Whole-exome Sequencing Platform Research Articles

Abstract 4272: Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model

Abstract Subpopulations of tumor cells characterized by mutation profiles may confer differential fitness and consequently influence the prognosis of cancers. Understanding subclonal architecture has the potential to provide biological insight in tumor evolution and advance cancer precision treatment. Recent subclonal reconstruction methods require heavy computational resources, prior knowledge of the number of subclones, and extensive postprocessing. These drawbacks can be addressed by using a regularized likelihood modeling approach, which is novel to the field. Therefore, we propose a model-based method, Clonal structure identification through pair-wise Penalization, or CliP, to address these drawbacks. To evaluate the performance of CliP against other methods, we generated a benchmark dataset of 4,050 simulated samples with varied tumor purity, read depth, copy number alteration rate, and true numbers of clusters. Our results suggest that CliP outperforms popular methods such as PhyloWGS in accuracy and shows similar robustness in most scenarios. We further compared CliP performance against 10 other subclonal reconstruction methods to the consensus subclonal reconstruction results on whole-genome sequencing (WGS) data from the Pan-Cancer Analysis of Whole Genomes (PCAWG, n = 1,993). Our result shows that of all 11 methods, CliP achieves the highest correlation with the consensus calls. In terms of speed, CliP can finish running a sample with 5,000 SNVs within one minute, which is ~1,000 times faster than MCMC-based algorithms. Next, we profiled the subclonal structures of 7,711 patient samples with well-annotated clinical outcomes from The Cancer Genome Atlas (TCGA) across 32 cancer types applying CliP to the whole-exome sequencing (WES) data. This is the largest and most complete pan-cancer characterization of intratumor heterogeneity (ITH) through the lens of subclonal reconstruction. We further used CliP outputs to address a commonly asked question on which sequencing platform to use for cancer evolution studies: the cost-effect WES data at higher read depth versus the more comprehensive WGS data at lower read depth. There were a total of 588 tumor samples from 21 cancer types, for which both PCAWG and TCGA have profiled using the WGS and WES platform, respectively. Using both datasets to compare results from these samples as benchmark, we observed that for most cancer types, subclonal reconstruction from WES is as informative as that from the matched WGS data. In summary, our study represents a significant methodological advancement in subclonal reconstruction and highlights the importance of measuring tumor subclone structure. Citation Format: Yujie Jiang, Kaixian Yu, Matthew D. Montierth, Shuangxi Ji, Seung Jun Shin, Shuai Guo, Shaolong Cao, Yuxin Tang, Scott Kopetz, Pavlos Msaouel, Jennifer R. Wang, Marek Kimmel, Peter Van Loo, Hongtu Zhu, Wenyi Wang. Pan-cancer analysis of intra-tumor heterogeneity in 9,116 cancers using a novel regularized likelihood model. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4272.

Analytical Performance of NGS-Based Molecular Genetic Tests Used in the Diagnostic Workflow of Pheochromocytoma/Paraganglioma.

Simple SummaryThe escalating use of Next Generation Sequencing in the routine clinical setting greatly facilitates the genetic diagnosis of hereditary cancer syndromes. However, these novel methods pose new and unique challenges. In our study we sought to demonstrate the evolution of these techniques, especially whole exome sequencing and targeted panel sequencing. This study highlights the multi-layered workflow and how each step affects the diagnostic outcome and demonstrates the effectiveness of an in-house developed targeted panel sequencing for hereditary endocrine tumor syndromes.Next Generation Sequencing (NGS)-based methods are high-throughput and cost-effective molecular genetic diagnostic tools. Targeted gene panel and whole exome sequencing (WES) are applied in clinical practice for assessing mutations of pheochromocytoma/paraganglioma (PPGL) associated genes, but the best strategy is debated. Germline mutations of at the least 18 PPGL genes are present in approximately 20–40% of patients, thus molecular genetic testing is recommended in all cases. We aimed to evaluate the analytical and clinical performances of NGS methods for mutation detection of PPGL-associated genes. WES (three different library preparation and bioinformatics workflows) and an in-house, hybridization based gene panel (endocrine-onco-gene-panel- ENDOGENE) was evaluated on 37 (20 WES and 17 ENDOGENE) samples with known variants. After optimization of the bioinformatic workflow, 61 additional samples were tested prospectively. All clinically relevant variants were validated with Sanger sequencing. Target capture of PPGL genes differed markedly between WES platforms and genes tested. All known variants were correctly identified by all methods, but methods of library preparations, sequencing platforms and bioinformatical settings significantly affected the diagnostic accuracy. The ENDOGENE panel identified several pathogenic mutations and unusual genotype–phenotype associations suggesting that the whole panel should be used for identification of genetic susceptibility of PPGL.

Improved Clinical Assessment of Myeloid Malignancies By Transcriptome Profiling

Clinical genetic testing for myeloid malignancies including acute myeloid leukemia (AML) and myelodysplatic syndromes (MDS) currently relies on cytogenetic assays and targeted sequencing of clinically relevant genes. As more genes with diagnostic and prognostic relevance to these diseases are discovered, traditional testing methods will not be able to scale to effectively meet clinical needs. Next-generation sequencing platforms offer a potential way around this bottle-neck, but the analytic and clinical validity of these methods must be firmly established. To determine whether RNA-Seq, whole-genome sequencing (WGS), or whole-exome sequencing (WES) could meet or exceed the current clinical standard of care, we used these platforms to study retrospective and prospective cohorts of patients with myeloid malignancies.From a retrospective cohort of 176 patients, we generated RNA-Seq, WES, WGS libraries (176, 92, and 18, respectively). The patient cohort spanned a broad range of myeloid malignancies, including AML, MDS, and therapy-related AML and MDS. We observed that, for similar sequencing efforts, RNA-Seq libraries provided the highest coverage depth over clinically relevant genes, while WGS and WES platforms suffered from recurrent coverage dropouts, particularly in the GC-rich CEBPA gene (median coverage depths of 406x, 115x, and 33x for RNA-Seq, WES, and WGS libraries). We used de novo assembly to assess gene fusions from the RNA-Seq libraries, and demonstrated that all gene fusions previously detected by karyotyping were detectable (41 distinct patients, including 13 inv(16), 9 t(15;17), 8 t(8;21), 3 t(9;11), and 2 t(9;11)). Additionally, we identified five patients with novel rearrangements in the MLL gene family, with potential therapy-altering relevance. We observed complete sensitivity (30 cases) for FLT3 -ITD detection, and detected nine novel low-frequency events undetectable by the previous assay, which were validated using a targeted sequencing panel. We generated SNV and short indel calls for all platforms, and observed that most variants were concordant between platforms (2,079 matched variants aross 92 patients for the RNA-Seq/WES comparison). Missed variant calls (102) in WES libraries were generally due to poor sequencing coverage, while missing calls (44) in RNA-Seq libraries were generally due to allele-specific expression. We generated HLA genotypes for all patients using the RNA-Seq patients, and observed near-total concordance with previous clinical results, increasing the clinical utility of RNA-Seq based testing (of 621 called alleles, only two mismatches were observed at two-digit resolution).To determine whether gene expression information could be used to identify distinct risk groups within normal-karyotype AMLs, we performed unsupervised clustering analysis and network-based clustering analysis, identifying distinct clusters using both approaches. We demonstrate distinct co-occurrence of two expression clusters with NPM1 - and FLT3 alterations, and distinct survival outcomes for these novel clusters. Additionally, we observed distinct pathway enrichments associated with these clusters, linking molecular subtypes with gene expression signatures.Altogether, we observed that RNA-Seq offered substantial clinical benefits, due to the ability to recover expressed gene fusions and whole-transcriptome expression information, SNV and short indel variants, and HLA genotype information. Additionally, we observed gene expression heterogeneity which can be used to better stratify intermediate-risk patients. WGS and WES platforms showed recurrent weaknesses in coverage for clinically-relevant genes, and provided less actionable information overall. This work provides crucial analytic validation for the incorporation of RNA-Seq based testing for patients with myeloid malignancies, which may lead to substantial clinical benefits for those patients. DisclosuresNo relevant conflicts of interest to declare.

The Missing "lnc" between Genetics and Cardiac Disease.

Cardiovascular disease (CVD) is one of the biggest threats to public health worldwide. Identifying key genetic contributors to CVD enables clinicians to assess the most effective treatment course and prognosis, as well as potentially inform family members. This often involves either whole exome sequencing (WES) or targeted panel analysis of known pathogenic genes. In the future, tailored or personalized therapeutic strategies may be implemented, such as gene therapy. With the recent revolution in deep sequencing technologies, we know that up to 90% of the human genome is transcribed, despite only 2% of the 6 billion DNA bases coding for proteins. The long non-coding RNA (lncRNA) “genes” make up an important and significant fraction of this “dark matter” of the genome. We highlight how, despite lncRNA genes exceeding that of classical protein-coding genes by number, the “non-coding” human genome is neglected when looking for genetic components of disease. WES platforms and pathogenic gene panels still do not cover even characterized lncRNA genes that are functionally involved in the pathophysiology of CVD. We suggest that the importance of lncRNAs in disease causation and progression be taken as seriously as that of pathogenic protein variants and mutations, and that this is maybe a new area of attention for clinical geneticists.

Burden of copy number alterations predicts outcomes in immune checkpoint blockade treated gastrointestinal cancer patients.

e14068 Background: Despite the great achievements made in immune checkpoint blockade (ICB) in cancer therapy, how to identify patients who may benefit from ICB still remains one of the central questions, especially in gastrointestinal (GI) cancer. Methods: To address this, we analyzed FFPE tumor specimens from 73 patients with metastatic GI cancers who were treated with ICB. All patients were randomly assigned into discovery (60%) and validation (40%) cohorts. Overall, tumor mutation burden (TMB) and copy number alterations (CNAs) were determined by using the whole-exome sequencing platform. FFPE samples of 65 patients were analyzed via a multiplex RNA immune oncology sequencing panel. Results: Here we show that lower burden of copy number alteration (CNA) was observed in responders to immunotherapy in both discovery and validation cohorts. More importantly, lower burden of CNA in GI cancers were associated with improved objective response, clinical benefit and overall survival. Efficacy also correlated with the higher TMB. Of note, a combinatorial biomarker of TMB and burden of CNA may better stratify responders from patients received immunotherapy. In addition, patients with lower burden of CNA revealed increased IFNγ and expanded immune signatures in our GI patient cohort and TCGA cohorts as well. Conclusions: Our results suggest that burden of CNA may expand the predictive and prognostic value of genomic determinants in identifying potential responders with GI cancer to immune checkpoint blockade therapy.

Comprehensive analysis of age-related somatic mutation profiles in Chinese young lung adenocarcinoma patients.

BackgroundLung adenocarcinoma in young adults is a rare entity with the oncogenic genetic alterations associated being poorly understood. In the present study, the effect of genetic alterations in lung adenocarcinoma patients diagnosed in young patients is reported.MethodsTwenty young lung adenocarcinoma patients (age years: median: 33.5, range: 24‐36) were enrolled in the current study and 24 patients who were at common age of the disease onset (age years: median: 61.5, range: 52‐79) were selected for comparison. Paraffin sections of lung adenocarcinoma were analyzed using the whole‐exome sequencing platform.ResultsSimilar number of somatic mutations per tumor were found in the young patients and their older counterparts. Although no age‐related differences were detected in the numbers of lung adenocarcinoma patients harboring well‐known gene variants, mutations in FRG1 and KMT2C were associated with a younger age especially after correcting for tobacco smoking and sex (FRG1: P = 0.027, KMT2C: P = 0.046). Five genetic variants showed higher alteration frequencies in young patients compared to the unclassified East Asian population, suggesting these mutations as disease‐related hereditary germline variants.ConclusionsThese results suggest different characteristics of lung adenocarcinoma between the young and the patients at common age of onset. Young patients with lung adenocarcinoma have a distinctly unique prevalence of oncogenic genetic alterations.

Abstract 5528: Evaluation of tumor mutation burden as a biomarker for immune checkpoint inhibitor efficacy: A calibration study of whole exome sequencing with FoundationOne®

Abstract Background: Tumor mutation burden (TMB) is emerging as a potential predictive biomarker for the efficacy of immune checkpoint inhibitors. TMB has traditionally been evaluated using whole exome sequencing (WES), an established method for analysis of genomic alterations that requires both tumor and germline DNA. In the phase 3 CheckMate 026 study (NCT02041533) of nivolumab vs chemotherapy in first-line non-small cell lung cancer (NSCLC), exploratory analyses were performed to determine the value of TMB as a predictive biomarker in 312 tumor samples using WES. Patients with baseline TMB in the upper tertile were associated with an increased objective response rate to nivolumab and longer median PFS, relative to patients with TMB in the lowest 2 tertiles and compared with chemotherapy-treated patients in the upper tertile (Carbone et al. N Engl J Med. 2017). Increasingly, targeted cancer gene panels, including the FoundationOne® (F1) assay, are being assessed as an alternative to WES for clinical use. To determine the feasibility of transitioning from WES to a potential in vitro diagnostic next-generation sequencing (NGS) platform for TMB analysis, we performed a study comparing values generated by WES with those generated by the F1 assay. Methods: Using the 2 hybridization-capture/NGS methods (WES and F1), TMB was assessed in formalin-fixed, paraffin-embedded NSCLC tumor samples. For WES, coding regions of 21,522 genes were analyzed, with TMB defined as the total number of missense mutations in the tumor exome. The F1 assay is a targeted gene panel of 315 cancer-related genes (Frampton et al. Nat Biotechnol. 2013), with TMB defined as the number of somatic mutations per megabase of sequenced tumor genome. Results: TMB data from 44 NSCLC samples were available on both F1 and WES platforms. We determined an empirical method to convert TMB values derived from WES into those derived from F1 to establish calibration between the 2 methodologies. TMB assessed by WES and by F1 was highly correlated (Spearman's r=0.9). As an additional test of concordance between the platforms, we examined agreement between the assays around the median WES value of 148 mutations. This value projects to 7.64 mutations per megabase on F1. The overall agreement between F1 and WES around these values was 86% (95% Wilson CI, 73-94). Positive and negative agreements between the 2 hybridization-capture/NGS methods were both 86% (95% Wilson CI, 67-95). Conclusion: Bridging TMB analysis by WES to F1 facilitates the transition of WES-derived biomarker data to the clinical in vitro diagnostic F1. This study demonstrates the feasibility of harmonization of TMB results across testing platforms, which provides alternative TMB testing options. Citation Format: Joseph D. Szustakowski, George Green, William J. Geese, Kim Zerba, Han Chang. Evaluation of tumor mutation burden as a biomarker for immune checkpoint inhibitor efficacy: A calibration study of whole exome sequencing with FoundationOne® [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 5528.

PDTB-27. PRECISION MEDICINE IN PEDIATRIC NEURO-ONCOLOGY

Current paradigms utilized in pediatric neuro-oncology as either primary or adjunctive modalities of therapy have failed in enhancing overall survival. Recent studies have shed light on the many facets of genetic instability that drive tumor heterogeneity and evolutionary change within an individual’s tumor that often leads to therapeutic resistance. Chemotherapeutic regimens largely focused on cell cycle inhibition are ineffective and outdated. Faced with dismal outcomes for high grade tumors, the implications for personalized medicine that targets the unique molecular landscape and genetic vulnerabilities of each person’s specific disease becomes paramount. We provide an overview of our institution’s preliminary experience with a patient-specific precision medicine algorithm offered to patients with central nervous system (CNS) tumors. We reviewed the logistics and coordination required for tissue procurement in the operating room to subsequent DNA extraction and whole exome sequencing (WES) culminating with a precision medicine report being generated for each patient. Germline analyses were also performed. Patient WES data is then analyzed for functional relevance using big data portals such as CBIOPORTAL. We report the successful coordination of our precision medicine algorithm for n=30 patients with reports being disseminated to treating neuro-oncology teams. WES data is ultimately presented at the multi-disciplinary precision medicine tumor board on a bi-weekly basis. The reporting mechanism time interval from initial receipt of all materials necessary for WES is roughly 6-8 weeks. Roughly 20% of somatic alterations detected from WES sequencing have yielded molecular targets that may have specificity for FDA approved compounds. We strongly encourage patients to enroll in our precision medicine pathway. The WES platform capture reads for over 20,000 genes and offers a unique data set that may shed light on both known cancer relevant somatic alterations but also functional relevance for less known mutations on a case-specific basis.

Use of Whole-Exome Sequencing for Diagnosis of Limb-Girdle Muscular Dystrophy

To our knowledge, the efficacy of transferring next-generation sequencing from a research setting to neuromuscular clinics has never been evaluated. To translate whole-exome sequencing (WES) to clinical practice for the genetic diagnosis of a large cohort of patients with limb-girdle muscular dystrophy (LGMD) for whom protein-based analyses and targeted Sanger sequencing failed to identify the genetic cause of their disorder. We performed WES on 60 families with LGMDs (100 exomes). Data analysis was performed between January 6 and December 19, 2014, using the xBrowse bioinformatics interface (Broad Institute). Patients with LGMD were ascertained retrospectively through the Institute for Neuroscience and Muscle Research Biospecimen Bank between 2006 and 2014. Enrolled patients had been extensively investigated via protein studies and candidate gene sequencing and remained undiagnosed. Patients presented with more than 2 years of muscle weakness and with dystrophic or myopathic changes present in muscle biopsy specimens. The diagnostic rate of LGMD in Australia and the relative frequencies of the different LGMD subtypes. Our central goals were to improve the genetic diagnosis of LGMD, investigate whether the WES platform provides adequate coverage of known LGMD-related genes, and identify new LGMD-related genes. With WES, we identified likely pathogenic mutations in known myopathy genes for 27 of 60 families. Twelve families had mutations in known LGMD-related genes. However, 15 families had variants in disease-related genes not typically associated with LGMD, highlighting the clinical overlap between LGMD and other myopathies. Common causes of phenotypic overlap were due to mutations in congenital muscular dystrophy-related genes (4 families) and collagen myopathy-related genes (4 families). Less common myopathies included metabolic myopathy (2 families), congenital myasthenic syndrome (DOK7), congenital myopathy (ACTA1), tubular aggregate myopathy (STIM1), myofibrillar myopathy (FLNC), and mutation of CHD7, usually associated with the CHARGE syndrome. Inclusion of family members increased the diagnostic efficacy of WES, with a diagnostic rate of 60% for "trios" (an affected proband with both parents) vs 40% for single probands. A follow-up screening of patients whose conditions were undiagnosed on a targeted neuromuscular disease-related gene panel did not improve our diagnostic yield. With WES, we achieved a diagnostic success rate of 45.0% in our difficult-to-diagnose cohort of patients with LGMD. We expand the clinical phenotypes associated with known myopathy genes, and we stress the importance of accurate clinical examination and histopathological results for interpretation of WES, with many diagnoses requiring follow-up review and ancillary investigations of biopsy specimens or serum samples.

ENVE: a novel computational framework characterizes copy-number mutational landscapes in colorectal cancers from African American patients.

Reliable detection of somatic copy-number alterations (sCNAs) in tumors using whole-exome sequencing (WES) remains challenging owing to technical (inherent noise) and sample-associated variability in WES data. We present a novel computational framework, ENVE, which models inherent noise in any WES dataset, enabling robust detection of sCNAs across WES platforms. ENVE achieved high concordance with orthogonal sCNA assessments across two colorectal cancer (CRC) WES datasets, and consistently outperformed a best-in-class algorithm, Control-FREEC. We subsequently used ENVE to characterize global sCNA landscapes in African American CRCs, identifying genomic aberrations potentially associated with CRC pathogenesis in this population. ENVE is downloadable at https://github.com/ENVE-Tools/ENVE.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-015-0192-9) contains supplementary material, which is available to authorized users.

New insights into the performance of human whole-exome capture platforms.

Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.

Whole-exome sequencing and clinical interpretation of formalin-fixed, paraffin-embedded tumor samples to guide precision cancer medicine.

Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a “long tail” of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. In one patient, previously undetected findings guided clinical trial enrollment leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.

Abstract 3152: CanSeq: prospective clinical whole-exome sequencing of FFPE tumor samples.

Abstract INTRODUCTION: Knowledge of tumor genomic alterations that may predict therapeutic responses represents a growing clinical need. Although there has been an increase in the use of hotspot genotyping and targeted sequencing panels of small numbers of genes, the use of clinical whole exome sequencing (WES) remains underdeveloped. Prospective WES in cancer patients presents several logistical and scientific challenges, including (i) generating robust sequencing data from small amounts of FFPE tumor tissue, (ii) establishing a clinically relevant turnaround time, (iii) achieving clinical interpretation of genomic alterations, and (iv) communicating results to the clinical team and patients. Here, we describe CanSeq, a clinical WES platform to detect genomic alterations in FFPE tumor samples and identify clinically actionable and biologically meaningful alterations in order to aid clinical decision-making and inform future research. METHODS: We performed prospective WES on tumor and germline DNA from patients with advanced refractory cancer. Sequencing was performed at the Broad Institute using the Illumina HiSeq, starting with 100 ng of DNA or less from FFPE tumor tissue and matched normal blood. Data were analyzed using a novel algorithm to highlight clinically actionable mutations, indels, and copy number alterations. These were annotated and assigned levels of evidence, and an interactive web-based report was generated for review by clinicians. RESULTS: The average turnaround time from sample receipt to data delivery was 16 days. Each tumor sample was sequenced at 90X or greater depth of coverage with more than 80% of exons with at least 30X coverage. Analysis of the first 15 patients revealed at least one plausibly actionable somatic mutation in 14 samples. These alterations include “standard of care” alterations (BRAF, EGFR), entry criteria for clinical trials (PIK3CA, KRAS, PTEN), potentially actionable alterations based on more limited evidence (STK11, ATM, CRKL, CTNNB1, PDGFRA, CDK4, CDKN2A, SMARCB1, TP53), and alterations that were theoretically targetable (JAK3, SYK). Additional biologically relevant somatic alterations and notable germline alterations were also identified. For several patients, actionable alterations were confirmed in a CLIA lab and impacted clinical decision-making, including enrollment in clinical trials. CONCLUSION: We have developed a prospective clinical WES platform to robustly detect genomic alterations in archival FFPE tumor samples (using <100 ng DNA) in a clinically appropriate time frame (<3 wks). The platform enables rapid identification of clinically relevant information from vast numbers of somatic and germline events. The ability to use real world biopsy samples could facilitate the routine incorporation of WES into the care of cancer patients, speeding the advent of precision cancer medicine by identifying the actionable genetic changes in each patient's tumor. Citation Format: Nikhil Wagle, Eliezer Van Allen, Danielle Perrin, Dennis Friedrich, Sheila Fisher, Gregory Kryukov, Lauren Ambrogio, Daniel Auclair, Stacy Gray, Steven Joffe, Pasi Janne, Judy Garber, Laura Macconaill, Neal Lindeman, Barrett Rollins, Phillip Kantoff, Gad Getz, Stacey Gabriel, Levi A. Garraway. CanSeq: prospective clinical whole-exome sequencing of FFPE tumor samples. [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 3152. doi:10.1158/1538-7445.AM2013-3152