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Patient-Derived Xenograft (PDX) provides important preclinical model for pharmacological testing of oncology drug candidates. Molecular profiling of PDX tumors contributes to many areas of drug discovery from target discovery to development of clinical biomarker hypotheses and clinical trial design. We established a work flow to perform genomic and histopathology analyses of large numbers of PDX tumor models being made available for Pfizer internal research. To date we have generated whole-genome sequencing (WGS), whole-exome sequencing (WES) and whole transcriptome sequencing (RNA-Seq) data on PDX models spanning six cancer types including colon, pancreatic and breast cancers. Bioinformatics pipelines were developed to quantify gene expression and detect genetic alterations including mutation, copy number variations and gene fusions. A controlled evaluation study demonstrated that in silico classification of NGS reads into human/mouse origins is more effective than laboratory-based methods for removing mouse tissue contamination. Comparative analyses of molecular profiles from PDX and primary tumors of the same cancer origins suggest that important patterns of gene expression are retained by PDX models. An integrative genomic classifier was developed using the random forest algorithm, trained on primary tumor data, and shown to identify PDX cancer subtypes with high accuracy. Citation Format: Zhengyan Kan, Edward Rosfjord, James Hardwick, Ying Ding, Xianxian Zheng, Julio Fernandez, Stephanie Shi, Mark Ozeck, Hui Wang, Gabriel Troche, Eric Upeslacis, Amy Jackson-Fisher, Keith Ching, Shibing Deng, Xie Tao, John Chionis, Maruja Lira, Xiaorong Li, Konstantinos Tsaparikos, Patrick Lappin, Pamela Vizcarra, David Shields, Judy Lucas, Paul Rejto. Molecular profiling of patient-derived xenograft models across cancers. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-33.

Gastric cancer is a heterogeneous disease with multiple environmental etiologies and alternative pathways of carcinogenesis. Beyond mutations in TP53, alterations in other genes or pathways account for only small subsets of the disease. We performed exome sequencing of 22 gastric cancer samples and identified previously unreported mutated genes and pathway alterations; in particular, we found genes involved in chromatin modification to be commonly mutated. A downstream validation study confirmed frequent inactivating mutations or protein deficiency of ARID1A, which encodes a member of the SWI-SNF chromatin remodeling family, in 83% of gastric cancers with microsatellite instability (MSI), 73% of those with Epstein-Barr virus (EBV) infection and 11% of those that were not infected with EBV and microsatellite stable (MSS). The mutation spectrum for ARID1A differs between molecular subtypes of gastric cancer, and mutation prevalence is negatively associated with mutations in TP53. Clinically, ARID1A alterations were associated with better prognosis in a stage-independent manner. These results reveal the genomic landscape, and highlight the importance of chromatin remodeling, in the molecular taxonomy of gastric cancer.

International audience; The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Alternative pre–messenger RNA (pre-mRNA) splicing plays important roles in development, physiology, and disease, and more than half of human genes are alternatively spliced. To understand the biological roles and regulation of alternative splicing across different tissues and stages of development, systematic methods are needed. Here, we demonstrate the use of microarrays to monitor splicing at every exon-exon junction in more than 10,000 multi-exon human genes in 52 tissues and cell lines. These genome-wide data provide experimental evidence and tissue distributions for thousands of known and novel alternative splicing events. Adding to previous studies, the results indicate that at least 74% of human multi-exon genes are alternatively spliced.

The expressed sequence tag (EST) collection in dbEST provides an extensive resource for detecting alternative splicing on a genomic scale. Using genomically aligned ESTs, a computational tool (TAP) was used to identify alternative splice patterns for 6400 known human genes from the RefSeq database. With sufficient EST coverage, one or more alternatively spliced forms could be detected for nearly all genes examined. To identify high (>95%) confidence observations of alternative splicing, splice variants were clustered on the basis of having mutually exclusive structures, and sample statistics were then applied. Through this selection, alternative splices expected at a frequency of >5% within their respective clusters were seen for only 17%–28% of genes. Although intron retention events (potentially unspliced messages) had been seen for 36% of the genes overall, the same statistical selection yielded reliable cases of intron retention for

With the availability of a nearly complete sequence of the human genome, aligning expressed sequence tags (EST) to the genomic sequence has become a practical and powerful strategy for gene prediction. Elucidating gene structure is a complex problem requiring the identification of splice junctions, gene boundaries, and alternative splicing variants. We have developed a software tool, Transcript Assembly Program (TAP), to delineate gene structures using genomically aligned EST sequences. TAP assembles the joint gene structure of the entire genomic region from individual splice junction pairs, using a novel algorithm that uses the EST-encoded connectivity and redundancy information to sort out the complex alternative splicing patterns. A method called polyadenylation site scan (PASS) has been developed to detect poly-A sites in the genome.TAP uses these predictions to identify gene boundaries by segmenting the joint gene structure at polyadenylated terminal exons. Reconstructing 1007 known transcripts, TAP scored a sensitivity (Sn) of 60% and a specificity (Sp) of 92% at the exon level. The gene boundary identification process was found to be accurate 78% of the time. TAP also reports alternative splicing patterns in EST alignments. An analysis of alternative splicing in 1124 genic regions suggested that more than half of human genes undergo alternative splicing. Surprisingly, we saw an absolute majority of the detected alternative splicing events affect the coding region. Furthermore, the evolutionary conservation of alternative splicing between human and mouse was analyzed using an EST-based approach. (See http://stl.wustl.edu/∼zkan/TAP/)

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

To survey hepatitis B virus (HBV) integration in liver cancer genomes, we conducted massively parallel sequencing of 81 HBV-positive and 7 HBV-negative hepatocellular carcinomas (HCCs) and adjacent normal tissues. We found that HBV integration is observed more frequently in the tumors (86.4%) than in adjacent liver tissues (30.7%). Copy-number variations (CNVs) were significantly increased at HBV breakpoint locations where chromosomal instability was likely induced. Approximately 40% of HBV breakpoints within the HBV genome were located within a 1,800-bp region where the viral enhancer, X gene and core gene are located. We also identified recurrent HBV integration events (in ≥ 4 HCCs) that were validated by RNA sequencing (RNA-seq) and Sanger sequencing at the known and putative cancer-related TERT, MLL4 and CCNE1 genes, which showed upregulated gene expression in tumor versus normal tissue. We also report evidence that suggests that the number of HBV integrations is associated with patient survival.

Background Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome. Methods We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays. Results Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%. We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the SLC45A3-ELK4 e4-e2 TIC to ERG-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines. Conclusions Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer.

Although genomewide association studies have successfully identified associations of many common single-nucleotide polymorphisms (SNPs) with common diseases, the SNPs implicated so far account for only a small proportion of the genetic variability of tested diseases. It has been suggested that common diseases may often be caused by rare alleles missed by genomewide association studies. To identify these rare alleles we need high-throughput, high-accuracy resequencing technologies. Although array-based genotyping has allowed genomewide association studies of common SNPs in tens of thousands of samples, array-based resequencing has been limited for 2 main reasons: the lack of a fully multiplexed pipeline for high-throughput sample processing, and failure to achieve sufficient performance. We have recently solved both of these problems and created a fully multiplexed high-throughput pipeline that results in high-quality data. The pipeline consists of target amplification from genomic DNA, followed by allele enrichment to generate pools of purified variant (or nonvariant) DNA and ends with interrogation of purified DNA on resequencing arrays. We have used this pipeline to resequence approximately 5 Mb of DNA (on 3 arrays) corresponding to the exons of 1,500 genes in >473 samples; in total >2,350 Mb were sequenced. In the context of this large-scale study we obtained a false positive rate of approximately 1 in 500,000 bp and a false negative rate of approximately 10%.

There was an error in the title of the article, which omitted the word "in." The correct title should read: ACC2 Is Expressed at High Levels in Human White Adipose and Has an Isoform with a Novel N-Terminus. This also affects the article's citation.

An important level at which the expression of programmed cell death (PCD) genes is regulated is alternative splicing. Our previous work identified an intronic splicing regulatory element in caspase-2 (casp-2) gene. This 100-nucleotide intronic element, In100, consists of an upstream region containing a decoy 3' splice site and a downstream region containing binding sites for splicing repressor PTB. Based on the signal of In100 element in casp-2, we have detected the In100-like sequences as a family of sequence elements associated with alternative splicing in the human genome by using computational and experimental approaches. A survey of human genome reveals the presence of more than four thousand In100-like elements in 2757 genes. These In100-like elements tend to locate more frequent in intronic regions than exonic regions. EST analyses indicate that the presence of In100-like elements correlates with the skipping of their immediate upstream exons, with 526 genes showing exon skipping in such a manner. In addition, In100-like elements are found in several human caspase genes near exons encoding the caspase active domain. RT-PCR experiments show that these caspase genes indeed undergo alternative splicing in a pattern predicted to affect their functional activity. Together, these results suggest that the In100-like elements represent a family of intronic signals for alternative splicing in the human genome.

The discovery of somatic mutations in cancer tissue is extremely laborious, time-consuming and costly. In an evaluation comparing mismatch repair detection (MRD) against Sanger sequencing for somatic-mutation detection, we found that MRD had a specificity of 96% and a sensitivity of 92%. Our results showed that MRD is a robust and cost-effective alternative to Sanger sequencing for identifying somatic mutations in human tumors.

To better decipher the functional impact of alternative splicing, we classified alternative splicing events in 10,818 pairs of human and mouse genes based on conservation at genome and transcript levels. Expression levels of conserved alternative splices in human and mouse expressed sequence tag databases show strong correlation, indicating that alternative splicing is similarly regulated in both species. A total of 43% (8921) of mouse alternative splices could be found in the human genome but not in human transcripts. Five of eleven tested mouse predictions were observed in human tissues, demonstrating that mouse transcripts provide a valuable resource for identifying alternative splicing events in human genes. Combining gene-specific measures of conserved and diverged alternative splicing with both gene classification based on Gene Ontology (GO) and microarray-determined gene expression in 52 diverse human tissues and cell lines, we found conserved alternative splicing most enriched in brain-expressed signaling pathways. Diverged alternative splicing is more prevalent in testis and cancerous cell line up-regulated processes, including protein biosynthesis, responses to stress and responses to endogenous stimuli. Using conservation as a surrogate for functional significance, these results suggest that alternative splicing plays an important role in enhancing the functional capacity of central nervous systems, while non-functional splicing more frequently occurs in testis and cell lines, possibly as a result of cellular stress and rapid proliferation.

Elucidating the molecular basis of Hepatocellular Carcinoma (HCC) is crucial to developing targeted diagnostics and therapies for this deadly disease. Somatically acquired structural variations (SVs) can lead to oncogenic gene fusions and gene expression deregulation in tumors. Although recent studies have delineated HCC genomic alterations including copy number variations, somatic mutations and HBV integrations, the landscape of SVs remains poorly characterized in HCC. We have predicted 4,314 SVs including large-scale insertions, deletions, inversions and translocations based on the whole-genome sequencing data for 88 primary HCC tumor/non-tumor tissues. We identified chromothripsis in 5 HCC genomes (5.7%) recurrently affecting chromosomal arms 1q and 8q. TP53 and RB1 alterations appear to cause increased levels of genomic arrangement and chromosomal instability. Albumin (ALB) was found to be the most significantly affected by SVs and harbor genomic alterations including deactivating mutations and deletions in 10.2% of cohort. Integrative analysis revealed a causal link between genomic rearrangements and copy number variations, such as focal amplifications of the CCND1/FGF19 loci, and distinctive patterns of copy number variation flanking SV breakpoints. Furthermore, we predicted 260 gene fusions which frequently result in aberrant over-expression of the 3′ genes in tumors. Citation Format: Julio Fernandez-Banet, Nikki P. Lee, Kin Tak Chan, Huan Gao, Xiao Liu, Wing Kin Sun, Winnie Tan, Sheung Tat Fan, Ronnie T. Poon, Shiyong Li, Keith Ching, Paul Rejto, Mao Mao, Zhengyan Kan. Decoding complex patterns of structural variations in hepatocellular carcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-231. doi:10.1158/1538-7445.AM2013-LB-231

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole genome sequencing (WGS) study of 88 matched HCC tumour/normal pairs, 81 of which are HBV positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find β-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumour suppressor (35.2%). The Wnt/β-catenin pathway, altered in 62.5% of cases, is likely to act as the major oncogenic driver in HCC. TP53 alterations appear to cause increased levels of genomic arrangement and chromosomal instability. We identified chromothripsis in 5 HCC genomes (5.7%) recurrently affecting chromosomal arms 1q and 8q. We also identified recurrent HBV integration events at the known and putative cancer-related genes such as TERT, MLL4 and CCNE1, which showed upregulated gene expression in tumour versus normal tissue. The frequently altered genes and pathways in HCC reflect classical cancer hallmarks. This study identified several prevalent and actionable mutations that provide a path towards therapeutic intervention of the disease. Citation Format: Mao Mao, Hancheng Zheng, Zhengyan Kan, Jiangchun Xu, Xiao Liu, Shuyu Li, Thomas Barber, Zhuolin Gong, Huan Gao, Ke Hao, Melinda Willard, Robert Hauptschein, Paul Rejto, Julio Fernandez, Guan Wang, Qinghui Zhang, Bo Wang, Ronghua Chen, Jian Wang, Nikki Lee, Wei Zhou, Zhao Lin, Zhiyu Peng, Kang Yi, Shengpei Chen, Lin Li, Xiaomei Fan, Jie Yang, Rui Ye, Jia Ju, Kai Wang, Heather Estrella, Shibing Deng, Ping Wei, Ming Qiu, Isabella Wulur, Jiangang Liu, Mariam Ehsani, Chunsheng Zhang, Andrey Loboda, Wing Kin Sung, Amit Aggarwal, Ronnie Poon, Sheung Tat Fan, Jun Wang, James Hardwick, Christoph Reinhard, Hongyue Dai, Yingrui Li, John Luk. Whole genome sequencing reveals genetic landscape of hepatocellular carcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr LB-229. doi:10.1158/1538-7445.AM2013-LB-229

We have systematic analyzed 4.5Mb of DNA representing 1507 genes in 450 human fresh frozen tumors covering four major human cancers and their subtypes for somatic mutations. For this analysis we used E. coli mismatch repair detection (MRD) for our primary mutation scans. All the identified variations were validated as somatic using nucleic acid mass spec and confirmed to be present in the original tumor and absent in the matched adjacent normal DNA. Of the all tumor samples analyzed ∼80% show somatic mutations in one or more genes studies. Of the genes analyzed we identified mutation in 842 genes. Applying statistical techniques and other measures we have identified 221 genes to be significantly mutated across all cancers studied. Further analysis of mutated genes by tumor types and subtypes revealed distinct patterns of significantly mutated genes. Besides the previously known mutated genes, we have identified several novel mutated genes with previously unknown role in cancers across the various cancer types studied. To further ascertain the relevance we have performed integrated analysis of mutation and copy number variations data from the samples studied and identified putative tumor supressors and oncogenes. Also, we have performed mutational analysis at the level of biological pathways and identified several mutated pathways. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2206.

The determinants of binding specificities of peptide recognition domains and their evolution remain important problems in molecular systems biology. Here, we present a new methodology to analyze the coevolution between a domain and its ligands by combining high-throughput phage display with deep sequencing. First, from a library of PDZ domains with diversity introduced at ten positions in the binding site, we evolved domains for binding to 15 distinct peptide ligands. Interestingly, for a given peptide many different functional domains emerged, which exhibited only limited sequence homology, showing that many different binding sites can recognize a given peptide. Subsequently, we used peptide-phage libraries and deep sequencing to map the specificity profiles of these evolved domains at high resolution, and we found that the domains recognize their cognate peptides with high affinity but low specificity. Our analysis reveals two aspects of evolution of new binding specificities. First, we were able to identify some common features amongst domains raised against a common peptide. Second, our analysis suggests that cooperative interactions between multiple binding site residues lead to a diversity of binding profiles with considerable plasticity. The details of intramolecular cooperativity remain to be elucidated, but nonetheless, we have established a general methodology that can be used to explore protein evolution in a systematic yet rapid manner.

Computational and microarray-based experimental approaches were used to generate a comprehensive transcript index for the human genome. Oligonucleotide probes designed from approximately 50,000 known and predicted transcript sequences from the human genome were used to survey transcription from a diverse set of 60 tissues and cell lines using ink-jet microarrays. Further, expression activity over at least six conditions was more generally assessed using genomic tiling arrays consisting of probes tiled through a repeat-masked version of the genomic sequence making up chromosomes 20 and 22. The combination of microarray data with extensive genome annotations resulted in a set of 28,456 experimentally supported transcripts. This set of high-confidence transcripts represents the first experimentally driven annotation of the human genome. In addition, the results from genomic tiling suggest that a large amount of transcription exists outside of annotated regions of the genome and serves as an example of how this activity could be measured on a genome-wide scale. These data represent one of the most comprehensive assessments of transcriptional activity in the human genome and provide an atlas of human gene expression over a unique set of gene predictions. Before the annotation of the human genome is considered complete, however, the previously unannotated transcriptional activity throughout the genome must be fully characterized.

Elucidating the molecular basis of hepatocellular carcinoma (HCC) is crucial to developing targeted diagnostics and therapies for this deadly disease. The landscape of somatic genomic rearrangements (GRs), which can lead to oncogenic gene fusions, remains poorly characterized in HCC. We have predicted 4314 GRs including large-scale insertions, deletions, inversions and translocations based on the whole-genome sequencing data for 88 primary HCC tumor/non-tumor tissues. We identified chromothripsis in 5 HCC genomes (5.7%) recurrently affecting chromosomal arms 1q and 8q. Albumin (ALB) was found to harbor GRs, deactivating mutations and deletions in 10% of cohort. Integrative analysis identified a pattern of paired intra-chromosomal translocations flanking focal amplifications and asymmetrical patterns of copy number variation flanking breakpoints of translocations. Furthermore, we predicted 260 gene fusions which frequently result in aberrant over-expression of the 3′ genes in tumors and validated 18 gene fusions, including recurrent fusion (2/88) of ABCB11 and LRP2.