Identification of a panel of sensitive and specific DNA methylation markers for squamous cell lung cancer

Identifying a Risk Signature of Methylation-Driven Genes as a Predictor of Survival Outcome for Colon Cancer Patients

Aberrant expression of gene is driven by its promoter methylation and is the key molecular basis of carcinogenic processes. This study aimed at identifying a risk signature of methylation-driven (MD) genes and evaluating its prognostic value for colon cancer (CC) patients. The expression profiles of methylation and mRNA in CC samples were obtained from the TCGA database, and the MethylMix algorithm was used to identify MD genes. The relationships between their expression levels and overall survival (OS) of CC patients were analyzed, and a prognostic signature of MD genes was established. The risk score of gene signature was calculated, and the median was used to divide all patients into high (H) and low (L) risk groups. The prognostic value of gene signature was tested by the TCGA cohort and an independent validation cohort (GSE17538 dataset). In total, 69 MD genes were identified, and 7 were associated with OS of CC patients. Ultimately, 4 (TWIST1, LDOC1, EPHX3, and STC2) were screened out to establish a risk signature. The H-risk patients (>0.923) had a worse OS than L-risk patients (≤0.923) in both the TCGA (5-year cumulative survival: 52.9% vs 72.0%, P=0.005) and GSE17538 cohort (49.4% vs 69.3%, P=0.004). The AUC values of MD genes signature for the prediction of 3- and 5-year OS were 0.648 and 0.643 in the TCGA dataset and 0.634 and 0.624 in the GSE17538 dataset, respectively. The risk signature of four MD genes was identified as an independent predictor of OS for CC patients (HR for TCGA dataset: 2.071, 95% CI=1.196-3.586, P=0.009; HR for GSE17538 dataset: 2.021, 95% CI=1.290-3.166, P=0.002). The risk signature of four MD genes might be a useful prognostic tool and help doctors improve the clinical management of CC patients.

Promoter DNA methylation patterns in oral, laryngeal and oropharyngeal anatomical regions are associated with tumor differentiation, nodal involvement and survival

Differentially methylated regions (DMRs) can be used as head and neck squamous cell carcinoma (HNSCC) diagnostic, prognostic and therapeutic targets in precision medicine workflows. DNA from 21 HNSCC and 10 healthy oral tissue samples was hybridized to a genome-wide tiling array to identify DMRs in a discovery cohort. Downstream analyses identified differences in promoter DNA methylation patterns in oral, laryngeal and oropharyngeal anatomical regions associated with tumor differentiation, nodal involvement and survival. Genome-wide DMR analysis showed 2,565 DMRs common to the three subsites. A total of 738 DMRs were unique to laryngeal cancer (n=7), 889 DMRs were unique to oral cavity cancer (n=10) and 363 DMRs were unique to pharyngeal cancer (n=6). Based on the genome-wide analysis and a Gene Ontology analysis, 10 candidate genes were selected to test for prognostic value and association with clinicopathological features. TIMP3 was associated with tumor differentiation in oral cavity cancer (P=0.039), DAPK1 was associated with nodal involvement in pharyngeal cancer (P=0.017) and PAX1 was associated with tumor differentiation in laryngeal cancer (P=0.040). A total of five candidate genes were selected, DAPK1, CDH1, PAX1, CALCA and TIMP3, for a prevalence study in a larger validation cohort: Oral cavity cancer samples (n=42), pharyngeal cancer tissues (n=25) and laryngeal cancer samples (n=52). PAX1 hypermethylation differed across HNSCC anatomic subsites (P=0.029), and was predominantly detected in laryngeal cancer. Kaplan-Meier survival analysis (P=0.043) and Cox regression analysis of overall survival (P=0.001) showed that DAPK1 methylation is associated with better prognosis in HNSCC. The findings of the present study showed that the HNSCC subsites oral cavity, pharynx and larynx display substantial differences in aberrant DNA methylation patterns, which may serve as prognostic biomarkers and therapeutic targets.

Epigenetic regulation in lung cancer

Lung cancer is indeed a major cause of cancer-related deaths worldwide. The development of tumors involves a complex interplay of genetic, epigenetic, and environmental factors. Epigenetic mechanisms, including DNA methylation (DNAm), histone modifications, and microRNA expression, play a crucial role in this process. Changes in DNAm patterns can lead to the silencing of important genes involved in cellular functions, contributing to the development and progression of lung cancer. MicroRNAs and exosomes have also emerged as reliable biomarkers for lung cancer. They can provide valuable information about early diagnosis and treatment assessment. In particular, abnormal hypermethylation of gene promoters and its effects on tumorigenesis, as well as its roles in the Wnt signaling pathway, have been extensively studied. Epigenetic drugs have shown promise in the treatment of lung cancer. These drugs target the aberrant epigenetic modifications that are involved in the development and progression of the disease. Several factors have been identified as drug targets in non-small cell lung cancer. Recently, combination therapy has been discussed as a successful strategy for overcoming drug resistance. Overall, understanding the role of epigenetic mechanisms and their targeting through drugs is an important area of research in lung cancer treatment.

Pre-clinical lung squamous cell carcinoma mouse models to identify novel biomarkers and therapeutic interventions

Primary lung carcinoma or lung cancer (LC) is classified into small-cell or non-small-cell (NSCLC) lung carcinoma. Lung squamous cell carcinoma (LSCC) is the second most common subtype of NSCLC responsible for 30% of all LCs, and its survival remains low with only 24% of patients living for five years or longer post-diagnosis primarily due to the advanced stage of tumors at the time of diagnosis. The pathogenesis of LSCC is still poorly understood and has hampered the development of effective diagnostics and therapies. This review highlights the known risk factors, genetic and epigenetic alterations, miRNA biomarkers linked to the development and diagnosis of LSCC and the lack of therapeutic strategies to target specifically LSCC. We will also discuss existing animal models of LSCC including carcinogen induced, transgenic and xenograft mouse models, and their advantages and limitations along with the chemopreventive studies and molecular studies conducted using them. The importance of developing new and improved mouse models will also be discussed that will provide further insights into the initiation and progression of LSCC, and enable the identification of new biomarkers and therapeutic targets.

Multiplex Digital Methylation-Specific PCR for Noninvasive Screening of Lung Cancer

There remains tremendous interest in developing liquid biopsy assays for detection of cancer-specific alterations, such as mutations and DNA methylation, in cell-free DNA (cfDNA) obtained through noninvasive blood draws. However, liquid biopsy analysis is often challenging due to exceedingly low fractions of circulating tumor DNA (ctDNA), necessitating the use of extended tumor biomarker panels. While multiplexed PCR strategies provide advantages such as higher throughput, their implementation is often hindered by challenges such as primer-dimers and PCR competition. Alternatively, digital PCR (dPCR) approaches generally offer superior performance, but with constrained multiplexing capability. This paper describes development and validation of the first multiplex digital methylation-specific PCR (mdMSP) platform for simultaneous analysis of four methylation biomarkers for liquid-biopsy-based detection of non-small cell lung cancer (NSCLC). mdMSP employs a microfluidic device containing four independent, but identical modules, housing a total of 40 160 nanowells. Analytical validation of the mdMSP platform demonstrates multiplex detection at analytical specificities as low as 0.0005%. The clinical utility of mdMSP is also demonstrated in a cohort of 72 clinical samples of low-volume liquid biopsy specimens from patients with computed tomography (CT)-scan indeterminant pulmonary nodules, exhibiting superior clinical performance when compared to traditional MSP assays for noninvasive detection of early-stage NSCLC.

Establishing a Prediction Model for the Efficacy of Platinum-Based Chemotherapy in NSCLC Based on a Two Cohorts GWAS Study

Platinum drugs combined with other agents have been the first-line treatment for non-small cell lung cancer (NSCLC) in the past decades. To better evaluate the efficacy of platinum-based chemotherapy in NSCLC, we establish a platinum chemotherapy response prediction model. Here, a total of 217 samples from Xiangya Hospital of Central South University were selected as the discovery cohort for a genome-wide association analysis (GWAS) to select SNPs. Another 216 samples were genotyped as a validation cohort. In the discovery cohort, using linkage disequilibrium (LD) pruning, we extract a subset that does not contain correlated SNPs. The SNPs with p < 10^-3 and p < 10^-4 are selected for modeling. Subsequently, we validate our model in the validation cohort. Finally, clinical factors are incorporated into the model. The final model includes four SNPs (rs7463048, rs17176196, rs527646, and rs11134542) as well as two clinical factors that contributed to the efficacy of platinum chemotherapy in NSCLC, with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.726.

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study

BACKGROUND

Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window.

OBJECTIVES

This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort.

METHODS

We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data.

RESULTS

We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease.

CONCLUSIONS

This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

Novel multiplex stool-based assay for the detection of early-stage colon cancer in a Chinese population

BACKGROUND

Stool DNA (sDNA) methylation analysis is a promising, noninvasive approach for colorectal cancer screening; however, reliable biomarkers for detecting early-stage colon cancer (ECC) are lacking, particularly in the Chinese population.

AIM

To identify a novel stool-based assay that can improve the effectiveness of ECC screening.

METHODS

A blinded case-control study was performed using archived stool samples from 125 ECC patients, and 125 control subjects with normal colonoscopy. The cohort was randomly divided into training and test sets at a 1.5:1 ratio. Targeted bisulfite sequencing (TBSeq) was conducted on five pairs of preoperative and postop-erative sDNA samples from ECC patients to identify DNA methylation biomarkers, which were validated using pyrosequencing. By logistic regression analysis, a multiplex stool-based assay was developed in the training set, and the detection performance was further assessed in the test set and combined set. The χ² test was used to investigate the association of detection sensitivity with clinico-pathological features.

RESULTS

Following TBSeq, three hypermethylated cytosine-guanine sites were selected as biomarkers, including paired box 8, Ras-association domain family 1 and secreted frizzled-related protein 2, which differed between the groups and were involved in important cancer pathways. An sDNA panel containing the three biomarkers was constructed with a logistic model. Receiver operating characteristic (ROC) analysis revealed that this panel was superior to the fecal immunochemical test (FIT) or serum carcinoembryonic antigen for the detection of ECC. We further found that the combination of the sDNA panel with FIT could improve the screening effectiveness. In the combined set, the sensitivity, specificity and area under the ROC curve for this multiplex assay were 80.0%, 93.6% and 0.918, respectively, and the performance remained excellent in the subgroup analysis by tumor stage. In addition, the detection sensitivity did not differ with tumor site, tumor stage, histological differentiation, age or sex, but was significantly higher in T4 than in T1-3 stage tumors (P = 0.041).

CONCLUSION

We identified a novel multiplex stool-based assay combining sDNA methylation biomarkers and FIT, which could detect ECC with high sensitivity and specificity throughout the colon, showing a promising application perspective.

Paired-like homeodomain 2B contributes to tumour progression and anti-autophagy in human lung cancer

Paired-like homeodomain transcription factor 2 (PITX2) is well known to play an essential role in normal embryonic development. Emerging evidence suggests that PITX2 may be involved in human tumorigenesis, but the role of PITX2 in tumour progression remains largely unclear. The expression levels of PITX2 in lung cancer cells were determined by qRT-PCR and Western blot analyses. Gain- and loss-of-function experiments were conducted to investigate the biological roles of PITX2 in the phenotype of lung cancer cells. Immunofluorescence staining and transmission electron microscopy were used to observe autophagy. The expression level and clinical significance of PITX2 were determined in a Taiwanese cohort and the Gene Expression Omnibus (GEO) database, respectively. Here, we show that PITX2B is the most abundant isoform of the bicoid homeodomain family in lung cancer cells. The enforced expression of PITX2B promoted lung cancer tumorigenesis and progression in vitro and in vivo. The mechanistic analysis revealed that the nuclear localization of PITX2B is correlated with its oncogenic functions and two important nuclear localization signals. In addition, PITX2B knockdown in lung cancer cells caused a marked increase in autophagy and apoptosis, suggesting that PITX2B plays an important role in lung cancer cell survival. Moreover, a high expression of PITX2B was associated with a poor overall survival (P<0.05) in both Taiwanese non-small-cell lung cancer patients and GEO lung cancer cohorts. These results provide new insight into the contribution of PITX2B to lung cancer progression, implicate PITX2B as an important component of cell survival signals and further establish PITX2B as a therapeutic target for lung cancer treatment.

Alternative Promoter Use Governs the Expression of IgLON Cell Adhesion Molecules in Histogenetic Fields of the Embryonic Mouse Brain

The members of the IgLON superfamily of cell adhesion molecules facilitate fundamental cellular communication during brain development, maintain functional brain circuitry, and are associated with several neuropsychiatric disorders such as depression, autism, schizophrenia, and intellectual disabilities. Usage of alternative promoter-specific 1a and 1b mRNA isoforms in Lsamp, Opcml, Ntm, and the single promoter of Negr1 in the mouse and human brain has been previously described. To determine the precise spatiotemporal expression dynamics of Lsamp, Opcml, Ntm isoforms, and Negr1, in the developing brain, we generated isoform-specific RNA probes and carried out in situ hybridization in the developing (embryonic, E10.5, E11.5, 13.5, 17; postnatal, P0) and adult mouse brains. We show that promoter-specific expression of IgLONs is established early during pallial development (at E10.5), where it remains throughout its differentiation through adulthood. In the diencephalon, midbrain, and hindbrain, strong expression patterns are initiated a few days later and begin fading after birth, being only faintly expressed during adulthood. Thus, the expression of specific IgLONs in the developing brain may provide the means for regionally specific functionality as well as for specific regional vulnerabilities. The current study will therefore improve the understanding of how IgLON genes are implicated in the development of neuropsychiatric disorders.

High-Dimensional Mediation Analysis With Confounders in Survival Models

Mediation analysis is a common statistical method for investigating the mechanism of environmental exposures on health outcomes. Previous studies have extended mediation models with a single mediator to high-dimensional mediators selection. It is often assumed that there are no confounders that influence the relations among the exposure, mediator, and outcome. This is not realistic for the observational studies. To accommodate the potential confounders, we propose a concise and efficient high-dimensional mediation analysis procedure using the propensity score for adjustment. Results from simulation studies demonstrate the proposed procedure has good performance in mediator selection and effect estimation compared with methods that ignore all confounders. Of note, as the sample size increases, the performance of variable selection and mediation effect estimation is as well as the results shown in the method which include all confounders as covariates in the mediation model. By applying this procedure to a TCGA lung cancer data set, we find that lung cancer patients who had serious smoking history have increased the risk of death via the methylation markers cg21926276 and cg20707991 with significant hazard ratios of 1.2093 (95% CI: 1.2019-1.2167) and 1.1388 (95% CI: 1.1339-1.1438), respectively.

Ultrasensitive detection of tumor-specific mutations in saliva of patients with oral cavity squamous cell carcinoma

BACKGROUND

Oral cavity squamous cell carcinoma (OCSCC) is the most common head and neck malignancy. Although the survival rate of patients with advanced-stage disease remains approximately 20% to 60%, when detected at an early stage, the survival rate approaches 80%, posing a pressing need for a well validated profiling method to assess patients who have a high risk of developing OCSCC. Tumor DNA detection in saliva may provide a robust biomarker platform that overcomes the limitations of current diagnostic tests. However, there is no routine saliva-based screening method for patients with OCSCC.

METHODS

The authors designed a custom next-generation sequencing panel with unique molecular identifiers that covers coding regions of 7 frequently mutated genes in OCSCC and applied it on DNA extracted from 121 treatment-naive OCSCC tumors and matched preoperative saliva specimens.

RESULTS

By using stringent variant-calling criteria, mutations were detected in 106 tumors, consistent with a predicted detection rate ≥88%. Moreover, mutations identified in primary malignancies were also detected in 93% of saliva samples. To ensure that variants are not errors resulting in false-positive calls, a multistep analytical validation of this approach was performed: 1) re-sequencing of 46 saliva samples confirmed 88% of somatic variants; 2) no functionally relevant mutations were detected in saliva samples from 11 healthy individuals without a history of tobacco or alcohol; and 3) using a panel of 7 synthetic loci across 8 sequencing runs, it was confirmed that the platform developed is reproducible and provides sensitivity on par with droplet digital polymerase chain reaction.

CONCLUSIONS

The current data highlight the feasibility of somatic mutation identification in driver genes in saliva collected at the time of OCSCC diagnosis.

Enhancer of zeste homolog 2-mediated paired box 8 methylation promotes gastrointestinal stromal tumor progression through Wnt4 downregulation

Gastrointestinal stromal tumor (GIST) is a refractory malignant tumor without satisfactory therapy. In recent years, aberrant gene methylation has been highlighted as an inducer for tumor progression. In this study, we explored whether enhancer of zeste homolog 2 (EZH2)-mediated paired box 8 (PAX8) methylation affects GIST development through regulation of Wnt4. A total of 50 cases of GIST tissues were collected and the human GIST cell lines were cultured. PAX8 methylation was examined using MS-PCR. Following loss- and gain-function approaches, GIST cell proliferation, migration, invasion, and apoptosis were examined by CCK-8 assay, Transwell assay and flow cytometry. The expression of proliferation related factors and apoptosis related factors was determined. Finally, xenograft tumors in nude mice were observed to examine in vivo tumorigenicity of GIST cells. Downregulated PAX8 and upregulated EZH2 expression was found in GIST tissues. Overexpression of PAX8 or suppression of PAX8 methylation using DNA methyltransferase inhibitor 5-Aza-dC inhibited the proliferation, migration, and invasion of GIST cells while promoting their apoptosis (diminished PCNA, Ki67 and Bcl-2, elevated Bax, and cleaved caspase-3). EZH2 promoted PAX8 methylation to inhibit its expression. Downregulated PAX8 decreased Wnt4 expression to accelerate GIST progression both in vitro and in vivo. Collectively, EZH2 inhibits PAX8 expression by promoting its methylation, which thus downregulates Wnt4 expression, thereby promoting the development of GIST.

Performance Evaluation of SHOX2 and RASSF1A Methylation for the Aid in Diagnosis of Lung Cancer Based on the Analysis of FFPE Specimen

Emerging molecular diagnostic methods are more sensitive and objective, which can overcome the intrinsic failings of morphological diagnosis. Here, a RT-PCR-based in vitro diagnostic test kit (LungMe^®) was developed and characterized to simultaneously quantify the DNA methylation of SHOX2 and RASSF1A in FFPE tissue specimens. The clinical manifestations were evaluated in 251 FFPE samples with specificity and sensitivity of 90.4 and 89.8%, respectively. Furthermore, the quantitative analysis shows that the degree of SHOX2 methylation was correlated with the stages of lung cancer, but not in the case of RASSF1A. Our observation indicated that the DNA methylation of SHOX2 and RASSF1A may play different roles in cancer development. Comparison of the methylation levels of SHOX2 and RASSF1A between cancer and cancer-adjacent specimens (n = 30), showed they have “epigenetic field defect”. As additional clinical validation, the hypermethylation of SHOX2 and RASSF1A was detected not only in surgical operative specimens, but also in histopathological negative puncture biopsies. SHOX2 and RASSF1A methylation detection can be used to increase sensitivity and NPV, which provide us with a more accurate method of differential diagnosis and are likely to be rapidly applied in clinical examinations.

Non coding RNAs as the critical factors in chemo resistance of bladder tumor cells

BACKGROUND

Bladder cancer (BCa) is the ninth frequent and 13th leading cause of cancer related deaths in the world which is mainly observed among men. There is a declining mortality rates in developed countries. Although, the majority of BCa patients present Non-Muscle-Invasive Bladder Cancer (NMIBC) tumors, only 30% of patients suffer from muscle invasion and distant metastases. Radical cystoprostatectomy, radiation, and chemotherapy have proven to be efficient in metastatic tumors. However, tumor relapse is observed in a noticeable ratio of patients following the chemotherapeutic treatment. Non-coding RNAs (ncRNAs) are important factors during tumor progression and chemo resistance which can be used as diagnostic and prognostic biomarkers of BCa.

MAIN BODY

In present review we summarized all of the lncRNAs and miRNAs associated with chemotherapeutic resistance in bladder tumor cells.

CONCLUSIONS

This review paves the way of introducing a prognostic panel of ncRNAs for the BCa patients which can be useful to select a proper drug based on the lncRNA profiles of patients to reduce the cytotoxic effects of chemotherapy in such patients.

mRNA expression and DNA methylation analysis of the inhibitory mechanism of H2O2 on the proliferation of A549 cells

Reactive oxygen species, particularly hydrogen peroxide (H₂O₂), can induce proliferation inhibition and death of A549 cells via oxidative stress. Oxidative stress has effect on DNA methylation. Oxidative stress and DNA methylation feature a common denominator: The one carbon cycle. To explore the inhibitory mechanism of H₂O₂ on the proliferation of lung cancer cells, the present study analysed the mRNA expression and methylation profiles in A549 cells treated with H₂O₂ for 24 h, as adenocarcinoma is the most common pathological type of lung cancer. The DNA methylation profile was constructed using reduced representation bisulphite sequencing, which identified 29,755 differentially methylated sites (15,365 upregulated and 14,390 downregulated), and 1,575 differentially methylated regions located in the gene promoters were identified using the methylKit. Analysis of the assocaition between gene expression and methylation levels revealed that several genes were downregulated and hypermethylated, including cyclin-dependent kinase inhibitor 3, denticleless E3 ubiquitin protein ligase homolog, centromere protein (CENP)F, kinesin family member (KIF)20A, CENPA, KIF11, PCNA clamp-associated factor and GINS complex subunit 2, which may be involved in the inhibitory process of H₂O₂ on the proliferation of A549 cells.

Emerging roles for the GPI-anchored tumor suppressor OPCML in cancers

OPCML is a highly conserved glycosyl phosphatidylinositol (GPI)-anchored protein belonging to the IgLON family of cell adhesion molecules. OPCML functions as a tumor suppressor and is silenced in over 80% of ovarian cancers by loss of heterozygosity and by epigenetic mechanisms. OPCML inactivation is also observed in many other cancers suggesting a conservation of tumor suppressor function. Although epigenetic silencing and subsequent loss of OPCML expression correlate with poor progression-free and overall patient survival, its mechanism of action is only starting to be fully elucidated. Recent discoveries have demonstrated that OPCML exerts its tumor suppressor effect by inhibiting several cancer hallmark phenotypes in vitro and abrogating tumorigenesis in vivo, by downregulating/inactivating a specific spectrum of Receptor Tyrosine Kinases (RTKs), including EphA2, FGFR1, FGFR3, HER2, HER4, and AXL. This modulation of RTKs can also sensitize ovarian and breast cancers to lapatinib, erlotinib, and anti-AXL therapies. Furthermore, OPCML has also been shown to function in synergy with the tumor suppressor phosphatase PTPRG to inactivate pro-metastatic RTKs such as AXL. Recently, the identification of inactivating point mutations and the elucidation of the crystal structure of OPCML have provided valuable insights into its structure-function relationships, giving rise to its potential as an anti-cancer therapeutic.

Downregulation of hsa-microRNA-204-5p and identification of its potential regulatory network in non-small cell lung cancer: RT-qPCR, bioinformatic- and meta-analyses

Background

Pulmonary malignant neoplasms have a high worldwide morbidity and mortality, so the study of these malignancies using microRNAs (miRNAs) has attracted great interest and enthusiasm. The aim of this study was to determine the clinical effect of hsa-microRNA-204-5p (miR-204-5p) and its underlying molecular mechanisms in non-small cell lung cancer (NSCLC).

Methods

Expression of miR-204-5p was investigated by real-time quantitative PCR (RT-qPCR). After data mining from public online repositories, several integrative assessment methods, including receiver operating characteristic (ROC) curves, hazard ratios (HR) with 95% confidence intervals (95% CI), and comprehensive meta-analyses, were conducted to explore the expression and clinical utility of miR-204-5p. The potential objects regulated and controlled by miR-204-5p in the course of NSCLC were identified by estimated target prediction and analysis. The regulatory network of miR-204-5p, with its target genes and transcription factors (TFs), was structured from database evidence and literature references.

Results

The expression of miR-204-5p was downregulated in NSCLC, and the downtrend was related to gender, histological type, vascular invasion, tumor size, clinicopathologic grade and lymph node metastasis (P<0.05). MiR-204-5p was useful in prognosis, but was deemed unsuitable at present as an auxiliary diagnostic or prognostic risk factor for NSCLC due to the lack of statistical significance in meta-analyses and absence of large-scale investigations. Gene enrichment and annotation analyses identified miR-204-5p candidate targets that took part in various genetic activities and biological functions. The predicted TFs, like MAX, MYC, and RUNX1, interfered in regulatory networks involving miR-204-5p and its predicted hub genes, though a modulatory loop or axis of the miRNA-TF-gene that was out of range with shortage in database prediction, experimental proof and literature confirmation.

Conclusions

The frequently observed decrease in miR-204-5p was helpful for NSCLC diagnosis. The estimated target genes and TFs contributed to the anti-oncogene effects of miR-204-5p.

Integrative analysis of DNA methylation-driven genes for the prognosis of lung squamous cell carcinoma using MethylMix

Background: DNA methylation acts as a key component in epigenetic modifications of genomic function and functions as disease-specific prognostic biomarkers for lung squamous cell carcinoma (LUSC). This present study aimed to identify methylation-driven genes as prognostic biomarkers for LUSC using bioinformatics analysis. Materials and Methods: Differentially expressed RNAs were obtained using the edge R package from 502 LUSC tissues and 49 adjacent non-LUSC tissues. Differentially methylated genes were obtained using the limma R package from 504 LUSC tissues and 69 adjacent non-LUSC tissues. The methylation-driven genes were obtained using the MethylMix R package from 500 LUSC tissues with matched DNA methylation data and gene expression data and 69 non-LUSC tissues with DNA methylation data. Gene ontology and ConsensusPathDB pathway analysis were performed to analyze the functional enrichment of methylation-driven genes. Univariate and multivariate Cox regression analyses were performed to identify the independent effect of differentially methylated genes for predicting the prognosis of LUSC. Results: A total of 44 methylation-driven genes were obtained. Univariate and multivariate Cox regression analyses showed that twelve aberrant methylated genes (ATP6V0CP3, AGGF1P3, RP11-264L1.4, HIST1H4K, LINC01158, CH17-140K24.1, CTC-523E23.14, ADCYAP1, COX11P1, TRIM58, FOXD4L6, CBLN1) were entered into a Cox predictive model associated with overall survival in LUSC patients. Methylation and gene expression combined survival analysis showed that the survival rate of hypermethylation and low-expression of DQX1 and WDR61 were low. The expression of DQX1 had a significantly negatively correlated with the methylation site cg02034222. Conclusion: Methylation-driven genes DQX1 and WDR61 might be potential biomarkers for predicting the prognosis of LUSC.

DNA Methylation-Based Method to Differentiate Malignant from Benign Thyroid Lesions

Background: The differential diagnosis of thyroid nodules using fine-needle aspiration biopsy (FNAB) is challenging due to the inherent limitation of the cytology tests. The use of molecular markers has potential to complement the FNAB-based diagnosis and avoid unnecessary surgeries. In this study, we aimed to identify DNA methylation biomarkers and to develop a diagnostic tool useful for thyroid lesions. Methods: Genome-wide DNA methylation profiles (Illumina 450K) of papillary thyroid carcinoma (PTC = 60) and follicular thyroid carcinoma (FTC = 10) were compared with non-neoplastic thyroid tissue samples (NT = 50) and benign thyroid lesions (BTL = 17). The results were confirmed in publicly available databases from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) using the same DNA methylation platform. Two classifiers were trained to discriminate FTC and PTC from BTL. To increase the applicability of the method, six differentially methylated CpGs were selected and evaluated in 161 thyroid tumors and 69 BTL postsurgical specimens and 55 prospectively collected FNAB using bisulfite-pyrosequencing. Results: DNA methylation analysis revealed 2130 and 19 differentially methylated CpGs in PTC and FTC, respectively. The CpGs confirmed by GEO and TCGA databases showing high areas under the receiver operating characteristic curve in all sample sets were used to train our diagnostic classifier. The model based on six CpGs was able to differentiate benign from malignant thyroid lesions with 94.3% sensitivity and 82.4% specificity. A similar performance was found applying the algorithm to TCGA and GEO external data sets (91.3-97.4% sensitivity and 87.5% specificity). We successfully evaluated the classifiers using a bisulfite-pyrosequencing technique, achieving 90.7% sensitivity and 75.4% specificity in surgical specimens (five of six CpGs). The study comprising FNAB cytology materials corroborated the applicability and performance of the methodology, demonstrating 86.7% sensitivity and 89.5% specificity in confirmed malignant tumors, and 100% sensitivity and 89% specificity in cases with indeterminate cytology. Conclusions: A novel diagnostic tool with potential application in preoperative screening of thyroid nodules is reported here. The proposed protocol has the potential to avoid unnecessary thyroidectomies.

Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models

Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients.

Extending Classification Algorithms to Case-Control Studies

Classification is a common technique applied to 'omics data to build predictive models and identify potential markers of biomedical outcomes. Despite the prevalence of case-control studies, the number of classification methods available to analyze data generated by such studies is extremely limited. Conditional logistic regression is the most commonly used technique, but the associated modeling assumptions limit its ability to identify a large class of sufficiently complicated 'omic signatures. We propose a data preprocessing step which generalizes and makes any linear or nonlinear classification algorithm, even those typically not appropriate for matched design data, available to be used to model case-control data and identify relevant biomarkers in these study designs. We demonstrate on simulated case-control data that both the classification and variable selection accuracy of each method is improved after applying this processing step and that the proposed methods are comparable to or outperform existing variable selection methods. Finally, we demonstrate the impact of conditional classification algorithms on a large cohort study of children with islet autoimmunity.

PITX2 methylation: a novel and effective biomarker for monitoring biochemical recurrence risk of prostate cancer

AIMS

Prostate cancer is one of the most common malignancies in men. Biochemical recurrence (BCR) and progression following curative treatment pose a significant public health challenge. Thus, it is essential to explore effective biomarkers for disease progression monitoring and risk stratification. The promoter region of the paired-like homeodomain transcription factor 2 (PITX2) gene has been found to be frequently methylated in prostate cancer. However, the prognostic role of PITX2 methylation in prostate cancer and which patients most likely to be recommended for PITX2 methylation tests to assess BCR risk remain controversial. Therefore, a systematic review was performed to explore the relationship of PITX2 methylation with the BCR risk of prostate cancer.

METHODS

The PubMed, EMBASE, and Cochrane Library databases were systematically searched for eligible studies. Seven studies with a total of 2185 patients were included. Pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were calculated.

RESULTS

The overall HR was 2.71 (95% CI, 2.21-3.31), suggesting that PITX2 methylation has an adverse impact on BCR of prostate cancer. The pooled estimate of 5-year BCR-free survival for patients with a high methylation status was significantly lower than that for patients with a low methylation status (71% vs 90%; odds ratio [OR] = 3.50; 95% CI, 2.67-4.60, P = .000). A subgroup analysis was conducted according to detection method; the combined HRs were 2.68 (95% CI, 2.02-3.55) for quantitative methylation-specific PCR (qMSP) and 3.29 (95% CI, 2.31-4.68) for microarray EpiChip. In subgroups defined by region, Gleason score, pathological stage, surgical margin status and ethnicity, high methylation status was also associated with BCR of prostate cancer.

CONCLUSIONS

As an effective biomarker, PITX2 methylation is feasible for individualized BCR risk assessment of prostate cancer following radical prostatectomy.

Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk

Genome-wide association studies (GWAS) identified the chromosome 15q25.1 locus as a leading susceptibility region for lung cancer. However, the pathogenic pathways, through which susceptibility SNPs within chromosome 15q25.1 affects lung cancer risk, have not been explored. We analyzed three cohorts with GWAS data consisting 42,901 individuals and lung expression quantitative trait loci (eQTL) data on 409 individuals to identify and validate the underlying pathways and to investigate the combined effect of genes from the identified susceptibility pathways. The KEGG neuroactive ligand receptor interaction pathway, two Reactome pathways, and 22 Gene Ontology terms were identified and replicated to be significantly associated with lung cancer risk, with P values less than 0.05 and FDR less than 0.1. Functional annotation of eQTL analysis results showed that the neuroactive ligand receptor interaction pathway and gated channel activity were involved in lung cancer risk. These pathways provide important insights for the etiology of lung cancer.

Genome-wide analysis of DNA methylation in bronchial washings

Background

The objective of this study was to discover DNA methylation biomarkers for detecting non-small lung cancer (NSCLC) in bronchial washings and understanding the association between DNA methylation and smoking cessation.

Methods

DNA methylation was analyzed in bronchial washing samples from 70 NSCLCs and 53 hospital-based controls using Illumina HumanMethylation450K BeadChip. Methylation levels in these bronchial washings were compared to those in 897 primary lung tissues of The Cancer Genome Atlas (TCGA) data.

Results

Twenty-four CpGs (p < 1.03E−07) were significantly methylated in bronchial washings from 70 NSCLC patients compared to those from 53 controls. The CpGs also had significant methylation in the TCGA cohort. The 123 participants were divided into a training set (N = 82) and a test set (N = 41) to build a classification model. Logistic regression model showed the best performance for classification of lung cancer in bronchial washing samples: the sensitivity and specificity of a marker panel consisting of seven CpGs in TFAP2A, TBX15, PHF11, TOX2, PRR15, PDGFRA, and HOXA11 genes were 87.0 and 83.3% in the test set, respectively. The area under the curve (AUC) was equal to 0.87 (95% confidence interval = 0.73–0.96, p < 0.001). Methylation levels of two CpGs in RUNX3 and MIR196A1 genes were inversely associated with duration of smoking cessation in the controls, but not in NSCLCs, after adjusting for pack-years of smoking.

Conclusions

The present study suggests that NSCLC may be detected by analyzing methylation changes of seven CpGs in bronchial washings. Furthermore, smoking cessation may lead to decreased DNA methylation in nonmalignant bronchial epithelial cells in a gene-specific manner.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0498-8) contains supplementary material, which is available to authorized users.

Epigenome-wide association study in hepatocellular carcinoma: Identification of stochastic epigenetic mutations through an innovative statistical approach

Hepatocellular carcinoma (HCC) results from accumulation of both genetic and epigenetic alterations. We investigated the genome-wide DNA methylation profile in 69 pairs of HCC and adjacent non-cancerous liver tissues using the Infinium HumanMethylation 450K BeadChip array. An innovative analytical approach has been adopted to identify Stochastic Epigenetic Mutations (SEMs) in HCC.HCC and peritumoral tissues showed a different epigenetic profile, mainly characterized by loss of DNA methylation in HCC. Total number of SEMs was significantly higher in HCC tumor (median: 77,370) than in peritumoral (median: 5,656) tissues and correlated with tumor grade. A significant positive association emerged between SEMs measured in peritumoral tissue and hepatitis B and/or C virus infection status. A restricted number of SEMs resulted to be shared by more than 90% of HCC tumor samples and never present in peritumoral tissue. This analysis allowed the identification of four epigenetically regulated candidate genes (AJAP1, ADARB2, PTPRN2, SDK1), potentially involved in the pathogenesis of HCC.In conclusion, HCC showed a methylation profile completely deregulated and very far from adjacent non-cancerous liver tissues. The SEM analysis provided valuable clues for further investigations in understanding the process of tumorigenesis in HCC.

pETM: a penalized Exponential Tilt Model for analysis of correlated high-dimensional DNA methylation data

Motivation

DNA methylation plays an important role in many biological processes and cancer progression. Recent studies have found that there are also differences in methylation variations in different groups other than differences in methylation means. Several methods have been developed that consider both mean and variance signals in order to improve statistical power of detecting differentially methylated loci. Moreover, as methylation levels of neighboring CpG sites are known to be strongly correlated, methods that incorporate correlations have also been developed. We previously developed a network-based penalized logistic regression for correlated methylation data, but only focusing on mean signals. We have also developed a generalized exponential tilt model that captures both mean and variance signals but only examining one CpG site at a time.

Results

In this article, we proposed a penalized Exponential Tilt Model (pETM) using network-based regularization that captures both mean and variance signals in DNA methylation data and takes into account the correlations among nearby CpG sites. By combining the strength of the two models we previously developed, we demonstrated the superior power and better performance of the pETM method through simulations and the applications to the 450K DNA methylation array data of the four breast invasive carcinoma cancer subtypes from The Cancer Genome Atlas (TCGA) project. The developed pETM method identifies many cancer-related methylation loci that were missed by our previously developed method that considers correlations among nearby methylation loci but not variance signals.

Availability and Implementation

The R package 'pETM' is publicly available through CRAN: http://cran.r-project.org .

Contact

sw2206@columbia.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Frequent silencing of the candidate tumor suppressor TRIM58 by promoter methylation in early-stage lung adenocarcinoma

In this study, we aimed to identify novel drivers that would be epigenetically altered through aberrant methylation in early-stage lung adenocarcinoma (LADC), regardless of the presence or absence of tobacco smoking-induced epigenetic field defects. Through genome-wide screening for aberrantly methylated CpG islands (CGIs) in 12 clinically uniform, stage-I LADC cases affecting six non-smokers and six smokers, we identified candidate tumor-suppressor genes (TSGs) inactivated by hypermethylation. Through systematic expression analyses of those candidates in panels of additional tumor samples and cell lines treated or not treated with 5-aza-deoxycitidine followed by validation analyses of cancer-specific silencing by CGI hypermethylation using a public database, we identified TRIM58 as the most prominent candidate for TSG. TRIM58 was robustly silenced by hypermethylation even in early-stage primary LADC, and the restoration of TRIM58 expression in LADC cell lines inhibited cell growth in vitro and in vivo in anchorage-dependent and -independent manners. Our findings suggest that aberrant inactivation of TRIM58 consequent to CGI hypermethylation might stimulate the early carcinogenesis of LADC regardless of smoking status; furthermore, TRIM58 methylation might be a possible early diagnostic and epigenetic therapeutic target in LADC.

A Review of Matched-pairs Feature Selection Methods for Gene Expression Data Analysis

With the rapid accumulation of gene expression data from various technologies, e.g., microarray, RNA-sequencing (RNA-seq), and single-cell RNA-seq, it is necessary to carry out dimensional reduction and feature (signature genes) selection in support of making sense out of such high dimensional data. These computational methods significantly facilitate further data analysis and interpretation, such as gene function enrichment analysis, cancer biomarker detection, and drug targeting identification in precision medicine. Although numerous methods have been developed for feature selection in bioinformatics, it is still a challenge to choose the appropriate methods for a specific problem and seek for the most reasonable ranking features. Meanwhile, the paired gene expression data under matched case-control design (MCCD) is becoming increasingly popular, which has often been used in multi-omics integration studies and may increase feature selection efficiency by offsetting similar distributions of confounding features. The appropriate feature selection methods specifically designed for the paired data, which is named as matched-pairs feature selection (MPFS), however, have not been maturely developed in parallel. In this review, we compare the performance of 10 feature-selection methods (eight MPFS methods and two traditional unpaired methods) on two real datasets by applied three classification methods, and analyze the algorithm complexity of these methods through the running of their programs. This review aims to induce and comprehensively present the MPFS in such a way that readers can easily understand its characteristics and get a clue in selecting the appropriate methods for their analyses.

Sumoylation of TCF21 downregulates the transcriptional activity of estrogen receptor-alpha

Aberrant estrogen receptor-α (ERα) signaling is recognized as a major contributor to the development of breast cancer. However, the molecular mechanism underlying the regulation of ERα in breast cancer is still inconclusive. In this study, we showed that the transcription factor 21 (TCF21) interacted with ERα, and repressed its transcriptional activity in a HDACs-dependent manner. We also showed that TCF21 could be sumoylated by the small ubiquitin-like modifier SUMO1, and this modification could be reversed by SENP1. Sumoylation of TCF21 occurred at lysine residue 24 (K24). Substitution of K24 with arginine resulted in complete abolishment of sumoylation. Sumoylation stabilized TCF21, but did not affect its subcellular localization. Sumoylation of TCF21 also enhanced its interaction with HDAC1/2 without affecting its interaction with ERα. Moreover, sumoylation of TCF21 promoted its repression of ERα transcriptional activity, and increased the recruitment of HDAC1/2 to the pS2 promoter. Consistent with these observations, sumoylation of TCF21 could inhibit the growth of ERα-positive breast cancer cells and decreased the proportion of S-phase cells in the cell cycle. These findings suggested that TCF21 might act as a negative regulator of ERα, and its sumoylation inhibited the transcriptional activity of ERα through promoting the recruitment of HDAC1/2.

Occupational exposure to pesticides is associated with differential DNA methylation

Objectives

Occupational pesticide exposure is associated with a wide range of diseases, including lung diseases, but it is largely unknown how pesticides influence airway disease pathogenesis. A potential mechanism might be through epigenetic mechanisms, like DNA methylation. Therefore, we assessed associations between occupational exposure to pesticides and genome-wide DNA methylation sites.

Methods

1561 subjects of LifeLines were included with either no (n=1392), low (n=108) or high (n=61) exposure to any type of pesticides (estimated based on current or last held job). Blood DNA methylation levels were measured using Illumina 450K arrays. Associations between pesticide exposure and 420 938 methylation sites (CpGs) were assessed using robust linear regression adjusted for appropriate confounders. In addition, we performed genome-wide stratified and interaction analyses by gender, smoking and airway obstruction status, and assessed associations between gene expression and methylation for genome-wide significant CpGs (n=2802).

Results

In total for all analyses, high pesticide exposure was genome-wide significantly (false discovery rate P<0.05) associated with differential DNA methylation of 31 CpGs annotated to 29 genes. Twenty of these CpGs were found in subjects with airway obstruction. Several of the identified genes, for example, RYR1, ALLC, PTPRN2, LRRC3B, PAX2 and VTRNA2-1, are genes previously linked to either pesticide exposure or lung-related diseases. Seven out of 31 CpGs were associated with gene expression levels.

Conclusions

We show for the first time that occupational exposure to pesticides is genome-wide associated with differential DNA methylation. Further research should reveal whether this differential methylation plays a role in the airway disease pathogenesis induced by pesticides.

Promoter methylation of TCF21 may repress autophagy in the progression of lung cancer

Lung cancer is a leading cause of cancer mortality worldwide. Promoter methylation of transcription factor 21 (TCF21) was frequently observed in the early stage of non-small cell lung cancer (NSCLC). However, clinical relevance and molecular functions of TCF21 in NSCLC progression remain unclear. In this study, we analyzed the associations between TCF21 expression and clinicopathological features in 100 patients with NSCLC and revealed the underlying molecular mechanisms of TCF21 methylation on cell viability, apoptosis and invasion of H1299 cells. We found that the expression of TCF21 was significantly regulated by its methylation level in patients with NSCLC and was associated with tumor stage, metastasis and invasion. Demethylation of H1299 cells by 5-aza-2'-deoxycytine (5-Aza) demonstrated that a higher level of TCF21 expression led to remarkable decreases of cell viability and invasion ability but an increase of cell apoptosis. Accordingly, TCF21 knockdown showed converse results to high expression of TCF21. TCF21 knockdown cells exhibited significantly upregulated ATG-9, BECLIN-1, and LC3-I/II expressions but decreased p62 expression compared to wildtype cells. Inhibition of autophagy by 3-methyladenine (3-MA) elevated TCF21 expression and increased cell apoptosis. TCF21 expression is clinically related to the progress of lung cancer and may inhibit autophagy by suppressing ATG-9 and BECLIN-1. In turn, autophagy may also play an important role in regulation TCF21 expression.

The Tumor-Suppressor Protein OPCML Potentiates Anti-EGFR- and Anti-HER2-Targeted Therapy in HER2-Positive Ovarian and Breast Cancer

Opioid-binding protein/cell adhesion molecule-like (OPCML) is a tumor-suppressor gene that is frequently inactivated in ovarian cancer and many other cancers by somatic methylation. We have previously shown that OPCML exerts its suppressor function by negatively regulating a spectrum of receptor tyrosine kinases (RTK), such as ErbB2/HER2, FGFR1, and EphA2, thus attenuating their related downstream signaling. The physical interaction of OPCML with this defined group of RTKs is a prerequisite for their downregulation. Overexpression/gene amplification of EGFR and HER2 is a frequent event in multiple cancers, including ovarian and breast cancers. Molecular therapeutics against EGFR/HER2 or EGFR only, such as lapatinib and erlotinib, respectively, were developed to target these receptors, but resistance often occurs in relapsing cancers. Here we show that, though OPCML interacts only with HER2 and not with EGFR, the interaction of OPCML with HER2 disrupts the formation of the HER2-EGFR heterodimer, and this translates into a better response to both lapatinib and erlotinib in HER2-expressing ovarian and breast cancer cell lines. Also, we show that high OPCML expression is associated with better response to lapatinib therapy in breast cancer patients and better survival in HER2-overexpressing ovarian cancer patients, suggesting that OPCML co-therapy could be a valuable sensitizing approach to RTK inhibitors. Mol Cancer Ther; 16(10); 2246-56. ©2017 AACR.

DNA methylation polymerase chain reaction (PCR) array of apoptosis-related genes in pleomorphic adenomas of the salivary glands

OBJECTIVE

The aim of this study was to evaluate the DNA methylation profile in 22 apoptosis-related genes in pleomorphic adenomas (PAs) of the salivary glands, in comparison with normal salivary glands (NSGs), and to address the differences in methylation patterns between smaller and larger tumors. Additionally, we investigated if the hypermethylation of differentially methylated genes between NSGs and PAs impacted the messenger RNA (mRNA) transcription.

DESIGN

Twenty-three fresh PA samples and 12 NSG samples were included. The PA samples were divided into 2 groups: PAs with clinical size larger than 2 cm (n = 12) and PAs with clinical size 2 cm or smaller (n = 11). DNA methylation at the promoter region of a panel of 22 genes involved in apoptosis was profiled by using a human apoptosis DNA methylation polymerase chain reaction array, and the transcriptional levels of genes showing differential methylation profiles between PAs and NSGs were assessed.

RESULTS

TNFRSF25 and BCL2 L11 were highly methylated in PAs, in comparison with NSGs, irrespective of tumor size. However, no difference could be observed in the mRNA transcription between PAs and NSGs.

CONCLUSIONS

Hypermethylation of the proapoptotic genes BCL2 L11 and TNFRSF25 is observed in PA. However, this phenomenon did not impact mRNA transcription.

Recurrent noncoding regulatory mutations in pancreatic ductal adenocarcinoma

The contributions of coding mutations to tumorigenesis are relatively well known; however, little is known about somatic alterations in noncoding DNA. Here we describe GECCO (Genomic Enrichment Computational Clustering Operation) to analyze somatic noncoding alterations in 308 pancreatic ductal adenocarcinomas (PDAs) and identify commonly mutated regulatory regions. We find recurrent noncoding mutations to be enriched in PDA pathways, including axon guidance and cell adhesion, and newly identified processes, including transcription and homeobox genes. We identified mutations in protein binding sites correlating with differential expression of proximal genes and experimentally validated effects of mutations on expression. We developed an expression modulation score that quantifies the strength of gene regulation imposed by each class of regulatory elements, and found the strongest elements were most frequently mutated, suggesting a selective advantage. Our detailed single-cancer analysis of noncoding alterations identifies regulatory mutations as candidates for diagnostic and prognostic markers, and suggests new mechanisms for tumor evolution.

Integration of high-risk human papillomavirus into cellular cancer-related genes in head and neck cancer cell lines

BACKGROUND

Human papillomavirus (HPV)-positive oropharyngeal cancer is generally associated with excellent response to therapy, but some HPV-positive tumors progress despite aggressive therapy. The purpose of this study was to evaluate viral oncogene expression and viral integration sites in HPV16- and HPV18-positive squamous cell carcinoma lines.

METHODS

E6/E7 alternate transcripts were assessed by reverse transcriptase-polymerase chain reaction (RT-PCR). Detection of integrated papillomavirus sequences (DIPS-PCR) and sequencing identified viral insertion sites and affected host genes. Cellular gene expression was assessed across viral integration sites.

RESULTS

All HPV-positive cell lines expressed alternate HPVE6/E7 splicing indicative of active viral oncogenesis. HPV integration occurred within cancer-related genes TP63, DCC, JAK1, TERT, ATR, ETV6, PGR, PTPRN2, and TMEM237 in 8 head and neck squamous cell carcinoma (HNSCC) lines but UM-SCC-105 and UM-GCC-1 had only intergenic integration.

CONCLUSION

HPV integration into cancer-related genes occurred in 7 of 9 HPV-positive cell lines and of these 6 were from tumors that progressed. HPV integration into cancer-related genes may be a secondary carcinogenic driver in HPV-driven tumors. © 2017 Wiley Periodicals, Inc. Head Neck 39: 840-852, 2017.

Bayesian Variable Selection Methods for Matched Case-Control Studies

Matched case-control designs are currently used in many biomedical applications. To ensure high efficiency and statistical power in identifying features that best discriminate cases from controls, it is important to account for the use of matched designs. However, in the setting of high dimensional data, few variable selection methods account for matching. Bayesian approaches to variable selection have several advantages, including the fact that such approaches visit a wider range of model subsets. In this paper, we propose a variable selection method to account for case-control matching in a Bayesian context and apply it using simulation studies, a matched brain imaging study conducted at Massachusetts General Hospital, and a matched cardiovascular biomarker study conducted by the High Risk Plaque Initiative.

Genome-wide analysis of DNA methylation and their associations with long noncoding RNA/mRNA expression in non-small-cell lung cancer

AIM

The goal of this study is to identify differentially methylated (DM) loci associated with long noncoding RNA (lncRNA)/mRNA expression in non-small-cell lung cancer (NSCLC).

MATERIALS & METHODS

Microarrays were used to interrogate genome-wide methylation and expression of lncRNA/mRNA in NSCLC.

RESULTS

We identified 113,644 DM loci between tumors and adjacent tissues. Among them, 26,310 DM loci were associated with 1685 differentially expressed genes, and 839 genes had significant correlations between methylation and expression, of which 26 hypermethylated loci in transcription start site 200 were correlated with low gene expression. We validated the correlations between methylation and expression in five genes (CDO1, C2orf40, SCARF1, ZFP106 and IFFO1) using pyrosequencing and quantitative polymerase chain reaction. We also found significant correlations between lncRNAs and mRNAs, and validated four of the correlations with quantitative polymerase chain reaction.

CONCLUSION

Integrated analysis of genome-wide DNA methylation and lncRNA/mRNA expression allows us to identify new DM loci-correlated with gene expression in NSCLC.

Analysis of Microarray Data on Gene Expression and Methylation to Identify Long Non-coding RNAs in Non-small Cell Lung Cancer

To identify what long non-coding RNAs (lncRNAs) are involved in non-small cell lung cancer (NSCLC), we analyzed microarray data on gene expression and methylation. Gene expression chip and HumanMethylation450BeadChip were used to interrogate genome-wide expression and methylation in tumor samples. Differential expression and methylation were analyzed through comparing tumors with adjacent non-tumor tissues. LncRNAs expressed differentially and correlated with coding genes and DNA methylation were validated in additional tumor samples using RT-qPCR and pyrosequencing. In vitro experiments were performed to evaluate lncRNA’s effects on tumor cells. We identified 8,500 lncRNAs expressed differentially between tumor and non-tumor tissues, of which 1,504 were correlated with mRNA expression. Two of the lncRNAs, LOC146880 and ENST00000439577, were positively correlated with expression of two cancer-related genes, KPNA2 and RCC2, respectively. High expression of LOC146880 and ENST00000439577 were also associated with poor survival. Analysis of lncRNA expression in relation to DNA methylation showed that LOC146880 expression was down-regulated by DNA methylation in its promoter. Lowering the expression of LOC146880 or ENST00000439577 in tumor cells could inhibit cell proliferation, invasion and migration. Analysis of microarray data on gene expression and methylation allows us to identify two lncRNAs, LOC146880 and ENST00000439577, which may promote the progression of NSCLC.

Establishing the clinical utility of epigenetic markers in cancer: many challenges ahead

The use of epigenetic biomarkers in cancer management relies on the availability of robust assays and evidence that these markers are able to segregate clinically significant groups of patients. While many cancers are characterized by genetic and epigenetic modifications, it is far simpler to develop molecular tests that detect genetic rather than epigenetic changes. In this special report, we will describe the challenges associated with developing epigenetic assays and the practical issues that must be overcome before they can be used in the clinic.

Pathway Implications of Aberrant Global Methylation in Adrenocortical Cancer

Context

Adrenocortical carcinomas (ACC) are a rare tumor type with a poor five-year survival rate and limited treatment options.

Objective

Understanding of the molecular pathogenesis of this disease has been aided by genomic analyses highlighting alterations in TP53, WNT, and IGF signaling pathways. Further elucidation is needed to reveal therapeutically actionable targets in ACC.

Design

In this study, global DNA methylation levels were assessed by the Infinium HumanMethylation450 BeadChip Array on 18 ACC tumors and 6 normal adrenal tissues. A new, non-linear correlation approach, the discretization method, assessed the relationship between DNA methylation/gene expression across ACC tumors.

Results

This correlation analysis revealed epigenetic regulation of genes known to modulate TP53, WNT, and IGF signaling, as well as silencing of the tumor suppressor MARCKS, previously unreported in ACC.

Conclusions

DNA methylation may regulate genes known to play a role in ACC pathogenesis as well as known tumor suppressors.

The Role of Epigenomics in the Study of Cancer Biomarkers and in the Development of Diagnostic Tools

Epigenetics plays a key role in cancer development. Genetics alone cannot explain sporadic cancer and cancer development in individuals with no family history or a weak family history of cancer. Epigenetics provides a mechanism to explain the development of cancer in such situations. Alterations in epigenetic profiling may provide important insights into the etiology and natural history of cancer. Because several epigenetic changes occur before histopathological changes, they can serve as biomarkers for cancer diagnosis and risk assessment. Many cancers may remain asymptomatic until relatively late stages; in managing the disease, efforts should be focused on early detection, accurate prediction of disease progression, and frequent monitoring. This chapter describes epigenetic biomarkers as they are expressed during cancer development and their potential use in cancer diagnosis and prognosis. Based on epigenomic information, biomarkers have been identified that may serve as diagnostic tools; some such biomarkers also may be useful in identifying individuals who will respond to therapy and survive longer. The importance of analytical and clinical validation of biomarkers is discussed, along with challenges and opportunities in this field.

SCT Promoter Methylation is a Highly Discriminative Biomarker for Lung and Many Other Cancers

Aberrant DNA methylation has long been implicated in cancers. In this work we present a highly discriminative DNA methylation biomarker for non-small cell lung cancers and fourteen other cancers. Based on 69 NSCLC cell lines and 257 cancer-free lung tissues we identified a CpG island in SCT gene promoter which was verified by qMSP experiment in 15 NSCLC cell lines and 3 immortalized human respiratory epithelium cells. In addition, we found that SCT promoter was methylated in 23 cancer cell lines involving >10 cancer types profiled by ENCODE. We found that SCT promoter is hyper-methylated in primary tumors from TCGA lung cancer cohort. Additionally, we found that SCT promoter is methylated at high frequencies in fifteen malignancies and is not methylated in~1000 non-cancerous tissues across >30 organ types. Our study indicates that SCT promoter methylation is a highly discriminative biomarker for lung and many other cancers.

TCF21 hypermethylation in genetically quiescent clear cell sarcoma of the kidney

Clear Cell Sarcoma of the Kidney (CCSK) is a rare childhood tumor whose molecular pathogenesis remains poorly understood. We analyzed a discovery set of 13 CCSKs for changes in chromosome copy number, mutations, rearrangements, global gene expression and global DNA methylation. No recurrent segmental chromosomal copy number changes or somatic variants (single nucleotide or small insertion/deletion) were identified. One tumor with t(10;17)(q22;p13) involving fusion of YHWAE with NUTM2B was identified. Integrated analysis of expression and methylation data identified promoter hypermethylation and low expression of the tumor suppressor gene TCF21 (Pod-1/capsulin/epicardin) in all CCSKs except the case with t(10;17)(q22;p13). TARID, the long noncoding RNA responsible for demethylating TCF21, was virtually undetectable in most CCSKs. TCF21 hypermethylation and decreased TARID expression were validated in an independent set of CCSK tumor samples. The presence of significant hypermethylation of TCF21, a transcription factor known to be active early in renal development, supports the hypothesis that hypermethylation of TCF21 and/or decreased TARID expression lies within the pathogenic pathway of most CCSKs. Future studies are needed to functionally verify a tumorigenic role of TCF21 down-regulation and to tie this to the unique gene expression pattern of CCSK.

Pancreatic cancer patient survival correlates with DNA methylation of pancreas development genes

DNA methylation is an epigenetic mark associated with regulation of transcription and genome structure. These markers have been investigated in a variety of cancer settings for their utility in differentiating normal tissue from tumor tissue. Here, we examine the direct correlation between DNA methylation and patient survival. We find that changes in the DNA methylation of key pancreatic developmental genes are strongly associated with patient survival.

Four DNA methylation biomarkers in biliary brush samples accurately identify the presence of cholangiocarcinoma

Early detection of the highly aggressive malignancy cholangiocarcinoma (CCA) remains a challenge but has the potential to render the tumor curable by surgical removal. This study evaluates a biomarker panel for the diagnosis of CCA by DNA methylation analyses of biliary brush samples. The methylation status of 13 candidate genes (CDO1, CNRIP1, DCLK1, FBN1, INA, MAL, SEPT9, SFRP1, SNCA, SPG20, TMEFF2, VIM, and ZSCAN18) was investigated in 93 tissue samples (39 CCAs and 54 nonmalignant controls) using quantitative methylation-specific polymerase chain reaction. The 13 genes were further analyzed in a test series of biliary brush samples (15 CCAs and 20 nonmalignant primary sclerosing cholangitis controls), and the methylation status of the four best performing markers was validated (34 CCAs and 34 primary sclerosing cholangitis controls). Receiver operating characteristic curve analyses were used to evaluate the performance of individual biomarkers and the combination of biomarkers. The 13 candidate genes displayed a methylation frequency of 26%-82% in tissue samples. The four best-performing genes (CDO1, CNRIP1, SEPT9, and VIM) displayed individual methylation frequencies of 45%-77% in biliary brushes from CCA patients. Across the test and validation biliary brush series, this four-gene biomarker panel achieved a sensitivity of 85% and a specificity of 98%, with an area under the receiver operating characteristic curve of 0.944.

CONCLUSION

We report a straightforward biomarker assay with high sensitivity and specificity for CCA, outperforming standard brush cytology, and suggest that the biomarker panel, potentially in combination with cytological evaluation, may improve CCA detection, particularly among primary sclerosing cholangitis patients.

Identification of module biomarkers from the dysregulated ceRNA–ceRNA interaction network in lung adenocarcinoma

The dysregulated ceRNA–ceRNA interaction network in lung adenocarcinoma.

Classification of lung cancer using ensemble-based feature selection and machine learning methods

Lung cancer is one of the leading causes of death worldwide. There are three major types of lung cancers, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC) and carcinoid. NSCLC is further classified into lung adenocarcinoma (LADC), squamous cell lung cancer (SQCLC) as well as large cell lung cancer. Many previous studies demonstrated that DNA methylation has emerged as potential lung cancer-specific biomarkers. However, whether there exists a set of DNA methylation markers simultaneously distinguishing such three types of lung cancers remains elusive. In the present study, ROC (Receiving Operating Curve), RFs (Random Forests) and mRMR (Maximum Relevancy and Minimum Redundancy) were proposed to capture the unbiased, informative as well as compact molecular signatures followed by machine learning methods to classify LADC, SQCLC and SCLC. As a result, a panel of 16 DNA methylation markers exhibits an ideal classification power with an accuracy of 86.54%, 84.6% and a recall 84.37%, 85.5% in the leave-one-out cross-validation (LOOCV) and independent data set test experiments, respectively. Besides, comparison results indicate that ensemble-based feature selection methods outperform individual ones when combined with the incremental feature selection (IFS) strategy in terms of the informative and compact property of features. Taken together, results obtained suggest the effectiveness of the ensemble-based feature selection approach and the possible existence of a common panel of DNA methylation markers among such three types of lung cancer tissue, which would facilitate clinical diagnosis and treatment.

Overexpression of MEOX2 and TWIST1 is associated with H3K27me3 levels and determines lung cancer chemoresistance and prognosis

Lung cancer is the leading cause of death from malignant diseases worldwide, with the non-small cell (NSCLC) subtype accounting for the majority of cases. NSCLC is characterized by frequent genomic imbalances and copy number variations (CNVs), but the epigenetic aberrations that are associated with clinical prognosis and therapeutic failure remain not completely identify. In the present study, a total of 55 lung cancer patients were included and we conducted genomic and genetic expression analyses, immunohistochemical protein detection, DNA methylation and chromatin immunoprecipitation assays to obtain genetic and epigenetic profiles associated to prognosis and chemoresponse of NSCLC patients. Finally, siRNA transfection-mediated genetic silencing and cisplatinum cellular cytotoxicity assays in NSCLC cell lines A-427 and INER-37 were assessed to describe chemoresistance mechanisms involved. Our results identified high frequencies of CNVs (66–51% of cases) in the 7p22.3–p21.1 and 7p15.3–p15.2 cytogenetic regions. However, overexpression of genes, such as MEOX2, HDAC9, TWIST1 and AhR, at 7p21.2–p21.1 locus occurred despite the absence of CNVs and little changes in DNA methylation. In contrast, the promoter sequences of MEOX2 and TWIST1 displayed significantly lower/decrease in the repressive histone mark H3K27me3 and increased in the active histone mark H3K4me3 levels. Finally these results correlate with poor survival in NSCLC patients and cellular chemoresistance to oncologic drugs in NSCLC cell lines in a MEOX2 and TWIST1 overexpression dependent-manner. In conclusion, we report for the first time that MEOX2 participates in chemoresistance irrespective of high CNV, but it is significantly dependent upon H3K27me3 enrichment probably associated with aggressiveness and chemotherapy failure in NSCLC patients, however additional clinical studies must be performed to confirm our findings as new probable clinical markers in NSCLC patients.