Citations

Abstract Chromosome rearrangements that result in gene fusions have important roles in the initial steps of tumorigenesis especially in leukemias and lymphomas, but the biological and clinical impact of gene fusions in the common solid tumor has been less appreciated. We previously generated RNAseq data from 12 oropharyngeal tumors along with matched normal tissue from the same patients. We utilized and compared two bioinformatic pipelines, SnowShoes-FTD and FusionHunter to identify two novel fusion events involving of MGST3-ZMAT5 and MS4A7-DKFZp586P0123. These fusions were validated utilizing. Reverse transcriptase polymerase chain reaction (RT-PCR) and Sanger sequencing validated. In the first translocation the 5′ UTR of MGST3 was fused with exon 1 of ZMAT5, and in the second translocation the exon 2 of MS4A7 was fused with 3′ UTR of DKFZp586P0123. These precise fusions were not present in the matched normal tissue, however, they were only found in the single tumor in which they were identified. Given a growing and powerful set of high-throughput massively parallel sequencing technologies, the future for genome-wide analysis of chromosome rearrangement appears open in many directions. Ultimately, we hope that this integrative methodology will elucidate key aspects of tumor biology as well as generate novel targets for cancer diagnostics and therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3100. doi:1538-7445.AM2012-3100

Abstract Motivation: Overexpression of HER2 (the product of the ERBB2 gene) occurs in about 15% of all breast tumors. We have undertaken to use next generation transcriptome sequencing technology to identify genomic features that are unique to HER2+ tumors. Interactome mapping was then used to integrate the genes associated with these features into a transcriptome landscape model, with a view towards identifying nodes of interaction that might be targeted in HER2+ tumors. Methods: We performed 50nt paired-end RNA-sequencing for 24 breast tumors: 8 each HER2+, ER+, triple negatives (TN). In addition to breast adenocarcinomas, we also sequenced 8 early passage non-transformed HMEC cell lines as normal controls. Reads from RNA sequencing were aligned to the genome and exon junctions using TopHat software. Gene counts were summarized and annotations were performed using our in-house programs. Tukey's test was used to obtain genes or transcripts that are specific to HER2 tumor group compared to other tumors/normal. A combination of bioinformatics softwares and algorithms were used to identify SNVs. Results: Only 13527 genes with median gene count greater than 16 reads in at least one of the 4 groups were considered for differential gene expression and splicing analysis. Some 696 genes were differentially expressed in HER2+ tumors compared to ER+, TN tumors and HMECs. We identified 272 alternately spliced transcripts for which the HER2+ tumors exhibited a mean transcript expression ratio significantly different from the means of other tumor groups. We also identified 4735 expressed single nucleotide variants that are uniquely associated with HER2+ tumors compared to other tumors/normal groups. Among these 3579/4735 sequence polymorphisms were not present in the 1000 genome germline sequence database or in the dbSNP132 database of naturally occurring germline polymorphisms. Integration of all the genes obtained from genomic feature analyses (differential expression, alternative splicing, single nucleotide variance) has been carried out to indentify biological processes that are specific to the HER2+ tumor subtype. Key nodes and pathways that are specific to HER2+ tumors will be evaluated for association with clinical outcome in a large series of patients who have received HER2-targeted therapy. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4926. doi:1538-7445.AM2012-4926

Abstract Peripheral T-cell lymphomas (PTCLs) are aggressive malignancies of mature T lymphocytes with 5-year overall survival rates of only ∼ 35%. Improvement in outcomes has been stymied by poor understanding of the genetics and molecular pathogenesis of PTCL, with a resulting paucity of molecular targets for therapy. We developed bioinformatic tools to identify chromosomal rearrangements using genome-wide, next-generation sequencing analysis of mate-pair DNA libraries and applied these tools to 16 PTCL patient tissue samples and 6 PTCL cell lines. Thirteen recurrent abnormalities were identified, of which 5 involved p53-related genes (TP53, TP63, CDKN2A, WWOX, and ANKRD11). Among these abnormalities were novel TP63 rearrangements encoding fusion proteins homologous to ΔNp63, a dominant-negative p63 isoform that inhibits the p53 pathway. TP63 rearrangements were seen in 11 (5.8%) of 190 PTCLs and were associated with inferior overall survival; they also were detected in 2 (1.2%) of 164 diffuse large B-cell lymphomas. As TP53 mutations are rare in PTCL compared with other malignancies, our findings suggest that a constellation of alternate genetic abnormalities may contribute to disruption of p53-associated tumor suppressor function in PTCL.

Abstract Motivation: KRAS is commonly mutated in a variety of cancers including lung cancer. The KRAS gene is frequently mutated at codons 12 and 13 in lung adenocarcinomas in patients with a history of smoking. Tumors harboring an activating KRAS mutation are aggressive and are often resistant to available therapies. In the present study, we set out to identify pathways that are specifically altered in lung cancer patients whose tumors harbor a KRAS mutation using next generation sequencing technology. Methods: We performed 50nt paired-end RNA-sequencing in 15 lung adenocarcinoma samples (8 and 7 samples with and without KRAS mutation). Reads were aligned to genome and exon junctions using Illumina's alignment tool ELAND_RNA. CASAVA and Genome Studio data analysis software were used to obtain read counts for genes, exons and exon junctions. We applied a variety of computational methods (Casper R package, Bowtie, TopHat) and softwares (Partek, R statistical software, JMP, Ingenuity Pathway Anlaysis, DAVID) to carry out our analyses. Results: Differential gene expression and splicing analysis were performed between the two groups. We identified 115 genes that were differentially expressed and 112 genes that consist of splicing variants with at least 2 fold changes and p-value < 0.01. We randomly selected 6/15 samples and performed real-time qRT-PCR for 6 differentially expressed genes. Significant correlations were observed ranging from 0.44 to 0.83, when qRT-PCR results were compared with RNA-sequencing expression data. Pathway analysis with 115 differentially expressed genes and 112 splicing variants revealed that the most significant pathway is composed entirely of NFκB focus genes, suggesting that there is a direct connection between oncogenic KRAS and activation of the NFκB signaling pathway. Conclusions: NFκB has been implicated in KRas-mediated formation of early stage lung adenomas in the LSL-Kas mouse model. Our data indicate that this connection also occurs in human lung cancer and establish NFκB activation as a key manifestation of KRAS mutation in human lung cancer. Hence drugs targeting NFκB and NFκB related genes may potentially be helpful for the treatment of patients with oncogenic KRAS mutations. (Supported in part by grants from the 26.2 with Donna Foundation and the Florida Department of Health Bankhead/Coley program.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4975. doi:10.1158/1538-7445.AM2011-4975

Abstract Background: Estrogen receptor (ER) expression in breast caner is an important biomarker for targeted therapy and outcome prediction. Nevertheless, the molecular mechanism that controls the phenotypic difference is little known. We used deep sequence technology to profile the transcriptome, gene copy number, and CpG island methylation simultaneously in eight commonly used breast cell lines to develop a model for how these genomic features are integrated in ER+ and ER- breast cancer. Materials and methods: Total mRNA sequence (mRNA-seq), gene copy number (DNA-seq), and genomic CpG island methylation (Methyl-seq) were carried out using the Illumina Genome Analyzer. Sequences were mapped to the human genome (hg18) to obtain digitized gene expression data, DNA copy number in reference to the non-tumor cell line (MCF10A), and methylation status of 21,570 CpG islands; differentially expressed genes between ER+ and ER- cell lines were selected and then correlated with methylation status of these genes’ CpG islands within 5kb of transcript start or copy number changes. The genes that appeared controlled by methylation or copy number changes in cell lines were further evaluated for their expression in the dataset of 129 primary breast tumors. Results: ER+ breast cancer cells had very different gene expression pattern from ER- cancer cells. The two cell line types formed two distinct clusters in unsupervised cluster and 1,873 genes were differentially expressed by moderated t statistics. We identified 149 differentially expressed genes that exhibited differential methylation of one or more CpG islands within 5kb of the 5’ end of the gene and for which mRNA abundance was inversely correlated with CpG island methylation status. Eighty nine of these 149 genes were also differentially expressed in the primary tumor samples and 84 of them were consistent with cell line gene expression and methylation data. The set of 149 genes were significantly enriched in the ER+ tumors by Gene Set Enrichment Analysis. Part of chromosome 8 was deleted in all ER- cells and part of chromosome 17 amplified in all ER+ cells. These loci encoded 30 genes that were overexpressed in ER+ cells; however, only 9 of these genes were overexpressed in ER+ tumors. Many of the methylation or CNA affected genes were functionally significant and some are known to be associated with breast cancer outcome such as GATA3 and LYN. Conclusions: A global pattern of differential CpG island methylation influences expression of a cohort of genes that contribute to the transcriptome landscape of ER+ and ER- breast cancer cells and tumors. The role of gene amplification/deletion in defining the transcriptome landscape of ER+ and ER- cells appears to more modest, although several potentially significant genes appear to be globally regulated by copy number aberrations. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4908. doi:10.1158/1538-7445.AM2011-4908

Abstract Several platforms for genome sequencing and methods for exon enrichment are now available and continue to evolve quickly. In this study, we compared the performance of whole exome sequencing using two instruments, Illumina's GAIIx and HiSeq 2000, comparing single versus duplicate runs. Eight runs of eight samples each were performed with genomic DNA derived from whole blood and sample libraries prepared with the Agilent SureSelect capture array. One run was conducted in duplicate on the GAIIx, and, for some analyses, the combined data were used. We used TREAT (Targeted RE-sequencing and Annotation Tool), developed in-house for data analysis, including sequence alignment (MAQ, BWA), local re-alignment (GATK), variant calling (utilizing MAQ), annotation (SIFT and Seattle Seq), and visualization. Overall, duplicate runs on the GAIIx platform (compared to a single run) increased the number of total reads by approximately two-fold: from ∼66 M to ∼130 M. For both single and duplicate runs, ∼90% of reads mapped to the reference sequence, and ∼55% of reads mapped on-target. Of importance, the percent coverage of the target region increased substantially with duplicate runs; ∼72% of the target region was covered at 40-fold or more when run in duplicate compared to only ∼52% when run once. At 30x, 20x, and 10x, there was a 1.3- (62% v. 78%), 1.2- (72% v. 84%), and 1.1-fold (84% v. 91%) increase respectively, in the percent coverage of the target region for samples run twice. A similar number of filtered, on-target SNPs per sample (∼24 K) was found for both single and duplicate run analyses. However, a 1.3-fold increase in the number of on-target indels was seen in the duplicate run (∼1,200) compared to the single run (∼900). When the combined data for samples run twice on a GAIIx were compared to the samples run using a HiSeq, the total number of reads were similar (∼130 M), although several of the samples had substantially more reads on the HiSeq platform. Samples run on a HiSeq had an increase in the percent coverage of the target region at 40x (72% v. 81%), 30x (78% v. 86%), 20x (84% v. 91%) and 10x (91% v. 95%) compared to the two-run approach on a GAIIx. A similar number of filtered on-target SNPs (∼24 K/sample) and indels (∼1200) was found with the HiSeq compared to two runs on a GAIIx. In summary, our results demonstrate increases in the total number of reads and in overall coverage with the HiSeq 2000 instrument. The total number of SNPs and indel that mapped on target for the version 1 Agilent SureSelect capture array is ∼25 K and 1,200 per sample, respectively. As capture is of variable efficiency for individual runs, higher average coverage of the target region is necessary for sufficient coverage of poorly captured regions. Additional analyses comparing Agilent SureSelect versions 1 and 2 arrays are underway. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 2742. doi:10.1158/1538-7445.AM2011-2742

Abstract The role of fusion gene transcripts such as BRC-ABL1 has been long appreciated in hematopoietic malignancies. Recent evidence from next generation sequencing projects has suggested that gene fusion events and the resultant chimaeric transcripts may be expressed in solid tumors. We have developed a novel bioinformatics analytical pipeline to detect fusion gene transcripts from paired-end mRNA-seq data. The bioinformatics tool used for fusion transcript discovery employs multiple steps of false positive filtering and nominates the fusion transcript candidates with high confidence (approaching 100%). The screening and validation of the fusion candidates were quickly carried out using the recommended primer design regions as one of the outputs of the SnowShoes-FD pipeline. This pipeline was used to analyze the transcriptome of 22 breast cancer cell lines and 9 non-transformed breast cell populations. Fifty-four fusion candidates were nominated, all of which were validated using reverse transcription PCR and Sanger sequencing. Five fusion products were predicted to have a second fusion junction point between two fusion partners. These 54 fusion transcripts consist of 103 partner genes that are involved in cell cycle and/or nuclear receptor signaling. No fusion transcripts were identified from the non-transformed breast cell lines. We subsequently analyzed a panel of primary breast tumors, 8 each HER2+, triple negative, and ER+. Fifteen novel fusion transcript candidates have been nominated. Validation and functional analysis of these candidates is in progress. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-276. doi:10.1158/1538-7445.AM2011-LB-276

Abstract Summary: Reduced representation bisulfite sequencing (RRBS) is a cost-effective approach for genome-wide methylation pattern profiling. Analyzing RRBS sequencing data is challenging and specialized alignment/mapping programs are needed. Although such programs have been developed, a comprehensive solution that provides researchers with good quality and analyzable data is still lacking. To address this need, we have developed a Streamlined Analysis and Annotation Pipeline for RRBS data (SAAP-RRBS) that integrates read quality assessment/clean-up, alignment, methylation data extraction, annotation, reporting and visualization. This package facilitates a rapid transition from sequencing reads to a fully annotated CpG methylation report to biological interpretation. Availability and implementation: SAAP-RRBS is freely available to non-commercial users at the web site http://ndc.mayo.edu/mayo/research/biostat/stand-alone-packages.cfm. Contact: baheti.saurabh@mayo.edu or sun.zhifu@mayo.edu Supplementary Information: Supplementary data are available at Bioinformatics online.

Abstract The longitudinal evolution of a myeloma genome from diagnosis to plasma cell leukemia has not previously been reported. We used whole-genome sequencing (WGS) on 4 purified tumor samples and patient germline DNA drawn over a 5-year period in a t(4;14) multiple myeloma patient. Tumor samples were acquired at diagnosis, first relapse, second relapse, and end-stage secondary plasma cell leukemia (sPCL). In addition to the t(4;14), all tumor time points also shared 10 common single-nucleotide variants (SNVs) on WGS comprising shared initiating events. Interestingly, we observed genomic sequence variants that waxed and waned with time in progressive tumors, suggesting the presence of multiple independent, yet related, clones at diagnosis that rose and fell in dominance. Five newly acquired SNVs, including truncating mutations of RB1 and ZKSCAN3, were observed only in the final sPCL sample suggesting leukemic transformation events. This longitudinal WGS characterization of the natural history of a high-risk myeloma patient demonstrated tumor heterogeneity at diagnosis with shifting dominance of tumor clones over time and has also identified potential mutations contributing to myelomagenesis as well as transformation from myeloma to overt extramedullary disease such as sPCL.

Abstract Fusion genes and fusion gene products are widely employed as biomarkers and therapeutic targets in hematopoietic cancers, but their applications have yet to be appreciated in solid tumors. Here, we report the use of SnowShoes-FTD, a powerful new analytic pipeline that can identify fusion transcripts and assess their redundancy and tumor subtype-specific distribution in primary tumors. In a study of primary breast tumors, SnowShoes-FTD was used to analyze paired-end mRNA-Seq data from a panel of estrogen receptor (ER)+, HER2+, and triple-negative primary breast tumors, identifying tumor-specific fusion transcripts by comparison with mRNA-Seq data from nontransformed human mammary epithelial cell cultures plus the Illumina Body Map data from normal tissues. We found that every primary breast tumor that was analyzed expressed one or more fusion transcripts. Of the 131 tumor-specific fusion transcripts identified, 86 were “private” (restricted to a single tumor) and 45 were “redundant” (distributed among multiple tumors). Among the redundant fusion transcripts, 7 were unique to ER+ tumors and 8 were unique to triple-negative tumors. In contrast, none of the redundant fusion transcripts were unique to HER2+ tumors. Both private and redundant fusion transcripts were widely expressed in primary breast tumors, with many mapping to genomic loci implicated in breast carcinogenesis and/or risk. Our finding that some fusion transcripts are tumor subtype-specific suggests that these entities may be critical determinants in the etiology of breast cancer subtypes, useful as biomarkers for tumor stratification, or exploitable as cancer-specific therapeutic targets. Cancer Res; 72(8); 1921–8. ©2012 AACR.