bluuebunny/crossref_metadata_2025 huggingface dataset:
Abstract 4800: Identification of candidate predisposition genes for familial uterine leiomyomas
Authors: Heinonen Hanna-Riikka , Uimari Outi , Tolvanen Jaana , Ryynänen Markku , Aaltonen Lauri A. , Vahteristo Pia
Published: August 2015

Uterine leiomyomas are benign smooth muscle tumors that cause considerable morbidity. They are among the most common human tumors and are the leading indication for hysterectomy. Genetic factors play an important role in the development of these hormone-dependent tumors. First-degree relatives of uterine leiomyoma patients are at increased risk for developing leiomyomas. Twin studies have shown that an inherited predisposition is likely to contribute to the formation of these lesions. Furthermore, the clinical and molecular features of familial leiomyomas differ from those of sporadic cases. Thus far, the only known high risk predisposition defect is dominantly inherited loss of function mutations in fumarate hydratase (FH) that underlie a tumor predisposition syndrome hereditary leiomyomatosis and renal cell cancer (HLRCC). The aim of this study is to identify novel candidate high risk susceptibility genes for uterine leiomyomas. The study material consists of five FH mutation-negative families, which have at least four individuals diagnosed with uterine leiomyomas, originating from Northern Finland. Genomic DNA extracted from peripheral blood lymphocytes from one affected individual from each family has been exome sequenced. Exome sequencing data have been analyzed for rare non-synonymous variants with allele frequencies less than 0.1% in 4 019 controls. All protein-truncating variants as well as missense and splice site variants affecting the same gene in at least two individuals that are predicted to be protein-damaging have been included for further analysis. Preliminarily 25 candidate susceptibility genes have been shortlisted. Relevant variant calls will be verified by direct sequencing, followed by segregation analysis and assessment of loss of heterozygosity in the corresponding tumor samples. Identification of novel genes predisposing to familial uterine leiomyomas may provide a better understanding into the tumorigenic mechanisms and could lead to new prevention approaches and personalized medical treatments in the future.

Citation Format: Hanna-Riikka Heinonen, Outi Uimari, Jaana Tolvanen, Markku Ryynänen, Lauri A. Aaltonen, Pia Vahteristo. Identification of candidate predisposition genes for familial uterine leiomyomas. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4800. doi:10.1158/1538-7445.AM2015-4800
Abstract 4802: Transcriptional landscape of lung squamous cell carcinoma in Northeast Asian patients
Authors: Rhie Arang , Cho Hyesun , Son Min Hwan , Yoo Seong-Keun , Shin Jong-Yeon , Seo Jeong-Sun
Published: August 2015

Lung Squamous Cell Carcinoma (LSCC), the second most prevalent type of lung cancer, is known to have different genetic and epigenetic characteristics from lung adenocarcinoma. Molecular pathogenesis remains to be elucidated to identify therapeutic targets, especially for patients with no driver mutations identified in previous studies. In this study, we obtained RNAs from fresh tissue of 101 patients of LSCC, and its paired normal site. RNA-seq was performed with paired-end sequencing of HiSeq2000. The average throughput uniquely mapped to the human genome reference was 10Gbp per sample. Differentially expressed genes showed higher expression in HOX families, FOXL2, SOX2, FGFR3, JAK3, and ALK. In contrast, WIF1, RSPO2, ROS1, TAL1, PRDM16 was down regulated in tumor cells. To subgroup patients with their driver mutation, somatic mutation have been detected with comparison to normal paired samples, filtering with MAF<0.01 of Northeast Asian Population, 1KG, and ExAC 65000 exomes. The average number of nonsynonymous somatic mutation was 49.63 per sample. Sixty-seven patients had somatic mutation in TP53, CDKN2A, NFE2L2, and PIK3CA. This was relatively small compared to patients from TCGA, mainly consisting of Western population. After excluding 4 patients identified to be close to normal cells by PCA analysis of expression pattern, and 2 other patients suspected to be false classified from adenocarcinoma presenting mutation in EGFR (L858R) and KRAS (G12D), 28 patients remained to be elucidated. No EGFR, ALK, RET, FGFR3, TACC fusion have been found, suggesting novel isoform of transcripts or other mechanisms driving carcinogenesis.

Citation Format: Arang Rhie, Hyesun Cho, Min Hwan Son, Seong-Keun Yoo, Jong-Yeon Shin, Jeong-Sun Seo. Transcriptional landscape of lung squamous cell carcinoma in Northeast Asian patients. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4802. doi:10.1158/1538-7445.AM2015-4802
Abstract 4809: Validation of molecular subtypes of urothelial carcinoma of bladder in multi-institutional and public cohorts
Authors: Dadhania Vipulkumar , Guo Charles G. , Majewski Tadeusz , Zhang Li , Bondaruk Jolanta , Zhang Shizhen , Choi Woonyoung , McConkey David , Dinney Colin , Baggerly Keith , Czerniak Bogdan A.
Published: August 2015

BACKGROUND: Recently we have proposed a molecular sub-classification of conventional urothelial carcinoma which could be divided into two major categories designated as basal and luminal similar to the ones defined for breast cancer. In addition, luminal cancers contain a group of cases characterized by upregulation of p53 regulatory genes and is referred to as p53-like. The purpose of this project is to verify whether such subtypes can be identified in several large independent cohorts of bladder cancers.

DESIGN: Gene expression profiles and molecular subtyping were performed by using previously described analytical algorithms on the following bladder cancer patient cohorts: (1) The Cancer Genome Atlas (TCGA) cohort containing tumor tissues from muscle invasive high grade urothelial carcinomas of 129 patients; (2) the MD Anderson Cancer Center (MDA) cohort of fresh frozen tumor tissues which included 65 superficial papillary carcinomas and 77 invasive carcinomas; (3) the Swedish cohort containing fresh frozen tumor samples of 116 superficial papillary tumors and 192 invasive tumors.

RESULTS: The three distinct molecular subtypes defined as luminal, p53-like and basal were identified in all three cohorts. The distribution of molecular subtypes in individual cohorts was as follows: the TCGA cohort contained 50 (39%) luminal, 30 (23%) p53-like and 49 (38%) basal tumors; the MDA cohort contained 54 (38%) luminal, 61 (43%) p53-like and 27 (19%) basal; the Swedish cohort contained 102 (33%) luminal, 129 (42%) p-53 like and 77 (25%) basal tumors. Interestingly, in the MDA and Swedish cohorts virtually all superficial tumors, of either low or high grade, were of luminal type.

CONCLUSION: The conventional bladder cancer can be separated into three distinct molecular subtypes with luminal phenotype defining the vast majority of superficial bladder cancers while muscle invasive tumors can be separated into luminal and basal forms. A subset of luminal cancers is characterized by upregulation of p53 regulatory genes. The identification of subtypes may help to stratify the patients for targeted therapies.

Citation Format: Vipulkumar Dadhania, Charles G. Guo, Tadeusz Majewski, Li Zhang, Jolanta Bondaruk, Shizhen Zhang, Woonyoung Choi, David McConkey, Colin Dinney, Keith Baggerly, Bogdan A. Czerniak. Validation of molecular subtypes of urothelial carcinoma of bladder in multi-institutional and public cohorts. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4809. doi:10.1158/1538-7445.AM2015-4809
Abstract 4821: Association of polymorphisms in TP53, CXCL2, MDM2, MDM4 and BCL2 genes and proliferative prostate diseases among Lebanese men
Authors: Kuddus Ruhul H. , El Ezzi Asmahan A. , El-Saidi Mohammed A. , Baker Scott , Zaidan Wissam
Published: August 2015

Specific Aims: To investigate possible relationships between certain polymorphisms in p53 protein (TP53) gene, chemokine (C-X-C motif) ligand 2 (CXCL-2) gene, mouse double minute 2 homologue (MDM2) gene, MDM4 protein (MDM4) gene and B cell lymphoma 2 protein (BCL2) gene and benign prostate hyperplasia (BPH) and prostate cancer (PCa) among middle-aged Lebanese men.

Methods: Blood was collected from volunteer prostate disease screening campaign participants ages 50-70. DNA was extracted from peripheral blood leucocytes of 85 donors diagnosed with clinical PCa, 178 donors diagnosed with BPH, and 140 donors with no prostrate-related pathologies. The 72 Arg/pro polymorphism of TP53 gene, 801 G/A polymorphism of CXCL2 gene, 309 G/T polymorphism of MDM2 gene, 103 T/C and D153G polymorphisms of MDM4 gene and 938 C/A polymorphism of BCL2 genes was investigated by polymerase chain reaction/restriction fragment-length polymorphism analysis. The genotype of the subjects for each of the genes was determined and allelic frequency was calculated. Association between the genotypes and PCa and BPH was estimated by calculating the odds ratio (OR) and 95% confidence intervals (CI). The relative risk (RR) of PCa or BPH for having a particular genotype was also calculated using MedCalc statistical software. The null hypotheses were rejected with a p value of <0.05%.

Results: There is no association between the examined polymorphisms of the TP53 gene, CXCL2 gene, MDM2 gene and BCL2 gene and BPH or PCa. The ratio of C/T alleles for the 103 T/C locus and the ratio of D/G alleles for D153G locus of MDM4 are lower for subjects with PCa and BPH compared to the controls (p<0.01 for both loci). The ratio of (CC+CT)/TT is lower for subjects with PCa compared to the control (OR = 0.12, 95% CI = 0.06-0.22, RR = 0.39, p<0.01), and BPH compared to the controls (OR = 0.17, 95% CI = 0.10-0.28, RR = 0.50, p<0.01); and the ratio of (GG+GD)/DD is higher for subjects with PCa compared to the control (RR = 1.86, p<0.01) and subjects with BPH compared to the controls (RR = 1.85, p<0.01).

Conclusions: There is no statistically significant association between polymorphisms in TP53 gene, CXCL2 gene, MDM2 gene and BCL2 gene and PCa or BPH but the C allele of 103 T/C locus and the G allele of the D153G locus of MDM4 are risk factors for both PCa and BPH among Lebanese men.

Citation Format: Ruhul H. Kuddus, Asmahan A. El Ezzi, Mohammed A. El-Saidi, Scott Baker, Wissam Zaidan. Association of polymorphisms in TP53, CXCL2, MDM2, MDM4 and BCL2 genes and proliferative prostate diseases among Lebanese men. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4821. doi:10.1158/1538-7445.AM2015-4821
Abstract 4830: The correlation between CXCR7 expression and EGFR mutation in non-small cell lung cancer
Authors: Han Yiping
Published: August 2015

Objective: To explore the correlation between CXCR7 expression and EGFR mutation in NSCLC.

Materials and Methods: Forty-nine paired cases of NSCLC carcinoma and para-carcinoma tissues were analyzed for the expression of CXCR7 mRNA by RT-PCR and CXCR7 protein by IHC. EGFR mutations were detected in carcinoma tissues by ARMS. T-test, one-way ANOVA and correlation analysis were used to analyze the data with SPSS software version 18.0.

Results: In NSCLC, CXCR7 protein expression in carcinoma tissues was higher than in para-carcinoma tissues (14450±2049 vs 5206±1066, p<0.0001), while CXCR7 mRNA was not. In NSCLC, CXCR7 mRNA and CXCR7 protein expression levels were both related to the TNM stage (p = 0.007, p = 0.008) and metastatic status (p<0.0001; p<0.0001), but not to gender, age, smoking index and pathology. EGFR and CXCR7 protein were positively correlated (r = 0.289,p = 0.044) Conclusion: Like EGFR, CXCR7 can be used as a marker to predict the prognosis and guide clinical therapy in NSCLC.

Keywords: CXCR7 RDC1 EGFR NSCLC

Note: This abstract was not presented at the meeting.

Citation Format: Yiping Han. The correlation between CXCR7 expression and EGFR mutation in non-small cell lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4830. doi:10.1158/1538-7445.AM2015-4830
Abstract 4845: Microarray analysis of melanoma autologous tumor cell lines used as the source of tumor associated antigens in patient-specific dendritic cell immunotherapy phase II trial in patients with metastatic melanoma
Authors: Cornforth Andrew N. , Fogel Gary , Carbonell Denysha , Dillman Robert O.
Published: August 2015

Melanoma cells that are proliferating and self-renewing in short-term cell culture, have the phenotypic and functional characteristics of tumor stem cells, and they express unique patient-specific neoantigens, as well as numerous common melanoma associated antigens. Patient-specific therapeutic vaccines, produced by Incubating autologous dendritic cells with autologous tumor cells from such cell lines (DC-TC), have yielded promising results in phase II trials in metastatic melanoma. In this study we examined the expression of genes on the tumor cell lines which had served as the sources of tumor associated antigens loaded onto autologous dendritic cells as part of a phase II trial in which there was an observed 5-year survival rate of 50%.[Dillman 2009] There was sufficient melanoma tumor cells to analyze for 50 of the 54 patients enrolled in the phase II trial. Microarray analysis was performed by Response Genetics, Inc. (Los Angeles) for 54,000 genes. The Excel data file was entered into an Affymetrix data processing algorithm using the R programming language. Gene ranking was performed using prediction analysis of microarrays.[Tibshirani 2002] Correlation with overall survival was done for 26 patients who survived 5 years or longer, and 24 patients who survived less than 5 years. Hierarchical clustering for over and under expression yielded 9 genes, VEPH1, ZNF280B, FGF13, ST6GALNAC3, QPCT, ZNF280B, BST, PBRM1 and C21orf91 which identified 11/11 patients who had a survival greater than 5 years, and 17/18 patients who died in less than 2 years. Using the top six genes, overall survival greater than 5 years was correctly predicted for 80.3% of patients, and survival less than 5 years was correctly predicted for 74.2% of patients. Gene array data obtained from self-renewing, proliferating, autologous tumor cells was prognostic for survival. It is unclear whether these genes are predictive of an effective immune response after repeated injections of a therapeutic dendritic cell-tumor cell vaccine.

Citation Format: Andrew N. Cornforth, Gary Fogel, Denysha Carbonell, Robert O. Dillman. Microarray analysis of melanoma autologous tumor cell lines used as the source of tumor associated antigens in patient-specific dendritic cell immunotherapy phase II trial in patients with metastatic melanoma. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4845. doi:10.1158/1538-7445.AM2015-4845
Abstract 4849: GenomeSpace: An environment for frictionless bioinformatics
Authors: Reich Michael M.
Published: August 2015

Over the past several years, cancer genome characterization initiatives such as The Cancer Genome Atlas and the International Cancer Genome Consortium have produced an explosion of genomic data. These efforts, together with the proliferation of repositories for small-molecule screens and large-scale data production efforts to discover the breadth of genomic variation in humans, offer a new era of potential for the understanding of the basic mechanisms of cancer and identification of novel treatments.

Comprehensive analysis of these datasets requires the coordinated use of Web-based applications and data repositories, desktop analysis tools and visualizers, and single-purpose algorithms. However, the effort required to transfer data between tools, convert between data formats, and manage results often prevents researchers from utilizing the wealth of methods available to them. Many integrative genomics and translational “bench to bedside” discoveries are possible with combinations of existing tools, but the necessary transitions between them puts them out of the reach of most researchers.

GenomeSpace, http://www.genomespace.org, is an environment that brings together diverse computational tools, enabling scientists without programming skills to easily combine their capabilities. It aims to offer a common space to create, manipulate and share an ever-growing range of genomic analysis tools. GenomeSpace features support for cloud-based data storage and analysis, multi-tool analytic workflows, automatic conversion of data formats, and ease of connecting new tools to the environment. A set of six “GenomeSpace-enabled” seed tools developed by collaborating organizations provides a comprehensive platform for the analysis of cancer data: Cytoscape (UCSD), Galaxy (Penn State University), GenePattern (Broad Institute), Genomica (Weitzmann Institute), Integrative Genomics Viewer (Broad Institute), and the UCSC Genome Browser (UCSC). Its open architecture has driven its adoption by a number of additional tools, including the Cancer Cell Line Encyclopedia, Multiple Myeloma Genomics Portal, Project Achilles Portal, ArrayExpress, and Cistrome, with new tools and resources being released regularly.

We show how researchers can use GenomeSpace to effortlessly combine the capabilities of all of these tools in several cancer research scenarios.

Citation Format: Michael M. Reich. GenomeSpace: An environment for frictionless bioinformatics. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4849. doi:10.1158/1538-7445.AM2015-4849
Abstract 4858: Cloud-based variant analysis solution using control-accessed sequencing data
Authors: Xiao Chunlin , Yaschenko Eugene , Sherry Stephen
Published: August 2015

Variation analysis plays an important role in elucidating the causes of various human diseases. The drastically reduced costs of genome sequencing driven by next generation sequence technologies now make it possible to analyze genetic variations with hundreds or thousands of samples simultaneously, but currently with the cost of ever increasing local storage requirements. The tera- and peta-byte scale footprint for sequence data imposes significant technical challenges for data management and analysis, including the tasks of collection, storage, transfer, sharing, and privacy protection. Currently, each analysis group facing these analysis tasks must download all the relevant sequence data into a local file system before variation analysis is initiated. This heavy-weight transaction not only slows down the pace of the analysis, but also creates financial burdens for researchers due to the cost of hardware and time required to transfer the data over typical academic internet connections. To overcome such limitations and explore the feasibility of analyzing control-accessed sequencing data in cloud environment while maintaining data privacy and security, here we introduce a cloud-based analysis framework that facilitates variation analysis using direct access to the NCBI Sequence Read Archive through NCBI sratoolkit, which allows the users to programmatically access data housed within SRA with encryption and decryption capabilities and converts it from the SRA format to the desired format for data analysis. A customized machine image (swift) with preconfigured tools (including NCBI sratoolkit) and resources essential for variant analysis has been created for instantiating an EC2 instance or instance cluster on Amazon cloud. Performance of this framework has been evaluated and compared with that from traditional analysis pipeline, and security handling in cloud environment when dealing with control-accessed sequence data has been addressed. We demonstrate that it is cost effective to make variant calls using control-accessed SRA sequence data without first transferring the entire set of aligned sequence data into a local storage environment, thereby accelerating variation discovery using control-accessed sequencing data.

Citation Format: Chunlin Xiao, Eugene Yaschenko, Stephen Sherry. Cloud-based variant analysis solution using control-accessed sequencing data. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4858. doi:10.1158/1538-7445.AM2015-4858
Abstract 4868: CODEX: a normalization and copy number variation detection method for whole-exome sequencing
Authors: Jiang Yuchao , Oldridge Derek A. , Diskin Sharon J. , Zhang Nancy R.
Published: August 2015

Background: High throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of cancer. Copy number aberration (CNA) is an important type of genomic change, but detecting and characterizing CNA from whole-exome sequencing (WES) is challenging due to the high level of biases and artifacts.

Methods: We propose CODEX, a normalization and CNA calling procedure for WES data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based WES data. CODEX can be used to detect both germline and somatic CNAs in cancer samples with or without matched normal.

Results: Compared to existing approaches, CODEX is shown to be more effective in removing the biases in WES, and attains better sensitivity and specificity in detecting copy number aberrations by in silico spike-in studies. We further evaluate performance on 222 neuroblastoma samples with matched normal from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Project. We carry out systematic genome-wide analysis and detailed characterization of both germline and somatic copy number events. With a focus on a well-studied rare somatic CNV within the ATRX gene, we show that the cross-sample normalization procedure of CODEX is more effective in removing noise than the standard pipeline of normalizing the tumor against the matched normal, and that the segmentation procedure performs well in detecting CNVs with recurrent complex nested structures. For detecting germline mutations, CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be perform well on three microarray-based validation data sets.

Conclusions: The cross-sample normalization procedure of CODEX, when applied to the matrix of tumor and normal samples, is more effective in reducing noise than normalizing each tumor to its matched normal. The somatic deletions in the ATRX region have a nested structure, which CODEX was able to recover. Through multiple types of validation, CODEX is shown to be applicable to a wide range of study designs for copy number estimation using WES data.

Citation Format: Yuchao Jiang, Derek A. Oldridge, Sharon J. Diskin, Nancy R. Zhang. CODEX: a normalization and copy number variation detection method for whole-exome sequencing. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4868. doi:10.1158/1538-7445.AM2015-4868
Abstract 4869: Validation of a procedure for simultaneous variant calling and differential expression in cancer study
Authors: Feng Gang , Osman Jamie , Leighton Sean , Carmichael Lynn , Bai Yuchen , Begemann John , Mazzarella Richard
Published: August 2015

We have designed an integrated RNA-seq pipeline that determines both sequence variants and the differential expression of the transcripts from the same alignment in cancer samples. Comparison with other widely used protocols for RNA-seq data analysis showed that our method was more sensitive for determining subtle phenotypes in studies with large sample size, which frequently occur in compound screening approaches for cancer therapy. This whole transcriptome sequencing technology provides a cost-effective approach to gain understanding into the RNA relative biological events by deciphering RNA sequences. Benefiting from the fast developing technology, the cost of deep RNA-seq is no longer a barrier for current applications. Furthermore, an RNA-seq dataset provides more insight into disease processes than DNA-seq, since single nucleotide variant (SNV) detection in addition to gene and exon level expression and new isoform detection can be garnered from the same information. Based on the recent public data for mixed cancer cell lines and pooled normal human samples in MicroArray Quality Control (MAQC) phase III, also referred to as Sequencing Quality Control (SEQC), we evaluated our method with previous published results by means of different alignment strategies, sequencing depths and replicates numbers. Receiver operating characteristic (ROC) analysis showed our gene expression results agreed with the ones from the SEQC teams. In most cases, our solution has similar performance with other widely used strategies, while our STAR 2 pass based strategy has better true positive and true negative rates in the experiments with large sample size and subtle difference between groups. At the same time, the Genome Analysis Toolkit (GATK) 3 in our pipeline gained a reasonable balance between accuracy and performance. In summary, our new RNA-seq analysis pipeline has good performance and balance between precision and speed. Furthermore, this work also implicitly indicates that our gene expression method generates more accurate results in a large sample size experiment among similar groups.

Citation Format: Gang Feng, Jamie Osman, Sean Leighton, Lynn Carmichael, Yuchen Bai, John Begemann, Richard Mazzarella. Validation of a procedure for simultaneous variant calling and differential expression in cancer study. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4869. doi:10.1158/1538-7445.AM2015-4869
Abstract 4872: Improving bioinformatic analysis pipelines for calling somatic mutations in tumors and tumor derived cell lines
Authors: Wubbenhorst Bradley
Published: August 2015

The use of massively parallel sequencing data (MPS) is a common technique for identifying genetic alterations in disease. A number of tools and resources have been developed to assist in variant identification, but most are not specifically designed for somatic cancer studies. Tumor samples often suffer from admixture and heterogeneity, and tumor DNA often is derived from formalin fixed paraffin embedded samples rather than fresh samples, which introduces artificial bias. These confounders require adjustments to variant quality filtering to ensure a confident call set, but no universal guidelines exist for bioinformatics analyses. In addition, no single tool characterizes the spectrum of possible DNA-based alterations in tumors, specifically single nucleotide variants, small to medium sized indels, large genomic rearrangements and copy number alterations. To address these issues, we compared several methods of bioinformatic analysis using whole exome and targeted high-throughput sequencing data from various tumor and tumor-derived cell line studies. Using a data sets with known somatic alterations, we developed modifications to best practices guidelines for the publically available Genome Analysis Toolkit (GATK) for use in tumor and cell line variant calling. The haplotype score annotation was removed from all filtering consideration due to its expectance of no more than two segregating haplotypes at a given site, which, for example, caused all known BRAF V600 mutations to be removed. Scores from the read position rank sum test required a reduced filter threshold due to presence of high alternate allele fractions, which may contribute an artificial bias for this annotation value. Where applicable, we combined GATK results with calls from MuTect to increase specificity of the somatic changes identified as well as further increase sensitivity to singleton mutations. Finally, we have analyzed three methods to detect large genomic rearrangements and copy number changes (Pindel, ngCGH, and Sequenza) from MPS data, and found inconsistent results which require further scrutiny. In conclusion, we have developed a somatic variant calling pipeline which includes several modifications to the best practices in standard variant calling algorithms to enhance the sensitivity and specificity for somatic variant calling of the entire range of DNA-based alterations in tumors.

Citation Format: Bradley Wubbenhorst. Improving bioinformatic analysis pipelines for calling somatic mutations in tumors and tumor derived cell lines. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4872. doi:10.1158/1538-7445.AM2015-4872
Abstract 4874: OASIS: A centralized portal for cancer omics data analysis
Authors: Fernandez-Banet Julio , Esposito Anthony , Coffin Scott , Schefzick Sabine , Ding Ying , Ching Keith , Horvath Istvan , Roberts Peter , Rejto Paul , Kan Zhengyan
Published: August 2015

Advances in cancer research and sequencing technologies have contributed to the proliferation of large-scale cancer omics data sets from both public consortia and privately funded collaborations. There are increasing demands for broadly accessible tools that enable scientists to perform ad hoc analyses of cancer omics data. Here we present OASIS (http://oasis.pfizer.com), an open-access web portal that enables complex analytical queries across somatic mutations, copy number changes (CNV) and gene expression data from public domain and Pfizer funded omics studies. OASIS was designed to perform multidimensional data integration, allowing users to analyze correlations among multiple data types, as well as visualize and compare alterations across different cancers. Users can browse alteration summary reports at the gene and sample level and perform analyses using interactive visualizations. These include the Pan-Cancer Report, a unique tool that provides a high-level overview of genetic variation across multiple cancer types. Through the use of the interactive visualizations researchers can explore differentially expressed genes, identify tumor samples for over expression, investigate the correlation between CNV and expression or survey alteration patterns for a list of genes. Users can explore molecular profiles from the Cancer Cell Line Encyclopedia (CCLE) and the Catalog of Somatic Mutations in Cancer (COSMIC), to identify cell line models of interest. Researchers can also construct complex queries through a user-friendly web interface supported by the Biomart query engine. Programmatic access is also available through web services. OASIS is a powerful tool that enables cancer researchers to perform integrative analyses of large-scale cancer omics data sets, thereby facilitating key steps in oncology drug discovery ranging from target identification to model selection.

Citation Format: Julio Fernandez-Banet, Anthony Esposito, Scott Coffin, Sabine Schefzick, Ying Ding, Keith Ching, Istvan Horvath, Peter Roberts, Paul Rejto, Zhengyan Kan. OASIS: A centralized portal for cancer omics data analysis. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4874. doi:10.1158/1538-7445.AM2015-4874
Abstract 4877: A modular software solution (under development) to expedite sequencing workflow and mitigate legacy workflow issues in regulatory environments
Authors: Kelly Lisa , Gordon Jessica
Published: August 2015

One of the challenges of working in regulatory environments is the need to revalidate legacy workflows when incorporating new information or tools. Even in unregulated environments, updating and integrating workflows can require a considerable expenditure of time and labor. To mitigate these issues, Illumina is developing an analysis framework software as part of the Universal Oncology Test System for the MiSeqDx™ System, the first next generation sequencer to achieve FDA clearance. By incorporating plug-in workflow modules that seamlessly integrate with the framework - yet remain self-contained and separately versioned from other workflow modules - the software will expedite and ensure scalable operations. Installing new modules to the framework will incur no need for code changes to the legacy workflows, a key consideration for development and validation in regulated environments. The updated MiSeqDx analysis framework includes user authentication and sample sheet setup, reducing the number of disparate application interactions and bringing them together in a clean, clinical user interface accessible via any computer web browser.

The Universal Oncology Test System software workflow module will allow an investigator to identify variants of interest via three methods: an eligibility list of specific coordinate nucleotide changes, configurable rules based on variant type and region, and an amplification gene list with specified amplification type. This flexible software solution can be used to produce, for example, clinical trial reports that require masking of non-investigational variants while not precluding the opportunity to informatically unfilter new information. A report definition can be applied per sample, and updated post-sequencing for a reanalyzed report. The in vitro diagnostic report, also in development, aims to support the pathologist end user by separate categorization of pathogenic variants based on companion diagnostics.

The MiSeqDx analysis software platform combined with the Universal Oncology Test System workflow module can help expedite immediate clinical trial uptake and detection of variants for interpretation and future patient care.

Citation Format: Lisa Kelly, Jessica Gordon. A modular software solution (under development) to expedite sequencing workflow and mitigate legacy workflow issues in regulatory environments. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4877. doi:10.1158/1538-7445.AM2015-4877
Abstract 4880: Characterization of genetic concordance between primary tumor cells, circulating tumor cells, and metastatic tumor cells from patients with prostate cancer
Authors: Yang Lixin , Chen Linling , Wang Yafan , Jones Jeremy , Yen Yun , Loera Sofia , Pillai Raju , Chu Peiguo , Weisenburger Dennis
Published: August 2015

Circulating tumor cells (CTCs) which disseminate from the primary tumor site have been found to be a major source of metastatic tumor. However, CTCs are heterogeneous and most CTC DNA is fragmented due to apoptosis. To better understand the molecular pathogenesis of metastasis, it is imperative to obtain single, non-apoptotic CTCs and investigate the genetic concordance between primary tumor cells, CTCs and metastatic tumor cells. Due to the abundance of normal cells present in the blood and in tumor tissue, isolation of single tumor cells or pure cell populations of these cells is extremely difficult. The DEPArray platform is designated to collect single CTCs after Cell-Search enrichment, and to sort pure intact tumor cells from formalin-fixed, paraffin-embedded (FFPE) tissues. Taking advantage of this technology, we have isolated single CTCs from prostate cancer patients. Whole genome amplification was performed and genomes with high integrity were used to evaluate the hotspot mutations in PIK3CA. For comparison, we also made single cell suspensions from FFPE tissue blocks of primary tumors and metastatic tumor in lymph nodes from the same patients. Immunofluorescence staining for cytokeratin (CK) and vimentin (Vim) was performed, followed by isolation of pure tumor cells (CK+), stromal cells (Vim+) and double-positive cells (CK+/Vim+) from both primary tumor and lymph node samples. We plan to do genetic analysis on these cells and compare the results to determine the genetic concordance between primary tumor cells, CTCs and metastatic tumor cells. By using the DEPArray, we have successfully isolated single CTCs, and populations of tumor cells, stromal cells and double-positive cells from primary and metastatic tumors. We will present new data on the genetic concordance between these cells, which will provide new insight into our understanding of metastasis in prostate cancer.

Citation Format: Lixin Yang, Linling Chen, Yafan Wang, Jeremy Jones, Yun Yen, Sofia Loera, Raju Pillai, Peiguo Chu, Dennis Weisenburger. Characterization of genetic concordance between primary tumor cells, circulating tumor cells, and metastatic tumor cells from patients with prostate cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4880. doi:10.1158/1538-7445.AM2015-4880
Abstract 4884: Highly sensitive fusion transcript detection and quantification in cancer
Authors: Watson Lisa C. , Gross Stephen M. , Khrevtukova Irina , Pathak Smita , Attwooll Claire , Goode Jason , Mai Anthony , Schroth Gary P.
Published: August 2015

Gene fusion detection in cancer samples can provide tumor-specific information for cancer research, clinical diagnosis and targeted treatment. Common fusion detection methods such as qPCR and FISH are restricted to known fusion junctions and limited in the number of genes that can be detected in parallel. In contrast, RNA sequencing is a powerful approach for simultaneous discovery of all possible fusion junctions in a single reaction. But, the sequencing depth required for sensitive detection of fusions from whole-transcriptome libraries can be cost-prohibitive. Here we describe a cancer-specific capture-based approach for fusion detection by RNA sequencing that requires only a fraction of the sequencing depth of whole-transcriptome methods. We designed oligo probes that densely target coding regions of over 200 clinically relevant gene fusions and cancer-associated genes. This oligo panel was used to capture cancer-specific fusions from total RNA-Seq libraries. We used commonly studied cancer cell lines including MCF-7, K562, PC-3, LnCAP, A431 and Universal Human Reference RNA (UHRR) to compare the sensitivity of fusion detection across three RNA-Seq library prep methods: (1) cancer panel library capture (2) whole-transcriptome library capture and (3) PolyA selection. We show that probes targeting individual exons can robustly capture well-characterized cancer gene fusions such as BCR-ABL and BCAS4-BCAS3, as well as translocations where fusion junctions are unknown. Furthermore, these comparisons demonstrate the enhanced sequencing efficiency of the targeted cancer panel, while maintaining highly accurate quantitation of gene expression. We show that selective enrichment of RNA-Seq libraries with cancer-specific capture probes enables high-resolution mapping of genomic rearrangements in patient cancer samples, even those derived from FFPE, facilitating sequencing studies that were not previously possible.

Citation Format: Lisa C. Watson, Stephen M. Gross, Irina Khrevtukova, Smita Pathak, Claire Attwooll, Jason Goode, Anthony Mai, Gary P. Schroth. Highly sensitive fusion transcript detection and quantification in cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4884. doi:10.1158/1538-7445.AM2015-4884
Abstract 4890: Duplex sequencing of AML reveals extensive sub clonal heterogeneity
Authors: Loeb Lawrence A. , Schmitt Michael W. , Prindle Mark J. , Becker Pamela S.
Published: August 2015

Subclonal mutations, that are present in a small subset of tumor cells prior to chemotherapy, could serve as a reservoir for the emergence of drug resistance. These could selectively expand during chemotherapy and result in relapse and death. We have used Duplex DNA Sequencing (DS) to detect low frequency subclonal mutations in AML, both prior to treatment and after relapse. DS focuses on a limited number of target genes at the level of single DNA molecules. Mutations are scored only if they are present at the same position in both strands of the same DNA molecule and are complementary, resulting in sequencing accuracy that is more than 10,000-fold greater than that of conventional next-generation DNA sequencing (NGS).

To follow the course of mutation accumulation in AML, we used capture hybridization to enrich for 15 genes previously reported to be mutated in AML. We identified multiple subclonal mutations prior to therapy that would not be detected by routine NGS. For example, in one relapse sample, we identified a mutation in NRAS that was present in 32% of the cells. The identical mutation was detected by DS prior to treatment in 1% of cells. To further assess the frequency of subclonal mutations in AML, we targeted a 30 kb panel of genes at 500,000 fold depth, which facilitates detection of mutations present in fewer than 0.01% of cells. 5 subclonal mutations were identified within the 30 kb target, corresponding to a frequency of 170 mutations per megabase, Extrapolation of these results to the whole genome indicates that there are approximately 500,000 subclonal mutations per AML genome, which is 1,000 fold higher than the frequency of clonal mutations. These subclonal mutations would be unevenly distributed throughout the genome and be an important source for the selection of drug resistance during therapy.

Citation Format: Lawrence A. Loeb, Michael W. Schmitt, Mark J. Prindle, Pamela S. Becker. Duplex sequencing of AML reveals extensive sub clonal heterogeneity. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4890. doi:10.1158/1538-7445.AM2015-4890
Abstract 4894: Targeted sequencing of myeloid cancers using single-molecule enrichment in picodroplets
Authors: Samuels Michael L. , Kotsopoulos Steve K. , Long Frances , Gettler Holly , Clement Omo , Olson Jeff
Published: August 2015

A new method for enrichment of targeted genomic regions for next generation sequencing (NGS) is the use of single-molecule formatted PCR amplification, with the sample's target DNA partitioned into uniform picoliter volume droplets such that there are either zero or one target molecule in each droplet. All the droplets contain all of the primers and PCR reagents, ensuring that every target molecule from the sample is amplified, minimizing the amount of input required. Endpoint PCR using this single molecule format results in highly uniform yields that facilitate efficient use of the sequencing platform. In addition, the primers contain ‘Illumina tails’ that enable easy sample indexing and a workflow for loading directly onto a MiSeq without additional library preparation.

Here we detail the use of this method with the ThunderBolts Myeloid Cancer Panel, which targets ∼550 commonly mutated regions in 49 genes implicated in the causation, prognosis, and recurrence of myeloid disorders. The panel targets include an expert-curated set of 16 full genes and 33 mutational hotspot regions, including challenging targets such as CEBPA and NOTCH1. We present results showing sample inputs as low as 10 nanograms (no pre-amplification used) provide sequencing metrics with 100% coverage at >100x depth (>95% at >500x depth) with a normalized mean read depth of 2500x and high uniformity (>90% of amplicons within 0.2x of the mean), enabling detection of low minor allele frequencies (<5%). The workflow is easy and rapid, with <2 hours hands-on time and sample-to-results in <48 hours. In addition, we demonstrate similar performance metrics when adding additional primer pairs (ThunderBolts PLUS), ensuring continued flexibility for researchers to use the core panel plus additional key targets as they are identified and validated.

In summary, the ThunderBolts Myeloid Cancer Panel shows excellent sequencing coverage, high read depth and uniformity, and detection of low frequency mutations implicated in myeloid cancers. Starting from low input DNA samples, the workflow is easy and fast, enabling low cost targeted Illumina NGS sequencing with an expert curated panel that provides flexibility for expansion.

Citation Format: Michael L. Samuels, Steve K. Kotsopoulos, Frances Long, Holly Gettler, Omo Clement, Jeff Olson. Targeted sequencing of myeloid cancers using single-molecule enrichment in picodroplets. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4894. doi:10.1158/1538-7445.AM2015-4894