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Identification of single-cell subtypes is one of the fundamental processes required to understand a heterogeneous population composed of multiple cells, based on single-cell RNA sequencing data. Previously, cell subtype identification was mainly carried out by dimension reduction and clustering approaches that grouped cells with similar expressed profiles together. However, for high robustness to noises and systematic annotation of the subtype in each cell, supervised classification approaches have been widely used. Recently, deep neural network (DNN) models have been widely presented in various fields, including biology. By capturing the composite relationship between sample features and target outcomes, a DNN model enables significant performance improvements in biological data mining analyses. In this paper, we constructed a DNN model, called scDAE for single-cell subtype identification combined with representative feature extraction using a multilayer denoising autoencoder (DAE). The feature sets were learned by the DAE and were further tuned by fully connected layers using a softmax classifier. The model was compared against four state-of-the-art cell subtype identification methods and two conventional machine learning algorithms. From multiple tests, scDAE significantly outperformed competing methods especially on data sets having a large number of cell subtypes and noises. Extracted cell features from the proposed model were clearly clustered with respect to subtype. The results of the experiments indicated that our proposed model is effective in identifying single-cell subtypes and molecular signatures representative of each cell subtype. scDAE is publicly available at https://github.com/cbi-bioinfo/scDAE .

BackgroundPheochromocytoma and paraganglioma (PPGL) are tumours that arise from chromaffin cells. Some genetic mutations influence PPGL, among which, those in genes encoding subunits of succinate dehydrogenase (SDHA, SDHB, SDHC and SDHD) and assembly factor (SDHAF2) are the most relevant. However, the risk of metastasis posed by these mutations is not reported except for SDHB and SDHD mutations. This study aimed to update the metastatic risks, considering prevalence and incidence of each SDHx mutation, which were dealt formerly all together.MethodsWe searched EMBASE and MEDLINE and selected 27 articles. The patients included in the studies were divided into three groups depending on the presence of PPGL. We checked the heterogeneity between studies and performed a meta-analysis using Hartung-Knapp-Sidik-Jonkman method based on a random effect model.ResultsThe highest PPGL prevalence was for SDHB mutation, ranging from 23% to 31%, and for SDHC mutation (23%), followed by that for SDHA mutation (16%). The lowest prevalence was for SDHD mutation, ranging from 6% to 8%. SDHAF2 mutation showed no metastatic events. The PPGL incidence showed a tendency similar to that of its prevalence with the highest risk of metastasis posed by SDHB mutation (12%–41%) and the lowest risk by SDHD mutation (~4%).ConclusionThere was no integrated evidence of how SDHx mutations are related to metastatic PPGL. However, these findings suggest that SDHA, SDHB and SDHC mutations are highly associated and should be tested as indicators of metastasis in patients with PPGL.

The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.

Motivation Bulk tumor samples used for high-throughput molecular profiling are often an admixture of cancer cells and non-cancerous cells, which include immune and stromal cells. The mixed composition can confound the analysis and affect the biological interpretation of the results, and thus, accurate prediction of tumor purity is critical. Although several methods have been proposed to predict tumor purity using high-throughput molecular data, there has been no comprehensive study on machine learning-based methods for the estimation of tumor purity. Results We applied various machine learning models to estimate tumor purity. Overall, the models predicted the tumor purity accurately and showed a high correlation with well-established gold standard methods. In addition, we identified a small group of genes and demonstrated that they could predict tumor purity well. Finally, we confirmed that these genes were mainly involved in the immune system. Availability The machine learning models constructed for this study are available at https://github.com/BonilKoo/ML_purity.

OBJECTIVE: This study aimed to investigate the underlying pathogenesis of acute unilateral vestibulopathy (AUV) using gene expression profiling combined with bioinformatics analysis. METHODS: Total RNA was extracted from the peripheral blood mononuclear cells of ten AUV patients in the acute phase and from ten controls. The differentially expressed genes (DEGs) between these two groups were screened using microarray analysis with the cut-off criteria (|fold changes| > 1.5 and p-value

Hyperventilation-induced downbeat nystagmus (HV-DBN) has been reported in cerebellar disorders and explained by a loss of the inhibitory cerebellar output via a metabolic effect on cerebellar Ca2+ channels. The aim of this study was to determine the clinical characteristics and underlying pathogenesis of episodic vestibular syndrome (EVS) with HV-DBN. Of 667 patients with EVS, we recruited 22 with HV-DBN and assessed their clinical characteristics, video-oculographic findings, and the results of molecular genetic analyses. The age at symptom onset was 47.5 ± 13.0 years (mean ± SD), and there was a female preponderance (n = 15, 68%). The duration of vertigo/dizziness attacks ranged from minutes to a few days, and 11 patients (50%) fulfilled the diagnostic criteria for vestibular migraine. HV-induced new-onset DBN in 8 patients, while the remaining 14 showed augmentation of spontaneous DBN by HV. The maximum slow-phase velocity of HV-DBN ranged from 2.2 to 11.9°/s, which showed a statistical difference with that of spontaneous DBN (median = 4.95, IQR = 3.68–6.55 vs. median = 1.25, IQR = 0.20–2.15, p

Objectives: The cause of Meniere's disease (MD) is unclear but likely involves genetic and environmental factors. The aim of this study was to investigate the genetic basis underlying MD by screening putative candidate genes for MD.Methods: Sixty-eight patients who met the diagnostic criteria for MD of the Barany Society were included. We performed targeted gene sequencing using next generation sequencing (NGS) panel composed of 45 MD-associated genes. We identified the rare variants causing non-synonymous amino acid changes, stop codons, and insertions/deletions in the coding regions, and excluded the common variants with minor allele frequency >0.01 in public databases. The pathogenicity of the identified variants was analyzed by various predictive tools and protein structural modeling.Results: The average read depth for the targeted regions was 1446.3-fold, and 99.4% of the targeted regions were covered by 20 or more reads, achieving the high quality of the sequencing. After variant filtering, annotation, and interpretation, we identified a total of 15 rare heterozygous variants in 12 (17.6%) sporadic patients. Among them, four variants were detected in familial MD genes (DTNA, FAM136A, DPT), and the remaining 11 in MD-associated genes (PTPN22, NFKB1, CXCL10, TLR2, MTHFR, SLC44A2, NOS3, NOTCH2). Three patients had the variants in two or more genes. All variants were not detected in our healthy controls (n = 100). No significant differences were observed between patients with and without a genetic variant in terms of sex, mean age of onset, bilaterality, the type of MD, and hearing threshold at diagnosis.Conclusions: Our study identified rare variants of putative candidate genes in some of MD patients. The genes were related to the formation of inner ear structures, the immune-associated process, or systemic hemostasis derangement, suggesting the multiple genetic predispositions in the development of MD.

Obesity is a highly prevalent, chronic disorder that has been increasing in incidence in young patients. Both epigenetic and genetic aberrations may play a role in the pathogenesis of obesity. Therefore, in-depth epigenomic and genomic analyses will advance our understanding of the detailed molecular mechanisms underlying obesity and aid in the selection of potential biomarkers for obesity in youth. Here, we performed microarray-based DNA methylation and gene expression profiling of peripheral white blood cells obtained from six young, obese individuals and six healthy controls. We observed that the hierarchical clustering of DNA methylation, but not gene expression, clearly segregates the obese individuals from the controls, suggesting that the metabolic disturbance that occurs as a result of obesity at a young age may affect the DNA methylation of peripheral blood cells without accompanying transcriptional changes. To examine the genome-wide differences in the DNA methylation profiles of young obese and control individuals, we identified differentially methylated CpG sites and investigated their genomic and epigenomic contexts. The aberrant DNA methylation patterns in obese individuals can be summarized as relative gains and losses of DNA methylation in gene promoters and gene bodies, respectively. We also observed that the CpG islands of obese individuals are more susceptible to DNA methylation compared to controls. Our pilot study suggests that the genome-wide aberrant DNA methylation patterns of obese individuals may advance not only our understanding of the epigenomic pathogenesis but also early screening of obesity in youth.

// Sung Hak Lee 1, * , Seung Hyun Jung 4, 6, * , Tae-Min Kim 2 , Je-Keun Rhee 2 , Hyeon-Chun Park 3, 4 , Min Sung Kim 5, 6 , Sung Soo Kim 7 , Chang Hyeok An 8 , Sug Hyung Lee 5, 6 , Yeun-Jun Chung 3, 4, 5 1 Departments of Hospital Pathology, The Catholic University of Korea, Seoul, Korea 2 Departments of Medical Informatics, The Catholic University of Korea, Seoul, Korea 3 Departments of Microbiology, The Catholic University of Korea, Seoul, Korea 4 Departments of Integrated Research Center for Genome Polymorphism, The Catholic University of Korea, Seoul, Korea 5 Departments of Pathology, The Catholic University of Korea, Seoul, Korea 6 Departments of Cancer Evolution Research Center, The Catholic University of Korea, Seoul, Korea 7 Department of Internal Medicine, The Catholic University of Korea, Seoul, Korea 8 Departments of General Surgery The Catholic University of Korea, Seoul, Korea * These two authors contributed equally to this work Correspondence to: Yeun-Jun Chung, email: yejun@catholic.ac.kr Sug Hyung Lee, email: suhulee@catholic.ac.kr Chang Hyeok An, email: achcolo@catholic.ac.kr Keywords: colon, adenoma, high grade adenoma, mutation, whole-exome sequencing Received: November 14, 2016 Accepted: December 02, 2016 Published: December 25, 2016 ABSTRACT Although gene-to-gene analyses identified genetic alterations such as APC, KRAS and TP53 mutations in colon adenomas, it is largely unknown whether there are any others in them. Mutational profiling of high-grade colon adenoma (HGCA) that just precedes colon carcinoma might identify not only novel adenoma-specific genes but also critical genes for its progression to carcinoma. For this, we performed whole-exome sequencing (WES) of 12 HGCAs and identified 11 non-hypermutated and one hypermutated ( POLE -mutated) cases. We identified 22 genes including APC, KRAS, TP53, GNAS, NRAS, SMAD4, ARID2 , and PIK3CA with non-silent mutations in the cancer Census Genes. Bi-allelic and mono-allelic APC alterations were found in nine and one HGCAs, respectively, while the other two harbored wild-type APC . Five HGCAs harbored either mono-allelic (four HGCAs) or bi-allelic (one HGCA) SMAD4 mutation or 18q loss that had been known as early carcinoma-specific changes. We identified MTOR , ACVR1B , GNAQ , ATM , CNOT1 , EP300 , ARID2, RET and MAP2K4 mutations for the first time in colon adenomas. Our WES data is largely matched with the earlier ‘adenoma-carcinoma model’ ( APC, KRAS , NRAS and GNAS mutations), but there are newly identified SMAD4 , MTOR , ACVR1B , GNAQ , ATM , CNOT1 , EP300 , ARID2, RET and MAP2K4 mutations in this study. Our findings provide resource for understanding colon premalignant lesions and for identifying genomic clues for differential diagnosis and therapy options for colon adenomas and carcinomas.

Background and aims Internet gaming disorder (IGD) has gained recognition as a potential new diagnosis in the fifth revision of the Diagnostic and Statistical Manual of Mental Disorders, but genetic evidence supporting this disorder remains scarce. Methods In this study, targeted exome sequencing was conducted in 30 IGD patients and 30 control subjects with a focus on genes linked to various neurotransmitters associated with substance and non-substance addictions, depression, and attention deficit hyperactivity disorder. Results rs2229910 of neurotrophic tyrosine kinase receptor, type 3 (NTRK3) was the only single nucleotide polymorphism (SNP) that exhibited a significantly different minor allele frequency in IGD subjects compared to controls (p = .01932), suggesting that this SNP has a protective effect against IGD (odds ratio = 0.1541). The presence of this potentially protective allele was also associated with less time spent on Internet gaming and lower scores on the Young's Internet Addiction Test and Korean Internet Addiction Proneness Scale for Adults. Conclusions The results of this first targeted exome sequencing study of IGD subjects indicate that rs2229910 of NTRK3 is a genetic variant that is significantly related to IGD. These findings may have significant implications for future research investigating the genetics of IGD and other behavioral addictions.

Intraindividual tumoural heterogeneity (ITH) is a hallmark of solid tumours and impedes accurate genomic diagnosis and selection of proper therapy. The aim of this study was to identify ITH of ovarian high-grade serous carcinomas (OSCs) and to determine the utility of ascitic cancer cells as a resource for mutation profiling in spite of ITH. We performed whole-exome sequencing, copy number profiling and DNA methylation profiling of four OSC genomes by using multiregional biopsies from 13 intraovarian lesions, 12 extraovarian tumour lesions (omentum/peritoneum), and ascitic cells. We observed substantial levels of heterogeneity in mutations and copy number alterations (CNAs) of the OSCs. We categorized the mutations into 'common', 'shared' and 'private' according to the regional distribution. Six common, eight shared and 24 private mutations were observed in known cancer-related genes. Common mutations had a higher mutant allele frequency, and included TP53 mutations in all four OSCs. Region-specific chromosomal amplifications and deletions involving BRCA1, PIK3CA and RB1 were also identified. It is of note that the mutations detected in ascitic cancer cells represented 92.3-100% of overall somatic mutations in the given case. Phylogenetic analyses of ascitic genomes predicted a polyseeding origin of somatic mutations in ascitic cells. Our results demonstrate that, despite ITH, somatic mutations, CNAs and DNA methylations in both 'common' category and cancer-related genes were highly conserved in ascitic cells of OSCs, highlighting the clinical relevance of genome analysis of ascitic cells. Ascitic tumour cells may serve as a potential resource for discovering somatic mutations of primary OSC with diagnostic and therapeutic relevance. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

// Jaeyun Jung 1, * , Cue Hyunkyu Lee 3, * , Hyang Sook Seol 4 , Yeon Sook Choi 4 , Eunji Kim 3, 5 , Eun Ji Lee 1 , Je-Keun Rhee 6 , Shree Ram Singh 7 , Eun Sung Jun 1 , Buhm Han 3 , Seung Mo Hong 8 , Song Cheol Kim 9 , Suhwan Chang 1, 2 1 Department of Biomedical Sciences, University of Ulsan College of Medicine, Seoul, Korea 2 Department of Physiology, University of Ulsan College of Medicine, Seoul, Korea 3 Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul, Korea 4 Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea 5 Department of Chemistry, Seoul National University, Seoul, Korea 6 Department of Medical Informatics, College of Medicine, The Catholic University of Korea, Seoul, Korea 7 Mouse Cancer Genetics Program, Center for Cancer Research, National Cancer Institute, Frederick, MD, USA 8 Department of Pathology, Asan Medical Center, Seoul, Korea 9 Department of Surgery, Asan Medical Center, Seoul, Korea * These authors have contributed equally to this work Correspondence to: Song Cheol Kim, email: drksc@amc.seoul.kr Suhwan Chang, email: suhwan.chang@amc.seoul.kr Keywords: pancreatic cancer, patient-derived xenograft, single nucleotide polymorphism, cancer panel, heterogeneity Received: June 01, 2016 Accepted: August 08, 2016 Published: August 23, 2016 ABSTRACT Pancreatic ductal adenocarcinoma (PDAC) is the most challenging type of cancer to treat, with a 5-year survival rate of

Mutation profiles and intratumoral heterogeneity are not well understood for benign gastric adenomas, some of which progress into malignant gastric adenocarcinomas. In this study, we performed whole-exome sequencing of three microsatellite stable (MSS) and two microsatellite instability-high (MSI-H) gastric adenomas with three regional tumor biopsies per case. We observed that the mutation abundance of benign gastric adenomas was comparable to those of gastric adenocarcinomas, suggesting that the mutational makeup for gastric carcinogenesis may already be achieved in benign adenomas. The extent of intratumoral heterogeneity was more substantial for MSS genomes in that only 1% - 14% of somatic mutations were common across the regional biopsies or ‘public’, while 50% - 94% of mutations were public in MSI-H gastric adenomas. We observed biallelic, loss-of-functional events of APC with truncating mutations and/or 5q losses for all cases, mostly as public events. All MSS gastric adenomas also harbored ARID2 truncating mutations, often as multiple, region-specific ones indicative of convergent evolution. Hotspot missense mutations on known cancer genes such as ERBB2 and KRAS were largely observed as region-specific aberrations. These findings suggest that biallelic functional APC inactivation initiates the gastric carcinogenesis and is followed by mutations of histone modifiers and then activation of known cancer-related genes. As the first exome-wide multi-region mutational profiling of gastric adenomas, our study provides clues on the chronological sequence of somatic mutations and their clonal architectures in early gastric carcinogenesis.

Tumor-initiating cells are important for the formation and maintenance of tumor bulks in various tumors. To identify surface markers of liver tumor-initiating cells, we performed primary tumorsphere culture and analyzed the expression of cluster of differentiation (CD) antigen genes using NanoString. Interestingly, we found significant upregulation of the complement proteins (p = 1.60 × 10(-18)), including C7 and CFH. Further studies revealed that C7 and CFH are required to maintain stemness in liver cancer cells. Knockdown of C7 and CFH expression abrogated tumorsphere formation and induced differentiation, whereas overexpression stimulated stemness factor expression as well as in vivo cell growth. Mechanistically, by studying C7 and CFH-dependent LSF-1 expression and its direct role on stemness factor transcription, we found that LSF-1 is involved in this regulation. Taken together, our data demonstrate the unprecedented role of complement proteins on the maintenance of stemness in liver tumor-initiating cells.

Pancreatic cancer is one of the most difficult cancers to cure due to the lack of early diagnostic tools and effective therapeutic agents. In this study, we aimed to isolate new bioactive compounds that effectively kill pancreatic ductal adenocarcinoma (PDAC) cells, but not untransformed, human pancreatic ductal epithelial (HPDE) cells. To this end, we established four primary PDAC cell lines and screened 4141 compounds from four bioactive‐compound libraries. Initial screening yielded 113 primary hit compounds that caused over a 50% viability reduction in all tested PDAC cells. Subsequent triplicate, dose‐dependent analysis revealed three compounds with a tumor cell‐specific cytotoxic effect. We found that these three compounds fall into a single category of thiopurine biogenesis. Among them, 6‐thioguanine (6‐TG) showed an IC50 of 0.39–1.13 μm toward PDAC cells but had no effect on HPDE cells. We propose that this cancer selectivity is due to differences in thiopurine methyltransferase (TPMT) expression between normal and cancer cells. This enzyme is responsible for methylation of thiopurine, which reduces its cytotoxicity. We found that TPMT levels were lower in all four PDAC cell lines than in HPDE or Panc1 cells, and that knockdown of TPMT in HPDE or Panc1 cells sensitized them to 6‐TG. Lastly, we used a patient‐derived xenograft model to confirm that 6‐TG has a significant antitumor effect in combination with gemcitabine. Overall, our study presents 6‐TG as a strong candidate for use as a therapeutic agent against PDAC with low levels of TPMT.

The primary aim of this study was to investigate the genetic predisposition of Internet gaming disorder (IGD), and the secondary aim was to compare the results to those of alcohol dependence (AD). Two independent case-control studies were conducted. A total of 30 male participants with IGD, diagnosed according to the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria, and 30 sex-matched controls participated in study 1. We designed targeted exome sequencing (TES) to test for 72 candidate genes that have been implicated in the pathogenesis of addiction. The genes included seven neurotransmitter (dopamine, serotonin, glutamate, r-aminobutyric acid (GABA), norepinephrine, acetylcholine, and opioid) system genes. A total of 31 male in-patients with AD and 29 normal male controls (NC) were enrolled in study 2. The same 72 genes included in study 1 and ten additional genes related to alcohol-metabolic enzyme were selected as the target genes, and we identified the genetic variants using the same method (TES). The IGD group had a lower frequency of the T allele of rs1044396 in the nicotinic acetylcholine receptor alpha 4 subunit (CHRNA4), and this variant represents a protective allele against IGD. However, we did not find a significant difference in the polymorphisms of the 72 genes that encode neurotransmitter systems between the AD and NC groups. This study demonstrated that rs1044396 of CHRNA4 was significantly associated with IGD.

Background Most bioinformatic tools for next generation sequencing (NGS) data are computationally intensive, requiring a large amount of computational power for processing and analysis. Here the utility of graphic processing units (GPUs) for NGS data computation is assessed. Method In a previous study, we developed a probabilistic evolutionary algorithm with toggling for haplotyping (PEATH) method based on the estimation of distribution algorithm and toggling heuristic. Here, we parallelized the PEATH method (PEATH/G) using general-purpose computing on GPU (GPGPU). Results The PEATH/G runs approximately 46.8 times and 25.4 times faster than PEATH on the NA12878 fosmid-sequencing dataset and the HuRef dataset, respectively, with an NVIDIA GeForce GTX 1660Ti. Moreover, the PEATH/G is approximately 13.3 times faster on the fosmid-sequencing dataset, even with an inexpensive conventional GPGPU (NVIDIA GeForce GTX 950). Conclusions PEATH/G can be a practical single individual haplotyping tool in terms of both its accuracy and speed. GPGPU can help reduce the running time of NGS analysis tools.

Aberrant DNA methylation of CpG islands, CpG island shores and first exons is known to play a key role in the altered gene expression patterns in all human cancers. To date, a systematic study on the effect of DNA methylation on gene expression using high resolution data has not been reported. In this study, we conducted an integrated analysis of MethylCap-sequencing data and Affymetrix gene expression microarray data for 30 breast cancer cell lines representing different breast tumor phenotypes. As well-developed methods for the integrated analysis do not currently exist, we created a series of four different analysis methods. On the computational side, our goal is to develop methylome data analysis protocols for the integrated analysis of DNA methylation and gene expression data on the genome scale. On the cancer biology side, we present comprehensive genome-wide methylome analysis results for differentially methylated regions and their potential effect on gene expression in 30 breast cancer cell lines representing three molecular phenotypes, luminal, basal A and basal B. Our integrated analysis demonstrates that methylation status of different genomic regions may play a key role in establishing transcriptional patterns in molecular subtypes of human breast cancer.

Dacomitinib, an irreversible pan-HER inhibitor, had shown modest clinical activity in squamous cell carcinoma of head and neck (SCCHN) patients. Therefore, validated predictive biomarkers are required to identify patients most likely to benefit from this therapeutic option. To characterize the genetic landscape of cisplatin-treated SCCHN genomes and identify potential predictive biomarkers for dacomitinib sensitivity, we performed whole exome sequencing on 18 cisplatin-resistant metastatic SCCHN tumors and their matched germline DNA. Platinum-based chemotherapy elevated the mutation rates of SCCHN compared to chemotherapy-naïve SCCHNs. Cisplatin-treated SCCHN genomes uniquely exhibited a novel mutational signature characterized by C:G to A:T transversions at CCR sequence contexts that may have arisen due to error-prone translesional synthesis. Somatic mutations in REV3L, the gene encoding the catalytic subunit of DNA polymerase ζ involved in translesional synthesis, are significantly enriched in a subset of patients who derived extended clinical benefit to dacomitinib (P = 0.04). Functional assays showed that loss-of-function of REV3L dramatically enhanced the sensitivity of SCCHN cells to dacomitinib by the loss of both translesion synthesis and homologous recombination pathways. Our data suggest that the ‘platinum’ mutational signature and inactivation of REV3L may inform treatment options in patients of recurrent SCCHN.

Caveolin-1 (Cav1) is an integral membrane, scaffolding protein found in plasma membrane invaginations (caveolae). Cav1 regulates multiple cancer-associated processes. In breast cancer, a tumor suppressive role for Cav1 has been suggested; however, Cav1 is frequently overexpressed in aggressive breast cancer subtypes, suggesting an oncogenic function in advanced-stage disease. To further delineate Cav1 function in breast cancer progression, we evaluated its expression levels among a panel of cell lines representing a spectrum of breast cancer phenotypes. In basal-like (the most aggressive BC subtype) breast cancer cells, Cav1 was consistently upregulated, and positively correlated with increased cell proliferation, anchorage-independent growth, and migration and invasion. To identify mechanisms of Cav1 gene regulation, we compared DNA methylation levels within promoter ‘CpG islands' (CGIs) with ‘CGI shores', recently described regions that flank CGIs with less CG-density. Integration of genome-wide DNA methylation profiles (‘methylomes') with Cav1 expression in 30 breast cancer cell lines showed that differential methylation of CGI shores, but not CGIs, significantly regulated Cav1 expression. In breast cancer cell lines having low Cav1 expression (despite promoter CGI hypomethylation), we found that treatment with a DNA methyltransferase inhibitor induced Cav1 expression via CGI shore demethylation. In addition, further methylome assessments revealed that breast cancer aggressiveness associated with Cav1 CGI shore methylation levels, with shore hypermethylation in minimally aggressive, luminal breast cancer cells and shore hypomethylation in highly aggressive, basal-like cells. Cav1 CGI shore methylation was also observed in human breast tumors, and overall survival rates of breast cancer patients lacking estrogen receptor α (ERα) negatively correlated with Cav1 expression. Based on this first study of Cav1 (a potential oncogene) CGI shore methylation, we suggest this phenomenon may represent a new prognostic marker for ERα-negative, basal-like breast cancer.

BRCA1 is a multifunctional tumor suppressor involved in several essential cellular processes. Although many of these functions are driven by or related to its transcriptional/epigenetic regulator activity, there has been no genome-wide study to reveal the transcriptional/epigenetic targets of BRCA1. Therefore, we conducted a comprehensive analysis of genomics/transcriptomics data to identify novel BRCA1 target genes. We first analyzed ENCODE data with BRCA1 chromatin immunoprecipitation (ChIP)-sequencing results and identified a set of genes with a promoter occupied by BRCA1. We collected 3085 loci with a BRCA1 ChIP signal from four cell lines and calculated the distance between the loci and the nearest gene transcription start site (TSS). Overall, 66.5% of the BRCA1-bound loci fell into a 2-kb region around the TSS, suggesting a role in transcriptional regulation. We selected 45 candidate genes based on gene expression correlation data, obtained from two GEO (Gene Expression Omnibus) datasets and TCGA data of human breast cancer, compared to BRCA1 expression levels. Among them, we further tested three genes (MEIS2, CKS1B and FADD) and verified FADD as a novel direct target of BRCA1 by ChIP, RT-PCR, and a luciferase reporter assay. Collectively, our data demonstrate genome-wide transcriptional regulation by BRCA1 and suggest target genes as biomarker candidates for BRCA1-associated breast cancer.

// Young-Ho Kim 1 , Eun-Kyung Hong 2 , Sun-Young Kong 1, 3, 4 , Sung-Sik Han 2 , Seoung-Hoon Kim 2 , Je-Keun Rhee 5 , Soo-Kyung Hwang 1 , Sang-Jae Park 2 , Tae-Min Kim 5, 6 1 Translational Epidemiology Research Branch, Research Institute and Hospital, National Cancer Center, Goyang, Republic of Korea 2 Center for Liver Cancer and Hospital, National Cancer Center, Goyang, Republic of Korea 3 Department of Laboratory Medicine, Diagnostic Oncology Center and Hospital, National Cancer Center, Goyang, Republic of Korea 4 Department of System Cancer Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Republic of Korea 5 Department of Medical Informatics, The Catholic University of Korea, Seoul, Republic of Korea 6 Cancer Research Institute, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea Correspondence to: Tae-Min Kim, e-mail: tmkim@catholic.ac.kr Sang-Jae Park, e-mail: spark@ncc.re.kr Keywords: cholangiocarcinoma, exome sequencing, transcriptome, somatic mutations Received: August 24, 2015 Accepted: March 02, 2016 Published: March 18, 2016 ABSTRACT Intrahepatic cholangiocarcinoma (ICC) is a biliary tree-origin epithelial malignancy in liver with unfavorable clinical outcomes. Systematic genome analyses may advance our understanding of ICC pathogenesis also improving current diagnostic and therapeutic modalities. In this study, we analyzed 17 ICC tumor-vs-matched normal pairs using either whole-exome ( n = 7), transcriptome sequencing ( n = 7) or both platforms ( n = 3). For somatic mutations, we identified recurrent mutations of previously reported genes such as KRAS, TP53, APC as well as epigenetic regulators and those of TGFβ signaling pathway. According to the abundance of somatic mutations and DNA copy number alterations (CNA), ten ICC exome cases were distinguished into two classes as those primarily driven by either somatic mutations (M class) or CNAs (C class). Compared to M class ICCs (92–147 somatic mutations; n = 5) with a relative deficit of CNAs, C class ICCs (54–84 mutations; n = 5) harbor recurrent focal CNAs including deletions involving CDKN2A, ROBO1, ROBO2 , RUNX3 , and SMAD4 . We also show that transcriptome sequencing can be used for expression-based ICC categorization but the somatic mutation calling from the transcriptome can be heavily influenced by the gene expression level and potentially, by posttranscriptional modification such as nonsense mediated decay. Along with a substantial level of mutational heterogeneity of ICC genomes, our study reveals previously unrecognized two ICC classes defined by relative abundance of somatic mutations over CNAs or vice versa, which should be considered in the selection of genotyping platforms and sensitive screening of targets for ICC therapeutics.