bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abstract 4816: Design, validation, and interpretation of an NGS assay for actionable variants in solid tumors
Authors: Mockus Susan M. , Ananda Guruprasad , Lundquist Micaela , Spotlow Vanessa , Simons Al , Mitchell Talia , Stafford Grace A. , Potter Christopher S. , Philip Vivek , Stearns Timothy , Srivastava Anuj , Barter Mary , Rowe Lucy , Malcolm Joan , Bult Carol , Katuturi Radha Krishna Murthy , Rasmussen Karen , Hinerfeld Douglas 
Published: August 2015

Abstract
The Jackson Laboratory Cancer Treatment Profile™ (JAX-CTP™) is a next generation sequencing (NGS)-based molecular diagnostic assay that detects actionable gene variants in solid tumors to inform the selection of targeted therapeutics for cancer treatment. We will describe the design of the 358- gene panel, analytical validation, and the curation and clinical reporting of actionable variants. Selection of the gene panel was based on known drug targets, casual implications in cancer, and a thorough pathway analysis. DNA is extracted from FFPE tumor samples and using hybrid capture, the genes of interest are enriched and sequenced on Illumina HiSeq 2500 or MiSeq sequencers. FASTQ files generated from Illumina's CASAVA software are submitted to the JAX Clinical Genome Analytics (CGA) data analysis pipeline to perform automated read quality assessment, alignment, and variant calling. Identified variants are then submitted for clinical curation using a combination of the in-house JAX Clinical Knowledgebase (CKB) and the external Genetic Variant Annotation (GVA) from CollabRx. Once clinically annotated, the variants are graded relative to their clinical utility for the specific tumor type and compiled into a clinical report to inform patient treatment. Extensive analytical validation, following CAP guidelines, was conducted to assess limit of detection, accuracy, precision, sensitivity, and specificity of the assay. The summarized optimized sensitivity of the assay is a minimum coverage of samples at 300X, a limit of detection of 10% for SNP’s/indels and ≥6 copies for CNV’s, and an average of 3-4 actionable variants per sample. The challenges of interpreting gene variants for clinical actionability and for establishing an analytically valid bioinformatic pipeline will be discussed in-depth.
Citation Format: Susan M. Mockus, Guruprasad Ananda, Micaela Lundquist, Vanessa Spotlow, Al Simons, Talia Mitchell, Grace A. Stafford, Christopher S. Potter, Vivek Philip, Timothy Stearns, Anuj Srivastava, Mary Barter, Lucy Rowe, Joan Malcolm, Carol Bult, Radha Krishna Murthy Katuturi, Karen Rasmussen, Douglas Hinerfeld. Design, validation, and interpretation of an NGS assay for actionable variants in solid tumors. [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 4816. doi:10.1158/1538-7445.AM2015-4816
Abstract 4863: Streamlining NGS workflows using cancer samples by the application of the DNA Integrity Number (DIN) from the Genomic DNA ScreenTape assay
Authors: Schmidt Eva , Pechtl Isabell , McHoull Barry , Liu Melissa 
Published: August 2015

Abstract
The results of numerous molecular screening and assay methods often rely on the overall quality of the genomic DNA (gDNA) input material. However extraction of genetic material can be challenging and often results in low amounts or variable quality of gDNA samples, which are further subjected to time and cost intensive downstream applications. For example, array comparative genome hybridization (aCGH) and Next Generation Sequencing (NGS) can require intact, high quality gDNA to ensure high quality, unambiguous results. It is therefore widely recommended to perform an initial quality control (QC) of the input material. Especially as only the final step of these workflows reveals if meaningful results have been achieved. In order to provide an objective and automated measure to standardize the gDNA integrity assessment, a software algorithm has been developed. This functionality of the 2200 TapeStation system provides a numerical determination of the gDNA integrity and is referred to as the DNA Integrity Number (DIN). This study demonstrates how DIN obtained by the upfront QC of gDNA on the Agilent Genomic DNA ScreenTape assay has allowed for significant saving of sequencing and sample preparation overhead using cancer samples in NGS workflows.
Citation Format: Eva Schmidt, Isabell Pechtl, Barry McHoull, Melissa Liu. Streamlining NGS workflows using cancer samples by the application of the DNA Integrity Number (DIN) from the Genomic DNA ScreenTape assay. [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 4863. doi:10.1158/1538-7445.AM2015-4863
Abstract 4870: GenePool: A cloud-based technology for rapidly data mining large-scale, patient-derived cancer genomic cohorts including The Cancer Genome Atlas
Authors: Sanga Sandeep , Vladimirova Antoaneta , Goold Richard D. , Klingler Tod M. 
Published: August 2015

Abstract
GenePool is a cloud-based system for the secure storage, management, analysis, visualization and interpretation of large-scale human genomics data. The GenePool platform enables rapid interrogation of massive amounts of data generated by current laboratory methods and was designed to meet the needs of scientists engaged in cancer biomarker discovery and characterization. The software solution provides users with an intuitive interface, an easy way to store and select genomics datasets according to sample-associated metadata for analysis, and an automated system for performing routine, well-characterized genomics workflows. Results are presented with multiple options for annotation, sorting and data export, with a visualization tool that facilitates browsing of genomic data for biomarker identification. We will demonstrate how GenePool removes the data download, management, and computing burdens faced by researchers interested in working with large amounts of patient-derived cancer genomics exemplified by The Cancer Genome Atlas. To date, TCGA has completed molecular characterization of more than 9,000 patient samples from a target of 17,000, and will have released an estimated 2.5 petabytes of data at project completion.
We will present case studies using the &gt;25 cancer cohorts worth of RNA-Seq, miRNA-Seq, Exome Sequencing, Protein Expression, Copy Number, and DNA Methylation data (provided to the community through the TCGA Data Portal) and made readily available for sample selection and analysis within GenePool. As validation of the GenePool platform, we will present results obtained within minutes that validate knowledge reported in the literature over the course of decades. We will then present novel findings for less understood cancer indications.
Note: This abstract was not presented at the meeting.
Citation Format: Sandeep Sanga, Antoaneta Vladimirova, Richard D. Goold, Tod M. Klingler. GenePool: A cloud-based technology for rapidly data mining large-scale, patient-derived cancer genomic cohorts including The Cancer Genome Atlas. [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 4870. doi:10.1158/1538-7445.AM2015-4870
Abstract 4871: A new multiple feature approach for rapid and highly accurate somatic structural variation discovery from whole cancer genome sequencing
Authors: Xia Li C. , Bell John , Chen Jiamin , Zhang Nancy R. , Ji Hanlee P. 
Published: August 2015

Abstract
We present SWAN, a statistical framework with implemented software package for accurate detection of genomic structural variants in next-generation sequencing (NGS) data from cancer. SWAN is designed to sensitively detect submicroscopic and lesser size genome structural variants that could possibly present at low allele frequency in the sample as may be the case in clonal subpopulations of a primary tumor. The likelihood ratio scan statistics module of SWAN collectively quantifies evidence from read-pair, hang-reads based on Marked Poisson Process models while the softclipping module additionally integrates the evidence from remapped soft-clipped reads. Using a spike-in dataset, we compared SWAN against established structural variant callers in recovering simulated homozygous and heterogeneous variants of various sizes and types. SWAN maintained high accuracy, high precision and low false positives across this broad spectrum and outperformed all the other callers. In additional benchmark with golden standard real data from sample NA12878, SWAN again showed the best-balanced accuracy among all callers and was 30% more sensitivity in detecting validated deletions than the next runner-up caller LUMPY in 50x coverage. Even at 5x coverage, SWAN was able to find 40% of the validated deletions while LUMPY did less than 20%. As an application to whole cancer genome sequencing, we analyzed a matched sequenced colorectal adenocarcinoma sample and found 39 somatic deletions, insertions and duplications, some of which could potentially drive the cancer progression. SWAN is quite efficient in memory utilization and speed, and can be used for large-scale genome-wide structural variant genotyping and discovery based on NGS data.
Citation Format: Li C. Xia, John Bell, Jiamin Chen, Nancy R. Zhang, Hanlee P. Ji. A new multiple feature approach for rapid and highly accurate somatic structural variation discovery from whole cancer genome 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 4871. doi:10.1158/1538-7445.AM2015-4871
Abstract 4873: Epicopy: Measuring DNA copy number variation using high-density methylation microarrays
Authors: Cho Soonweng , Kim Hyun-seok , Cope Leslie M. , Umbricht Christopher B. 
Published: August 2015

Abstract
Background:
Cancers exploit changes in both genomic copy number and DNA methylation to promote growth and escape tumor-suppressor pathways. Under the 2-hit hypothesis, a single gene is likely to be altered by multiple mechanisms at the same time and integrated analysis can sharpen the focus on the most likely drivers. Requiring larger amounts of input material and imposing additional costs may limit multiplatform analysis, especially in studies using archival tissues with long clinical follow-up information where the nucleic acids are degraded and yields are generally lower than are obtained from fresh tissues. Taking advantage of similarities between methylation arrays and SNP arrays, we developed Epicopy, a robust computational method to identify DNA copy number variation (CNV) using high-density Illumina Human Methylation 450K methylation microarrays, thereby delivering two complementary genetic and epigenetic profiles from a single chip.
Methods:
Epicopy was developed using data from thyroid carcinoma samples arrayed by The Cancer Genome Atlas (TCGA) and subsequently validated on breast and lung small cell carcinoma TCGA datasets. Using Epicopy, we identified circumstances where CNV information can be reliably measured by methylation microarrays.
Results:
Using TCGA SNP microarrays as the gold standard to assess the performance of methylation derived CNV data from the thyroid, breast, and lung small cell carcinoma datasets, we showed that Epicopy is able to detect CNVs identified by SNP arrays at a sensitivity of 0.69 and specificity of 0.90. Frequently occurring CNVs identified using Genomic Identification of Significant Targets in Cancer (GISTIC), were identified with even higher accuracy.
Conclusion:
Epicopy provides a robust method to obtain both copy number and methylation information from a single methylation microarray experiment and will add value to methylation microarrays at no additional cost to the user. Tools to highlight regions of high sensitivity and specificity will also be provided to help users decide on the feasibility of using Epicopy to identify CNVs in regions of interest. Epicopy is implemented in the R statistical language and will be made available as a freestanding package as part of the Bioconductor bioinformatics software project.
Citation Format: Soonweng Cho, Hyun-seok Kim, Leslie M. Cope, Christopher B. Umbricht. Epicopy: Measuring DNA copy number variation using high-density methylation microarrays. [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 4873. doi:10.1158/1538-7445.AM2015-4873
Abstract 4879: Reducing amplification artifacts in highly multiplex amplicon sequencing by using molecular barcodes
Authors: Peng Quan , Vijaya Satya Ravi , Lewis Marcus , Randad Pranay , DiCarlo John , Wang Yexun 
Published: August 2015

Abstract
Background
PCR amplicon sequencing has been widely used as a targeted approach for both DNA and RNA sequence analysis. Highly multiplex PCR has further enabled the enrichment of hundreds of amplicons in one simple reaction. At the same time, the performance of PCR amplicon sequencing can be negatively affected by issues such as high duplicate reads, polymerase artifacts and PCR amplification bias. Recently, people have made good progress at addressing those shortcomings by incorporating molecular barcodes into PCR primer design. So far, most work has been demonstrated using one to a few pairs of primers, which limits the size of the region one can analyze at one time.
Results
We described a simple protocol, which enables the use of molecular barcodes in highly multiplex PCR with hundreds of amplicons. Using this protocol and reference materials, we studied how molecular barcodes can increase the accuracy of variant calling at very low allelic frequency and reduce PCR amplification bias. We also evaluated its utility in profiling FFPE samples.
Conclusions
We demonstrated the successful implementation of molecular barcodes in highly multiplex PCR, at a scale many folds beyond earlier work. We showed that the new protocol combined the benefits of both highly multiplex PCR and molecular barcodes, i.e. the analysis of a very large region, low DNA input requirement, very good reproducibility and the ability to detect as low as 1% mutation with minimal false positives.
Citation Format: Quan Peng, Ravi Vijaya Satya, Marcus Lewis, Pranay Randad, John DiCarlo, Yexun Wang. Reducing amplification artifacts in highly multiplex amplicon sequencing by using molecular barcodes. [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 4879. doi:10.1158/1538-7445.AM2015-4879
Abstract 4883: A novel target capture approach for next generation sequencing and its application to oncogenic mutation detection
Authors: Bei Yanxia , Galvin Brendan , Richard Cynthia 
Published: August 2015

Abstract
Due to the complexity and heterogeneity of cancer genetics, next generation sequencing has played an increasingly important role in cancer diagnosis, prognosis and therapeutics. An effective target enrichment strategy further simplifies data analysis associated with NGS and further reduces costs.
We have developed a novel target capture technique that offers advantages over traditional in-solution hybridization and multiplex PCR protocols. With this method, genomic DNA is first enzymatically nicked to generate single stranded DNA of desirable length, in a sequence independent manner. The DNA fragments are then rapidly hybridized to short probes that can be captured by beads. The off target sequence of the captured DNA, defined by the probes, is subsequently removed via enzymatic digestion. The resulting targeted sequence are ligated with NGS platform specific adaptors and amplified by PCR. With our method, genomic DNA can be converted into libraries ready for sequencing within 6 hours; and the procedure is easily scalable for automation.
To demonstrate the efficacy of this method, we have designed a cancer panel to interrogate 50 genes that are commonly mutated in cancer, and tested it on various DNA samples including FFPE. The results demonstrate that our approach captures targeted sequence with high specificity and uniformity, and detects variants with great accuracy and sensitivity.
Citation Format: Yanxia Bei, Brendan Galvin, Cynthia Richard. A novel target capture approach for next generation sequencing and its application to oncogenic mutation detection. [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 4883. doi:10.1158/1538-7445.AM2015-4883
Abstract 4885: TOMA OS-Seq: A clinically oriented targeted resequencing method for detecting all mutation classes in DNA isolated from FFPE, FNAs and plasma
Authors: Bouhlal Yosr , McKenzie Alexander , So Austin P. 
Published: August 2015

Abstract
Critical genetic errors, namely specific mutations, are required for the development and maintenance of cancer. Molecular diagnostics that leverage the breadth of next-generation sequencing (NGS) to identify this mutational landscape are therefore becoming an important clinical tool in the precision treatment of cancer. However, the widespread clinical adoption of NGS technologies is hampered not only by the challenges of assaying from various clinical matrices, but also by the complexity of the workflows utilized to create, analyze, and annotate an NGS library.
To address these challenges, an adaptation of oligo-selective sequencing (OS-Seq) was developed with a workflow designed specifically for the requirements of the clinical laboratory. Termed TOMA OS-Seq)a panel of 96 genes - each with diagnostic or prognostic value - can be sequenced end-to-end from as little as 1 ng of input material, enabling targeted library construction from diverse sources such as fine-needle aspirates (FNAs), plasma as well as formalin-fixed paraffin embedded (FFPE) tissue. The minimized number of high-efficiency steps reduces the requirement for PCR, allowing the identification of copy number alterations (CNAs), re-arrangements, insertions and deletions (indels), as well as single nucleotide variants (SNVs) from these matrices.
The performance of TOMA OS-Seq) was assessed using a panel of cell lines harboring known variants in all classes of mutations. Specifically, comparison with a 12-gene droplet digital PCR (ddPCR) based test (the Amplinome Test) demonstrated a high correlation (R2 &gt; 0.95) of CNA measurements via TOMA OS-Seq) with ddPCR, when further challenged with FNAs. The application of TOMA OS-Seq) in assaying all mutation classes in circulating tumor DNA from plasma demonstrates the robustness and flexibility of this platform as clinically oriented targeted resequencing method.
Citation Format: Yosr Bouhlal, Alexander McKenzie, Austin P. So. TOMA OS-Seq: A clinically oriented targeted resequencing method for detecting all mutation classes in DNA isolated from FFPE, FNAs and plasma. [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 4885. doi:10.1158/1538-7445.AM2015-4885
Abstract 4901: Comparison of gene expression platforms: RNA-Seq, Fluidigm, and Nanostring
Authors: Schleifman Erica B. , Motlhabi Maipelo , Cummings Craig , Nakamura Rin , Bosch Linda , Patel Rajesh , Do An , Watson Andrew , Sandmann Thomas , Darbonne Walter , McCaffery Ian , Peters Eric , Raja Rajiv 
Published: August 2015

Abstract
Accurately measuring the expression of genes in formalin-fixed paraffin embedded (FFPE) tumor tissues has long been a struggle due to the inherent degradation of RNA isolated from these materials. Accurate quantification of gene expression levels in FFPE samples can enable the testing of biomarker hypotheses in the clinic and can potentially be used for patient stratification or selection in clinical trials. Platforms such as Fluidigm, Nanostring and microarrays are currently the high-throughput technologies utilized. Each of these platforms has different drawbacks and challenges such as lack of sensitivity, reproducibility or dynamic range when working with degraded FFPE samples. Currently, whole transcriptome RNA sequencing (RNA-Seq) is the only platform that offers a truly high-throughput, sensitive, and reproducible method to accurately quantify mRNA levels in RNA derived from FFPE samples. RNA-Seq, however has not yet been widely evaluated and adapted for use with degraded FFPE samples. Here we report the direct comparison of whole transcriptome RNA-Seq with two platforms that are currently compatible with FFPE derived RNA, Fluidigm and Nanostring, to determine the accuracy and feasibility of using this technology on degraded RNA. Utilizing a collection of matched fresh frozen (FF) and FFPE samples we analyzed gene expression using all three platforms to allow for a direct evaluation of each technology. By comparing the results to the matching FF sample, we were able to determine the accuracy and sensitivity of each platform when using degraded FFPE derived RNA. By titrating down the input of FFPE RNA into the RNA-Seq library prep we were also able to define the optimal input of FFPE RNA needed to accurately and reproducibly quantify gene expression. This work allows for a systematic comparison of different gene expression platforms for their use with degraded FFPE RNA.
Citation Format: Erica B. Schleifman, Maipelo Motlhabi, Craig Cummings, Rin Nakamura, Linda Bosch, Rajesh Patel, An Do, Andrew Watson, Thomas Sandmann, Walter Darbonne, Ian McCaffery, Eric Peters, Rajiv Raja. Comparison of gene expression platforms: RNA-Seq, Fluidigm, and Nanostring. [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 4901. doi:10.1158/1538-7445.AM2015-4901