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Background The amounts of circulating cell-free DNA (cfDNA) and circulating-tumor DNA (ctDNA) present in peripheral blood liquid biopsies can vary due to preanalytic/analytic variables. In this study, we examined the impact of patient age, sex, stage, and tumor type on cfDNA yield, ctDNA fraction, and estimated ctDNA quantity from a large cohort of clinical liquid biopsy samples. Methods We performed a retrospective analysis of 12 139 consecutive samples received for liquid biopsy (FoundationOne® Liquid) clinical testing. Results Significant differences in both cfDNA yield and estimated ctDNA quantity were observed based on the underlying tumor type that initiated the liquid biopsy analysis and the stage of the patient (P Conclusions In this study, we show that ctDNA quantity varied significantly based on patient age, sex, stage, and tumor type, which could offer an explanation as to why certain liquid biopsy specimens are more likely to fail sequencing or provide clinically meaningful results. In addition, this could affect future clinical decisions on the blood sample volumes required to allow successful liquid biopsy testing.

Purpose: Comprehensive genomic profiling (CGP) is of increasing value for patients with metastatic castration-resistant prostate cancer (mCRPC). mCRPC tends to metastasize to bone, making tissue biopsies challenging to obtain. We hypothesized CGP of cell-free circulating tumor DNA (ctDNA) could offer a minimally invasive alternative to detect targetable genomic alterations (GA) that inform clinical care. Experimental Design: Using plasma from 3,334 patients with mCRPC (including 1,674 screening samples from TRITON2/3), we evaluated the landscape of GAs detected in ctDNA and assessed concordance with tissue-based CGP. Results: A total of 3,129 patients (94%) had detectable ctDNA with a median ctDNA fraction of 7.5%; BRCA1/2 was mutated in 295 (8.8%). In concordance analysis, 72 of 837 patients had BRCA1/2 mutations detected in tissue, 67 (93%) of which were also identified using ctDNA, including 100% of predicted germline variants. ctDNA harbored some BRCA1/2 alterations not identified by tissue testing, and ctDNA was enriched in therapy resistance alterations, as well as possible clonal hematopoiesis mutations (e.g., in ATM and CHEK2). Potential androgen receptor resistance alterations were detected in 940 of 2,213 patients (42%), including amplifications, polyclonal and compound mutations, rearrangements, and novel deletions in exon 8. Conclusions: Genomic analysis of ctDNA from patients with mCRPC recapitulates the genomic landscape detected in tissue biopsies, with a high level of agreement in detection of BRCA1/2 mutations, but more acquired resistance alterations detected in ctDNA. CGP of ctDNA is a compelling clinical complement to tissue CGP, with reflex to tissue CGP if negative for actionable variants. See related commentary by Hawkey and Armstrong, p. 2961

Genomic profiling of circulating tumor DNA derived from cell-free DNA (cfDNA) in blood can provide a noninvasive method for detecting genomic biomarkers to guide clinical decision making for cancer patients. We developed a hybrid capture–based next-generation sequencing assay for genomic profiling of circulating tumor DNA from blood (FoundationACT). High-sequencing coverage and molecular barcode–based error detection enabled accurate detection of genomic alterations, including short variants (base substitutions, short insertions/deletions) and genomic re-arrangements at low allele frequencies (AFs), and copy number amplifications. Analytical validation was performed on 2666 reference alterations. The assay achieved >99% overall sensitivity (95% CI, 99.1%–99.4%) for short variants at AF >0.5%, >95% sensitivity (95% CI, 94.2%–95.7%) for AF 0.25% to 0.5%, and 70% sensitivity (95% CI, 68.2%–71.5%) for AF 0.125% to 0.25%. No false positives were detected in 62 samples from healthy volunteers. Genomic alterations detected by FoundationACT demonstrated high concordance with orthogonal assays run on the same clinical cfDNA samples. In 860 routine clinical FoundationACT cases, genomic alterations were detected in cfDNA at comparable frequencies to tissue; for the subset of cases with temporally matched tissue and blood samples, 75% of genomic alterations and 83% of short variant mutations detected in tissue were also detected in cfDNA. On the basis of analytical validation results, FoundationACT has been approved for use in our Clinical Laboratory Improvement Amendments–certified/College of American Pathologists–accredited/New York State–approved laboratory.

Background: F1LCDx is an FDA-approved liquid biopsy test offering pan-tumor profiling of >300 genes with CDx indications for multiple cancer types. One key limitation is that sensitivity for detection of genomic alterations in ctDNA is impaired when the plasma tumor fraction (TF) is low. TF is known to vary in advanced cancer and has been correlated with overall survival (Stover, JCO, 2018). While some ctDNA assays use variant allele fraction (VAF) to quantify tumor content, such methods may be prone to interference from germline variants, copy number alterations and a limited number of mutations. We studied SNP aneuploidy to develop a variant-independent measure of TF which we hypothesized could inform assay sensitivity. Methods: For each liquid sample, coverages from heterozygous SNPs, across the genome, were used to measure allelic deviations from normal via a root-mean-square (RMS) metric. The relationship between RMS and TF was established based on a training data set of clinical samples with known TF that were diluted in silico. In this way, the RMS metric for any sample could be linked to a distribution of TF values. TF is reported when the lower bounds of the predicted TF distribution is >0%. Positive percentage agreement (PPA) of liquid NGS versus tissue genotype was studied in those with a TF reported vs TF not quantified. Results: For a pilot concordance analysis, we studied a real-world cohort of NSCLC patients where NGS was performed on both tissue and on a 70-gene ctDNA assay (FoundationOne®Liquid (F1L), median 314 days between results). Among 251 cases with tissue NGS showing an EGFR L858R or 19del mutation and a F1L result available, the EGFR mutation was detected 90% of the time (57/63) when TF was reported (range 13-74%) but was detected 51% of the time (96/188) when TF was not quantified. Next, we analyzed a cohort of 3 clinical trials in advanced cancers where tissue genotype was known and with F1LCDx results available, including studies of activating PIK3CA mutations in breast cancer, MET exon 14 mutations in NSCLC and BRCA1/2 mutations in prostate cancer. For the subset of patients with TF reported (range 9.6-72%), PPA was 94.7% (breast, n=38), 100% (NSCLC, n=19), and 90.1% (prostate, n=46), versus 66.7% (breast, n=33), 66.7% (NSCLC, n=45) and 89.6% (prostate, n=48) for TF not quantified. Conclusions: We describe a novel method to measure TF in plasma ctDNA based on aneuploidy, which may overcome some limitations of TF measurement based on VAF. When TF confirms tumor content, sensitivity of F1LCDx for short variant detection is excellent (90%-100%), suggesting reduced value from a reflex to tissue genotyping in the absence of a targetable genomic alteration. When TF is not quantified, sensitivity can be lower and the value of reflex to tissue genotyping may be heightened. Citation Format: Meijuan Li, Bernard Fendler, Lei Yang, Russell Madison, Brennan Decker, Ole Gjoerup, Kimberly McGregor, Aparna Aiyer, Jason Hughes, Priti Hegde, Christine Vietz, Geoffrey R. Oxnard. Utility of plasma tumor fraction (TF) to inform sensitivity of FoundationOne Liquid CDx (F1LCDx) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2231.

25 Background: Comprehensive genomic profiling (CGP) by next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) from plasma provides a minimally invasive method to identify targetable genomic alterations (GAs) and resistance mechanisms in patients with metastatic castration-resistant prostate cancer (mCRPC). The circulating tumor fraction in patients with mCRPC and the clinical validity of GAs detected in plasma remain unknown. We evaluated the landscape of GAs using ctDNA-based CGP and assessed concordance with tissue-based CGP. Methods: Plasma from 3,334 patients with advanced prostate cancer (including 1,674 mCRPC screening samples from the TRITON2/3 trials and 1,660 samples from routine clinical CGP) was analyzed using hybrid-capture-based gene panel NGS assays. Results were compared with CGP of 2,006 metastatic prostate cancer tissue biopsies. Concordance was evaluated in 837 patients with both tissue (archival or contemporaneous) and plasma NGS results. Results: 3,127 patients [94%] had detectable ctDNA. BRCA1/2 were mutated in 295 patients [8.8%]. In concordance analysis, 72/837 [8.6%] patients had BRCA1/2 mutations detected in tissue, 67 [93%] of whom were also identified by ctDNA, and 20 patients were identified using ctDNA but not tissue [23% of all patients identified using ctDNA]. ctDNA detected subclonal BRCA1/2 reversions in 10 of 1,660 [0.6%] routine clinical CGP samples. AR alterations, including amplifications and hotspot mutations, which were detected in 940/2,213 patients [42%]. Rare AR compound mutations, rearrangements, and novel in-frame deletions were identified. Altered pathways included PI3K/AKT/mTOR [14%], WNT/β-catenin [17%], and RAS/RAF/MEK [5%]. Microsatellite instability was detected in 31/2,213 patients [1.4%]. Conclusions: In the largest study of mCRPC plasma samples conducted to date, CGP of ctDNA recapitulated the genomic landscape detected in tissue biopsies, with a high level of agreement in detection of BRCA1/2 alterations. It also identified patients who may have gained somatic BRCA1/2 alterations since archival tissue was collected. ctDNA detected more acquired resistance GAs than tissue, including novel AR-activating variants. The large percentage of patients with rich genomic signal from ctDNA, and the sensitive, specific detection of BRCA1/2 alterations position liquid biopsy as a compelling clinical complement to tissue CGP for patients with mCRPC.

Plasma insulin is pulsatile and reflects oscillatory insulin secretion from pancreatic islets. Although both islet Ca(2+) and metabolism oscillate, there is disagreement over their interrelationship, and whether they can be dissociated. In some models of islet oscillations, Ca(2+) must oscillate for metabolic oscillations to occur, whereas in others metabolic oscillations can occur without Ca(2+) oscillations. We used NAD(P)H fluorescence to assay oscillatory metabolism in mouse islets stimulated by 11.1 mM glucose. After abolishing Ca(2+) oscillations with 200 microM diazoxide, we observed that oscillations in NAD(P)H persisted in 34% of islets (n = 101). In the remainder of the islets (66%) both Ca(2+) and NAD(P)H oscillations were eliminated by diazoxide. However, in most of these islets NAD(P)H oscillations could be restored and amplified by raising extracellular KCl, which elevated the intracellular Ca(2+) level but did not restore Ca(2+) oscillations. Comparatively, we examined islets from ATP-sensitive K(+) (K(ATP)) channel-deficient SUR1(-/-) mice. Again NAD(P)H oscillations were evident even though Ca(2+) and membrane potential oscillations were abolished. These observations are predicted by the dual oscillator model, in which intrinsic metabolic oscillations and Ca(2+) feedback both contribute to the oscillatory islet behavior, but argue against other models that depend on Ca(2+) oscillations for metabolic oscillations to occur.

Individual mouse pancreatic islets exhibit oscillations in [Ca(2+)](i) and insulin secretion in response to glucose in vitro, but how the oscillations of a million islets are coordinated within the human pancreas in vivo is unclear. Islet to islet synchronization is necessary, however, for the pancreas to produce regular pulses of insulin. To determine whether neurohormone release within the pancreas might play a role in coordinating islet activity, [Ca(2+)](i) changes in 4-6 isolated mouse islets were simultaneously monitored before and after a transient pulse of a putative synchronizing agent. The degree of synchronicity was quantified using a novel analytical approach that yields a parameter that we call the "Synchronization Index". Individual islets exhibited [Ca(2+)](i) oscillations with periods of 3-6 min, but were not synchronized under control conditions. However, raising islet [Ca(2+)](i) with a brief application of the cholinergic agonist carbachol (25 microM) or elevated KCl in glucose-containing saline rapidly synchronized islet [Ca(2+)](i) oscillations for/=30 min, long after the synchronizing agent was removed. In contrast, the adrenergic agonists clonidine or norepinephrine, and the K(ATP) channel inhibitor tolbutamide, failed to synchronize islets. Partial synchronization was observed, however, with the K(ATP) channel opener diazoxide. The synchronizing action of carbachol depended on the glucose concentration used, suggesting that glucose metabolism was necessary for synchronization to occur. To understand how transiently perturbing islet [Ca(2+)](i) produced sustained synchronization, we used a mathematical model of islet oscillations in which complex oscillatory behavior results from the interaction between a fast electrical subsystem and a slower metabolic oscillator. Transient synchronization simulated by the model was mediated by resetting of the islet oscillators to a similar initial phase followed by transient "ringing" behavior, during which the model islets oscillated with a similar frequency. These results suggest that neurohormone release from intrapancreatic neurons could help synchronize islets in situ. Defects in this coordinating mechanism could contribute to the disrupted insulin secretion observed in Type 2 diabetes.

We investigate the effects of rare regions on the dynamics of Ising magnets with planar defects, i.e., disorder perfectly correlated in two dimensions. In these systems, the magnetic phase transition is smeared because static long-range order can develop on isolated rare regions. We first study an infinite-range model by numerically solving local dynamic mean-field equations. Then we use extremal statistics and scaling arguments to discuss the dynamics beyond mean-field theory. In the tail region of the smeared transition the dynamics is even slower than in a conventional Griffiths phase: the spin autocorrelation function decays like a stretched exponential at intermediate times before approaching the exponentially small equilibrium value following a power law at late times., 10 pages, 8eps figures included, final version as published

We have studied fully differential cross sections (FDCS) for single ionization in 75 keV p + He collisions by measuring the recoil-ion momentum and the projectile momentum in coincidence. The measured FDCS are completely dominated by the binary peak while the recoil peak is absent. This is a clear signature of the post-collision interaction between the outgoing projectile and the ejected electron. Furthermore, our continuum distorted wave calculation demonstrates the importance of the projectile?target nucleus interaction. While the shape of the experimental FDCS is well reproduced by this calculation, there are significant discrepancies in magnitude.

Pancreatic islets exhibit bursting oscillations in response to elevated blood glucose. These oscillations are accompanied by oscillations in the free cytosolic Ca 2+ concentration (Cac), which drives pulses of insulin secretion. Both islet Ca 2+ and metabolism oscillate, but there is some debate about their interrelationship. Recent experimental data show that metabolic oscillations in some cases persist after the addition of diazoxide (Dz), which opens K(ATP) channels, hyperpolarizing β- cells and preventing Ca 2+ entry and Ca 2+ oscillations. Further, in some islets in which metabolic oscillations were eliminated with Dz, increasing the cytosolic Ca 2+ concentration by the addition of KCl could restart the metabolic oscillations. Here we address why metabolic oscillations persist in some islets but not others, and why raising Cac restarts oscillations in some islets but not others. We answer these questions using the dual oscillator model (DOM) for pancreatic islets. The DOM can reproduce the experimental data and shows that the model supports two different mechanisms for slow metabolic oscillations, one that requires calcium oscillations and one that does not.

e23049Background: With an increasing number of circulating tumor DNA (ctDNA) profiling assays available, physicians must be empowered to distinguish which assays have the high level of accuracy req...

Background: Profiling cell-free circulating tumor DNA (ctDNA) for genomic alterations which drive oncogenesis in patients with cancer promises to provide information important for understanding cancer biology, informing therapy selection when conventional FFPE biopsies are unobtainable and potentially monitoring response to therapy. To allow routine use of blood-based ctDNA molecular profiling with clinical samples we developed and performed analytic validation of an accurate, targeted NGS-based assay. The analytic validation included over 400 samples demonstrating ≥99% sensitivity and ≥99% positive predictive value for base substitutions, indels and rearrangements with limit-of-detection below 1%. Methods: To ensure robust performance, the ctDNA assay was developed as part of an integrated workflow including sample collection, storage and transport, and ctDNA purification, followed by optimized construction of adaptor-ligated sequencing libraries and enrichment by solution hybridization and then sequencing to high depth (Illumina HiSeq). Computational methodologies were developed to enable sensitive and specific detection of base substitutions, indels, genomic rearrangements and high-level amplifications from ctDNA. Accuracy and reproducibility were analytically validated in a CLIA-certified laboratory using reference samples with known alterations (117 cell-line mixtures and synthetic constructs) and 268 clinical ctDNA samples. Many alterations found in clinical ctDNA samples were validated with orthogonal reference methods including a CLIA-validated NGS assay, droplet digital PCR and break-point PCR. Results: The ctDNA assay validation demonstrated ≥99% sensitivity and ≥99% positive predictive value for base substitutions, indels and rearrangements with a limit-of-detection below 1% and robust detection of high-level, focal amplifications when present at adequate tumor fraction. In addition, the assay accurately reports the allele frequency of alterations in the sample. In 48 clinical ctDNA samples, 95 alterations of all classes were 100% confirmed by orthogonal testing. As part of our extensive clinical utility study, we report results comparing alterations from patient-matched ctDNA and FFPE biopsies across more than 200 lung, breast and other cancer samples. Conclusions: Accurate clinical profiling of ctDNA enables detection of genomic alterations in patient plasma samples to provide rationale targeted therapeutic options. Our rigorous analytic validation study demonstrates high-sensitivity detection of alterations present in blood at low frequency with a very low rate of false positives, realizing the potential of ctDNA-based molecular profiling for the management of patients with cancer. This validated assay allows us to embark upon a rigorous investigation of clinical best-practices based on tumor-type specific assessment of matched ctDNA and solid biopsy specimens. Citation Format: Travis A. Clark, Mark Kennedy, Jie He, Geneva Young, Mandy Zhao, Mike Coyne, Virginia Breese, Lauren Young, Shan Zhong, Mark Bailey, Bernard Fendler, Erica Schleifman, Eric Peters, Phil J. Stephens, Geoff A. Otto, Doron Lipson. Rigorous validation of a clinical circulating tumor DNA assay for cancer molecular profiling. [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 3965.

When growth regulatory genes are damaged in a cell, it may become cancerous. Current technological advances in the last decade have allowed the characterization of the whole genome of these cells by directly or indirectly measuring DNA changes. Complementary analyses were developed to make sense of the massive amounts of data generated. A large majority of these analyses were developed to construct interaction networks between genes from, primarily, expression array data. We review the current technologies and analyses that have developed in the last decade. We further argue that as cancer genomics evolves from single gene validations to gene network inferences, new analyses must be developed for the different technological platforms.

The evolutionary pressures that underlie the large-scale functional organization of the genome are not well understood in eukaryotes. Recent evidence suggests that functionally similar genes may colocalize (cluster) in the eukaryotic genome, suggesting the role of chromatin-level gene regulation in shaping the physical distribution of coordinated genes. However, few of the bioinformatic tools currently available allow for a systematic study of gene colocalization across several, evolutionarily distant species. Kerfuffle is a web tool designed to help discover, visualize, and quantify the physical organization of genomes by identifying significant gene colocalization and conservation across the assembled genomes of available species (currently up to 47, from humans to worms). Kerfuffle only requires the user to specify a list of human genes and the names of other species of interest. Without further input from the user, the software queries the e!Ensembl BioMart server to obtain positional information and discovers homology relations in all genes and species specified. Using this information, Kerfuffle performs a multi-species clustering analysis, presents downloadable lists of clustered genes, performs Monte Carlo statistical significance calculations, estimates how conserved gene clusters are across species, plots histograms and interactive graphs, allows users to save their queries, and generates a downloadable visualization of the clusters using the Circos software. These analyses may be used to further explore the functional roles of gene clusters by interrogating the enriched molecular pathways associated with each cluster., Comment: BMC Bioinformatics, In press

Plasma insulin measurements from mice, rats, dogs, and humans indicate that insulin levels are oscillatory, reflecting pulsatile insulin secretion from individual islets. An unanswered question, however, is how the activity of a population of islets is coordinated to yield coherent oscillations in plasma insulin. Here, using mathematical modeling, we investigate the feasibility of a potential islet synchronization mechanism, cholinergic signaling. This hypothesis is based on well-established experimental evidence demonstrating intrapancreatic parasympathetic (cholinergic) ganglia and recent in vitro evidence that a brief application of a muscarinic agonist can transiently synchronize islets. We demonstrate using mathematical modeling that periodic pulses of acetylcholine released from cholinergic neurons is indeed able to coordinate the activity of a population of simulated islets, even if only a fraction of these are innervated. The role of islet-to-islet heterogeneity is also considered. The results suggest that the existence of cholinergic input to the pancreas may serve as a regulator of endogenous insulin pulsatility in vivo.

Identification of predictive and prognostic biomarkers is central to clinical oncology. Use of targeted next generation sequencing (NGS) is increasing in molecular diagnostics labs, however the feasibility and impact of its routine application across all tumor types is largely untested. We launched an institution-wide effort to generate targeted NGS data (Oncopanel) for invasive tumors of all consenting patients. We hypothesized that this approach could replace traditional targeted testing, generate robust data on copy number alterations and structural variants, and provide novel patient-specific observations to facilitate clinical trial enrollment. Illumina NGS was performed on libraries prepared with Agilent SureSelect custom-designed hybrid capture of 4430 exons from 275 genes plus selected introns of 30 genes. Results were analyzed by an internally-developed computational pipeline for mutations, small insertions/deletions, copy number variation and rearrangements. Variants were characterized according to predictive, prognostic, or diagnostic actionability. Data is available for the first 4291 cases sequenced. Oncopanel succeeded in 96% of specimens with adequate DNA. In a subset analysis performed on the first 1000 cases, assay success ranged from 83-100% according to tumor type; breast carcinoma was most prone to failure (p Citation Format: Lynette M. Sholl, Elizabeth Garcia, Yonghui Jia, Matthew Ducar, Bernard Fendler, Priyanka Shivdasani, Frank C. Kuo, Azra H. Ligon, Barrett J. Rollins, Neal I. Lindeman, Laura E. MacConaill. Revolutionizing clinical care using prospective, institution-wide tumor sequencing. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4666. doi:10.1158/1538-7445.AM2015-4666

Identification of copy number alterations (CNAs) in tumors can assist in determining diagnosis, prognosis, or predicting response to therapy in certain cancer types. Many CNA detection tools have been developed for whole genome sequencing (WGS). These algorithms typically “call” alterations by using significant deviations of the log2 ratio of tumor to normal coverage from the expected diploid log2 ratio. Several factors, however, including reporting pertinent genomic information, hardware and software limitations, and cost, have impeded the routine application of WGS in a clinical setting. Targeted sequencing - hybrid capture and massively parallel sequencing of defined regions (targets) of the genome can overcome some of these challenges and can specifically interrogate, for example, known cancer genes, thus maximizing the “actionability” or utility of the information generated. Though more suited for large-scale clinical testing, targeted sequencing of smaller gene panels with specific clinical reference presents some significant bioinformatic challenges that hinder the application of pre-existing CNA detection tools, resulting in a heavy dependence on manual review in the clinic. In addition, varying quality of DNA, minor variations in laboratory protocols, along with batch effects, are known to confound CNA profiles and are exasperated by the decreased number of sequenced regions of targeted gene panels. These variables alter the log2 ratio, and thus, our ability to call CNAs suffers. We note, that using matched normals may mitigate some deleterious effects, however, to minimize clinical cost and throughput, we tackle these challenges with unmatched tumor-normal pairs. Similar to the closest normal approach used in SNP array analyses, we rely on the assumption that some “normal” (non-tumor) samples experience similar experimental variability that affects the tumor samples. Minimizing maximally informative cost-functions (incorporating both global and local CNA variation), we iteratively investigate different combinations of normal samples which best resemble a given cancer sample. The new set of normals which minimize the cost-function, defines a panel of normals (PON) whose target medians are used to generate the log2 ratio. Along with batch-effect reduction techniques, we then call CNAs with statistically significant thresholds at the target-level. Interestingly, we find that approximately 15 normals are typically needed to minimize CNA profile variation, as opposed to our typical approach of using all available normals (∼60). In addition, we demonstrate that our procedure can improve our sensitivity and specificity from 58±1% to 81±2% and 94±1% to 99.5±0.1%, respectively, on simulated data. We further compared our approach with other published algorithms and found a significant improvement in performance, reducing the time required to manually review CNAs and interpret copy number profiles in the clinic. Citation Format: Bernard Fendler, Ryan Abo, Samuel Hunter, Matthew Ducar, Elizabeth Garcia, Paul Van Hummelen, Neal Lindeman, Laura MacConaill. Identifying copy number alterations from targeted sequencing data. [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 4850. doi:10.1158/1538-7445.AM2015-4850