Network-based analysis identifies epigenetic biomarkers of esophageal squamous cell carcinoma progression

Promises and challenges in pharmacoepigenetics

Pharmacogenetics, the study of how interindividual genetic differences affect drug response, does not explain all observed heritable variance in drug response. Epigenetic mechanisms, such as DNA methylation, and histone acetylation may account for some of the unexplained variances. Epigenetic mechanisms modulate gene expression and can be suitable drug targets and can impact the action of nonepigenetic drugs. Pharmacoepigenetics is the field that studies the relationship between epigenetic variability and drug response. Much of this research focuses on compounds targeting epigenetic mechanisms, called epigenetic drugs, which are used to treat cancers, immune disorders, and other diseases. Several studies also suggest an epigenetic role in classical drug response; however, we know little about this area. The amount of information correlating epigenetic biomarkers to molecular datasets has recently expanded due to technological advances, and novel computational approaches have emerged to better identify and predict epigenetic interactions. We propose that the relationship between epigenetics and classical drug response may be examined using data already available by (1) finding regions of epigenetic variance, (2) pinpointing key epigenetic biomarkers within these regions, and (3) mapping these biomarkers to a drug-response phenotype. This approach expands on existing knowledge to generate putative pharmacoepigenetic relationships, which can be tested experimentally. Epigenetic modifications are involved in disease and drug response. Therefore, understanding how epigenetic drivers impact the response to classical drugs is important for improving drug design and administration to better treat disease.

Multi-omic characterization of genome-wide abnormal DNA methylation reveals diagnostic and prognostic markers for esophageal squamous-cell carcinoma

This study investigates aberrant DNA methylations as potential diagnosis and prognosis markers for esophageal squamous-cell carcinoma (ESCC), which if diagnosed at advanced stages has <30% five-year survival rate. Comparing genome-wide methylation sites of 91 ESCC and matched adjacent normal tissues, we identified 35,577 differentially methylated CpG sites (DMCs) and characterized their distribution patterns. Integrating whole-genome DNA and RNA-sequencing data of the same samples, we found multiple dysregulated transcription factors and ESCC-specific genomic correlates of identified DMCs. Using featured DMCs, we developed a 12-marker diagnostic panel with high accuracy in our dataset and the TCGA ESCC dataset, and a 4-marker prognostic panel distinguishing high-risk patients. In-vitro experiments validated the functions of 4 marker host genes. Together these results provide additional evidence for the important roles of aberrant DNA methylations in ESCC development and progression. Our DMC-based diagnostic and prognostic panels have potential values for clinical care of ESCC, laying foundations for developing targeted methylation assays for future non-invasive cancer detection methods.

THYLENETETRAHYDROFOLATE REDUCTASE GENE POLYMORPHISMS AND SUSCEPTIBILITY TO ESOPHAGEAL CANCER: A CASE-CONTROL STUDY

BACKGROUND:

The enzyme methylenetetrahydrofolate reductase is engaged in DNA synthesis through folate metabolism. Inhibiting the activity of this enzyme increases the susceptibility to mutations, and damage and aberrant DNA methylation, which alters the gene expression of tumor suppressors and proto-oncogenes, potential risk factors for esophageal cancer.

AIMS:

This study aimed to investigate the association between methylenetetrahydrofolate reductase 677C>T and methylenetetrahydrofolate reductase 1298A>C polymorphisms and susceptibility to esophageal cancer, by assessing the distribution of genotypes and haplotypes between cases and controls, as well as to investigate the association of polymorphisms with clinical and epidemiological characteristics and survival.

METHODS:

A total of 109 esophageal cancer patients who underwent esophagectomy were evaluated, while 102 subjects constitute the control group. Genomic DNA was isolated from the peripheral blood buffy coat followed by amplification by polymerase chain reaction and real-time analysis. Logistic regression was used to assess associations between polymorphisms and the risk of developing esophageal cancer.

RESULTS:

There was no association for methylenetetrahydrofolate reductase 677C>T and methylenetetrahydrofolate reductase 1298A>C polymorphisms and haplotypes, with esophageal cancer susceptibility. Esophageal cancer patients carrying methylenetetrahydrofolate reductase 677TT polymorphism had higher risk of death from the disease. For polymorphic homozygote TT genotype, the risk of death significantly increased compared to wild-type genotype methylenetetrahydrofolate reductase 677CC (reference) cases (p=0.045; RR=2.22, 95%CI 1.02–4.83).

CONCLUSIONS:

There was no association between methylenetetrahydrofolate reductase 677C>T and methylenetetrahydrofolate reductase 1298A>C polymorphisms and esophageal cancer susceptibility risk. Polymorphic homozygote genotype methylenetetrahydrofolate reductase 677TT was associated with higher risk of death after surgical treatment for esophageal cancer.

Alterations in the Ca2+ toolkit in oesophageal adenocarcinoma

Aim:

To investigate alterations in transcription of genes, encoding Ca²⁺ toolkit proteins, in oesophageal adenocarcinoma (OAC) and to assess associations between gene expression, tumor grade, nodal-metastatic stage, and patient survival.

Methods:

The expression of 275 transcripts, encoding components of the Ca²⁺ toolkit, was analyzed in two OAC datasets: the Cancer Genome Atlas [via the University of Alabama Cancer (UALCAN) portal] and the oesophageal-cancer, clinical, and molecular stratification [Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS)] dataset. Effects of differential expression of these genes on patient survival were determined using Kaplan-Meier log-rank tests. OAC grade- and metastatic-stage status was investigated for a subset of genes. Adjustment for the multiplicity of testing was made throughout.

Results:

Of the 275 Ca²⁺-toolkit genes analyzed, 75 displayed consistent changes in expression between OAC and normal tissue in both datasets. The channel-encoding genes, N-methyl-D-aspartate receptor 2D (GRIN2D), transient receptor potential (TRP) ion channel classical or canonical 4 (TRPC4), and TRP ion channel melastatin 2 (TRPM2) demonstrated the greatest increase in expression in OAC in both datasets. Nine genes were consistently upregulated in both datasets and were also associated with improved survival outcomes. The 6 top-ranking genes for the weighted significance of altered expression and survival outcomes were selected for further analysis: voltage-gated Ca²⁺ channel subunit α 1D (CACNA1D), voltage-gated Ca²⁺ channel auxiliary subunit α2 δ4 (CACNA2D4), junctophilin 1 (JPH1), acid-sensing ion channel 4 (ACCN4), TRPM5, and secretory pathway Ca²⁺ ATPase 2 (ATP2C2). CACNA1D, JPH1, and ATP2C2 were also upregulated in advanced OAC tumor grades and nodal-metastatic stages in both datasets.

Conclusions:

This study has unveiled alterations of the Ca²⁺ toolkit in OAC, compared to normal tissue. Such Ca²⁺ signalling findings are consistent with those from studies on other cancers. Genes that were consistently upregulated in both datasets might represent useful markers for patient diagnosis. Genes that were consistently upregulated, and which were associated with improved survival, might be useful markers for patient outcome. These survival-associated genes may also represent targets for the development of novel chemotherapeutic agents.

Network-Based Identification of Altered Stem Cell Pluripotency and Calcium Signaling Pathways in Metastatic Melanoma

Malignancy of cancer has been linked to distinct subsets of stem-like cells, the so-called cancer stem cells (CSCs), which persist during treatment and seem to lead to drug-resistant recurrence. Metastatic spread of cancer cells is one of the hallmarks of malignancy and contributes to most human melanoma-related deaths. Recently, overlapping groups of proteins and pathways were shown to regulate stem cell migration and cancer metastasis, raising the question of whether genes/proteins involved in stem cell pluripotency may have important implications when applied to the biology of cancer metastasis. Furthermore, it is well known that ion channels and receptors, particularly those responsible for calcium (Ca²⁺) signal generation, are critical in determining the cellular fate of stem cells (SCs). In the present study, we searched for evidence of altered stem cell pluripotency and Ca²⁺ signaling-related genes in the context of melanoma metastasis. We did this by using network analysis of gene expression in tissue biopsies from three different independent datasets of patients. First, we created an in silico network model (“STEMCa” interactome) showing the landscape of interactions between stem cell pluripotency and Ca²⁺ signaling-related genes/proteins, and demonstrated that around 51% (151 out of 294) of the genes within this model displayed significant changes of expression (False Discovery Rate (FDR), corrected p-value < 0.05) in at least one of the datasets of melanoma metastasis when compared with primary tumor biopsies (controls). Analysis of the properties (degree and betweenness) of the topological network revealed 27 members as the most central hub (HB) and nonhub-bottlenecks (NH-B) among the 294 genes/proteins of the whole interactome. From those representative genes, CTNNB1, GNAQ, GSK3B, GSTP1, MAPK3, PPP1CC, PRKACA, and SMAD4 showed equal up- or downregulation (corrected p-value < 0.05) in at least 2 independent datasets of melanoma metastases samples and PTPN11 showed upregulation (corrected p-value < 0.05) in three of them when compared with control samples. We postulate that altered expression of stem cell pluripotency and Ca²⁺ signaling pathway-related genes may contribute to the metastatic transformation, with these central members being an optimal candidate group of biomarkers and in silico therapeutic targets for melanoma metastasis, which deserve further investigation.

Promoter methylation and expression of Raf kinase inhibitory protein in esophageal squamous cell carcinoma

Raf kinase inhibitory protein (RKIP) regulates multiple cellular processes, and its downregulation is associated with distinct human cancers. In the present study, the status of RKIP promoter methylation, as well as its expression and clinical significance in esophageal squamous cell carcinoma (ESCC), were examined. The promoter methylation status in the 5'-CpG island of the RKIP gene and the expression level of the RKIP protein were examined using a modified methylation-specific polymerase chain reaction (MSP) method and immunohistochemical staining, respectively, in 77 ESCC samples and matched paratumor normal tissues. The incidence of RKIP promoter methylation was significantly higher in tumor samples (75.3%) than in the matched normal tissues (27.3%; P<0.001). A higher incidence of promoter methylation was also detected in poorly differentiated cancers (93.5%) compared with well-differentiated cancers (50.0%; P<0.001), as well as in tumor samples with positive lymph node metastasis (86.7%) compared with those with negative lymph node metastasis (59.4%; P<0.001). Consistent with the promoter methylation status, the expression level of RKIP was significantly reduced in cancer tissues (36.4%) compared with matched normal tissues (76.6%; P<0.01), as well as in cancers with positive lymph node metastasis (24.4%) compared with those with negative lymph node metastasis (53.1%; P=0.01). Promoter methylation-induced gene silencing significantly correlated with the down regulation of RKIP and the development of ESCC. The results of the present study suggested that the methylation status of the RKIP promoter, when combined with its expression level, may serve as a biomarker for predicting the biological behaviors of ESCC.

Epigenetic and genetic deregulation in cancer target distinct signaling pathway domains

Cancer is characterized by both genetic and epigenetic alterations. While cancer driver mutations and copy-number alterations have been studied at a systems-level, relatively little is known about the systems-level patterns exhibited by their epigenetic counterparts. Here we perform a pan-cancer wide systems-level analysis, mapping candidate cancer-driver DNA methylation (DNAm) alterations onto a human interactome. We demonstrate that functional DNAm alterations in cancer tend to map to nodes of lower connectivity and inter-connectivity, compared to the corresponding alterations at the genomic level. We find that epigenetic alterations are relatively over-represented in extracellular and transmembrane signaling domains, whereas cancer genes undergoing amplification or deletion tend to be enriched within the intracellular domain. A pan-cancer wide meta-analysis identifies WNT and chemokine signaling, as two key pathways where epigenetic deregulation preferentially targets extracellular components. We further pinpoint specific chemokine ligands/receptors whose epigenetic deregulation associates with key epigenetic enzymes, representing potential targets for epigenetic therapy. Our results suggest that epigenetic deregulation in cancer not only targets tissue-specific transcription factors, but also modulates signaling within the extra-cellular domain, providing novel system-level insight into the potential distinctive role of genetic and epigenetic alterations in cancer.

A CpG-methylation-based assay to predict survival in clear cell renal cell carcinoma

Clear cell renal cell carcinomas (ccRCCs) display divergent clinical behaviours. Molecular markers might improve risk stratification of ccRCC. Here we use, based on genome-wide CpG methylation profiling, a LASSO model to develop a five-CpG-based assay for ccRCC prognosis that can be used with formalin-fixed paraffin-embedded specimens. The five-CpG-based classifier was validated in three independent sets from China, United States and the Cancer Genome Atlas data set. The classifier predicts the overall survival of ccRCC patients (hazard ratio=2.96−4.82; P=3.9 × 10⁻⁶−2.2 × 10⁻⁹), independent of standard clinical prognostic factors. The five-CpG-based classifier successfully categorizes patients into high-risk and low-risk groups, with significant differences of clinical outcome in respective clinical stages and individual ‘stage, size, grade and necrosis' scores. Moreover, methylation at the five CpGs correlates with expression of five genes: PITX1, FOXE3, TWF2, EHBP1L1 and RIN1. Our five-CpG-based classifier is a practical and reliable prognostic tool for ccRCC that can add prognostic value to the staging system.

Using molecular markers is a useful way to predict the prognosis of cancer patients. Here, Wei et al. describe a five gene methylation signature that can predict the prognosis of renal clear cell cancer and validate its use in multiple patient cohorts.

Personalized targeted therapy for esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma continues to heavily burden clinicians worldwide. Researchers have discovered the genomic landscape of esophageal squamous cell carcinoma, which holds promise for an era of personalized oncology care. One of the most pressing problems facing this issue is to improve the understanding of the newly available genomic data, and identify the driver-gene mutations, pathways, and networks. The emergence of a legion of novel targeted agents has generated much hope and hype regarding more potent treatment regimens, but the accuracy of drug selection is still arguable. Other problems, such as cancer heterogeneity, drug resistance, exceptional responders, and side effects, have to be surmounted. Evolving topics in personalized oncology, such as interpretation of genomics data, issues in targeted therapy, research approaches for targeted therapy, and future perspectives, will be discussed in this editorial.

The variation game: Cracking complex genetic disorders with NGS and omics data

Tremendous advances in Next Generation Sequencing (NGS) and high-throughput omics methods have brought us one step closer towards mechanistic understanding of the complex disease at the molecular level. In this review, we discuss four basic regulatory mechanisms implicated in complex genetic diseases, such as cancer, neurological disorders, heart disease, diabetes, and many others. The mechanisms, including genetic variations, copy-number variations, posttranscriptional variations, and epigenetic variations, can be detected using a variety of NGS methods. We propose that malfunctions detected in these mechanisms are not necessarily independent, since these malfunctions are often found associated with the same disease and targeting the same gene, group of genes, or functional pathway. As an example, we discuss possible rewiring effects of the cancer-associated genetic, structural, and posttranscriptional variations on the protein-protein interaction (PPI) network centered around P53 protein. The review highlights multi-layered complexity of common genetic disorders and suggests that integration of NGS and omics data is a critical step in developing new computational methods capable of deciphering this complexity.