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PDF file - 880K, Volcano plots for 28 FDA approved cancer drugs of interest.

XLSX file - 713K, Excel sheet containing additional data for main Figure 4.

XLSX file - 271K, Excel sheet containing additional data for the main text.

XLSX file - 337K, Excel sheet containing the list of compounds from Supplemental Figure 9.

PDF file - 3388K, Supplementary Figure 1: Variant filtering decision tree. Supplementary Figure 2: Distribution of variants by annotation. Supplementary Figure 3: The NCI-60 cell lines. Supplementary Figure 4: Distribution of variants by type. Supplementary Figure 5: Phylogenic conservation of POL epsilon-P286. Supplementary Figure 6: A snapshot of the WES dataset in Variant Analysis by Ingenuity Systems (http://www.ingenuity.com/NCI60_WES). Supplementary Figure 7: Pattern comparison for cell with wild-type TP53 status. Supplementary Figure 8: Receiver operating curves (ROC) for cross-validated drug predictors.

PDF file - 4628K, Volcano plots for 46 cancer genes of interest.

PDF file - 125K

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor–normal genomic DNA (gDNA) samples derived from a breast cancer cell line—which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations—and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking ‘tumor-only’ or ‘matched tumor–normal’ analyses.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor–normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

We characterized two reference samples for NGS technologies: a human triple-negative breast cancer cell line and a matched normal cell line. Leveraging several whole-genome sequencing (WGS) platforms, multiple sequencing replicates, and orthogonal mutation detection bioinformatics pipelines, we minimized the potential biases from sequencing technologies, assays, and informatics. Thus, our “truth sets” were defined using evidence from 21 repeats of WGS runs with coverages ranging from 50X to 100X (a total of 140 billion reads). These “truth sets” present many relevant variants/mutations including 193 COSMIC mutations and 9,016 germline variants from the ClinVar database, nonsense mutations inBRCA1/2and missense mutations inTP53andFGFR1.Independent validation in three orthogonal experiments demonstrated a successful stress test of the truth set. We expect these reference materials and “truth sets” to facilitate assay development, qualification, validation, and proficiency testing. In addition, our methods can be extended to establish new fully characterized reference samples for the community.

Patient-Derived Xenografts (PDX) are proven models to study novel drugs or drug combinations and test hypothesis in preclinical studies. The overarching goal of the PDXNet is to coordinate the development of appropriate PDX models and methods for preclinical drug testing to advance CTEP clinical development of new cancer agents. The PDXNet is an NCI-funded consortium of six PDX Development and Trial Centers (PDTCs) and one PDCCC. Four PDTCs are responsible for developing PDXs and executing specific preclinical trials focused on cancer types including breast cancer, melanoma, and lung cancer. The other two recently awarded centers are specifically focused on minority PDX models and preclinical trials. Besides the PDTCs, the NCI Patient-Derived Models Repository (PDMR) at the Frederick National Laboratory for Cancer Research (FNLCR) is also providing models and data to the PDXNet. The PDCCC is responsible for coordination and developing standards for PDX generation as well as data analysis and metadata harmonization. The PDX Data Commons is built on top of existing NCI resources, leveraging the Cancer Genomics Cloud maintained by Seven Bridges Genomics, where PDXNet data is co-located with TCGA and other large-scale datasets. The PDCCC is co-led by experts from the Jackson Laboratory, providing scientific leadership in xenograft methods and cancer biology to ensure the promulgation of standards that are well-suited for the PDX community. A new portal has been set up at https://www.pdxnetwork.org/ to serve as the point of access to PDXNet resources. In addition, we established ongoing network-wide meetings to facilitate knowledge exchange, held PDXNet portal trainings, and set up working groups to tackle specific challenges. For instance, the Data Ontology working group has been working towards building a common data ontology model specifically for PDX datasets. We are in the process of annotating the very first dataset using this new ontology on the PDXNet portal. Also, the Workflows working group has been working on building and benchmarking various RNA-seq and whole exome sequencing analysis workflows to standardize data processing between PDXNet grantees and create a harmonized PDXNet dataset. These PDX models and the accompanying data will be opened to the community for data mining and/or preclinical research. The PDXNet is a strong step toward building a consensus around PDX models, so that the power for discovery can be expanded by making multi-institutional PDX cohorts a reality. As the coordination center, we are also working closely with the EuroPDX project to exchange standards and knowledge to support the PDX community with a set of standards going forward. The PDCCC is a central part of this process to systematically capture and analyze the variables most influential to PDX models and share protocols and tools to make PDXs an interchangeable research currency for preclinical discovery. Citation Format: Jacqueline Rosains, Anuj Srivastava, Wingyi Woo, Vishal Sarsani, ZiMing Zhao, Javad Noorbakhsh, Ogan D. Abaan, Christian Frech, Jack DiGiovanna, Ryan Jeon, Steve Neuhauser, Peter Robinson, Yvonne A. Evrard, Carol Bult, Jeffrey A. Moscow, Brandi Davis-Dusenbery, Jeffrey H. Chuang. The PDX Data Commons and Coordinating Center (PDCCC) for PDXNet in support of preclinical research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1074.

The NCI-60 cell lines are the most frequently studied human tumor cell lines in cancer research. This panel has generated the most extensive cancer pharmacology database worldwide. In addition, these cell lines have been intensely investigated, providing a unique platform for hypothesis-driven research focused on enhancing our understanding of tumor biology. Here, we report a comprehensive analysis of coding variants in the NCI-60 panel of cell lines identified by whole exome sequencing, providing a list of possible cancer specific variants for the community. Furthermore, we identify pharmacogenomic correlations between specific variants in genes such as TP53, BRAF, ERBBs, and ATAD5 and anticancer agents such as nutlin, vemurafenib, erlotinib, and bleomycin showing one of many ways the data could be used to validate and generate novel hypotheses for further investigation. As new cancer genes are identified through large-scale sequencing studies, the data presented here for the NCI-60 will be an invaluable resource for identifying cell lines with mutations in such genes for hypothesis-driven research. To enhance the utility of the data for the greater research community, the genomic variants are freely available in different formats and from multiple sources including the CellMiner and Ingenuity websites. Cancer Res; 73(14); 4372–82. ©2013 AACR.

Identification of Protein Tyrosine Phosphatase (PTP) substrates is critical in understanding cellular role in normal cells as well as cancer cells. We have previously shown that reduction of PTPL1 protein levels in Ewings sarcoma (ES) inhibit cell growth and tumorigenesis. Therefore, we sought to identify novel PTPL1 substrates that may be important for tumorigenesis. In this current work, we demonstrated that mouse embryonic fibroblasts without PTPL1 catalytic activity fail to form foci when transfected with oncogenes. We proved that catalytic activity of PTPL1 is important for ES cell growth. Using a substrate-trapping mutant of PTPL1 we identified putative PTPL1 substrates by mass-spectrometry. One of these putative substrates was characterized as Valosin Containing Protein (VCP/p97). Using multiple biochemical assays we validated VCP as a novel substrate of PTPL1. We also provide evidence that tyrosine phosphorylation of VCP might be important for its midbody localization during cytokinesis. In conclusion, our work identifies VCP as a new substrate for PTPL1, which may be important in cellular transformation. Our investigation link an oncogenic transcription factor EWS-FLI1, with a key transcriptional target protein tyrosine phosphatase PTPL1, and its substrate VCP. Given our observation that PTPL1 catalytic activity is important for cell transformation, our results may also suggest that VCP regulation by PTPL1 might be important for tumorigenesis.

Patient-Derived Xenografts (PDX) are powerful models to study tumors' drug-response in the context of personalized medicine. In the PDX model settings, by virtue of expanding the patient's tumor sample, testing multiple drug or drug-combinations can be executed rapidly and has no ethical limitations. However, there are major issues around standards that need to be addressed to make these models widely accessible and usable. The overarching goal of the PDXNet is to coordinate the development of appropriate PDX models and methods for preclinical drug testing to advance CTEP clinical development of new cancer agents. In an effort to standardize protocols for PDX generation as well as data analysis and metadata harmonization, we are building a data storage, sharing, and analysis platform that harmonizes PDXNet data with other large datasets and analysis workflows. The PDX Data Commons is built on top of existing NCI resources, leveraging the Cancer Genomics Cloud maintained by Seven Bridges Genomics, where PDXNet data is co-located with TCGA and other large-scale datasets. The PDCCC is co-led by experts from The Jackson Laboratory, providing scientific leadership in xenograft methods and cancer biology to ensure the promulgation of standards that are well-suited for the PDX community. In addition, the PDCCC is responsible for establishing studies to identify best-practices for PDX data analysis and metadata schemas. The data collected as part of the PDXNet is currently stored on the PDXNet portal that has a query interface for identifying models for pre-clinical trials. Simultaneously, we administer training activities and research pilots to build synergies within the PDXNet, enhancing the ability of the PDXNet to develop clinical trials from PDX studies. In PDXNet, besides the PDCCC, there are 4 PDX Development and Trial Centers (PDTCs) responsible for executing specific pre-clinical trials focused around cancer types including breast cancer, melanoma, and lung cancer. Data generated by the PDTCs will be hosted by the PDCCC, and metadata will be collected based on schemas developed by the network for systematic ontological analysis. These PDX models, in coordination with the NCI Patient-Derived Models Repository (PDMR) at the Frederick National Laboratory for Cancer Research (FNLCR) will be shared with the broader community. In addition, PDTC's will collaborate with non-PDXNet investigators for PDX studies through an administrative supplement program supported by the NCI. The PDXNet is a strong step toward building a consensus around PDX models, so that the power for discovery can be expanded by making multi-institutional PDX cohorts a reality. The PDCCC is a central part of this process to systematically capture and analyze the variables most influential to PDX models and share protocols and tools to make PDXs an interchangeable research currency for pre-clinical discovery. Citation Format: Anurag Sethi, Anuj Srivastava, Xingyi Woo, Vishal Sarsani, Ziming Zhao, Javad Noorbakhsh, Christian French, Jack DiGiovanna, Ogan D. Abaan, Steve Neuhauser, Peter Robinson, Yvonne A. Evrard, Carol J. Bult, Jeffrey A. Moscow, Brandi Davis-Dusenbery, Jeffrey H. Chuang. The PDX Data Commons and Coordinating Center (PDCCC) for PDXNet [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 1029.

Many sarcomas and leukemias carry nonrandom chromosomal translocations encoding tumor-specific mutant fusion transcription factors that are essential to their molecular pathogenesis. Ewing's sarcoma family tumors (ESFTs) contain a characteristic t(11;22) translocation leading to expression of the oncogenic fusion protein EWS-FLI1. EWS-FLI1 is a disordered protein that precludes standard structure-based small-molecule inhibitor design. EWS-FLI1 binding to RNA helicase A (RHA) is important for its oncogenic function. We therefore used surface plasmon resonance screening to identify compounds that bind EWS-FLI1 and might block its interaction with RHA. YK-4-279, a derivative of the lead compound from the screen, blocks RHA binding to EWS-FLI1, induces apoptosis in ESFT cells and reduces the growth of ESFT orthotopic xenografts. These findings provide proof of principle that inhibiting the interaction of mutant cancer-specific transcription factors with the normal cellular binding partners required for their oncogenic activity provides a promising strategy for the development of uniquely effective, tumor-specific anticancer agents.

Protein tyrosine phosphatase, PTPL1, (also known as PTPN13, FAP-1, PTP-BAS, PTP1E) is a non-receptor type PTP and, at 270 kDa, is the largest phosphatase within this group. In addition to the well-conserved PTP domain, PTPL1 contains at least 7 putative macromolecular interaction domains. This structural complexity indicates that PTPL1 may modulate diverse cellular functions, perhaps exerting both positive and negative effects. In accordance with this idea, while certain studies suggest that PTPL1 can act as a tumor-promoting gene other experimental studies have suggested that PTPL1 may function as a tumor suppressor. The role of PTPL1 in the cancer cell is therefore likely to be both complex and context dependent with possible roles including the modulation of growth, stress-response, and cytoskeletal remodeling pathways. Understanding the nature of molecular complexes containing PTPL1, its interaction partners, substrates, regulation and subcellular localization are key to unraveling the complex personality of this protein phosphatase.

To understand the genetic mechanisms driving variant and IGHV4-34-expressing hairy-cell leukemias, we performed whole-exome sequencing of leukemia samples from ten affected individuals, including six with matched normal samples. We identified activating mutations in the MAP2K1 gene (encoding MEK1) in 5 of these 10 samples and in 10 of 21 samples in a validation set (overall frequency of 15/31), suggesting potential new strategies for treating individuals with these diseases.

Tyrosyl-DNA-phosphodiesterase 1 (TDP1) repairs 3′-blocking DNA lesions by catalytically hydrolyzing the tyrosyl-DNA-phosphodiester bond of trapped topoisomerase I (Top1) cleavage complexes (Top1cc). It also removes 3′-blocking residues derived from oxidative damage or incorporation of chain terminating anticancer and antiviral nucleosides. Thus, TDP1 is regarded as a determinant of resistance to Top1 inhibitors and chain terminating nucleosides, and possibly of genomic stability. In the 60 cell lines of the NCI Developmental Therapeutic Anticancer Screen (the NCI-60), whose whole genome transcriptome and mutations have recently been characterized, we discovered two human lung cancer cell lines deficient for TDP1 (NCI_H522 and HOP_62). HOP_62 shows undetectable TDP1 mRNA and NCI_H522 bears a homozygous deleterious mutation of TDP1 at a highly conserved amino acid residue (K292E). Absence of TDP1 protein and lack of TDP1 catalytic activity were demonstrated in cell lysates from both cell lines. Lack of TDP1 expression in HOP_62 was shown to be due to TDP1 promoter hypermethylation. Our study provides insights into the possible inactivation of TDP1 in cancers and its relationship to cellular response to Top1-targeted drugs. It also reveals two TDP1 knockout lung cancer cell lines for further TDP1 functional analyses.

The unlimited proliferative capacity of cancer cells is closely linked to maintenance of their telomeres, which shorten with each cell division in normal cells. Cancer cells are able to maintain telomere length by multiple mechanisms, including activation of telomerase and the recombination based alternative lengthening of telomeres (ALT) pathway. ALT is prevalent in osteosarcoma, with approximately 50% of osteosarcoma cases using ALT for telomere maintenance. Mutations in the ATRX/DAXX chromatin remodeling complex and histone H3.3 correlate with activation of the ALT pathway in several tumor systems. While loss of ATRX is a frequent event in osteosarcoma tumors, alterations of DAXX have not been reported. We characterized the telomere maintenance mechanisms utilized by 11 osteosarcoma cell lines. Of these, 45% (5/11) were ALT positive and 45% (5/11) were telomerase positive. One cell line possessed features of both telomere maintenance mechanisms. Among ALT positive osteosarcoma cell lines, we observed frequent loss of ATRX expression (4/5) and a previously unreported translocation resulting in disruption of DAXX. The translocation abolishes recruitment of DAXX to nuclear PML bodies and prevents normal DAXX function. By reintroducing full length DAXX, we were able to suppress telomere maintenance by ALT as evidenced by multiple assays including loss of C-circles and ALT-associated PML bodies, thus demonstrating that continued DAXX deficiency is necessary for maintenance of the ALT mechanism. Suppression of ALT by DAXX reintroduction did not result in compensatory activation of telomerase. This first demonstration of ALT suppression by DAXX supports a mechanistic connection between loss of the ATRX/DAXX chromatin remodeling complex and telomere maintenance by ALT. Understanding this relationship may uncover vulnerabilities specific to ALT tumors that could potentially lead to the development of targeted therapies for diverse cancers that depend on the ALT pathway. Citation Format: Kathryn E. Driest, Joshua J. Waterfall, Robert L. Walker, Marbin A. Pineda, Ogan Abaan, Yuelin J. Zhu, Yonghong Wang, Corbin D. Ester, Sean R. Davis, Sven Bilke, Paul S. Meltzer. Reintroduction of DAXX suppresses alternative lengthening of telomeres in osteosarcoma. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2717.

CHEK2 encodes a serine/threonine kinase (Chk2) activated by ATM in response to DNA double-strand breaks. On the one hand, CHEK2 has been described as a tumor suppressor with proapoptotic, cell-cycle checkpoint and mitotic functions. On the other hand, Chk2 is also commonly activated (phosphorylated at T68) in cancers and precancerous lesions. Here, we report an extensive characterization of CHEK2 across the panel of 60 established cancer cell lines from the NCI Anticancer Screen (the NCI-60) using genomic and proteomic analyses, including exon-specific mRNA expression, DNA copy-number variation (CNV) by aCGH, exome sequencing, as well as western blot analyses for total and activated (pT68-Chk2) Chk2. We show that the high heterogeneity of Chk2 levels in cancer cells is primarily due to its inactivation (owing to low gene expression, alternative splicing, point mutations, copy-number alterations and premature truncation) or reduction of protein levels. Moreover, we observe that a significant percentage of cancer cells (12% of the NCI-60 and HeLa cells) show high endogenous Chk2 activation, which is always associated with p53 inactivation, and which is accompanied by downregulation of the Fanconi anemia and homologous recombination pathways. We also report the presence of activated Chk2 (pT68-Chk2) along with histone γ-H2AX in centrosomes.

Our understanding of the genetic basis for cancer is advancing at a rapid rate due to the application of next generation sequencing (NGS) technologies. It is becoming common to sequence tumors and patients in an attempt to find actionable mutations that could offer the patient a more targeted and effective treatment. However, the genomics of cancer is very complex and only a handful of actionable mutations have been characterized. Larger-scale studies are needed to understand the pathogenic spectrum of cancer variants and deliver reliable clinical decision-making support to providers. Several large-scale sequencing projects are underway to collect NGS data on tumors (e.g. TCGA, ICGC, and TARGET) but a national platform for analysis, interpretation, and reporting does not exist. We propose that a consolidated informatics platform for the collection of outcomes data with genomics and clinical data would accelerate research and provide patients with the opportunity for personalized cancer treatment. In addition, with 1,665,540 new cancer cases predicted in the US for 2014, a national-scale genomics platform is needed, capable of sequencing 3 million genomes per year, storing exabytes of data, while supporting over 20,000 oncologists, researchers, and analysts. At Lockheed Martin, we deliver highly scalable and reliable information systems for a variety of missions and citizen services. Here, we will present our vision for a national cancer genomics platform to include NGS data collection, cost-efficient storage, scalable and modular processing pipelines, and collaborative analytics and data sharing capabilities, within a compliant privacy and security framework. In conclusion, by leveraging the scale of clinical cancer sequencing and capturing these data into a case management system for translational research, this platform provides data at-scale needed for finding actionable mutations, designing effective treatments and implementing prevention strategies, faster. Citation Format: Ogan Abaan, Amrita Basu, Noah Brown, Bret Light, David Deal, Michael Hultner. A population-based approach to address clinical cancer care: The national genomics platform. [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 4743. doi:10.1158/1538-7445.AM2015-4743

RNA helicase A (RHA), a member of the DEXH box helicase family of proteins, is an integral component of protein complexes that regulate transcription and splicing. The EWS-FLI1 oncoprotein is expressed as a result of the chromosomal translocation t(11;22) that occurs in patients with the Ewing's sarcoma family of tumors (ESFT). Using phage display library screening, we identified an EWS-FLI1 binding peptide containing homology to RHA. ESFT cell lines and patient tumors highly expressed RHA. GST pull-down and ELISA assays showed that EWS-FLI1 specifically bound RHA fragment amino acids 630 to 1020, which contains the peptide region discovered by phage display. Endogenous RHA was identified in a protein complex with EWS-FLI1 in ESFT cell lines. Chromatin immunoprecipitation experiments showed both EWS-FLI1 and RHA bound to EWS-FLI1 target gene promoters. RHA stimulated the transcriptional activity of EWS-FLI1 regulated promoters, including Id2, in ESFT cells. In addition, RHA expression in mouse embryonic fibroblast cells stably transfected with EWS-FLI1 enhanced the anchorage-independent phenotype above that with EWS-FLI1 alone. These results suggest that RHA interacts with EWS-FLI1 as a transcriptional cofactor to enhance its function. (Cancer Res 2006; 66(11): 5574-81)

Ewing's Sarcoma family tumors (ESFT) are characterized by a translocation t(11:22) forming an aberrant transcription factor EWS-FLI1. Protein tyrosine phosphatase L1 (PTPL1) was identified as a gene upregulated by EWS-FLI1 in transfected cells by microarray. Our results show that PTPL1 is a transcriptional target of EWS-FLI1 both by chromatin immunoprecipitation and promoter activation studies. We demonstrate that PTPL1 is highly expressed in ESFT cells and patient tumors compared with normal tissues, with a trend towards higher expression in metastatic versus primary tumors. Reduction of PTPL1 protein in ESFT cells correlated with a significant reduction in both monolayer and soft-agar cell growth. In addition, these PTPL1-reduced cells were more sensitive to etoposide-induced apoptosis than the controls. We therefore report a novel transcriptional activation of a phosphatase involved in the oncogenesis of ESFT. Increasing interest in specific phosphatase inhibitors would allow PTPL1 to be evaluated as a therapeutic target in ESFT.

Telomeres play an essential role in maintaining the fidelity of chromosome ends during replication, but without an active telomere maintenance mechanism, their length decreases with each successive cell division. Aberrant telomere biology is a critical component of tumorigenesis. Replicative immortality is a hallmark of cancer and tumor cells circumvent cellular crisis associated with telomere shortening via two main mechanisms, activation of telomerase or the alternative lengthening of telomeres process (ALT). Targeted-resequencing, such as whole exome sequencing (WES), is becoming a tool for molecular diagnostics and gene discovery. While WES contains mostly data from the targeted region, a significant amount of off-target reads are not utilized for analysis. These off-target sequences likely contain additional information from the patients' genome that may be analyzed as well. Telomeric repeats, in general, are not targeted in WES, however due to their high abundance, they are present in the off-target fraction. We developed an algorithm that can estimate relative telomere length (RTL) using off-target reads from targeted-resequencing data. For proof-of-principle, we used the WES data for 14 osteosarcoma cell lines. RTL values calculated demonstrate correlations between lower RTL values in samples with hTERT expression and higher values in ALT positive cell lines, consistent with the known association of ALT and longer telomeres. In order to validate the algorithm's robustness, we evaluated published WES data for the NCI-60 panel of cell lines. The results suggest that most cells display the classic telomere shortening, while a few cell lines, such as LOX-IMVI, have long telomeres. These results will be compared to alternative techniques for measuring telomere length. In summary, we believe that this approach will enable utilization of otherwise overlooked off-target data generated by targeted-resequencing based molecular diagnostic tests. Citation Format: Ogan D. Abaan, Joshua Waterfall, Sean Davis, Daniel Edelman, Allison Gomez, Sharon Savage, Yves Pommier, Paul Meltzer. Harvesting knowledge from unexploited genomic data: Estimating relative telomere length from targeted-resequencing. [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 4167. doi:10.1158/1538-7445.AM2014-4167

High-throughput data is increasingly being integrated into the fields of biology, molecular biology, and pharmacology. However, a difficult problem has been the rapid and fluid access to and integration of the data, which tends to reside in huge unwieldy databases. One set of cell lines with substantial potential for benefit from this type of access and integration is the NCI-60 cancerous cell lines. We present here a set of tools within our CellMiner web-application designed to address this need for the areas of transcript expression, microRNA expression, gene DNA copy number, variant status, and drug activity. CellMiner allows the user to rapidly access data for relative levels of transcript expression for 26,065 genes, 360 microRNAs, and 20,602 compounds including 102 Food and Drug Administration (FDA)-approved drugs. These levels in turn create patterns across the NCI-60 that can be compared to one another using our “pattern match” tool. Together, these tools allow one to query the data for potential relationships between these parameters, in a manner specific to a users area of expertise and interest, in a rapid and flexible manner without the need for expertise in computer science or bioinformatics. Comparisons of transcript/drug will be demonstrated with SLFN11/topotecan; variant/drug with BRAF V600E/vemurafinib; colon tissue-of origin specific genes with TRIM15, RNF43, and VIL1; and DNA copy number change with CDKN2A (p16). The data are publicly available at http://discover.nci.nih.gov/cellminer. Citation Format: William C. Reinhold, Margot Sunshine, Sudir Varma, Hongfang Liu, Ogan Abaan, Paul Meltzer, Joel Morris, Kurt Kohn, James Doroshow, Yves Pommier. Web-based access using CellMiner for gene expression, DNA copy number, microRNA transcript levels, variant status, drug activity, and their pattern comparisons for the NCI-60. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3177. doi:10.1158/1538-7445.AM2013-3177

Understanding of how cancer initiates and progresses is a fundamental goal of cancer research. Identification of cancer mutations is of profound importance for both understanding of the disease and for developing novel therapies. Soft-tissue sarcomas include multiple uncommon histotypes with features of diverse connective tissue lineages. Although some of their underlying genetic changes have been elucidated, for example in those types which contain etiologic chromosome translocations, in general, the genetic basis of these tumors is incompletely described. To investigate mutations in 8 subtypes of adult soft tissue sarcomas, we resequenced coding exons from about 1300 cancer relevant genes in 66 tumor samples. Data was analyzed for somatic variants in samples with matched normals while samples without normal were analyzed individually. The most frequent events were TP53 mutations (26%) followed by RB1 (9%) and APC (8%) mutations. Even though, well-defined oncogene activating mutations were present, they were very rare. Given the prevalence of tumor suppressor mutations in these samples we are currently integrating CGH results to look for chromosomal deletions to support loss of tumor suppressor genes. In addition, we are investigating low-frequency mutations in lesser-known genes that may be of potential interest. Our preliminary results suggest that these subtypes of soft-tissue sarcomas depend on tumor-suppressor loss predominantly, and may have gained multiple complex sets of mutations in a number of other pathways. In conclusion, our work will be important in cataloging novel cancer mutations in rare types of adult sarcomas, with potential implications for understanding their biology and the development of new therapies. Citation Format: Ogan D. Abaan, Princy Francis, Marbin Pineda, Robert L. Walker, Yuelin J. Zhu, Sven Bilke, Sean R. Davis, Paul S. Meltzer. Cancer-specific mutations in adult soft tissue sarcomas. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3147. doi:10.1158/1538-7445.AM2013-3147

Acquired and constitutional genetic variations in cancers have a substantial influence on response to therapy. The NCI60 panel of cell lines provides a unique opportunity to investigate this problem. These 60 human tumor cell lines represent 9 cancer types, and are richly characterized as the result of many previous studies which have collected various biochemical and genomics data [1]. In addition, there exists a comprehensive dataset of sensitivity and resistance profiles of over 100,000 compounds with potential antineoplastic activity. However, characterization of coding region DNA sequence variants has been lacking. In this study, we sequenced the whole exomes of the NCI60 cell lines and identified single nucleotide variants and short insertions/deletions. Variants found by sequencing were in excellent agreement with variants previously identified by SNP analysis or targeted capillary sequencing. Even though most cell lines displayed similar mutation counts, cell lines with microsatellite instability displayed a hypermutator phenotype. In addition, observation from ti/tv ratio and nature of base changes revealed preservation of possible carcinogen specific DNA mutation signatures. Deleterious variants were identified at higher frequency in known cancer genes while TP53 mutations where the most frequent event among the NCI60. Finally, notable instances of correlation between gene/pathway mutations with sensitivity to certain drug/compounds was identified. For example, sensitivity to vemurafenib was highly correlated with BRAF mutation. This comprehensive dataset enhances the value of cell lines widely used as disease models in many laboratories by adding depth to the existing genomic data. Our analysis identifies a large number of genomic variants correlated with drug responsiveness, including a number of genes known to be targeted by specific agents as well as numerous candidates for future investigation. 1. Shankavaram, U.T., et al., CellMiner: a relational database and query tool for the NCI-60 cancer cell lines. BMC Genomics, 2009. 10: p. 277. 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 1879. doi:1538-7445.AM2012-1879

Osteosarcoma is an aggressive cancer of bone, which typically occurs during adolescence. The genetic hallmark of osteosarcoma is the presence of extensive and complex genomic rearrangements. However, few consistent aberrations have been identified, hampering the development of targeted therapy for osteosarcoma. Next generation RNA-sequencing (RNA-seq) is a powerful tool for comprehensive characterization of whole transcriptome, with the unique ability of identifying novel fusion genes. We applied paired-end RNA-seq to explore the transcriptome of 16 human OS cell lines and primary osteoblasts from two healthy individuals. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for each sample. Several thousand SNVs (single nucleotide variants) that have not been reported in the dbSNP database were identified. Bioinformatic analysis identified several fusion genes (e.g. PAFAH1B2-FOXR1and FAM119B-TSFM), which involved both known cancer related genes as well as genes previously unrelated to cancer. Fusion transcripts were validated using RT-PCR, Western blot and capillary sequencing. These rearrangements tended to occur at copy number transitions on the partner chromosome regions. Our findings have the potential to provide important insights into osteosarcoma biology, and potential translational applications for diagnostic and therapeutic development. 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 5070. doi:1538-7445.AM2012-5070

CHEK2 codes for a serine/threonine kinase (Chk2) activated by ATM in response to DNA double-strand breaks (DSB). CHEK2 has been described as a tumor suppressor with pro-apoptotic, cell cycle checkpoint and mitotic functions. However, Chk2 is also commonly activated (phosphorylated at T68) in cancers and precancerous lesions. In the present report, we characterized CHEK2 across the panel of 60 established cancer cell lines from the NCI Anticancer Tumor Cell Line panel (the NCI-60) using genomic and proteomic analyses including exon-specific mRNA expression, DNA copy number variation (CNV) by aCGH, exome sequencing, as well as Western blotting analyses for total and activated (pT68-Chk2) Chk2. We demonstrate that the high heterogeneity of Chk2 levels in the NCI-60 is primarily due to its inactivation (owing to low gene expression, alternative splicing, point mutations, copy number alterations and premature truncation) or reduction of protein levels. Notably, we also found that a significant percentage of cancer cells (12% of the NCI-60 and the HeLa cervix cell line) display high endogenous Chk2 activation, always associated with p53 loss of function. Notably, all the 12 cancer cell lines characterized as being p53 wild-type showed almost undetectable levels of pT68-Chk2. The potential impact of endogenous Chk2 activation was analyzed by transcriptome profiling of the five highest pT68-Chk2 cell lines, comparing them with five, tissue-matched low pT68-Chk2 and p53-matched deficient cell lines. Two-sided t tests revealed 176 genes differentially expressed with statistical significance (P < 0.01, uncorrected) in the two groups (high vs. low pT68-Chk2). Among the downregulated expressed genes, a significant number codes for proteins involved in DNA recombination, replication and repair (FANCA, FANCG, FANCL, BRCA2, RAD51C, EME1, and RECQL5 being the most relevant), and centromere organization. Several of these downregulated genes were parts of the Fanconi Anemia pathway or related to homologous recombination (HR, P < 0.05 for statistically significant enrichment using Ingenuity Pathway Analysis®). In conclusion, the biology of Chk2 remains complex, multifaceted and fast evolving. Our study provides information on the relationship between different genomic and proteomic parameters related to Chk2 in cancer, and suggests a possible role for activated Chk2 in p53-deficient or HR/Fanconi Anemia-deficient cells. 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 2116. doi:1538-7445.AM2012-2116

Osteosarcomas are rare but aggressive tumors that predominantly affect adolescents. These neoplasms of mesenchymal origin are biologically heterogeneous and produce immature osteoid or bone. The pathogenesis of osteosarcomas is poorly understood although defective osteogenic differentiation seems to play a key role. In order to elucidate the underlying molecular mechanisms, 16 osteosarcoma cell lines, 2 osteoblast cell lines and 45 osteosarcoma tumors were studied using a combination of high-throughput techniques such as microRNA (miRNA) and gene expression profiling, miRNA sequencing and array comparative genomic hybridization. Overexpression of the miRNA clusters miR-23a∼27a∼24-2 (19p13.13) and miR-23b∼27b∼24-1 (9q22.32) was identified in a subset of the osteosarcoma tumors and cell lines. Furthermore, quantitative RT-PCR revealed that the miR-23a and miR-23b clusters were downregulated during osteoblast differentiation of the osteosarcoma cell line HOS and overexpression of these miRNAs (by transient transfection of miRNA mimics) delayed osteoblast differentiation and matrix mineralization evaluated by alkaline phosphatase and Alizarin Red staining. Target gene identification experiments were then performed for each of the members of the miR-23a and miR-23b clusters. Gain of function (using miRNA mimics for exogenous expression) and loss of function (using antisense miRNAs to inhibit endogenous expression) experiments followed by downstream gene expression analysis identified several putative targets in osteosarcoma cell lines HOS and HuO3N1. The gene lists were highly enriched in targets (including differentiation genes) identified by TargetScan and other target prediction software. These results suggest that deregulation of the miR-23∼27∼24 clusters may play a role in defective osteogenic differentiation and osteosarcoma. 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 1113. doi:1538-7445.AM2012-1113

Understanding of the genetic basis of cancer initiation and progression is a fundamental goal of cancer research. Identification of cancer variants is of profound importance for both understanding disease mechanism and for developing novel therapies. Soft-tissue sarcomas are multiple uncommon histotypes with features of diverse connective tissue lineages. Although some of their underlying genetic changes have been elucidated, for example in those types which contain etiologic chromosome translocations, in general, the genetics of these tumors is incompletely described. Adult soft tissue sarcomas often exhibit highly complex genomic rearrangements. To search for novel variants in these tumors, we utilized a custom “targeted-resequencing” approach to sequence coding exons from over 1300 known cancer-related genes and candidate gene families in 65 soft-tissue sarcoma patient samples covering several subtypes and their matching normal tissues where available. We used the previously published method of “In-solution capture” to enrich for regions of interest and sequenced both the normals and the tumors using the Illumina GAII platform. The variant calls reveal the distribution of mutations affecting the exons of the targeted regions across histotypes, and reveal the role of critical functional pathways in sarcoma genesis. Preliminary data suggest that TP53 single nucleotide variants are mostly confined to one histotype. This work is an important step in cataloging novel cancer mutations in these cancers, with potential implications for understanding their biology and the development of new therapies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3934. doi:10.1158/1538-7445.AM2011-3934

Somatic mutations are one of the major factors contributing to oncogenesis and tumor progression. Second generation sequencing allows rapid generation of several giga-bases of sequence, enabling genome-wide mutation discovery in individual samples. This is particularly effective when used with genome partitioning strategies. The biological significance of mutations may be assessed by their prevalence at the gene or pathway level and by their functional implications, requiring larger sample cohorts. Adding sequence barcodes to discriminate individual identity allows pooling of sample sets larger than those described by current Illumina protocols which are relatively complex and currently offer only up to 12 barcodes. We report a novel barcoding protocol for Illumina GA2-x sequencers, which permits multiplexing up to 2048 samples per flow-cell. Reducing hands-on time in the protocol was one major goal in designing the protocol. Throughput has been increased by up to ten-fold compared to Illumina protocols. This improvement was achieved by eliminating several enzymatic steps and gel purification/size selection and replacing those with two consecutive PCR steps. Instead of enzymatically ligating of the bar-code, our protocol incorporates barcode, sequencing and flow cell binding sites into the DNA product through a universal set of oligo primers, independent of target selection. Additionally, the PCR based protocol utilized the Fluidigm Biomark system for parallel processing allowing the processing of 317 amplimers x 48 samples in parallel. “Cross-talk” between samples and loss of usable sequences induced by read-errors in the bar-code is a major concern in multiplexed experiments. In order to minimize such effects, we introduced an error correcting 8nt DNA code using concepts from computer science. The double 8,4 Hamming code utilized guarantees error correction of read errors affecting up to 2nt, thereby boosting the number of usable codes. Additionally, error detection of read errors affecting up to 4nt minimize cross-talk between multiplexed samples. The protocol has been validated in a 48-way multiplexed experiment demonstrating the viability of the more automated, less laborious library preparation. Error detection and correction was highly effective with the number of reads mapped to a valid bar-codes could be increased by15-20% on average. In one particularly difficult barcode, almost 60% of reads were rescued by error correction. In summary, the protocol presented here extends the use of Illumina GA2 sequencers for mutation screening in cohorts of up to 2048 samples per experiment for a small set of target genes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2186.

Understanding of how cancer initiates and progresses is the fundamental of cancer research. Identification of cancer mutations is of profound importance for both understanding of the disease and for developing novel therapies. To search novel cancer mutations, we have utilized a “targeted resequencing” approach to resequence coding exons from about 1300 genes in a panel of various sarcoma patient samples. We used the previously published method of “In-solution capture” to enrich for regions of interest and resequenced the enriched population on an Illumina GAII platform using single-ended or paired ended reads. The performance and depth of the enrichment and resequencing was adequate for variant calling. We obtained roughly 70% on genome reads and about 30% of the reads fall on target while about 40% of the reads fall on target±500bp. An in house variant calling script was used for SNP/variant calling. Each sample yielded multiple genes with novel variations some of which are either missense or nonsense and in a highly conserved residue that were also previously identified in other cancers as well. Preliminary results from samples resequenced so far demonstrate that these sarcoma samples have variations in a variety of genes with diverse functions, including but not limited to signaling pathway intermediates. In conclusion, our work will be important in cataloging novel cancer mutations in rare sarcomas, with potential implications for understanding their biology and the development of new therapies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2213.