Abstract Motivation: Reference genome assemblies are subject to change and refinement from time to time. Generally, researchers need to convert the results that have been analyzed according to old assemblies to newer versions, or vice versa, to facilitate meta-analysis, direct comparison, data integration and visualization. Several useful conversion tools can convert genome interval files in browser extensible data or general feature format, but none have the functionality to convert files in sequence alignment map or BigWig format. This is a significant gap in computational genomics tools, as these formats are the ones most widely used for representing high-throughput sequencing data, such as RNA-seq, chromatin immunoprecipitation sequencing, DNA-seq, etc. Results: Here we developed CrossMap, a versatile and efficient tool for converting genome coordinates between assemblies. CrossMap supports most of the commonly used file formats, including BAM, sequence alignment map, Wiggle, BigWig, browser extensible data, general feature format, gene transfer format and variant call format. Availability and implementation: CrossMap is written in Python and C. Source code and a comprehensive user’s manual are freely available at: http://crossmap.sourceforge.net/. Contact: Kocher.JeanPierre@mayo.edu or wang.liguo@mayo.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Abstract 2924: Constitutively active androgen receptor splice variants function independently of full-length androgen receptor in a cell-based model of castrate-resistant prostate cancer
Cancer Research | August 13, 2012 | Volume: 72 | Issue: 8_Supplement | Pages: 2924-2924
Abstract Recent studies suggest that progression to castrate-resistant prostate cancer (CRPC) is due to generation of androgen receptor (AR) splice variants, lacking the ligand binding domain. These AR variants originally identified in cell-based models of CRPC, have also been detected in benign and malignant human prostate tissue, with the highest levels observed in late state CRPC. The diversity and complexity of AR variants is well appreciated but not fully understood. Using RT-PCR we assessed the expression of a number of AR variants in cell-based models of both castrate-resistant and androgen-dependent prostate cancer. Several AR variants were expressed in both 22Rv1 and VCaP cells, but not in LNCaP cells. Coding sequences for AR variants were cloned into expression vectors and constitutive transcriptional activity was observed using a luciferase reporter assay. Augmented transcriptional activity of AR variants was observed in cells that express full-length AR, when full-length AR was silenced using shRNA targeting exons 7/8. This observation suggests the constitutive activity of AR variants may be independent of full-length AR. We profiled the AR variant transcriptome in 22Rv1 cells, using the Illumina HumanHT12 v4 whole-genome expression array platform. shRNA targeting exon 1 was used to silence all AR isoforms and shRNA targeting exons 7/8 was used to silence full-length AR. 5,256 genes were modulated by knocking down all AR isoforms and 5,086 genes were modulated by knocking down full-length AR. A total of 3,714 genes were common to both groups, leaving 1542 genes modulated by AR variants and 1372 modulated by full-length AR (p<0.05). The represents a subset of genes differentially regulated by AR variants independently of full length AR. Aggregate function of multiple AR variants may confer a CRPC phenotype independent of full-length AR. Pathway analysis of these genes differentially regulated by AR variants may reveal potential targets for therapeutic intervention in patients who progress despite androgen deprivation or anti-androgen therapy. (Supported by NIH grants CA125747, CA091956 and CA121277, T.J. Martell Foundation and the Mayo Clinic Prostate Cancer SPORE). 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 2924. doi:1538-7445.AM2012-2924
Abstract 940: Inhibition of androgen receptor activity in refractory prostate cancer cells by the novel Millennium-Takeda compound T-1759243
Cancer Research | August 9, 2012 | Volume: 72 | Issue: 8_Supplement | Pages: 940-940
Abstract Purpose. Prostate cancer (PCa) continues to be a leading cause of cancer death in males worldwide. In the prostate, androgens play a crucial role in both normal and cancerous growth by acting through the androgen receptor (AR), a member of the nuclear receptor super-family; hence, the AR has become a target of therapeutic intervention. The standard treatment for advanced PCa is androgen ablation therapy, initially leading to tumor regression through inhibition of AR activity. However, the success of androgen ablation therapy is often terminated by the emergence of castration- recurrent PCa (CRPC), for which there is still no cure. CRPC remains dependent on a functional AR-axis for proliferation and drugs targeting this network are continually being developed. We have examined the effects of Millennium-Takeda investigational compound T-1759243 on both androgen-responsive and androgen-refractory PCa cells in order to assess its therapeutic potential. Methods. We used PCa cell lines LNCaP, LNCaP-C42 and 22RV1 and assessed effects on cell viability and proliferation using MTS and BrdU assays. AR activity was measured using PSA-luciferase reporter constructs and protein levels by western blot. Microarray analysis with the Illumina HT-12 platform was used to identify genes affected by treatment with T-1759243, followed by real-time PCR confirmation. Pathway analysis was performed using MetaCoreTM software. Results. Our studies have revealed that T-1759243 reduces viability in all cell lines examined, regardless of androgen responsiveness. Treatment resulted in decreased proliferation in androgen-responsive cells and increased apoptosis in refractory cells. AR activity, as measured by PSA-luciferase assay, was greatly decreased in all cell lines by 10uM T-1759243 and T-1759243 abrogated the ability of synthetic androgen R1881 to increase AR activity by inhibiting nuclear translocation of the AR in refractory cells. Pathway analysis revealed changes in genes involved in cell-cycle, cell adhesion and cytoskeletal remodeling in addition to genes in androgen target pathways. Conclusions. T-1759243 is a novel AR antagonist that inhibits AR activity in both androgen-dependent and androgen-refractory prostate cancer cells. Additionally, it inhibits the ability of androgen to promote nuclear translocation of the AR and thus stimulate AR activity in castrate-resistant prostate cancer cells. Pathways affected by treatment with T-1759243 are cell-specific and dependent on AR status and may reveal novel gene targets in PCa treatment. This work was supported in part by Grant #35 from Millennium Pharmaceuticals, Inc the Takeda Oncology Company. 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 940. doi:1538-7445.AM2012-940
Abstract 4926: Modeling the transcriptome landscape of HER2+ breast cancer
Cancer Research | August 9, 2012 | Volume: 72 | Issue: 8_Supplement | Pages: 4926-4926
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 LB-346: MiRNA and gene expression signatures in lung adenocarcinoma from never-smokers
Cancer Research | July 21, 2012 | Volume: 71 | Issue: 8_Supplement | Pages: LB-346-LB-346
Abstract Lung cancer is the most common cause of smoking-related mortality in worldwide. However, approximately 10 to 25 % cases are not attributable to smoking. Cumulative evidence suggests that lung cancer from never smokers (<100 cigarettes lifetime) may develop via molecular mechanisms that are different from lung cancers in smokers. Recently, miRNAs have been identified as a new class of regulatory molecules that participate in a variety of biological processes. Because each miRNAs can potentially target a large set of mRNA making and therefore may play a critical role in lung tumorigenesis and patient outcome, we sought to examine the role of miRNA in lung adenocarcinoma among never smokers. A total of 298 samples were analyzed in this study including 168 fresh frozen (FF) tissues from 88 lung adenocarcinomas and 80 adjacent non-involved lung tissues; and 132 formalin-fixed paraffin embedded (FFPE) tissues from 68 tumors and 64 normal lung samples. Gene expression profiling was performed for miRNA and mRNA using Illumina Whole Genome DASL platform. We identified 20 miRNAs with the most significant expression changes between the tumor and normal in both FF and FFPE samples (Fold change > 1.5, p <0.01, FDR <0.05). We also examined mRNA expression signature using 56 matched FF tumors and normal lung tissues. Cox proportional hazard analysis was performed independently for both FF and FFPE cohorts and showed that increased expression of mir-708 was strongly associated with an increased risk of patient death after adjusting for age, sex and tumor stage (FF cohort, HR =1.92; 95% CI =1.02–3.63; p < 0.05 and FFPE cohort, HR=1.90; 95% CI=1.08–3.34; P < 0.05). Candidate biological targets of mir-708 were identified using TargetScan and MicroCosm Targets databases. A total of 13 candidate genes were found and one of these genes, CMT11 (Candidate Mir-708 Target), was down-regulated 1.6 fold on average in tumors that were high in mir-708 expression. Based on the sequence, CMT11 is a novel transmembrane protein. In Cox analysis, reduced CMT11 expression was strongly correlated with an increased risk of death in patients (HR = 2.43, 95% CI = 1.17 − 5.26; P <0.01). Functionally, overexpression of mir-708 in A549 and HEK293T cells significantly increased the rate of cellular proliferation and migration. Over expression of mir-708 in HEK293T cells also repressed ∼70% of the luciferase activity when the reporter RNA contained the 3′ UTR of CMT11. Recently, several studies have showed mir-708 is a potential squamous cell lung cancer marker and one of miRNAs that may predict the recurrence of Stage I lung cancer after surgical resection. Additional evidence also suggests that CMT11 is a negative regulator of Wnt-signaling pathway. Our data provides clinical and functional evidence supporting an important role of mir-708 in lung cancer progression and identifies CMT11 as a down stream target gene mediating this process. 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-346. doi:10.1158/1538-7445.AM2011-LB-346
Abstract 5060: Gene network predicts overall survival in patients with primary lung adenocarcinoma
Cancer Research | June 27, 2012 | Volume: 71 | Issue: 8_Supplement | Pages: 5060-5060
Abstract Lung adenocarcinoma is the most common type of primary lung cancer. Previous studies have shown that gene expression signatures may predict clinical outcome. In this study, we used a systems biology approach, weighted gene co-expression network analysis (WGCNA), to identify survival related networks and gene signatures. We first analyzed whole genome gene expression profiles in 82 lung adenocarcinoma tumor tissues from never smokers (smoked <100 cigarettes lifetime) and found a significant correlation of an expression module with tumor grade of differentiation (r=0.38, p=4×10−4) and overall survival (OS, p =0.027, HR, 1.71; 95% CI, 1.06-2.74) after adjusting for potential confounders (age and tumor grade). When this module signature was incorporated and compared to the conventional model consisting of clinical variables only, the survival prediction accuracy was increased from 0.70 to 0.75. Gene Ontology (GO) enrichment analysis indicated this module was significantly enriched in biological process GO term “cell cycle” (p = 2.1×10−53). To explore the effect of this network module at germline level, we performed the WGCNA on normal lung tissues derived from 78 of the 82 patients and observed significant association of an expression module with OS (adjusted p=3×10−4, HR=1.98; 95% CI, 1.36-2.87). Interestingly, this module was also significantly enriched in cell cycle-related genes (p=4.1×10−41). To further validate this result, we analyzed an independent microarray gene expression dataset including 442 lung adenocarcinoma patients from NCI Director's Challenge Consortium. We found the same association: the cell cycle-enriched module was correlated with tumor grade of cell differentiation (r=0.55, p-value=5×10−37) and OS (adjusted p=7.4×10−3; HR, 1.20; 95% CI, 1.05-1.37). We further identified 30 genes in the OS-related module that overlapped between the discovery and validation data sets. Furthermore, all these 30 genes were found to be up-regulated in adenocarcinoma compared to adjacent normal lung tissues in the discovery data set. Of the 30 genes, three key genes, UBE2C, TPX2 and MELK, were identified with highest connectivity in cell cycle-enriched module; their expression levels were significantly associated with OS in both discovery and validation sets. UBE2C and TPX2 have been reported as gene signatures for human lung cancer prognosis in vitro lung carcinogenesis system; MELK was identified as a key regulator of the proliferation of malignant brain tumors and malignant grade in human astrocytomas, and was also associated with breast cancer prognosis. Our results suggest that genes involved in cell-cycle are likely related with tumor aggressiveness and therefore can predict survival in lung adenocarcinoma. Further studies are needed to validate the key genes that could improve survival prediction and provide potential new targets to intervene progression of lung adenocarcinoma. 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 5060. doi:10.1158/1538-7445.AM2011-5060
Abstract 4975: Next generation sequencing reveals a connection between KRAS mutation and the NFkB pathway in lung adenocarcinoma samples
Cancer Research | June 27, 2012 | Volume: 71 | Issue: 8_Supplement | Pages: 4975-4975
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 4908: Deep sequence analysis of the relationship between gene expression, CpG island methylation, and gene copy number in breast cancer cells
Cancer Research | June 27, 2012 | Volume: 71 | Issue: 8_Supplement | Pages: 4908-4908
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 1285: Genetic variations predicting cisplatin cytotoxicity associated with the overall survival in lung cancer patients receiving platinum-based chemotherapy
Cancer Research | June 27, 2012 | Volume: 71 | Issue: 8_Supplement | Pages: 1285-1285
Abstract Background: Candidate gene and candidate pathway-based pharmacogenomic studies have been used to investigate the inherited variability of prognosis of lung cancer treated with platinum-based chemoptherapy. In order to make it possible to conduct an ‘unbiased’ query across the entire genome, a genome-wide association study (GWAS) in 283 lymphoblastoid cell lines (LCLs) was carried out to help identify candidate SNPs associated with variation in cisplatin cytotoxicity. Furthermore, we set out to test the hypothesis that genetic variation resulting in differences in cisplatin cytotoxicity might influence the overall survival of patients with lung cancer treated with platinum-based antineoplastic agents. Material and Methods: We applied ethnically diverse Coriell “Human Variation Panel” LCLs for GWAS. Then, we picked 168 top significant SNPs selected from GWAS in 283 LCLs and genotyped these SNPs in 1183 lung cancer patients (222 SCLC and 961 NSCLC) who received platinum-based chemotherapy. Genotyping was performed using the Illumina Golden Gate platform. The association of SNPs with lung cancer overall survival was analyzed by Cox regression model after adjusting for disease stage. Functional validation of candidate genes was performed by siRNA screening in NSCLC cell lines CRL5872, H1299 and SCLC cell line CRL5823. Results: A total of 157 SNPs were successfully genotyped for 1183 lung cancer patient samples. The Cox regression analysis indicated that 9 and 10 different SNPs were associated with overall survival for NSCLC and SCLC patients, respectively (p value <0.05). Fifteen genes including 7 genes located in the region of 200kb up or downstream of 4 SNPs (rs11169748, rs2440915, rs5952066 and rs7620841) and 8 genes for which the expression was correlated with three SNPs (rs11169748, rs2440915 and rs5952066) were selected for siRNA screening. Knockdown of DAPK3 and METTL6, for which the expression levels were correlated with the SNPs rs11169748 and rs2440915, significantly decreased cisplatin sensitivity in lung cancer cell lines CRL5872, H1299 and CRL5823. Conclusions: This series of clinical and complementary laboratory-based functional studies identified several candidate genes and SNPs that might help predict treatment outcomes of platinum-based therapy in lung cancer. 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 1285. doi:10.1158/1538-7445.AM2011-1285
SAAP-RRBS: streamlined analysis and annotation pipeline for reduced representation bisulfite sequencing
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.