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  • 1
    In: Chemosphere, Elsevier BV, Vol. 65, No. 10 ( 2006-12), p. 1836-1845
    Type of Medium: Online Resource
    ISSN: 0045-6535
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    Language: English
    Publisher: Elsevier BV
    Publication Date: 2006
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  • 2
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 23_Supplement ( 2015-12-01), p. PR04-PR04
    Abstract: Background: Brain metastases are associated with a dismal prognosis. There is a limited understanding of the oncogenic alterations harbored by brain metastases and whether these are shared with their primary tumors. Our objectives were to (1) elucidate the evolutionary patterns leading to brain metastases and (2) identify whether brain metastases are genetically distinct from their primary tumors and other distal metastatic sites. Methods: We performed whole-exome sequencing of 104 matched brain metastases, primary tumors and normal tissue, including 7 cases with spatially and temporally separated brain metastasis sites and 8 cases with additional extracranial disease sites, including regional lymph nodes, and distal metastases. We developed novel computational tools to perform an integrative analysis of somatic mutations and copy-number alterations. This analysis allowed us to estimate the clonal architecture of the primary and metastases, and to reconstruct a phylogenetic tree relating the subclones from each patient. Results: In all related cancer samples, we observed branched evolution, where all metastatic and primary sites shared a common ancestor yet continued to evolve independently. In 53% of cases, we found clinically actionable driver alterations in the brain metastases that were not detectable in the matched primary-tumor sample. In contrast, spatially and temporally separated brain metastasis sites were more genetically homogenous and shared nearly all driver alterations detected. Extracranial metastases and regional lymph nodes were highly divergent from brain metastases. Several clinically actionable pathways were enriched in brain metastases. Conclusions: These observations demonstrate that brain metastasis tissue provides an opportunity to identify clinically important driver alterations that may be undetected in single samples of primary tumors, regional lymph nodes, or extracranial metastases. Genetic divergence between primary tumors and brain metastases may underlie some of the difficulties encountered with the combined treatment of systemic disease and brain metastases in patients. When clinically feasible, genomic characterization of brain metastasis tissue should be considered when selecting therapeutic agents for patients with brain metastases. Citation Format: Priscilla K. Brastianos, Scott L. Carter, Sandro Santagata, Daniel Cahill, Amaro Taylor-Weiner, Robert T. Jones, Eliezer Van Allen, Peleg Horowitz, Keith L. Ligon, William T. Curry, Ian F. Dunn, Paul Van Hummelen, Matthew Meyerson, Levi Garraway, Josep Tabernero, Joan Seoane, Stacey Gabriel, Eric S. Lander, Rameen Beroukhim, Tracy T. Batchelor, Jose Baselga, David N. Louis, William C. Hahn, Gad Getz. Genomic characterization of brain metastases reveals branched evolution and metastasis-specific mutations. [abstract]. In: Proceedings of the AACR Special Conference: Advances in Brain Cancer Research; May 27-30, 2015; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2015;75(23 Suppl):Abstract nr PR04.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2015
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  • 3
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 76, No. 5_Supplement ( 2016-03-01), p. B38-B38
    Abstract: Of pediatric solid tumors, as many as 10% of tumors are categorized as rare. Many of these rare tumors lack standard effective known therapy. The ability to identify vulnerabilities for many rare tumors has been significantly limited by the lack of in vitro and in vivo models. Furthermore, current approaches to study such vulnerabilities are usually limited to a specific compound or target. Our objectives were 1) to develop a platform to collect tumor samples and generate in vitro models and 2) to develop systematic and orthogonal approaches focused on currently known druggable cancer targets to identify vulnerabilities in these difficult to treat cancers. We have developed a proof of concept cell line from a patient who succumbed to progressive undifferentiated sarcoma treated on an aggressive multi-therapy regimen. This cell line, in its early passages, has novel gene fusions that match that of the primary tumor. Furthermore, even at early passages, this cell line was amenable to high throughput functional screens. Using a targeted pooled shRNA screen (employing matched seed controls) and an analogous CRISPR screen we identified dependencies to XPO1 and CDK4. In parallel, compounds against these targets were identified in a small molecule compound screen. These targetable dependencies were further validated in vivo with a micro-dosing device. These observations identify new targets in this rare malignancy. Furthermore, this suggests that the interrogation of patient derived cell lines facilitates the identification of testable therapeutic approaches. Citation Format: Andrew L. Hong, Glenn S. Cowley, Yuen-Yi Tseng, Jaime H. Cheah, Oliver Jonas, Mihir B. Doshi, Bryan D. Kynnap, Coyin Oh, Stephanie Meyer, Paul Clemons, Michael Burger, Francisca Vazquez, Barbara Weir, Gregory V. Kryukov, Alanna Church, Alma Imamovic, Aviad Tsherniak, Craig Bielski, Brian Crompton, Elizabeth Mullen, Charles Roberts, Carlos Rodriguez-Galindo, Katherine A. Janeway, Kimberly Stegmaier, Paul van Hummelen, Robert Langer, Levi A. Garraway, Stuart L. Schreiber, David E. Root, Jesse S. Boehm, William C. Hahn. Developing a functional genomics platform to interrogate rare pediatric cancers. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Pediatric Cancer Research: From Mechanisms and Models to Treatment and Survivorship; 2015 Nov 9-12; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Res 2016;76(5 Suppl):Abstract nr B38.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2016
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  • 4
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 30, No. 15_suppl ( 2012-05-20), p. 5011-5011
    Abstract: 5011 Background: Cervical adenocarcinomas (AC) have higher rates of recurrence and distant metastasis, compared with squamous cell carcinomas (SCC), and decreased survival in advanced disease. Yet, tailored treatments for cervical cancers have not emerged. The aim of this study was to compare the frequency and type of somatic mutations in cervical AC and SCC to identify novel therapeutic targets for both subtypes. Methods: Tumors from 61 patients with cervical cancer (36 AC, 25 SCC) underwent genomic profiling by OncoMap, a multiplexed mass spectrometric genotyping technology that interrogates more than 400 known mutations in 33 cancer genes. Results: Overall, 31/61 (50.8%) tumors harbored candidate mutations, and 6/61 (9.8%) had ≥2 mutations. PIK3CA mutations were present in 21/64 (34.4%) of cervical cancers, with a trend towards higher rates in SCC compared with ACC (21/25 or 48.0% vs. 9/27 or 33.3%, p=0.10). KRAS mutations were present in 6/31 (16.7%) of AC, but none of the SCC (0%; 0/25). EGFR mutations were present in 9/25 (36.0%) of SCC, including G719S, but none of AC (0%; 0/31). Conclusions: The identification of distinct genomic alterations in SCC and AC of the cervix suggest different therapeutic rationales for each subtype. EGFR amplification in cervical SCC has been previously reported, but this is the first identification, to our knowledge, of activating EGFR mutations in cervical SCC. Together, this suggests that EGFR-inhibitors might be useful in selected patients with cervical SCC. Similarly, activating mutations in KRAS and PIK3CA in AC suggest that inhibition of the MAPK pathway (MEK inhibitors) and/or PI3K pathway may be beneficial in this subtype. Future studies should include more comprehensive genomic profiling strategies, such as targeted massively parallel sequencing, to detect multiple types of genomic alterations.
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2012
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  • 5
    In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 34, No. 15_suppl ( 2016-05-20), p. 2069-2069
    Type of Medium: Online Resource
    ISSN: 0732-183X , 1527-7755
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    Language: English
    Publisher: American Society of Clinical Oncology (ASCO)
    Publication Date: 2016
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  • 6
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 77, No. 13_Supplement ( 2017-07-01), p. 562-562
    Abstract: Viruses are a major contributor to oncogenesis, causing 10-15% of human cancers. Molecular pathways involved in malignant transformation are frequently activated by genetic alterations, including but not limited to, somatic mutations, copy number aberrations, structural variants, and oncoviruses. Precision cancer medicine aims to classify tumors by site, histology, and molecular tests to determine an “individualized” profile of cancer alterations. However, clinical tests for these various alterations are sequential, time consuming, and use a lot of material, which is often quite limited (e.g., biopsies). Moreover, tests for the presence of viral sequence are generally performed separately to tests (such as massively parallel sequencing) to detect human genomic alterations. Here we present a hybrid capture and massively parallel sequencing approach to detect viral infection concurrently with targeted genomic analysis, which may decrease assay costs, increase sensitivity and scalability, and detect many types of alterations, thereby providing a more complete tumor genetic profile all from a single sample. We have created a custom hybrid capture probeset for targeted Illumina sequencing to determine whether oncoviruses are present in tissue samples and also determine if the virus has integrated into the host’s genome. We have created both ‘detection’ and ‘integration’ baits for several oncoviruses, including polyomaviruses, human papilloma viruses, Epstein-Barr virus, human cytomegalovirus, Kaposi sarcoma herpesvirus, human T-lymphotropic virus, and hepatitis B virus. To distinguish between different strains of a single virus, strain-specific detection baits were created to bind to variable regions of viral genomes. The integration bait was designed to bind to regions of the viral genomes that are commonly integrated into the human genome. This baitset can also be combined with other capture panels targeting oncogenes to simultaneously determine infection and integration statuses, as well as somatic mutations, copy number and structural variants. To detect virus presence, reads were aligned to a hybrid reference of both the human, and targeted virus genomes. Viral integration status and integration loci were determined by leveraging discordant read pairs that aligned to both the human genome and a viral genome. We have tested our techniques on tissue samples that were infected with either Merkel Cell Polyomavirus or Epstein-Barr virus, as determined using quantitative polymerase chain reaction (qPCR) or immunohistochemistry (IHC) techniques, and have successfully detected these viruses and identified viral integration loci. Overall, this viral hybrid capture probeset provides the ability to simultaneously determine a tissue sample’s infection and viral integration status alongside other somatic genomic analyses, saving both time and sample material. Citation Format: Robert T. Burns, Samuel S. Hunter, Matthew D. Ducar, Aaron R. Thorner, James A. Decaprio, Paul Van Hummelen, Alexander Frieden, Anwesha Nag, Haley A. Coleman, Michael K. Slevin, Andrea Clapp, Samantha D. Drinan, Suzanne R. McShane, Edwin Thai, Priyanka Shivdasani, Joshua Bohannon, Johann Hoeftberger, Reuben Jacobs, Bruce M. Wollison, Neil A. Patel, Monica D. Manam, Phani Davineni, Matthew Meyerson, Laura E. MacConaill. Oncovirus detection and integration analysis from human tumor samples using targeted massively parallel sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 562. doi:10.1158/1538-7445.AM2017-562
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2017
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  • 7
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 72, No. 8_Supplement ( 2012-04-15), p. 3178-3178
    Abstract: Formalin-fixed paraffin embedded (FFPE) tissues are far more abundant in most tissue banks and pathology departments than fresh or fresh frozen (FF) samples, but typically yield varying degrees of degraded DNA as a result of the fixation process. The quality of FFPE tissues may vary based on a number of factors such as: age of the block, fixation time, storage and handling conditions. Being able to harness the power of next generation sequencing technologies to genomically characterize these abundant and diverse achieved samples would be tremendously valuable to the cancer research community and would enable the use of this material for clinical purposes. The goal of this study was to assess the performance of FFPE samples in next generation sequencing applications. We monitored close to 100 samples from tumor and normal tissues of FFPE, FF and blood origin. These samples underwent several processes for whole-exome or targeted sequencing, including DNA fragmentation, size selection, library preparation, and hybrid-capture enrichment. We observed variable performance across these samples at several of the above steps, which correlated predominantly with FFPE tissues and the age of block. Other quality metrics that showed relative lower performance of FFPE DNA were the cluster density, duplication rate or library complexity. Most FFPE samples still generated good quality sequence, however, older FFPE blocks, over 10 years, may need more input DNA or higher sequence depth to reach minimum coverage if somatic mutation analysis is the goal. There was no difference in performance between DNA from tumor and normal tissues. 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 3178. doi:1538-7445.AM2012-3178
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2012
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  • 8
    Online Resource
    Online Resource
    Future Science Ltd ; 2002
    In:  BioTechniques Vol. 32, No. 6 ( 2002-06), p. 1330-1340
    In: BioTechniques, Future Science Ltd, Vol. 32, No. 6 ( 2002-06), p. 1330-1340
    Abstract: Microarray expression analysis demands large amounts of RNA that are often not available. RNA amplification techniques have been developed to overcome this problem, but limited data are available regarding the reproducibility and maintenance of original transcript ratios. We optimized and validated two amplification techniques: a modified in vitro transcription for the linear amplification of 3 μg total RNA and a SMART TM PCR-based technique for the exponential amplification of 50 ng total RNA. To determine bias between transcript ratios, we compared the expression profiles in mouse testis versus spleen between the two amplification methods and a standard labeling protocol, using microarrays containing 4596 cDNAs spotted in duplicate. With each method, replicate hybridizations were highly reproducible. However, when comparing the amplification methods to standard labeling, correlation coefficients were lower. Twelve genes that exhibited inconsistent or contradictory expression ratios among the three methods were verified by quantitative RT-PCR. The amplification methods showed slightly more discrepancies in the expression ratios when compared to quantitative RT-PCR results but were more sensitive in terms of detecting expressed genes. In conclusion, although amplification methods introduce slight changes in the transcript ratios compared to standard labeling, they are highly reproducible. For small sample size, in vitro transcription is the preferred method, but one should never combine different labeling strategies within a single study.
    Type of Medium: Online Resource
    ISSN: 0736-6205 , 1940-9818
    Language: English
    Publisher: Future Science Ltd
    Publication Date: 2002
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    SSG: 12
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  • 9
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 74, No. 19_Supplement ( 2014-10-01), p. 5321-5321
    Abstract: Targeted next-generation sequencing (NGS) to capture genes or regions of interest has proven to be a cost-effective alternative to whole genome sequencing (WGS), particularly for cancer research and clinical cancer care. In this context, biologically or clinically relevant selected genes/regions are sequenced to several hundred-fold coverage. However, current algorithms and tools for detecting large structural variants (SVs), such as translocations, fail to achieve either high specificity or sensitivity, due to the fact that most available methods were designed for WGS data, and thus do not take advantage of the reduced size and higher coverage of targeted sequencing to improve SV calling. We developed a novel method, BreaKmer, to detect indels, rearrangements, and translocations from single sample targeted genomic reads. The algorithm extracts mis-mapped single or paired-end NGS reads. From these reads, hypothesized to contain SV breakpoints, contigs are built with a kmer strategy: reads are broken into k-length substrings or kmers, and those occurring in the reference are filtered. The remaining kmers represent sequences containing any sequence variant from the reference, ranging from single nucleotides to larger variants. Contigs are assembled from reads containing sample specific kmers. SVs are called based on alignment of the contigs to the reference sequence. With paired-end (PE) reads, discordantly mapped paired reads are extracted and coupled with SV calls that are made. To demonstrate BreaKmer, we analyzed NGS data from 166 samples enriched using 3 different capture panels (ranging from 305-504 genes). Our dataset contained 25 cancer specimens with known translocation events verified by orthogonal clinical methods and a negative control set of 141 ‘normal’ samples with no known SVs. The samples represented DNA extracted from FFPE, fresh frozen, blood and cell lines. Among 25 samples, 15 had additional replicate samples. Mean target coverage over all the samples was on average 150x. Specimens were barcoded at library preparation and pooled, followed by hybrid-capture targeting cancer genes and sequenced 2x100bp PE. All translocation events from the 25 test samples and their replicates (46) were detected by BreaKmer. An additional 19 translocations were detected among all the samples and their replicates, while no translocation calls were made for the 141 negative control samples. Our novel kmer strategy to detect SVs displayed high sensitivity and specificity. We reliably detected rearrangements of ALK, BCL2-IGH, BCR-ABL1 from lung adenocarcinoma, B-cell lymphoma, and chronic myeloid leukemia samples, respectively; indicating real clinical utility of this algorithm. In addition, our tool effectively detects other SV types - such as indels in FLT3 and KIT, among other genes. Our algorithm thus serves a pressing need for improved SV detection in targeted NGS data, particularly in precision cancer medicine. Citation Format: Ryan P. Abo, Elizabeth P. Garcia, Matthew Ducar, Ravali Adusumilli, Marc Breneiser, Vanessa Rojas-Rudilla, Lynette M. Sholl, Neal I. Lindeman, Matthew L. Meyerson, William C. Hahn, Paul Van Hummelen, Laura E. MacConaill. BreaKmer: Detection of structural rearrangements in targeted next-generation sequencing data using kmers. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5321. doi:10.1158/1538-7445.AM2014-5321
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2014
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  • 10
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 13_Supplement ( 2018-07-01), p. 438-438
    Abstract: Changes in DNA copy number, i.e., somatic CNVs, are common genetic aberrations in cancers. The effects of CNV include alteration in gene dosage across large segments of the cancer genome affecting the expression of cancer driver genes by amplifications, or cancer suppressor genes by deletions. In addition, CNVs are markers of underlying rearrangements within or between chromosomes and there is increasing evidence supporting a greater role for CNVs in developing and maintaining neoplastic cell population diversity. Copy number aberrations can be estimated from next generation sequencing data, with high sensitivity and genomic resolution by sequencing the whole genome (WGS). For this study, we demonstrated that high quality CNV calls can be extracted in a fast and cost-effective way from low-coverage whole genome sequencing. Novaseq S2 flowcells (Illumina Inc) enables to obtain an average coverage of 3-4x per sample after pooling up to 96 samples per flowcell. We examined three different copy number detection tools (CNVkit, BicSeq, and seqCBS) from paired tumor and normal WGS using microarray data as a reference. Pearson correlations were computed between the reference and CNVs from the WGS in two fashion; i) segment based and ii) gene based. The segment based comparison used sliding window of 100 K bp while gene based comparison used segments at the gene level. We found high correlations between microarray and WGS segments. The highest correlations were obtained by CNVkit, ranging from 0.964 to 0.985 (SD: 0.973 - 0.007) and BicSeq, ranging from 0.963 to 0.986 (SD: 0.975 - 0.008). These results open the prospect of assessing large cancer cohorts of hundreds of samples at a reasonable cost. We are planning to apply this method to a large cohort of Stage III colon cancer patients and determine the clinical relevance of CNVs for survival. Citation Format: HoJoon Lee, Li Charlie Xia, Stephanie Greer, John Bell, Sue M. Grimes, Christina Wood Bouwens, Giwon Shin, Billy TC Lau, Lucas Johnson, Noemi Andor, Kenneth Day, Mickey Miller, Helaman Escobar, Lincoln Nadauld, Hanlee P. Ji, Paul Van Hummelen. High-quality CNV segments from low-coverage whole genome sequencing from FFPE cancer biopsies based on an evaluation of multiple CNV tools [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago , IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 438.
    Type of Medium: Online Resource
    ISSN: 0008-5472 , 1538-7445
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    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2018
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