bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 5054: Inferring mutational chronology in breast cancer by deep-sequencing tumor subpopulations
Authors: Navin Nicholas E. , Wang Yong , Waters Jill , Chen Ken , Hall Ira , Malhotra Ankit , Quinlan Aaron 
Published: August 2012

Abstract
Heterogeneous breast carcinomas often contain nuclei with multiple distributions of ploidy, each representing a distinct genomic subpopulation. We present an approach called Ploidy-Seq that combines flow-sorting and next-generation sequencing to isolate tumor subpopulations and deep-sequence the nuclei at high coverage (80-100X) to identify somatic mutations. We applied Ploidy-Seq to a triple-negative (ER-, PR-, Her2-) ductal carcinoma that showed three major tumor subpopulations and one stromal subpopulation. In order to distinguish germline from somatic mutations, we first identified all of the SNPs in the 2N stromal cells. We then studied the evolution of different molecular clocks within the breast tumor, including single nucleotide variations (SNVs), indels, structural rearrangements, copy number changes and translocations. By applying set theory operations, we compared the three tumor subpopulations to identify early mutations (present in all subpopulations), intermediate events (shared between two subpopulations) and late mutations (exclusive to each subpopulation). Overall we identified 101 nonsynonymous point mutations of which 31 had occurred early and were present in all tumor subpopulations. Many of the early mutations occurred in cancer genes including THSD7B involved in TGFβ signaling, the CDH26 cadherin-like 26 gene, and the kinesin gene KIF2B. Early mutations were further studied by single-cell sequencing, which showed evidence of clonal expansions within the tumor, suggesting that they provided a major selective advantage. These early mutations are of considerable interest for therapeutic targeting since they are present in all of the tumor subpopulations, and are likely to be driving the growth of the cancer.
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 5054. doi:1538-7445.AM2012-5054
Abstract 5058: Application of a high throughput cancer mutation profiling platform to clinical research
Authors: Garcia Elizabeth P. , Shivdasani Priyanka , Sharaf Nematullah , Crosby Lauren , Byrne Mark N. , Wade Jacqueline E. , Joshi Ruchi , Ducar Matthew , Palescandolo Emanuele , Hummelen Paul Van , Lindeman Neal I. , Kuo Frank C. , Longtine Janina A. , MacConaill Laura E. 
Published: August 2012

Abstract
Detection of critical cancer gene mutations in tumor samples may result in improved care, treatment and outcomes for patients. It has become clear that for specific cancer types there is a high association between mutations in a defined set of oncogenes or tumor suppressors some of which are actionable. While it has become common practice to screen for specific mutations in specific cancer types, to date broad mutation screening has not been practical. We report here the first large scale screening initiative between the Dana Farber Cancer Institute and Brigham and Women's Hospital that allows adult cancer patients the option to have their tumor tissue screened for genetic mutations implicated in cancer. OncoMap is a high throughput mutation profiling platform developed to detect 471 genetic mutations across 41 known oncogenes and tumor suppressor genes. The goal is to utilize OncoMap to identify genetic mutations in cancerous tissue across all tumor and tissue types. Because there is no bias as to which cancers are screened for specific mutations our aim is to identify new trends and associations between cancer types, mutational status and patient outcome. OncoMap has been analytically validated under CLIA guidelines as recommended by the Clinical Laboratory Standards Institute. Our findings show that OncoMap detects somatic mutations that are present at an allele frequency of 7.5% with 95% confidence. Precision and reproducibility studies were performed using 30 distinct formalin-fixed paraffin embedded tumor samples from various tissue types known to harbor somatic mutations in KRAS, BRAF or exon 19 deletions in EGFR. Further concordance studies demonstrate that OncoMap shows ninety-six percent sensitivity with respect to detection of codon 12 and 13 mutations in KRAS, detection of BRAF V600E mutations and JAK2 V617F mutations. Using the OncoMap cancer genetic profiling platform we anticipate that ∼10,000 individual tumors from adult cancer patients will be screened on a yearly basis enabling the identification of newly discovered associations between cancer tissues, their mutational status and patient outcome.
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 5058. doi:1538-7445.AM2012-5058
Abstract 5063: International Cancer Genome Consortium (ICGC)
Authors: Hudson Thomas J. , Jennings Jennifer L. 
Published: August 2012

Abstract
The International Cancer Genome Consortium (ICGC) was established to bring together researchers from around the globe to comprehensively analyze the genomic, transcriptomic, and epigenomic changes in 50 different tumor types or subtypes that are of clinical and societal importance across the globe. (International network of cancer genome projects (Nature 464, 993-998 (15 April 2010)). As of November 2011, the ICGC has received commitments from funding organizations in Asia, Australia, Europe and North America for 43 project teams in 13 jurisdictions to study over 18,000 tumor genomes. The genomic analyses of tumors conducted by ICGC members in Australia and Canada (pancreatic cancer), Japan (liver cancer), Spain (blood cancer), the UK (breast, lung and skin cancer) and the USA (blood, brain, breast, colon, kidney, lung, ovarian, rectal, stomach and uterine cancer) are now available through the Data Coordination Center housed on the ICGC website at www.icgc.org. The ICGC's informed consent and ethical oversight policies state that cancer patients enrolled in an ICGC-related study should be informed that their participation is voluntary, that their clinical care will not be affected by their participation and that data obtained from analyses using their samples will be made available to the international research community. Ultimately, over 25,000 tumor genomes will be sequenced worldwide. This will provide a comprehensive catalogue of genomic abnormalities associated with cancer, a collection of data that will reveal the repertoire of mutations that cause this wide-ranging disease and help define clinically relevant subtypes of cancer. The data will also provide a rich resource for the world's researchers who are working to develop new treatments to make patient care move forward.

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 5063. doi:1538-7445.AM2012-5063
Abstract 5069: Genomic profiles of primary non-small cell lung cancer (NSCLC) xenograft tumors identify distinct gene signatures associated with histological subtypes
Authors: To Christine , Strumpf Dan , Panchal Devang , Li Ming , Pham Nhu-An , Xie Wing , Yanagawa Naoki , Bandarchi Bizhan , Chui Michael Herman , Der Sandy , Shepherd Frances A. , Kislinger Thomas , Moran Michael , Jurisica Igor , Muthuswamy Lakshmi , Tsao Ming-Sound 
Published: August 2012

Abstract
Xenografts established directly from patient tumors mirror closely the histology of the primary tumors. Therefore, primary tumor xenografts (PTXG) may serve as important preclinical models to evaluate novel anti-cancer drugs. We previously reported that the ability of resected tumors to engraft in NOD-scid mice is a strong predictor of relapse after surgery and poorer prognosis in NSCLC patients, and thus may represent biologically more aggressive cancers (Clin Cancer Res 2011;17:134-41). Genomic characterization of PTXG would help identify genetic aberrations that drive malignant oncogenic pathways in NSCLC. We characterized the somatic copy number alterations (CNA) of 36 PTGX, consisting of 15 adenocarcinoma (ADC), 18 squamous cell carcinoma (SCC), 2 large cell neuroendocrine carcinoma (LCNEC) and 1 large cell carcinoma (LC), along with 34 patient normal samples as controls using Illumina Omni-1 Quad SNP arrays. The gene expression profiles of the 36 PTGX were analyzed using Illumina Omni-1 Quad HT-12 v4 arrays. Histology-specific recurrent regions of CNA observed in PTGX are concordant with the published and publicly available primary NSCLC CNAs. We identified 1053 genes with somatic copy number gains and 932 genes with somatic copy number losses that distinguish between SCC and ADC. From integrative analysis of mRNA expression and somatic CNAs, we identified 325 genes specific to ADC and 2232 specific to SCC that are well correlated. Gene candidates that are deregulated in ADC include WRN, STK35, SIX1; and genes that are over-expressed in SCC include SOX2, RNF13, WNK1, PIK3CA, TFRC, TP63, PAK2 suggesting there is differential deregulation of signaling pathways between these two subtypes of lung cancer. We have identified candidate gene signatures that distinguish between ADC and SCC from PTXG, suggesting these xenograft models can provide a valuable resource to study cancer biology and preclinical drug target evaluation in vivo.
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 5069. doi:1538-7445.AM2012-5069
Abstract 5086: Frequent genetic alteration in transitional cell carcinoma of the bladder by large scale exome sequencing
Authors: da Hu Xue 
Published: August 2012

Abstract
Bladder cancer is the ninth most common cancer worldwide, with TCC being the predominant form (90%). We completed a preliminary research that investigated into exomes of 9 TCCs and target genes of additional TCCs, and discovered frequent aberrations of the chromatin remodeling genes. Six genes, including UTX, MLL/MLL3, CREBBP/EP300, NCOR1, ARID1A and CHD6, were identified in 59% of the 97 TCC patients. Here, in order to obtain a more comprehensive genetic overview of TCC, we sequenced both exomes and whole genomes for another 92 TCC samples. For exome sequencing, we had an average coverage of 75.3x for targeted regions encompassing 38M of Refseq census coding sequence, and &gt;92% of the target bases were covered sufficiently for variant calling (≥10×). As for whole genome resequencing, we achieved the average coverage at 3.8x. We analyzed the exome and genome sequencing data of 92 TCC samples together with the 9 TCCs from the preliminary study to identify the somatic mutations and copy number variations (CNVs), and detected 11,143 non-sysnonymous point mutations, 1,041 small Indels in coding regions (&lt;100bp) and 12,034 CNVs. A total of 12,216 genes were found to be affected by these somatic genetic changes. Furthermore, 125 genes that harbored the confirmed non-silent mutations in at least five other tumors types were observed to have a significantly higher (likelihood test, p&lt;0.01) non-silent mutation rate than the background. We also analyzed the biological pathways by Gene Set Enrichment Analysis, and discovered that the MAPK signaling pathway and the pathway of actin cytoskeleton regulation were mutated in 76 and 75 TCC tumor samples, respectively. Our studies gathered a large number of genetic data on Bladder cancer by applying exome and whole genome sequencing, and provided an unprecedented panoramic view of the genetic basis of TCC.
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 5086. doi:1538-7445.AM2012-5086
Abstract 5087: UCSC Cancer Genomics Browser 2.0
Authors: Zhu Jingchun , Craft Brian , Swatloski Teresa , Ellrott Kyle , Goldman Mary , Wilks Christopher , Ma Singer , Szeto Christopher , Collisson Eric , Haussler David 
Published: August 2012

Abstract
As the rate of cancer genomic information production has increased so has the task of managing the computational infrastructure required to host, visualize and analyze that data. The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) provides a variety of tools to help researchers analyze their data. It includes sortable genomic heatmaps linked to patient clinical attributes that can be explored on demand. A user can run statistical tests between user defined groupings of samples, genomic signature evaluations, and toggle between chromosomal and custom gene sets views. The browser is linked to the UCSC Genome Browser; thus inheriting and integrating the Genome Browser's rich set of human biological and genetic data that enhances the interpretability of the cancer genomics information. UCSC Cancer Genomics Browser 2.0 has been released with drastically enhanced user. Other recent improvements in the Cancer Genomics Browser have been in response to the growing number of collaborative cancer analysis projects. Designed with the privacy issues that come along with patient data in mind, cancer browser accounts provide user-specific sessions, gene sets, genomic profiles, and user-specific data tracks controls. In addition to the public portal, the Cancer Genomics Browser also supports projects that require secured access control. The system hosts results from TCGA, SU2C (Stand Up To Cancer), LINCS (Library of Integrated Network-based Cellular Signatures), GEO (Gene Expression Omnibus) and the ISPY trials along with information from individual labs. Researchers that have been authenticated to multiple projects can see the results from all of their projects in a single page. The other aspect of working with multiple collaborative cancer projects is the issue of properly defining data interchange formats. For the Cancer Genome Browser we have created a specification called cgData, which will be used by UCSC to consolidate various types of information from TCGA. cgData is a designed to provide the variety of file formats that are required to describe the heterogeneous data required for the browser. Formats for defining expression matrices, genomic probe definitions, clinical feature data, mutation information and sample mapping have all been specified to enable rapid integration of new data into the Cancer Genome Browser. This format is being developed in collaboration with partners from SU2C and LINCS, and utilities to convert The Broad Institutes TCGA Firehose analysis and MSKCC cBio portal information have already been developed. The publicly available data is organized into downloadable releases on a monthly basis.
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 5087. doi:1538-7445.AM2012-5087
Abstract 5088: Identification of effective genotype-selective drug combinations in melanoma
Authors: Held Matthew , Langdon Casey , Platt James , Steed Tisheeka , Chakraborty Ashok , Bachiocchi Antonella , Liu Zonghzhi , Bosenberg Marcus , Stern David F. 
Published: August 2012

Abstract
Resistance and partial responses to individual therapeutic agents are major obstacles in cancer treatment. In certain cases, combination therapies are clearly more effective, but systematic approaches to the identification of synergistic combinations of drugs are not well established. Here we present a bioinformatics-guided, high-throughput combinatorial screening platform that tests an array of small molecule drug combinations. A panel of over one hundred fifty agents was curated for compounds that inhibit receptors and signaling pathways active in melanoma, and broader groups of conventional cell cycle-active and genotoxic agents. Sixteen-point dose-effect curves were determined. Forty of the compounds exhibiting activity and representing the major classes tested were further analyzed. Three doses each were chosen, set up in all pair-wise combinations using a hit-picking robot, and analyzed against cell lines with activated BRAF, activated RAS, or neither mutation. Several combinations were selectively effective for melanomas containing activating mutations in BRAF, but were ineffective for mutant RAS melanomas, which were most susceptible to a small group of other drug combinations. Work is underway to validate the effective combinations in animal models, and to mine transcriptome and phosphoproteomic data associated with the cell lines to better predict sensitivity and resistance.
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 5088. doi:1538-7445.AM2012-5088
Abstract 5092: Localized and disseminated histiocytic sarcoma complex: A canine model
Authors: Dervisis Nikolaos , Klahn Shawna L. , Kiupel Matti , Parys Maciej , Gregory-Bryson Emmalena , Yuzbasiyan-Gurkan Vilma 
Published: August 2012

Abstract
Canine histiocytic sarcoma is an aggressive and uniformly-fatal round-cell neoplasm. The localized, peri-articular form of the disease (PAHS) appears to have statistically significant prolonged survival, when compared to the non - peri-articular form of the disease (non-PAHS). Knowledge of the molecular basis for the aggressiveness of the canine histiocytic sarcoma is foundational for developing effective treatments. The aim of this study was to characterize the molecular expression profiles of the different sub-types of the disease. Canine patients, with spontaneously-arising histiocytic sarcoma, were recruited for the study. Tumor tissue samples and peripheral blood were obtained and used for primary cell line development and gene expression analysis. Eight PAHS and 8 non-PAHS tumor samples were selected. RNA extraction, amplification and labeling were performed using standard techniques. Raw gene expression values were obtained using the Affymetrix GeneChip Canine Genome 2.0 Array. Background correction, normalization, PM correction, summarization, and expression analysis were performed using R/affy/limma. Gene set analysis was performed using BRB-ArrayTools, and the Molecular Signatures Database (MSigDB), to investigate gene ontology groups of genes whose expression was differentially regulated. Primary cell lines from tumor biopsies and peripheral blood samples were developed and characterized based on cellular morphology, growth characteristics, and immunophenotyping. In our gene expression array experiments, we identified specific gene transcripts that are more likely to represent true and biologically meaningful differences in expression levels between PAHS and non-PAHS. More specifically, metallopeptidase genes, and homeobox domain gene expression levels were enriched in the PAHS group, while ATP-binding cassette genes, and interleukin 1 receptor signaling gene expression levels were enriched in the non-PAHS group. Our results suggest presence of gene expression signatures that can provide insight in the diverse biologic behavior of the disease and highlight canine spontaneous tumors in understanding tumor biology.
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 5092. doi:1538-7445.AM2012-5092
Abstract 5093: Genome wide DNA copy number analysis of serous type ovarian carcinomas identifies genetic markers predictive of clinical outcome
Authors: Engler David , Gupta Sumeet , Growdan Whitfield , Drapkin Ronny , Nitta Mai , Sergent Petra , Allred Serena , Gross Jenny , Deavers Michael , Kuo Wen-Lin , Karlan Beth , Rueda Bo , Orsulic Sandra , Gershenson David , Birrer Michael , Gray Joe , Mohapatra Gayatry 
Published: August 2012

Abstract
Ovarian cancer is the fifth leading cause of cancer death in women. Ovarian cancers display a high degree of complex genetic alterations involving many oncogenes and tumor suppressor genes. Analysis of the association between genetic alterations and clinical endpoints such as survival will lead to improved patient management via genetic stratification of patients into clinically relevant subgroups. In this study, we aim to define subgroups of high-grade serous ovarian carcinomas that differ with respect to prognosis and overall survival. Genome-wide DNA copy number alterations (CNAs) were measured in 72 clinically annotated, high-grade serous tumors using high-resolution oligonucleotide arrays. Two clinically annotated, independent cohorts were used as validation sets. Unsupervised hierarchical clustering of copy number data resulted in two clusters with significant difference in progression free survival (PFS) and marginal difference in overall survival (OS). GISTIC analysis of the two clusters identified altered regions unique to each cluster. Supervised clustering of two independent large cohorts of high-grade serous tumors using the classification scheme derived from the two initial clusters validated our results and identified 8 genomic regions that are distinctly different among the subgroups. These 8 regions map to 8p21.3, 8p23.2, 12p12.1, 17p11.2, 17p12, 19q12, 20q11.21 and 20q13.12; and harbor potential oncogenes and tumor suppressor genes that are likely to be involved in the pathogenesis of ovarian carcinoma. We have identified a set of genetic alterations that could be used for stratification of high-grade serous tumors into clinically relevant treatment subgroups.
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 5093. doi:1538-7445.AM2012-5093