Identification and Comparison of Aberrant Key Regulatory Networks in Breast,Colon, Liver,Lung, and Stomach Cancers through Methylome Database Analysis

Aberrant methylation of specific CpG sites at the promoter is widely responsible for genesis and development of various cancer types. Even though the microarray-based methylome analyzing techniques have contributed to the elucidation of the methylation change at the genome-wide level, the identification of key methylation markers or top regulatory networks appearing common in highly incident cancers through comparison analysis is still limited. In this study, we in silico performed the genome-wide methylation analysis on each 10 sets of normal and cancer pairs of five tissues: breast, colon, liver, lung, and stomach. The methylation array covers 27,578 CpG sites, corresponding to 14,495 genes, and significantly hypermethylated or hypomethylated genes in the cancer were collected (FDR adjusted p-value <0.05; methylation difference >0.3). Analysis of the dataset confirmed the methylation of previously known methylation markers and further identified novel methylation markers, such as GPX2, CLDN15, and KL. Cluster analysis using the methylome dataset resulted in a diagram with a bipartite mode distinguishing cancer cells from normal cells regardless of tissue types. The analysis further revealed that breast cancer was closest with lung cancer, whereas it was farthest from colon cancer. Pathway analysis identified that either the “cancer” related network or the “cancer” related bio-function appeared as the highest confidence in all the five cancers, whereas each cancer type represents its tissue-specific gene sets. Our results contribute toward understanding the essential abnormal epigenetic pathways involved in carcinogenesis. Further, the novel methylation markers could be applied to establish markers for cancer prognosis.     

GHSR DNA hypermethylation is a new epigenetic biomarker for gastric adenocarcinoma and beyond

Aberrations of DNA methylation are early events in the development of tumors. In this study, we investigated the DNA methylation status of growth hormone secretagogue receptor (GHSR), a promising pan-cancer biomarker, in gastric cancer (GC). Initially, data sets from DNA methylation and gene expression studies available at Gene Expression Omnibus (GEO) were analyzed. Confirmation was done on primary tumor specimens and adjacent normal stomach tissue samples. Both analyses showed significant hypermethylation of GHSR. For further validation, The Cancer Genome Atlas data on stomach cancer was used. A receiver operating characteristic curve analysis yielded an area under the curve value of 0.85, corroborating its usefulness as a diagnostic marker. A genome-wide comethylation analysis revealed several correlated genes. CREB1 was found to act as an upstream regulator of this gene network. Furthermore, GHSR methylation was found to be a biomarker in several other tumor entities, namely cancers of the bladder, endometrium, esophagus, head and neck, liver, thyroid, kidney, and ovary. Our findings along with previous reports on other types of cancer suggest a high potential of GHSR gene methylation as a pan-cancer biomarker, which could be considered for liquid biopsy applications.     

Diagnosis and prognosis potential of four gene promoter hypermethylation in prostate cancer

The current prostate special antigen (PSA) test causes the overtreatment of indolent prostate cancer (PCa). It also increases the risk of delayed treatment of aggressive PCa. DNA methylation aberrations are important events for gene expression dysregulation during tumorigenesis and have been suggested as novel candidate biomarkers for PCa. This may improve the diagnosis and prognosis of PCa. This study assessed the differential methylation and messenger RNA (mRNA) expression between normal and PCa samples. Correlation between promoter methylation and mRNA expression was estimated using Pearson's correlation coefficients. Moreover, the diagnostic potential of candidate methylation markers was estimated by the receiver operating characteristic (ROC) curve using continuous beta values. Survival and Cox analysis was performed to evaluate the prognostic potential of the candidate methylation markers. A total of 359 hypermethylated sites 3435 hypomethylation sites, 483 upregulated genes, and 1341 downregulated genes were identified from The Cancer Genome Atlas database. Furthermore, 17 hypermethylated sites (covering 13 genes), including known genes associated with hypermethylation in PCa (e.g., AOX1 and C1orf114), showed high discrimination between adjacent normal tissues and PCa samples with the area under the ROC curve from 0.88 to 0.94. Notably, ANXA2, FGFR2, HAAO, and KCNE3 were identified as valuable prognostic markers of PCa through the Kaplan–Meier analysis. Using gene methylation as a continuous variable, four promoter hypermethylation was significantly associated with disease-free survival in univariate Cox regression and multivariate Cox regression. This study identified four novel diagnostic and prognostic markers for PCa. The markers provide important strategies for improving the timely diagnosis and prognosis of PCa.     

Combined hypermethylation of APC and GSTP1 as a molecular marker for prostate cancer: quantitative pyrosequencing analysis

A total of 149 human prostate tissues obtained from our institute were assessed: 52 specimens of benign prostate hyperplasia (BPH) and 97 specimens of prostate cancer (PCa). The methylation status of the genes of Adenomatous polyposis coli (APC) and glutathione-S-transferase-P1 (GSTP1) was analyzed by quantitative pyrosequencing. A methylation score (M score) was calculated to capture the combined methylation level of both genes. The methylation level of each single gene and that of both genes combined was significantly higher in PCa specimens than in BPH (each p < 0.001). The value of APC methylation, GSTP1 methylation, and M score for predicting PCa was measured by the area under the receiver operating characteristic (ROC) curve and reached 0.954, 0.942, and 0.983, respectively. The sensitivity and specificity of the M score in discriminating between PCa and BPH reached 92.8% and 100.0%, respectively. The M score was positively associated with the serum prostate-specific antigen (PSA) level (p trend < 0.001). Our study demonstrates that the quantitative measurement of two methylation markers might drastically improve the ability to discriminate PCa from BPH.     

Genome-scale analysis of DNA methylation in colorectal cancer using Infinium HumanMethylation450 BeadChips

Illumina’s Infinium HumanMethylation450 BeadChip arrays were used to examine genome-wide DNA methylation profiles in 22 sample pairs from colorectal cancer (CRC) and adjacent tissues and 19 colon tissue samples from cancer-free donors. We show that the methylation profiles of tumors and healthy tissue samples can be clearly distinguished from one another and that the main source of methylation variability is associated with disease status. We used different statistical approaches to evaluate the methylation data. In general, at the CpG-site level, we found that common CRC-specific methylation patterns consist of at least 15,667 CpG sites that were significantly different from either adjacent healthy tissue or tissue from cancer-free subjects. Of these sites, 10,342 were hypermethylated in CRC, and 5,325 were hypomethylated. Hypermethylated sites were common in the maximum number of sample pairs and were mostly located in CpG islands, where they were significantly enriched for differentially methylated regions known to be cancer-specific. In contrast, hypomethylated sites were mostly located in CpG shores and were generally sample-specific. Despite the considerable variability in methylation data, we selected a panel of 14 highly robust candidates showing methylation marks in genes SND1, ADHFE1, OPLAH, TLX2, C1orf70, ZFP64, NR5A2, and COL4A. This set was successfully cross-validated using methylation data from 209 CRC samples and 38 healthy tissue samples from The Cancer Genome Atlas consortium (AUC = 0.981 [95% CI: 0.9677–0.9939], sensitivity = 100% and specificity = 82%). In summary, this study reports a large number of loci with novel differential methylation statuses, some of which may serve as candidate markers for diagnostic purposes.     

Colorectal adenoma and cancer detection based on altered methylation pattern of SFRP1, SFRP2, SDC2, and PRIMA1 in plasma samples

Aberrant methylation is one of the most frequent epigenetic alterations that can contribute to tumor formation. Cell-free DNA can originate from tumor tissue; therefore, the evaluation of methylation markers in cell-free DNA can be a promising method for cancer screening. Our aim was to develop a panel of biomarkers with altered methylation along the colorectal adenoma-carcinoma sequence in both colonic tissue and plasma. Methylation of selected CpG sites in healthy colonic (n = 15), adenoma (n = 15), and colorectal cancer (n = 15) tissues was analyzed by pyrosequencing. MethyLight PCR was applied to study the DNA methylation of SFRP1, SFRP2, SDC2, and PRIMA1 gene promoters in 121 plasma and 32 biopsy samples. The effect of altered promoter methylation on protein expression was examined by immunohistochemistry. Significantly higher (P < 0.05) DNA methylation levels were detected in the promoter regions of all 4 markers, both in CRC and adenoma tissues compared with healthy controls. Methylation of SFRP1, SFRP2, SDC2, and PRIMA1 promoter sequences was observed in 85.1%, 72.3%, 89.4%, and 80.9% of plasma samples from patients with CRC and 89.2%, 83.8%, 81.1% and 70.3% from adenoma patients, respectively. When applied as a panel, CRC patients could be distinguished from controls with 91.5% sensitivity and 97.3% specificity [area under the curve (AUC) = 0.978], while adenoma samples could be differentiated with 89.2% sensitivity and 86.5% specificity (AUC = 0.937). Immunohistochemical analysis indicated decreasing protein levels of all 4 markers along the colorectal adenoma-carcinoma sequence. Our findings suggest that this methylation biomarker panel allows non-invasive detection of colorectal adenoma and cancer from plasma samples.     

Methylomic analysis identifies frequent DNA methylation of zinc finger protein 582 (ZNF582) in cervical neoplasms

Background

Despite of the trend that the application of DNA methylation as a biomarker for cancer detection is promising, clinically applicable genes are few. Therefore, we looked for novel hypermethylated genes for cervical cancer screening.

Methods and Findings

At the discovery phase, we analyzed the methylation profiles of human cervical carcinomas and normal cervixes by methylated DNA immunoprecipitation coupled to promoter tiling arrays (MeDIP-on-chip). Methylation-specific PCR (MSP), quantitative MSP and bisulfite sequencing were used to verify the methylation status in cancer tissues and cervical scrapings from patients with different severities. Immunohistochemical staining of a cervical tissue microarray was used to confirm protein expression. We narrowed to three candidate genes: DBC1, PDE8B, and ZNF582; their methylation frequencies in tumors were 93%, 29%, and 100%, respectively. At the pre-validation phase, the methylation frequency of DBC1 and ZNF582 in cervical scraping correlated significantly with disease severity in an independent cohort (n = 330, both P<0.001). For the detection of cervical intraepithelial neoplasia 3 (CIN3) and worse, the area under the receiver operating characteristic curve (AUC) of ZNF582 was 0.82 (95% confidence interval  = 0.76–0.87).

Conclusions

Our study shows ZNF582 is frequently methylated in CIN3 and worse lesions, and it is demonstrated as a potential biomarker for the molecular screening of cervical cancer.     

Genome-Scale Discovery of DNA-Methylation Biomarkers for Blood-Based Detection of Colorectal Cancer

Background

There is an increasing demand for accurate biomarkers for early non-invasive colorectal cancer detection. We employed a genome-scale marker discovery method to identify and verify candidate DNA methylation biomarkers for blood-based detection of colorectal cancer.

Methodology/Principal Findings

We used DNA methylation data from 711 colorectal tumors, 53 matched adjacent-normal colonic tissue samples, 286 healthy blood samples and 4,201 tumor samples of 15 different cancer types. DNA methylation data were generated by the Illumina Infinium HumanMethylation27 and the HumanMethylation450 platforms, which determine the methylation status of 27,578 and 482,421 CpG sites respectively. We first performed a multistep marker selection to identify candidate markers with high methylation across all colorectal tumors while harboring low methylation in healthy samples and other cancer types. We then used pre-therapeutic plasma and serum samples from 107 colorectal cancer patients and 98 controls without colorectal cancer, confirmed by colonoscopy, to verify candidate markers. We selected two markers for further evaluation: methylated THBD (THBD-M) and methylated C9orf50 (C9orf50-M). When tested on clinical plasma and serum samples these markers outperformed carcinoembryonic antigen (CEA) serum measurement and resulted in a high sensitive and specific test performance for early colorectal cancer detection.

Conclusions/Significance

Our systematic marker discovery and verification study for blood-based DNA methylation markers resulted in two novel colorectal cancer biomarkers, THBD-M and C9orf50-M. THBD-M in particular showed promising performance in clinical samples, justifying its further optimization and clinical testing.     

p16基因甲基化状态与散发性大肠癌的相关性研究

为探讨p1 6基因甲基化状态与散发性大肠癌发生发展的关系 ,用甲基化特异性的聚合酶链反应 (methylati omspecificPCR ,MSP)结合测序检测散发性大肠癌及相应癌旁组织p1 6基因甲基化状态。研究发现p1 6基因在散发性大肠癌中甲基化率为 2 8 9% (1 3 4 5 ) ,有 8例癌及癌旁组织都发生了甲基化 ;有淋巴结及远处转移的甲基化率为5 0 % (8 1 6 ) ,高于无转移的甲基化率 2 0 8(5 2 4 ) (P <0 0 5 )。p1 6基因高甲基化是散发性大肠癌中常见的分子改变之一 ,大肠癌中p1 6基因高甲基化可能发生在癌变早期并与大肠癌的恶性进展有相关性     

A suite of DNA methylation markers that can detect most common human cancers

Cancer-specific DNA methylation from the tumor derived fraction of cell free DNA found in blood samples could be used for minimally invasive detection and monitoring of cancer. The knowledge of marker regions with cancer-specific DNA methylation is necessary to the success of such a process. We analyzed the largest cancer DNA methylation dataset available—TCGA Illumina HumanMethylation450 data with over 8,500 tumors—in order to find cancer-specific DNA methylation markers for most common human cancers. First, we identified differentially methylated regions for individual cancer types and those were further filtered against data from normal tissues to obtain marker regions with cancer-specific methylation, resulting in a total of 1,250 hypermethylated and 584 hypomethylated marker CpGs. From hypermethylated markers, optimal sets of six markers for each TCGA cancer type were chosen that could identify most tumors with high specificity and sensitivity [area under the curve (AUC): 0.969-1.000] and a universal 12 marker set that can detect tumors of all 33 TCGA cancer types (AUC >0.84). In addition to hundreds of new DNA methylation markers, our approach also identified markers that are in current clinical use, SEPT9 and GSTP1, indicating the validity of our approach and a significant potential utility for the newly discovered markers. The hypermethylated markers are linked to polycomb associated loci and a significant fraction of the discovered markers is within noncoding RNA genes; one of the best markers is MIR129-2. Future clinical testing of herein discovered markers will confirm new markers that will improve minimally invasive diagnosis and monitoring for multiple cancers.     

Adaptive Boosting (AdaBoost)‐based multiwavelength spatial frequency domain imaging and characterization for ex vivo human colorectal tissue assessment

The current gold standard diagnostic test for colorectal cancer remains histological inspections of endoluminal neoplasia in biopsy specimens. However, biopsy site selection requires visual inspection of the bowel, typically with a white‐light endoscope. Therefore, this technique is poorly suited to detect small or innocuous‐appearing lesions. We hypothesize that an alternative modality—multiwavelength spatial frequency domain imaging (SFDI)—would be able to differentiate various colorectal neoplasia from normal tissue. In this ex vivo study of human colorectal tissues, we report the optical absorption and scattering signatures of normal, adenomatous polyp and cancer specimens. An abnormal vs. normal adaptive boosting (AdaBoost) classifier is trained to dichotomize tissue based on SFDI imaging characteristics, and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.95 is achieved. We conclude that AdaBoost‐based multiwavelength SFDI can differentiate abnormal from normal colorectal tissues, potentially improving endoluminal screening of the distal gastrointestinal tract in the future.     

Altered methylation at microRNA-associated CpG islands in hereditary and sporadic carcinomas: a methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA)-based approach

MicroRNAs (miRNAs) are small noncoding RNAs that contribute to tumorigenesis by acting as oncogenes or tumor suppressor genes and may be important in the diagnosis, prognosis and treatment of cancer. Many miRNA genes have associated CpG islands, suggesting epigenetic regulation of their expression. Compared with sporadic cancers, the role of miRNAs in hereditary or familial cancer is poorly understood. We investigated 96 colorectal carcinomas, 58 gastric carcinomas and 41 endometrial carcinomas, occurring as part of inherited DNA mismatch repair (MMR) deficiency (Lynch syndrome), familial colorectal carcinoma without MMR gene mutations or sporadically. Methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) assays were developed for 11 miRNA loci that were chosen because all could be epigenetically regulated through the associated CpG islands and some could additionally modulate the epigenome by putatively targeting the DNA methyltransferases or their antagonist retinoblastoma-like 2 (RBL2). Compared with the respective normal tissues, the predominant alteration in tumor tissues was increased methylation for the miRNAs 1-1, 124a-1, 124a-2, 124a-3, 148a, 152 and 18b; decreased methylation for 200a and 208a; and no major change for 373 and let-7a-3. The frequencies with which the individual miRNA loci were affected in tumors showed statistically significant differences relative to the tissue of origin (colorectal versus gastric versus endometrial), MMR proficiency versus deficiency and sporadic versus hereditary disease. In particular, hypermethylation at miR-148a and miR-152 was associated with microsatellite-unstable (as opposed to stable) tumors and hypermethylation at miR-18b with sporadic disease (as opposed to Lynch syndrome). Hypermethylation at miRNA loci correlated with hypermethylation at classic tumor suppressor promoters in the same tumors. Our results highlight the importance of epigenetic events in hereditary and sporadic cancers and suggest that MS-MLPA is an excellent choice for quantitative analysis of methylation in archival formalin-fixed, paraffin-embedded samples, which pose challenges to many other techniques commonly used for methylation studies.     

DNA methylation-based diagnostic,prognostic, and predictive biomarkers in colorectal cancer

DNA methylation is an epigenetic mechanism regulating gene expression. Changes in DNA methylation were suggested to be useful biomarkers for diagnosis, and for the determination of prognosis and treatment response. Here, we provide an overview of methylation-based biomarkers in colorectal cancer.First, we start with the two methylation-based diagnostic biomarkers already approved for colorectal cancer, SEPT9 and the combination of NDRG4 and BMP3. Then, we provide a list-based overview of new biomarker candidates depending on the sample source including plasma, stool, urine, and surgically removed tumor tissues. The most often identified markers like SDC2, VIM, APC, MGMT, SFRP1, SFRP2, and NDRG4 have distinct functions previously linked to tumor progression.Although numerous studies have identified tumor-specific methylation changes, most of these alterations were observed in a single study only. The lack of validation in independent samples means low reproducibility and is a major limitation. The genome-wide determination of methylation status (methylome) can provide data to solve these issues. In the third section of the review, methylome studies focusing on different aspects related to CRC, including precancerous lesions, CRC-specific changes, molecular subtypes, aging, and chemotherapy response are summarized. Notably, techniques simultaneously analyzing a large set of regions can also uncover epigenetic regulation of genes which have not yet been associated with tumorigenesis previously.A remaining constraint of studies published to date is the low patient number utilized in these preventing the identification of clinically valuable biomarker candidates. Either future large-scale studies or the integration of already available methylome-level data will be necessary to uncover biomarkers sufficiently robust for clinical application.     

Comparison of Breast Cancer to Healthy Control Tissue Discovers Novel Markers with Potential for Prognosis and Early Detection

This study was initiated to identify biomarkers with potential value for the early detection of poor-outcome breast cancer. Two sets of well-characterized tissues were utilized: one from breast cancer patients with favorable vs. poor outcome and the other from healthy women undergoing reduction mammaplasty. Over 46 differentially expressed genes were identified from a large list of potential targets by a) mining publicly available expression data (identifying 134 genes for quantitative PCR) and b) utilizing a commercial PCR array. Three genes show elevated expression in cancers with poor outcome and low expression in all other tissues, warranting further investigation as potential blood markers for early detection of cancers with poor outcome. Twelve genes showed lower expression in cancers with poor outcome than in cancers with favorable outcome but no differential expression between aggressive cancers and most healthy controls. These genes are more likely to be useful as prognostic tissue markers than as serum markers for early detection of aggressive disease. As a secondary finding was that, when histologically normal breast tissue was removed from a distant site in a breast with cancer, 7 of 38 specimens displayed a cancer-like expression profile, while the remaining 31 were genetically similar to the reduction mammaplasty control group. This finding suggests that some regions of ipsilateral histologically ‘normal’ breast tissue are predisposed to becoming malignant and that normal-appearing tissue with malignant signature might warrant treatment to prevent new primary tumors.     

NTRK3 Is a Potential Tumor Suppressor Gene Commonly Inactivated by Epigenetic Mechanisms in Colorectal Cancer

NTRK3 is a member of the neurotrophin receptor family and regulates cell survival. It appears to be a dependence receptor, and thus has the potential to act as an oncogene or as a tumor suppressor gene. NTRK3 is a receptor for NT-3 and when bound to NT-3 it induces cell survival, but when NT-3 free, it induces apoptosis. We identified aberrantly methylated NTRK3 in colorectal cancers through a genome-wide screen for hypermethylated genes. This discovery led us to assess whether NTRK3 could be a tumor suppressor gene in the colon. NTRK3 is methylated in 60% of colon adenomas and 67% of colon adenocarcinomas. NTRK3 methylation suppresses NTRK3 expression. Reconstitution of NTRK3 induces apoptosis in colorectal cancers, if NT-3 is absent. Furthermore, the loss of NTRK3 expression associates with neoplastic transformation in vitro and in vivo. We also found that a naturally occurring mutant NTRK3 found in human colorectal cancer inhibits the tumor suppressor activity of NTRK3. In summary, our findings suggest NTRK3 is a conditional tumor suppressor gene that is commonly inactivated in colorectal cancer by both epigenetic and genetic mechanisms whose function in the pathogenesis of colorectal cancer depends on the expression status of its ligand, NT-3.     

Hypermethylated and downregulated MEIS2 are involved in stemness properties and oxaliplatin-based chemotherapy resistance of colorectal cancer

The resistance against oxaliplatin (L-OHP) based regimens remains a major obstacle for its efficient usage in treating metastatic colorectal cancer (mCRC). In this study, we performed weighted gene coexpression network analysis (WGCNA) to systematically screen the relevant hub genes for L-OHP resistance using the raw microarray data of 30 consecutive mCRC samples from our earlier study (GSE69657). The results were further confirmed through datasets from Gene Expression Omnibus (GEO). From L-OHP resistance module, nine genes in both the coexpression and protein–protein interaction networks were chosen as hub genes. Among these genes, Meis Homeobox 2 (MEIS2) had the highest correlation with L-OHP resistance (r = −0.443) and was deregulated in L-OHP resistant tissues compared with L-OHP sensitive tissues in both our own dataset and GSE104645 testing dataset. The receiver operating characteristic curve validated that MEIS2 had a good ability in predicting L-OHP response in both our own dataset (area under the curve [AUC] = 0.802) and GSE104645 dataset (AUC = 0.746). Then, the down expression of MEIS2 was observed in CRC tissue compared with normal tissue in 12 GEO-sourced datasets and The Cancer Genome Atlas (TCGA) and was correlated with poor event-free survival. Furthermore, analyzing methylation data from TCGA showed that MEIS2 had increased promoter hypermethylation. In addition, MEIS2 expression was significantly decreased in CRC stem cells compared with nonstem cells in two GEO datasets (GSE14773 and GSE24747). Further methylation analysis from GSE104271 demonstrated that CRC stem cells had higher MEIS2 promoter methylation levels in cg00366722 and cg00610348 sites. Gene set enrichment analysis showed that MEIS2 might be involved in the Wnt/β-catenin pathway. In the overall view, MEIS2 had increased promoter hypermethylation and was downregulated in poor L-OHP response mCRC tissues. MEIS2 might be involved in the Wnt/β-catenin pathway to maintain CRC stemness, which leads to L-OHP resistance.     

DNA methylation-based biomarkers in serum of patients with breast cancer

Alterations of genetic and epigenetic features can provide important insights into the natural history of breast cancer. Although DNA methylation analysis is a rapidly developing field, a reproducible epigenetic blood-based assay for diagnosis and follow-up of breast cancer has yet to be successfully developed into a routine clinical test. The aim of this study was to review multiple serum DNA methylation assays and to highlight the value of those novel biomarkers in diagnosis, prognosis and prediction of therapeutic outcome. Serum is readily accessible for molecular diagnosis in all individuals from a peripheral blood sample. The list of hypermethylated genes in breast cancer is heterogeneous and no single gene is methylated in all breast cancer types. There is increasing evidence that a panel of epigenetic markers is essential to achieve a higher sensitivity and specificity in breast cancer detection. However, the reported percentages of methylation are highly variable, which can be partly explained by the different sensitivities and the different intra-/inter-assay coefficients of variability of the analysis methods. Moreover, there is a striking lack of receiver operating characteristic (ROC) curves of the proposed biomarkers. Another point of criticism is the fact that 'normal' patterns of DNA methylation of some tumor suppressor and other cancer-related genes are influenced by several factors and are often poorly characterized. A relatively frequent methylation of those genes has been observed in high-risk asymptomatic women. Finally, there is a call for larger prospective cohort studies to determine methylation patterns during treatment and follow-up. Identification of patterns specific for a differential response to therapeutic interventions should be useful. Only in this way, it will be possible to evaluate the predictive and prognostic characteristics of those novel promising biomarkers.     

Outlier Analysis Defines Zinc Finger Gene Family DNA Methylation in Tumors and Saliva of Head and Neck Cancer Patients

Head and Neck Squamous Cell Carcinoma (HNSCC) is the fifth most common cancer, annually affecting over half a million people worldwide. Presently, there are no accepted biomarkers for clinical detection and surveillance of HNSCC. In this work, a comprehensive genome-wide analysis of epigenetic alterations in primary HNSCC tumors was employed in conjunction with cancer-specific outlier statistics to define novel biomarker genes which are differentially methylated in HNSCC. The 37 identified biomarker candidates were top-scoring outlier genes with prominent differential methylation in tumors, but with no signal in normal tissues. These putative candidates were validated in independent HNSCC cohorts from our institution and TCGA (The Cancer Genome Atlas). Using the top candidates, ZNF14, ZNF160, and ZNF420, an assay was developed for detection of HNSCC cancer in primary tissue and saliva samples with 100% specificity when compared to normal control samples. Given the high detection specificity, the analysis of ZNF DNA methylation in combination with other DNA methylation biomarkers may be useful in the clinical setting for HNSCC detection and surveillance, particularly in high-risk patients. Several additional candidates identified through this work can be further investigated toward future development of a multi-gene panel of biomarkers for the surveillance and detection of HNSCC.