coverage of genomic regions was considerably increased in both high-CG and low-CG regions using the double-enzyme RRBS method, leading to more accurate detection of their average methylation levels and identification of differential methylation regions between samples. We also applied this double-enzyme RRBS method to comprehensively analyze the CpG methylation profiles of two colorectal cancer cell lines.

CONCLUSION

The double-enzyme RRBS increases the CpG coverage of genomic regions considerably over the previous single-enzyme RRBS method, leading to more accurate detection of their average methylation levels. It will facilitate genome-wide DNA methylation studies in multiple and complex clinical samples.