AVIA: an interactive web-server for annotation, visualization and impact analysis of genomic variations

A Comparative Genomic Analysis of Parathyroid Adenomas and Carcinomas Harboring Heterozygous Germline CDC73 Mutations

CONTEXT

Parathyroid cancer has been linked to germline mutations of the Cell Division Cycle 73 (CDC73) gene. However, carriers harboring cancer-associated germline CDC73 mutations may develop only parathyroid adenoma or no parathyroid disease. This incomplete penetrance indicates that additional genomic events are required for parathyroid tumorigenesis.

OBJECTIVE

(1) Determine the status of the second CDC73 allele in parathyroid tumors harboring germline CDC73 mutations and (2) compare the genomic landscapes between parathyroid carcinomas and adenomas.

DESIGN

Whole-exome and RNA sequencing of 12 parathyroid tumors harboring germline CDC73 mutations (6 adenomas and 6 carcinomas) and their matched normal tissues.

RESULTS

All 12 parathyroid tumors had gained 1 somatic event predicted to cause a complete inactivation of the second CDC73 allele. Several distinctive genomic features were identified in parathyroid carcinomas compared to adenomas, including more single nucleotide variants bearing the C > G transversion and APOBEC deamination signatures, frequent mutations of the genes involved in the PI-3K/mTOR signaling, a greater number of copy number variations, and substantially more genes with altered expression. Parathyroid carcinomas also share some genomic features with adenomas. For instance, both have recurrent somatic mutations and copy number loss that impact the genes involved in T-cell receptor signaling and tumor antigen presentation, suggesting a shared strategy to evade immune surveillance.

CONCLUSION

Biallelic inactivation of CDC73 is essential for parathyroid tumorigenesis in carriers harboring germline mutations of this gene. Despite sharing some genomic features with adenomas, parathyroid carcinomas have more distinctive alterations in the genome, some of which may be critical for cancer formation.

AVIA 3.0: interactive portal for genomic variant and sample level analysis

SUMMARY

The Annotation, Visualization and Impact Analysis (AVIA) is a web application combining multiple features to annotate and visualize genomic variant data. Users can investigate functional significance of their genetic alterations across samples, genes and pathways. Version 3.0 of AVIA offers filtering options through interactive charts and by linking disease relevant data sources. Newly incorporated services include gene, variant and sample level reporting, literature and functional correlations among impacted genes, comparative analysis across samples and against data sources such as TCGA and ClinVar, and cohort building. Sample and data management is now feasible through the application, which allows greater flexibility with sharing, reannotating and organizing data. Most importantly, AVIA's utility stems from its convenience for allowing users to upload and explore results without any a priori knowledge or the need to install, update and maintain software or databases. Together, these enhancements strengthen AVIA as a comprehensive, user-driven variant analysis portal.

AVAILABILITYAND IMPLEMENTATION

AVIA is accessible online at https://avia-abcc.ncifcrf.gov.

Molecular analysis of urothelial cancer cell lines for modeling tumor biology and drug response

The utility of tumor-derived cell lines is dependent on their ability to recapitulate underlying genomic aberrations and primary tumor biology. Here, we sequenced the exomes of 25 bladder cancer (BCa) cell lines and compared mutations, copy number alterations (CNAs), gene expression and drug response to BCa patient profiles in The Cancer Genome Atlas (TCGA). We observed a mutation pattern associated with altered CpGs and APOBEC-family cytosine deaminases similar to mutation signatures derived from somatic alterations in muscle-invasive (MI) primary tumors, highlighting a major mechanism(s) contributing to cancer-associated alterations in the BCa cell line exomes. Non-silent sequence alterations were confirmed in 76 cancer-associated genes, including mutations that likely activate oncogenes TERT and PIK3CA, and alter chromatin-associated proteins (MLL3, ARID1A, CHD6 and KDM6A) and established BCa genes (TP53, RB1, CDKN2A and TSC1). We identified alterations in signaling pathways and proteins with related functions, including the PI3K/mTOR pathway, altered in 60% of lines; BRCA DNA repair, 44% and SYNE1–SYNE2, 60%. Homozygous deletions of chromosome 9p21 are known to target the cell cycle regulators CDKN2A and CDKN2B. This loci was commonly lost in BCa cell lines and we show the deletions extended to the polyamine enzyme methylthioadenosine (MTA) phosphorylase (MTAP) in 36% of lines, transcription factor DMRTA1 (27%) and antiviral interferon epsilon (IFNE, 19%). Overall, the BCa cell line genomic aberrations were concordant with those found in BCa patient tumors. We used gene expression and copy number data to infer pathway activities for cell lines, then used the inferred pathway activities to build a predictive model of cisplatin response. When applied to platinum-treated patients gathered from TCGA, the model predicted treatment-specific response. Together, these data and analysis represent a valuable community resource to model basic tumor biology and to study the pharmacogenomics of BCa.

AVIA v2.0: annotation, visualization and impact analysis of genomic variants and genes

As sequencing becomes cheaper and more widely available, there is a greater need to quickly and effectively analyze large-scale genomic data. While the functionality of AVIA v1.0, whose implementation was based on ANNOVAR, was comparable with other annotation web servers, AVIA v2.0 represents an enhanced web-based server that extends genomic annotations to cell-specific transcripts and protein-level functional annotations. With AVIA's improved interface, users can better visualize their data, perform comprehensive searches and categorize both coding and non-coding variants.

AVAILABILITY AND IMPLEMENTATION

AVIA is freely available through the web at http://avia.abcc.ncifcrf.gov.

CONTACT

Hue.Vuong@fnlcr.nih.gov

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Current trend of annotating single nucleotide variation in humans--A case study on SNVrap

As high throughput methods, such as whole genome genotyping arrays, whole exome sequencing (WES) and whole genome sequencing (WGS), have detected huge amounts of genetic variants associated with human diseases, function annotation of these variants is an indispensable step in understanding disease etiology. Large-scale functional genomics projects, such as The ENCODE Project and Roadmap Epigenomics Project, provide genome-wide profiling of functional elements across different human cell types and tissues. With the urgent demands for identification of disease-causal variants, comprehensive and easy-to-use annotation tool is highly in demand. Here we review and discuss current progress and trend of the variant annotation field. Furthermore, we introduce a comprehensive web portal for annotating human genetic variants. We use gene-based features and the latest functional genomics datasets to annotate single nucleotide variation (SNVs) in human, at whole genome scale. We further apply several function prediction algorithms to annotate SNVs that might affect different biological processes, including transcriptional gene regulation, alternative splicing, post-transcriptional regulation, translation and post-translational modifications. The SNVrap web portal is freely available at http://jjwanglab.org/snvrap.