Identification of chromosomal copy number variations and novel candidate loci in hereditary nonpolyposis colorectal cancer with mismatch repair proficiency

Integrated Whole-Transcriptome Profiling and Bioinformatics Analysis of the Polypharmacological Effects of Ganoderic Acid Me in Colorectal Cancer Treatment

Ganoderic acid Me (GA-Me) is a natural bioactive compound derived from Ganoderma lucidum. Our present results suggested that GA-Me inhibited proliferation, induced DNA fragmentation and significantly activated caspase-9 and caspase-3 in HCT116 cells. As shown in our previous studies, GA-Me targets several genes to prevent cancer, including colorectal cancer (CRC). Thus, we hypothesized that GA-Me might be a multitarget ligand against cancer. However, its exact mechanism in CRC remains unclear. Here, whole-transcriptome sequencing was employed to assess the long noncoding RNA (lncRNA), circular RNA (circRNA), microRNA (miRNA), and messenger RNA (mRNA) profiles of GA-Me-treated HCT116 cells. In total, 1572 differentially expressed (DE) lncRNAs, 123 DEcircRNAs, 87 DEmiRNAs, and 1508 DEmRNAs were identified. DCBLD2 and RAPGEF5 were validated as two core mRNAs in the DElncRNA, DEcircRNA, and DEmiRNA networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed the biological functions and potential mechanisms of TCONS-00008997, XR-925056.2, circRNA-07908, hsa-miR-100-3p, hsa-miR-1257, hsa-miR-3182, NAV3, ADAM20, and STARD4, which were altered after GA-Me treatment. The regulatory relationships of the XR-925056.2-hsa-miR-3182-NAV3/ADAM20/STARD4, circRNA-07908|Chr22:38986298-39025349-hsa-miR-3182-NAV3/ADAM20, ENST00000414039/ENST00000419190-novel874_mature-MMP9 and circRNA-00314|Chr1:35470863-35479212/circRNA-05460|Chr17:72592203-72649268-novel874_mature-MMP9 immune-regulatory networks involved both noncoding RNAs (ncRNAs) and mRNAs. Molecular docking studies showed that Zn²⁺ and the His201, His205, His211, Glu202, and Ala165 residues of MMP2 contributed to its high affinity for GA-Me. Zn²⁺ and the Glu402 and Gly186 residues of MMP9 are important for its interaction with GA-Me. Our results suggested and confirmed that GA-Me is a potential multitarget lead compound for CRC treatment with unique polypharmacological advantages.

Single nucleotide polymorphism array-based signature of low hypodiploidy in acute lymphoblastic leukemia

Low hypodiploidy (30-39 chromosomes) is one of the most prevalent genetic subtypes among adults with ALL and is associated with a very poor outcome. Low hypodiploid clones can often undergo a chromosomal doubling generating a near-triploid clone (60-78 chromosomes). When cytogenetic techniques detect a near triploid clone, a diagnostic challenge may ensue in differentiating presumed duplicated low hypodiploidy from good risk high hyperdiploid ALL (51-67 chromosomes). We used single-nucleotide polymorphism (SNP) arrays to analyze low hypodiploid/near triploid (HoTr) (n = 48) and high hyperdiploid (HeH) (n = 40) cases. In addition to standard analysis, we derived log2 ratios for entire chromosomes enabling us to analyze the cohort using machine-learning techniques. Low hypodiploid and near triploid cases clustered together and separately from high hyperdiploid samples. Using these approaches, we also identified three cases with 50-60 chromosomes, originally called as HeH, which were, in fact, HoTr and two cases incorrectly called as HoTr. TP53 mutation analysis supported the new classification of all cases tested. Next, we constructed a classification and regression tree model for predicting ploidy status with chromosomes 1, 7, and 14 being the key discriminators. The classifier correctly identified 47/50 (94%) HoTr cases. We validated the classifier using an independent cohort of 44 cases where it correctly called 7/7 (100%) low hypodiploid cases. The results of this study suggest that HoTr is more frequent among older adults with ALL than previously estimated and that SNP array analysis should accompany cytogenetics where possible. The classifier can assist where SNP array patterns are challenging to interpret.

High-Risk Clinicopathological and Genetic Features and Outcomes in Patients Receiving Neoadjuvant Radiochemotherapy for Locally Advanced Rectal Cancer

Administering preoperative radiochemotherapy (RCT) in stage II-III tumors to locally advanced rectal carcinoma patients has proved to be effective in a high percentage of cases. Despite this, 20-30% of patients show no response or even disease progression. At present, preoperative response is assessed by a combination of imaging and tumor regression on histopathology, but recent studies suggest that various genetic abnormalities may be associated with the sensitivity or resistance of rectal cancer tumor cells to neoadjuvant therapy. In the present study we investigated the relationship between genetic lesions detected by high-density single-nucleotide polymorphisms (SNP) arrays 6.0 and response to neoadjuvant RCT, evaluated according to Dworak criteria in 39 rectal cancer tumors before treatment. The highest frequency of copy-number (CN) losses detected corresponded to chromosomes 18q (n = 27; 69%), 1p (n = 22; 56%), 15q (n = 19; 49%), 8p (n = 18; 48%), 4q (n = 17; 46%), and 22q (n = 17; 46%); in turn, CN gains more frequently involved chromosomes 20p (n = 22; 56%), 8p (n = 20; 51%), and 15q (n = 16; 41%). There was a significant association between alterations in the 1p, 3q, 7q, 12p, 17q, 20p, and 22q chromosomal regions and the degree of response to therapy prior to surgery. However, 4q, 15q11.1, and 15q14 chromosomal region alterations were identified as important by five prediction algorithms, i.e., those with the greatest influence on predicting the tumor response to treatment with preoperative RCT. Multivariate analysis of prognostic factors showed that gains on 15q11.1 and carcinoembryonic antigen (CEA) levels serum at diagnosis were the only independent variables predicting disease-free survival (DFS). Lymph node involvement also showed a prognostic impact on overall survival (OS) in the multivariate analysis. A deep-learning-based algorithm showed a 100% success rate in predicting both DFS and OS at 60 months after diagnosis of the disease. In summary, our results indicate the existence of an association between tumor genetic abnormalities at diagnosis, response to neoadjuvant therapy, and survival of patients with locally advanced rectal cancer. In addition to the clinical and biological characteristics of locally advanced rectal cancer patients, these could be used in the future as therapeutic and prognostic biomarkers, to identify patients sensitive or resistant to preoperative treatment, helping guide therapeutic decision-making. Additional prospective studies in larger series of patients are required to confirm the clinical utility of the newly identified biomarkers.

Genetic Analysis of Multiple Myeloma Identifies Cytogenetic Alterations Implicated in Disease Complexity and Progression

Multiple myeloma (MM) is a genetically heterogeneous disease characterized by genomic chaos making it difficult to distinguish driver from passenger mutations. In this study, we integrated data from whole genome gene expression profiling (GEP) microarrays and CytoScan HD high-resolution genomic arrays to integrate GEP with copy number variations (CNV) to more precisely define molecular alterations in MM important for disease initiation, progression and poor clinical outcome. We utilized gene expression arrays from 351 MM samples and CytoScan HD arrays from 97 MM samples to identify eight CNV events that represent possible MM drivers. By integrating GEP and CNV data we divided the MM into eight unique subgroups and demonstrated that patients within one of the eight distinct subgroups exhibited common and unique protein network signatures that can be utilized to identify new therapeutic interventions based on pathway dysregulation. Data also point to the central role of 1q gains and the upregulated expression of ANP32E, DTL, IFI16, UBE2Q1, and UBE2T as potential drivers of MM aggressiveness. The data presented here utilized a novel approach to identify potential driver CNV events in MM, the creation of an improved definition of the molecular basis of MM and the identification of potential new points of therapeutic intervention.

A multiple genomic data fused SF2 prediction model, signature identification, and gene regulatory network inference for personalized radiotherapy

Radiotherapy is one of the most important cancer treatments, but its response varies greatly among individual patients. Therefore, the prediction of radiosensitivity, identification of potential signature genes, and inference of their regulatory networks are important for clinical and oncological reasons. Here, we proposed a novel multiple genomic fused partial least squares deep regression method to simultaneously analyze multi-genomic data. Using 60 National Cancer Institute cell lines as examples, we aimed to identify signature genes by optimizing the radiosensitivity prediction model and uncovering regulatory relationships. A total of 113 signature genes were selected from more than 20,000 genes. The root mean square error of the model was only 0.0025, which was much lower than previously published results, suggesting that our method can predict radiosensitivity with the highest accuracy. Additionally, our regulatory network analysis identified 24 highly important ‘hub’ genes. The data analysis workflow we propose provides a unified and computational framework to harness the full potential of large-scale integrated cancer genomic data for integrative signature discovery. Furthermore, the regression model, signature genes, and their regulatory network should provide a reliable quantitative reference for optimizing personalized treatment options, and may aid our understanding of cancer progress mechanisms.

An accurate and powerful method for copy number variation detection

MOTIVATION

Integration of multiple genetic sources for copy number variation detection (CNV) is a powerful approach to improve the identification of variants associated with complex traits. Although it has been shown that the widely used change point based methods can increase statistical power to identify variants, it remains challenging to effectively detect CNVs with weak signals due to the noisy nature of genotyping intensity data. We previously developed modSaRa, a normal mean-based model on a screening and ranking algorithm for copy number variation identification which presented desirable sensitivity with high computational efficiency. To boost statistical power for the identification of variants, here we present a novel improvement that integrates the relative allelic intensity with external information from empirical statistics with modeling, which we called modSaRa2.

RESULTS

Simulation studies illustrated that modSaRa2 markedly improved both sensitivity and specificity over existing methods for analyzing array-based data. The improvement in weak CNV signal detection is the most substantial, while it also simultaneously improves stability when CNV size varies. The application of the new method to a whole genome melanoma dataset identified novel candidate melanoma risk associated deletions on chromosome bands 1p22.2 and duplications on 6p22, 6q25 and 19p13 regions, which may facilitate the understanding of the possible roles of germline copy number variants in the etiology of melanoma.

AVAILABILITY AND IMPLEMENTATION

http://c2s2.yale.edu/software/modSaRa2 or https://github.com/FeifeiXiaoUSC/modSaRa2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

RAPGEF5 Regulates Nuclear Translocation of β-Catenin

Canonical Wnt signaling coordinates many critical aspects of embryonic development, while dysregulated Wnt signaling contributes to common diseases, including congenital malformations and cancer. The nuclear localization of β-catenin is the defining step in pathway activation. However, despite intensive investigation, the mechanisms regulating β-catenin nuclear transport remain undefined. In a patient with congenital heart disease and heterotaxy, a disorder of left-right patterning, we previously identified the guanine nucleotide exchange factor, RAPGEF5. Here, we demonstrate that RAPGEF5 regulates left-right patterning via Wnt signaling. In particular, RAPGEF5 regulates the nuclear translocation of β-catenin independently of both β-catenin cytoplasmic stabilization and the importin β1/Ran-mediated transport system. We propose a model whereby RAPGEF5 activates the nuclear GTPases, Rap1a/b, to facilitate the nuclear transport of β-catenin, defining a parallel nuclear transport pathway to Ran. Our results suggest new targets for modulating Wnt signaling in disease states.

Genome-wide association study identified copy number variants associated with sporadic colorectal cancer risk

Background

Multiple single nucleotide polymorphisms (SNPs) have been associated with colorectal cancer (CRC) risk. The role of structural or copy number variants (CNV) in CRC, however, remained unclear. We investigated the role of CNVs in patients with sporadic CRC.

Methods

A genome-wide association study (GWAS) was performed on 1000 Singapore Chinese patients aged 50 years or more with no family history of CRC and 1000 ethnicity-matched, age-matched and gender-matched healthy controls using the Affymetrix SNP 6 platform. After 16 principal component corrections, univariate and multivariate segmentations followed by association testing were performed on 1830 samples that passed quality assurance tests.

Results

A rare CNV region (CNVR) at chromosome 14q11 (OR=1.92 (95% CI 1.59 to 2.32), p=2.7e-12) encompassing CHD8, and common CNVR at chromosomes 3q13.12 (OR=1.54 (95% CI 1.33 to 1.77), p=2.9e-9) and 12p12.3 (OR=1.69 (95% CI 1.41 to 2.01), p=2.8e-9) encompassing CD47 and RERG/ARHGDIB, respectively, were significantly associated with CRC risk. CNV loci were validated in an independent replication panel using an optimised copy number assay. Whole-genome expression data in matched tumours of a subset of cases demonstrated that copy number loss at CHD8 was significantly associated with dysregulation of several genes that perturb the Wnt, TP53 and inflammatory pathways.

Conclusions

A rare CNVR at 14q11 encompassing the chromatin modifier CHD8 was significantly associated with sporadic CRC risk. Copy number loss at CHD8 altered expressions of genes implicated in colorectal tumourigenesis.

Familial Colorectal Cancer Type X

The genetic background is unknown for the 50-60% of the HNPCC families, who fulfill the Amsterdam criteria, but do not have a mutation in an MMR gene, and is referred to as FCCTX. This study reviews the clinical, morphological and molecular characteristics of FCCTX, and discusses the molecular genetic methods used to localize new FCCTX genes, along with an overview of the genes and chromosomal areas that possibly relate to FCCTX. FCCTX is a heterogeneous group, mainly comprising cases caused by single high-penetrance genes, or by multiple low-penetrance genes acting together, and sporadic CRC cases. FCCTX differs in clinical, morphological and molecular genetic characteristics compared to LS, including a later age of onset, distal location of tumours in the colon, lower risk of developing extracolonic tumours and a higher adenoma/carcinoma ratio, which indicates a slower progression to CRC. Certain characteristics are shared with sporadic CRC, e.g. similarities in gene expression and a high degree of CIN+, with significanly increased 20q gain in FCCTX. Other molecular characteristics of FCCTX include longer telomere length and hypomethylation of LINE-1, both being a possible explanation for CIN+. Some genes in FCCTX families (RPS20, BMPR1A, SEMA4A) have been identified by using a combination of linkage analysis and sequencing. Sequencing strategies and subsequent bioinformatics are improving fast. Exome sequencing and whole genome sequencing are currently the most promising tools. Finally, the involvement of CNV’s and regulatory sequences are widely unexplored and would be interesting for further investigation in FCCTX.

Genome-wide analysis of DNA copy number alterations in early and advanced gastric cancers

To better understand progressive changes in gastric cancer (GC), early and advanced GCs (EGC and AGC, respectively) were examined for copy number alterations (CNAs). A crypt isolation method was used to isolate DNA from tumors and normal glands in 20 AGCs, and fresh tumor samples were obtained from 45 EGCs. We assessed CNAs for differentiated-type GCs using an Infinium HumanCytoSNP-12v2.1 BeadChip in EGCs and AGCs. The most frequent aberrations in EGC were gains at 8q23.3 (42.2%) and 8q23.2 (40%), and loss of heterozygosity (LOH) at 3p14.2 (24.2%), suggesting that these CNAs were involved in the development of EGC. On the other hand, the highest frequencies of gains in AGC were found at 8q24.21 (65%) and 8q24.3 (60%). The most frequent LOHs in AGC were at 11q24.3-25, 11q23.2-24.1, 11q14.1, and 12p11.21-13.33, whereas that in EGC was at 3p14.2. In addition, regions of copy-neutral LOHs in AGC were detected at 11q21, 11q13.3-14.3, 11q11, 11p13-15.3, 12q21.1, 12q12-13.3 and 5q33.3-35.1. Comparisons of gains in EGC and AGC showed significant differences at 12q22-q23.2, 12q21.33, 11p12, 11p14.1, 12q21.31-32.32, 3p12.3, 3p14.1, 10p15.1, 1q24.2 and 2q12.1. Copy neutral LOHs were significantly higher in AGC than in EGC at 14q32.11-32.33, 14q21.3, 14q11.2, 5q11.2, 5q 13.3, 14q21.1-23.2, 14q13.2-13.3, 5q12.1-12.3, 5q11.1, and 17p13.3. The total lengths of the CNAs were significantly greater in AGC than in EGC. We found that the pattern of CNAs in AGC was quite different from that in EGC. We suggest that increasing numbers of CNAs are associated with disease progression from EGC to AGC. © 2016 Wiley Periodicals, Inc.

Somatic gene copy number alterations in colorectal cancer: new quest for cancer drivers and biomarkers

Colorectal cancer (CRC) results from the accumulation of genetic alterations, and somatic copy number alterations (CNAs) are crucial for the development of CRC. Genome-wide survey of CNAs provides opportunities for identifying cancer driver genes in an unbiased manner. The detection of aberrant CNAs may provide novel markers for the early diagnosis and personalized treatment of CRC. A major challenge in array-based profiling of CNAs is to distinguish the alterations that play causative roles from the random alterations that accumulate during colorectal carcinogenesis. In this view, we systematically discuss the frequent CNAs in CRC, focusing on functional genes that have potential diagnostic, prognostic and therapeutic significance.

Molecular biomarkers in colorectal carcinoma

Colorectal cancer is a tumor with increasing incidence which represents one of the first leading causes of death worldwide. Gene alterations described for colorectal cancer include genome instability (microsatellite and chromosomal instability), CpG islands methylator phenotype, microRNA, histone modification, protein biomarkers, gene mutations (RAS, BRAF, PI3K, TP53, PTEN) and polymorphisms (APC, CTNNB1, DCC). In this article, biomarkers with prognostic value commonly found in colorectal cancer will be reviewed.

Genetic variation analysis in a Chinese Maffucci syndrome patient

OBJECTIVE

To report on the molecular genetic analysis of a Chinese patient with Maffucci syndrome.

METHODS

Using the genomic DNA extracted from the patient's hemangioma sample, the coding exons and exon/intron splice junctions of the IDH1 and IDH2 genes were amplified by polymerase chain reaction (PCR) and then sequenced. Genomic DNA was extracted from blood and a hemangioma sample from the patient, and also from her mother's blood, for chromosome microarray analysis (CMA) by Affymetrix CytoScan HD array.

RESULTS

None of the known pathogenic mutations in the whole IDH1 or IDH2 genes was found in the patient's hemangioma sample. CMA detected 40 tumor-specific copy number variations (CNVs), and one copy number neutral loss of heterozygosity (LOH) region. Among the 73 known genes included in the 40 CNV regions, only 2 genes, CHEK2 (604373) located in 22q12.1 and EP300 (602700) located in 22q13.2, were found to be related to tumorigenesis. We did not find any CNVs at the IDH1 and IDH2 loci.

CONCLUSIONS

This is the first molecular genetic analysis report on a Chinese patient with Maffucci syndrome and our data enrich the understanding of the genetic background of Maffucci syndrome in different ethnic groups. The relationship between CHEK2, EP300 and Maffucci syndrome needs to be further explored.

Allele-specific imbalance mapping at human orthologs of mouse susceptibility to colon cancer (Scc) loci

Colorectal cancer (CRC) can be classified into different types. Chromosomal instable (CIN) colon cancers are thought to be the most common type of colon cancer. The risk of developing a CIN-related CRC is due in part to inherited risk factors. Genome-wide association studies have yielded over 40 single nucleotide polymorphisms (SNPs) associated with CRC risk, but these only account for a subset of risk alleles. Some of this missing heritability may be due to gene-gene interactions. We developed a strategy to identify interacting candidate genes/loci for CRC risk that utilizes both linkage and RNA-seq data from mouse models in combination with allele-specific imbalance (ASI) studies in human tumors. We applied our strategy to three previously identified CRC susceptibility loci in the mouse that show evidence of genetic interaction: Scc4, Scc5 and Scc13. 525 SNPs from genes showing differential expression in the mouse and/or a previous role in cancer from the literature were evaluated for allele-specific imbalance in 194 paired human normal/tumor DNAs from CIN-related CRCs. One hundred three SNPs showing suggestive evidence of ASI (31 variants with uncorrected p values < 0.05) were genotyped in a validation set of 296 paired DNAs. Two variants in SNX10 (SCC13) showed significant evidence of allelic selection after multiple comparisons testing. Future studies will evaluate the role of these variants in combination with interacting genetic partners in colon cancer risk in mouse and humans.

Integrated exon level expression analysis of driver genes explain their role in colorectal cancer

Integrated analysis of genomic and transcriptomic level changes holds promise for a better understanding of colorectal cancer (CRC) biology. There is a pertinent need to explain the functional effect of genome level changes by integrating the information at the transcript level. Using high resolution cytogenetics array, we had earlier identified driver genes by ‘Genomic Identification of Significant Targets In Cancer (GISTIC)’ analysis of paired tumour-normal samples from colorectal cancer patients. In this study, we analyze these driver genes at three levels using exon array data – gene, exon and network. Gene level analysis revealed a small subset to experience differential expression. These results were reinforced by carrying out separate differential expression analyses (SAM and LIMMA). ATP8B1 was found to be the novel gene associated with CRC that shows changes at cytogenetic, gene and exon levels. Splice index of 29 exons corresponding to 13 genes was found to be significantly altered in tumour samples. Driver genes were used to construct regulatory networks for tumour and normal groups. There were rearrangements in transcription factor genes suggesting the presence of regulatory switching. The regulatory pattern of AHR gene was found to have the most significant alteration. Our results integrate data with focus on driver genes resulting in highly enriched novel molecules that need further studies to establish their role in CRC.

Comprehensive molecular characterisation of hereditary non-polyposis colorectal tumours with mismatch repair proficiency

BACKGROUND

Hereditary non-polyposis colorectal cancer (CRC) without mismatch repair (MMR) defects occurs in almost half of high-risk CRC families, but its genetic cause(s) is(are) still unknown. We aimed to identify unique molecular features that differentiate hereditary from sporadic MMR-proficient colorectal tumours.

METHODS

Genomic alterations in 16 tumours from 14 Amsterdam I-II families were studied using the genome-wide copy number OncoScan™ FFPE microarray. Somatic mutation hotspots in BRAF, KRAS, PIK3CA and TP53 were analysed in 37 colorectal tumours from 26 families and in 99 sporadic MMR-proficient CRCs, using direct automated sequencing and KASPar genotyping assays. CpG methylation index was studied in 25 tumours from 19 families by methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA).

RESULTS

Our findings indicate that hereditary MMR-proficient tumours have overlapping genomic profiles to those obtained in sporadic cases, both suggestive of high chromosomal instability, and no high CpG methylation index. Nevertheless, we identified a significant increase in the frequency of chromosome 2p and 2q gains, and of 10 q loss in Amsterdam I families, as well as low frequency of >2 Mb copy-neutral or -gained loss of heterozygosity (LOH). No statistically significant differences in the frequency of BRAF, KRAS, PIK3CA and TP53 mutations or in the gene mutation patterns were observed. However, TP53 mutations appeared almost twice more frequently in sporadic tumours.

CONCLUSIONS

Overall, hereditary MMR-proficient CRCs display similar molecular characteristics than their sporadic counterparts. However, the differences identified, such as the chromosome 2 gain, 10 q loss, or the under-representation of TP53 mutations, if validated in larger series, might be of relevance in the clinical setting and/or in the identification of germline defects underlying some of these familial cases.

Use of single nucleotide polymorphism array technology to improve the identification of chromosomal lesions in leukemia

Acute leukemias are characterized by recurring chromosomal and genetic abnormalities that disrupt normal development and drive aberrant cell proliferation and survival. Identification of these abnormalities plays important role in diagnosis, risk assessment and patient classification. Until the last decade methods to detect these aberrations have included genome wide approaches, such as conventional cytogenetics, but with a low sensitivity (5-10%), or gene candidate approaches, such as fluorescent in situ hybridization, having a greater sensitivity but being limited to only known regions of the genome. Single nucleotide polymorphism (SNP) technology is a screening method that has revolutionized our way to find genetic alterations, enabling linkage and association studies between SNP genotype and disease as well as the identification of alterations in DNA content on a whole genome scale. The adoption of this approach for the study of lymphoid and myeloid leukemias contributed to the identification of novel genetic alterations, such as losses/gains/uniparental disomy not visible by cytogenetics and implicated in pathogenesis, improving risk assessment and patient classification and in some cases working as targets for tailored therapies. In this review, we reported recent advances obtained in the knowledge of the genomic complexity of chronic myeloid leukemia and acute leukemias thanks to the use of high-throughput technologies, such as SNP array.

CNVannotator: a comprehensive annotation server for copy number variation in the human genome

Copy number variation (CNV) is one of the most prevalent genetic variations in the genome, leading to an abnormal number of copies of moderate to large genomic regions. High-throughput technologies such as next-generation sequencing often identify thousands of CNVs involved in biological or pathological processes. Despite the growing demand to filter and classify CNVs by factors such as frequency in population, biological features, and function, surprisingly, no online web server for CNV annotations has been made available to the research community. Here, we present CNVannotator, a web server that accepts an input set of human genomic positions in a user-friendly tabular format. CNVannotator can perform genomic overlaps of the input coordinates using various functional features, including a list of the reported 356,817 common CNVs, 181,261 disease CNVs, as well as, 140,342 SNPs from genome-wide association studies. In addition, CNVannotator incorporates 2,211,468 genomic features, including ENCODE regulatory elements, cytoband, segmental duplication, genome fragile site, pseudogene, promoter, enhancer, CpG island, and methylation site. For cancer research community users, CNVannotator can apply various filters to retrieve a subgroup of CNVs pinpointed in hundreds of tumor suppressor genes and oncogenes. In total, 5,277,234 unique genomic coordinates with functional features are available to generate an output in a plain text format that is free to download. In summary, we provide a comprehensive web resource for human CNVs. The annotated results along with the server can be accessed at http://bioinfo.mc.vanderbilt.edu/CNVannotator/.