Integrated analysis of epigenomic and genomic changes by DNA methylation dependent mechanisms provides potential novel biomarkers for prostate cancer

Epigenetic regulation of somatostatin and somatostatin receptors in neuroendocrine tumors and other types of cancer

Both somatostatin (SST) and somatostatin receptors (SSTRs) are proteins with important functions in both physiological tissue and in tumors, particularly in neuroendocrine tumors (NETs). NETs are frequently characterized by high SSTRs expression levels. SST analogues (SSAs) that bind and activate SSTR have anti-proliferative and anti-secretory activity, thereby reducing both the growth as well as the hormonal symptoms of NETs. Moreover, the high expression levels of SSTR type-2 (SSTR2) in NETs is a powerful target for therapy with radiolabeled SSAs. Due to the important role of both SST and SSTRs, it is of great importance to elucidate the mechanisms involved in regulating their expression in NETs, as well as in other types of tumors. The field of epigenetics recently gained interest in NET research, highlighting the importance of this process in regulating the expression of gene and protein expression. In this review we will discuss the role of the epigenetic machinery in controlling the expression of both SSTRs and the neuropeptide SST. Particular attention will be given to the epigenetic regulation of these proteins in NETs, whereas the involvement of the epigenetic machinery in other types of cancer will be discussed as well. In addition, we will discuss the possibility to target enzymes involved in the epigenetic machinery to modify the expression of the SST-system, thereby possibly improving therapeutic options.

Obscurin: A multitasking giant in the fight against cancer

Giant obscurins (720-870 kDa), encoded by OBSCN, were originally discovered in striated muscles as cytoskeletal proteins with scaffolding and regulatory roles. Recently though, they have risen to the spotlight as key players in cancer development and progression. Herein, we provide a timely prudent synopsis of the expanse of OBSCN mutations across 16 cancer types. Given the extensive work on OBSCN's role in breast epithelium, we summarize functional studies implicating obscurins as potent tumor suppressors in breast cancer and delve into an in silico analysis of its mutational profile and epigenetic (de)regulation using different dataset platforms and sophisticated computational tools. Lastly, we formally describe the OBSCN-Antisense-RNA-1 gene, which belongs to the long non-coding RNA family and discuss its potential role in modulating OBSCN expression in breast cancer. Collectively, we highlight the escalating involvement of obscurins in cancer biology and outline novel potential mechanisms of OBSCN (de)regulation that warrant further investigation.

The remodelling of actin composition as a hallmark of cancer

Actin is a key structural protein that makes up the cytoskeleton of cells, and plays a role in functions such as division, migration, and vesicle trafficking. It comprises six different cell-type specific isoforms: ACTA1, ACTA2, ACTB, ACTC1, ACTG1, and ACTG2. Abnormal actin isoform expression has been reported in many cancers, which led us to hypothesize that it may serve as an early biomarker of cancer. We show an overview of the different actin isoforms and highlight mechanisms by which they may contribute to tumorigenicity. Furthermore, we suggest how the aberrant expression of actin subunits can confer cells with greater proliferation ability, increased migratory capability, and chemoresistance through incorporation into the normal cellular F-actin network and altered actin binding protein interaction. Studying this fundamental change that takes place within cancer cells can further our understanding of neoplastic transformation in multiple tissue types, which can ultimately aid in the early-detection, diagnosis and treatment of cancer.

A newly developed age estimation method based on CpG methylation of teeth-derived DNA using real-time methylation-specific PCR

Age estimation of unidentified bodies is important in forensic medicine and crime scenes. There is accumulating evidence that DNA methylation in the human genome isolated from body fluids changes with age. Most of the data have been obtained by pyrosequencing. In the forensic field, a simple, quick, and economical method is required to evaluate the age of various types of samples. In this study, an age estimation method based on methylation levels of DNA extracted from teeth using real-time methylation-specific PCR (MSP) was developed. The CpG island in the upstream region of ELOVL2, which is known as a validated biomarker in blood samples, was selected as a target site. The CpG methylation levels highly correlated with age (r = 0.843, n = 29). Age-related increase in DNA methylation levels was not affected by sex differences. In addition, the simple regression model based on methylation status of the CpG island exhibited moderate accuracy with a mean absolute deviation between chronological age and predicted age of 8.94 years. The results imply that real-time MSP can be a new tool to perform age prediction of unidentified bodies in forensic scenes.

The roles and regulation of TBX3 in development and disease

TBX3, a member of the ancient and evolutionary conserved T-box transcription factor family, is a critical developmental regulator of several structures including the heart, mammary glands, limbs and lungs. Indeed, mutations in the human TBX3 lead to ulnar mammary syndrome which is characterized by several clinical malformations including hypoplasia of the mammary and apocrine glands, defects of the upper limb, areola, dental structures, heart and genitalia. In contrast, TBX3 has no known function in adult tissues but is frequently overexpressed in a wide range of epithelial and mesenchymal derived cancers. This overexpression greatly impacts several hallmarks of cancer including bypass of senescence, apoptosis and anoikis, promotion of proliferation, tumour formation, angiogenesis, invasion and metastatic capabilities as well as cancer stem cell expansion. The debilitating consequences of having too little or too much TBX3 suggest that its expression levels need to be tightly regulated. While we have a reasonable understanding of the mutations that result in low levels of functional TBX3 during development, very little is known about the factors responsible for the overexpression of TBX3 in cancer. Furthermore, given the plethora of oncogenic processes that TBX3 impacts, it must be regulating several target genes but to date only a few have been identified and characterised. Interestingly, while there is compelling evidence to support oncogenic roles for TBX3, a few studies have indicated that it may also have tumour suppressor functions in certain contexts. Together, the diverse functional elasticity of TBX3 in development and cancer is thought to involve, in part, the protein partners that it interacts with and this area of research has recently received some attention. This review provides an insight into the significance of TBX3 in development and cancer and identifies research gaps that need to be explored to shed more light on this transcription factor.

Prostate Cancer Genomic Subtypes

Over the last decade, advancements in massively-parallel DNA sequencing and computational biology have allowed for unprecedented insights into the fundamental mutational processes that underlie virtually every major cancer type. Two major cancer genomics consortia-The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC)-have produced rich databases of mutational, pathological, and clinical data that can be mined through web-based portals, allowing for correlative studies and testing of novel hypotheses on well-powered patient cohorts.In this chapter, we will review the impact of these technological developments on the understanding of molecular subtypes that promote prostate cancer initiation, progression, metastasis, and clinical aggression. In particular, we will focus on molecular subtypes that define clinically-relevant patient cohorts and assess how a better understanding of how these subtypes-in both somatic and germline genomes-may influence the clinical course for individual men diagnosed with prostate cancer.

Analysis of long non-coding RNAs in glioblastoma for prognosis prediction using weighted gene co-expression network analysis, Cox regression, and L1-LASSO penalization

Purpose

This study focused on identification of long non-coding RNAs (lncRNAs) for prognosis prediction of glioblastoma (GBM) through weighted gene co-expression network analysis (WGCNA) and L1-penalized least absolute shrinkage and selection operator (LASSO) Cox proportional hazards (PH) model.

Materials and methods

WGCNA was performed based on RNA expression profiles of GBM from Chinese Glioma Genome Atlas (CGGA), National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), and the European Bioinformatics Institute ArrayExpress for the identification of GBM-related modules. Subsequently, prognostic lncRNAs were determined using LASSO Cox PH model, followed by constructing a risk scoring model based on these lncRNAs. The risk score was used to divide patients into high- and low-risk groups. Difference in survival between groups was analyzed using Kaplan-Meier survival analysis. IncRNA-mRNA networks were built for the prognostic lncRNAs, followed by pathway enrichment analysis for these networks.

Results

This study identified eight preserved GBM-related modules, including 188 lncRNAs. Consequently, C20orf166-AS1, LINC00645, LBX2-AS1, LINC00565, LINC00641, and PRRT3-AS1 were identified by LASSO Cox PH model. A risk scoring model based on the lncRNAs was constructed that could divide patients into different risk groups with significantly different survival rates. Prognostic value of this six-lncRNA signature was validated in two independent sets. C20orf166-AS1 was associated with antigen processing and presentation and cell adhesion molecule pathways, involving nine common genes. LBX2-AS1, LINC00641, PRRT3-AS1, and LINC00565 were related to focal adhesion, extracellular matrix receptor interaction, and mitogen-activated protein kinase signaling pathways, which shared 12 common genes.

Conclusion

This prognostic six-lncRNA signature may improve prognosis prediction of GBM. This study reveals many pathways and genes involved in the mechanisms behind these lncRNAs.

Comparison of pre-processing methods for Infinium HumanMethylation450 BeadChip array

Motivation

Microarrays are widely used to quantify DNA methylation because they are economical, require only small quantities of input DNA and focus on well-characterized regions of the genome. However, pre-processing of methylation microarray data is challenging because of confounding factors that include background fluorescence, dye bias and the impact of germline polymorphisms. Therefore, we present valuable insights and a framework for those seeking the most optimal pre-processing method through a data-driven approach.

Results

Here, we show that Dasen is the optimal pre-processing methodology for the Infinium HumanMethylation450 BeadChip array in prostate cancer, a frequently employed platform for tumour methylome profiling in both the TCGA and ICGC consortia. We evaluated the impact of 11 pre-processing methods on batch effects, replicate variabilities, sensitivities and sample-to-sample correlations across 809 independent prostate cancer samples, including 150 reported for the first time in this study. Overall, Dasen is the most effective for removing artefacts and detecting biological differences associated with tumour aggressivity. Relative to the raw dataset, it shows a reduction in replicate variances of 67% and 76% for β- and M-values, respectively. Our study provides a unique pre-processing benchmark for the community with an emphasis on biological implications.

Availability and implementation

All software used in this study are publicly available as detailed in the article.

Contact

paul.boutros@oicr.on.ca.

Supplementary information

Supplementary data are available at Bioinformatics online.

Comprehensive analysis of gene expression and DNA methylation datasets identify valuable biomarkers for rheumatoid arthritis progression

Rheumatoid arthritis (RA) represents a common systemic autoimmune disease which lays chronic and persistent pain on patients. The purpose of our study is to identify novel RA-related genes and biological processes/pathways. All the datasets of this study, including gene expression and DNA methylation datasets of RA and OA samples, were obtained from the free available database, i.e. Gene Expression Omnibus (GEO). We firstly identified the differentially expressed genes (DEGs) between RA and OA samples through the limma package of R programming software followed by the functional enrichment analysis in the Database for Annotation, Visualization and Integrated Discovery (DAVID) for the exploring of potential involved biological processes/pathways of DEGs. For DNA methylation datasets, we used the IMA package for their normalization and identification of differential methylation genes (DMGs) in RA compared with OA samples. Comprehensive analysis of DEGs and DMGs was also conducted for the identification of valuable RA-related biomarkers. As a result, we obtained 394 DEGs and 363 DMGs in RA samples with the thresholds of |log2fold change|> 1 and p-value < 0.05, and |delta beta|> 0.2 and p-value < 0.05 respectively. Functional analysis of DEGs obtained immune and inflammation associated biological processes/pathways. Besides, several valuable biomarkers of RA, including BCL11B, CCDC88C, FCRLA and APOL6, were identified through the integrated analysis of gene expression and DNA methylation datasets. Our study should be helpful for the development of novel drugs and therapeutic methods for RA.

Promoter DNA methylation analysis reveals a combined diagnosis of CpG-based biomarker for prostate cancer

Background

Prostate cancer (PCa) is the most common tumor in elderly men. However, the specificity and sensitivity of serum prostate-specific antigen levels in PCa diagnosis are controversial. This study aims to reveal a novel diagnosis biomarker in PCa.

Materials and Methods

The differential methylated CpG sites between 423 primary PCa and 39 adjacent samples from The Cancer Genome Atlas (TCGA) on Illumina HumanMethylation 450 platform were analyzed. The diagnostic methylation markers were mined using the Prediction Analysis of Microarrays package in Bioconductor. Then, the Gene Expression Omnibus data was used for verification. Pyrosequencing was applied to improve methylation levels of five CpGs (cg06363129, cg08843517, cg05385513, cg07220448 and cg11417025).

Results

The area under curve of receiver operating characteristic of eight diagnostic methylation CpGs (cg06363129, cg08843517, cg03576469, cg05385513, cg07220448, cg11417025, cg20883831, and cg23824801) in TCGA data ranged from 0.910 to 0.939. Except for cg20883831 and cg23824801, the correlations between methylation levels of six other sites and their expressions in patients were significant (r > 0.5 and P < 0.001). The methylation level of cg06363129 was significantly different between the groups of Gleason Score (GS) = 7 and GS ≥ 8 (P < 0.05). Pyrosequencing in our samples confirmed that four diagnostic methylation sites (cg06363129, cg08843517, cg05385513, and cg11417025) had high diagnostic efficacy.

Conclusions

The combined diagnosis of four methylation CpGs sites (cg06363129, cg08843517, cg05385513, and cg11417025) in the gene promoter has high tissue specificity and diagnostic efficacy for PCa. Results revealed a novel potential biomarker for prostate cancer diagnosis.

Epigenetic signature of Gleason score and prostate cancer recurrence after radical prostatectomy

BACKGROUND

Identifying the subset of patients with clinically localized prostate cancer (PCa) at the highest risk of recurrence remains challenging, and better prognostic markers are needed. Gleason score is the best predictor of PCa aggressiveness and prognosis. In the present study, we generated an epigenetic signature based on high versus low Gleason score tumors and evaluated its ability to predict recurrence after radical prostatectomy.

METHODS

Genome-wide DNA methylation data from The Cancer Genome Atlas (TCGA; no. of patients = 333) and the elastic net method were used to generate an epigenetic signature by contrasting patients with high (8-10) versus low (≤6) Gleason score tumors. The signature was then tested in a cohort of 523 patients with clinically localized disease who had radical prostatectomy. Samples taken from the primary tumor were used for DNA methylation and mRNA expression profiling. Patients were followed for PCa recurrence on average for 8 years after diagnosis.

RESULTS

The epigenetic signature includes 52 differentially methylated CpG sites. In the testing cohort, the signature was associated with poorer recurrence-free survival (hazard ratio per 25 % increase = 1.78; 95 % confidence interval 1.48, 2.16). The signature significantly improved the area under the curve (AUC) for PCa recurrence compared to clinical-pathological parameters alone, particularly among patients diagnosed with Gleason score 7 tumors (0.64 vs. 0.76, P = 1.34E-4). Results were comparable for patients with Gleason 3 + 4 and those with 4 + 3 tumors. Gene Set Enrichment Analysis showed that higher levels of the signature were associated with increased expression of genes related to cell cycle proliferation and decreased expression of androgen-responsive genes.

CONCLUSIONS

This report shows evidence that DNA methylation patterns measured in prostate tumor cells are predictive of PCa aggressiveness. The epigenetic signature may have clinical utility to improve prognostication particularly in patients with intermediate Gleason score 7 tumors.

A cancer specific hypermethylation signature of the TERT promoter predicts biochemical relapse in prostate cancer: a retrospective cohort study

The identification of new biomarkers to differentiate between indolent and aggressive prostate tumors is an important unmet need. We examined the role of THOR (TERT Hypermethylated Oncological Region) as a diagnostic and prognostic biomarker in prostate cancer (PCa).We analyzed THOR in common cancers using genome-wide methylation arrays. Methylation status of the whole TERT gene in benign and malignant prostate samples was determined by MeDIP-Seq. The prognostic role of THOR in PCa was assessed by pyrosequencing on discovery and validation cohorts from patients who underwent radical prostatectomy with long-term follow-up data.Most cancers (n = 3056) including PCa (n = 300) exhibited hypermethylation of THOR. THOR was the only region within the TERT gene that is differentially methylated between normal and malignant prostate tissue (p < 0.0001). Also, THOR was significantly hypermethylated in PCa when compared to paired benign tissues (n = 164, p < 0.0001). THOR hypermethylation correlated with Gleason scores and was associated with tumor invasiveness (p = 0.0147). Five years biochemical progression free survival (BPFS) for PCa patients in the discovery cohort was 87% (95% CI 73-100) and 65% (95% CI 52-78) for THOR non-hypermethylated and hypermethylated cancers respectively (p = 0.01). Similar differences in BPFS were noted in the validation cohort (p = 0.03). Importantly, THOR was able to predict outcome in the challenging (Gleason 6 and 7 (3 + 4)) PCa (p = 0.007). For this group, THOR was an independent risk factor for BPFS with a hazard-ratio of 3.685 (p = 0.0247). Finally, THOR hypermethylation more than doubled the risk of recurrence across all PSA levels (OR 2.5, p = 0.02).

Calcium-permeable ion channels in the kidney

Calcium ions (Ca(2+)) are crucial for a variety of cellular functions. The extracellular and intracellular Ca(2+) concentrations are thus tightly regulated to maintain Ca(2+) homeostasis. The kidney, one of the major organs of the excretory system, regulates Ca(2+) homeostasis by filtration and reabsorption. Approximately 60% of the Ca(2+) in plasma is filtered, and 99% of that is reabsorbed by the kidney tubules. Ca(2+) is also a critical signaling molecule in kidney development, in all kidney cellular functions, and in the emergence of kidney diseases. Recently, studies using genetic and molecular biological approaches have identified several Ca(2+)-permeable ion channel families as important regulators of Ca(2+) homeostasis in kidney. These ion channel families include transient receptor potential channels (TRP), voltage-gated calcium channels, and others. In this review, we provide a brief and systematic summary of the expression, function, and pathological contribution for each of these Ca(2+)-permeable ion channels. Moreover, we discuss their potential as future therapeutic targets.

The T-box transcription factor 3 is a promising biomarker and a key regulator of the oncogenic phenotype of a diverse range of sarcoma subtypes

Sarcomas represent a complex group of malignant neoplasms of mesenchymal origin and their heterogeneity poses a serious diagnostic and therapeutic challenge. There is therefore a need to elucidate the molecular mechanisms underpinning the pathogenesis of the more than 70 distinguishable sarcoma subtypes. The transcription factor TBX3, a critical developmental regulator, is overexpressed in several cancers of epithelial origin where it contributes to tumorigenesis by different molecular mechanisms. However, the status and role of TBX3 in sarcomas have not been reported. Here we show that a diverse subset of soft tissue and bone sarcoma cell lines and patient-derived sarcoma tissues express high levels of TBX3. We further explore the significance of this overexpression using a small interferring RNA approach and demonstrate that TBX3 promotes the migratory ability of chondrosarcoma, rhabdomyosarcoma and liposarcoma cells but inhibits fibrosarcoma cell migration. This suggested that TBX3 may play a key role in the development of different sarcoma subtypes by functioning as either an oncoprotein or as a brake to prevent tumour progression. To further explore this, TBX3 knockdown and overexpression cell culture models were established using chondrosarcoma and fibrosarcoma cells as representatives of each scenario, and the resulting cells were characterized with regard to key features of tumorigenesis. Results from in vitro and in vivo assays reveal that, while TBX3 promotes substrate-dependent and -independent cell proliferation, migration and tumour formation in chondrosarcoma cells, it discourages fibrosarcoma formation. Our findings provide novel evidence linking TBX3 to cancers of mesenchymal origin. Furthermore, we show that TBX3 may be a biomarker for the diagnosis of histologically dynamic sarcoma subtypes and that it impacts directly on their oncogenic phenotype. Indeed, we reveal that TBX3 may exhibit oncogene or tumour suppressor activity in sarcomas, which suggests that its role in cancer progression may rely on cellular context.