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Supplementary Tables 1-3 Supplementary Table 1. Location and number of NSCLC, normal and field of cancerization specimens analyzed for genome-wide allelic imbalance Supplementary Table 2. Summary of identified allelic imbalance events in the normal-appearing airway field of cancerization in early-stage NSCLC Supplementary Table 3. Airway events with negative B-allele frequency correlations

Supplementary information including supplementary methods, supplementary tables and figures as well as supplementary figure legends. Supplementary Figure 1. HapLOH results for matched normal large airway and NSCLC tumor from case 18 Supplementary Figure 2. Distribution of posterior probabilities for airway events called by hapLOH Supplementary Figure 3: Allelic imbalance events detected in normal-appearing airway brushings Supplementary Figure 4. Event classification using B-allele frequencies and log R ratios Supplementary Figure 5. Effect of allelic imbalance on B-allele frequencies Supplementary Figure 6: Distribution of focal and arm airway events

Visually normal cells adjacent to, and extending from, tumors of the lung may carry molecular alterations characteristics of the tumor itself, an effect referred to as airway field of cancerization. This airway field has been postulated as a model for early events in lung cancer pathogenesis. Yet the genomic landscape of somatically acquired molecular alterations in airway epithelia of lung cancer patients has remained unknown. To begin to fill this void, we sought to comprehensively characterize the genomic architecture of chromosomal alterations inducing allelic imbalance (AI) in the airway field of the most common type of lung tumors, non–small cell lung cancer (NSCLC). To do so, we conducted a genome-wide survey of multiple spatially distributed normal-appearing airways, multiregion tumor specimens, and uninvolved normal tissues or blood from 45 patients with early-stage NSCLC. We detected alterations in airway epithelia from 22 patients, with an increased frequency in NSCLCs of squamous histology. Our data also indicated a spatial gradient of AI in samples at closer proximity to the NSCLC. Chromosome 9 displayed the highest levels of AI and comprised recurrent independent events. Furthermore, the airway field AI included oncogenic gains and tumor suppressor losses in known NSCLC drivers. Our results demonstrate that genome-wide AI is common in the airway field of cancerization, providing insights into early events in the pathogenesis of NSCLC that may comprise targets for early treatment and chemoprevention. Cancer Res; 76(13); 3676–83. ©2016 AACR.

Visually normal cells adjacent to, and extending from, tumors of the lung may carry molecular alterations characteristics of the tumor itself, an effect referred to as airway field of cancerization. This airway field has been postulated as a model for early events in lung cancer pathogenesis. Yet the genomic landscape of somatically acquired molecular alterations in airway epithelia of lung cancer patients has remained unknown. To begin to fill this void, we sought to comprehensively characterize the genomic architecture of chromosomal alterations inducing allelic imbalance (AI) in the airway field of the most common type of lung tumors, non–small cell lung cancer (NSCLC). To do so, we conducted a genome-wide survey of multiple spatially distributed normal-appearing airways, multiregion tumor specimens, and uninvolved normal tissues or blood from 45 patients with early-stage NSCLC. We detected alterations in airway epithelia from 22 patients, with an increased frequency in NSCLCs of squamous histology. Our data also indicated a spatial gradient of AI in samples at closer proximity to the NSCLC. Chromosome 9 displayed the highest levels of AI and comprised recurrent independent events. Furthermore, the airway field AI included oncogenic gains and tumor suppressor losses in known NSCLC drivers. Our results demonstrate that genome-wide AI is common in the airway field of cancerization, providing insights into early events in the pathogenesis of NSCLC that may comprise targets for early treatment and chemoprevention. Cancer Res; 76(13); 3676–83. ©2016 AACR.

Genomic mosaicism arising from post-zygotic mutation has recently been demonstrated to occur in normal tissue of individuals ascertained with varied phenotypes, indicating that detectable mosaicism may be less an exception than a rule in the general population. A challenge to comprehensive cataloging of mosaic mutations and their consequences is the presence of heterogeneous mixtures of cells, rendering low-frequency clones difficult to discern. Here we applied a computational method using estimated haplotypes to characterize mosaic megabase-scale structural mutations in 31,100 GWA study subjects. We provide in silico validation of 293 previously identified somatic mutations and identify an additional 794 novel mutations, most of which exist at lower aberrant cell fractions than have been demonstrated in previous surveys. These mutations occurred across the genome but in a nonrandom manner, and several chromosomes and loci showed unusual levels of mutation. Our analysis supports recent findings about the relationship between clonal mosaicism and old age. Finally, our results, in which we demonstrate a nearly 3-fold higher rate of clonal mosaicism, suggest that SNP-based population surveys of mosaic structural mutations should be conducted with haplotypes for optimal discovery.

Motivation: The detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data. Results: Our method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA. Availability and Implementation: hapLOHseq is available at scheet.org/software, distributed under an open source MIT license. Contact: pscheet@alum.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Potential bias introduced during DNA isolation is inadequately explored, although it could have significant impact on downstream analysis. To investigate this in human brain, we isolated DNA from cerebellum and frontal cortex using spin columns under different conditions, and salting-out. We first analysed DNA using array CGH, which revealed a striking wave pattern suggesting primarily GC-rich cerebellar losses, even against matched frontal cortex DNA, with a similar pattern on a SNP array. The aCGH changes varied with the isolation protocol. Droplet digital PCR of two genes also showed protocol-dependent losses. Whole genome sequencing showed GC-dependent variation in coverage with spin column isolation from cerebellum. We also extracted and sequenced DNA from substantia nigra using salting-out and phenol / chloroform. The mtDNA copy number, assessed by reads mapping to the mitochondrial genome, was higher in substantia nigra when using phenol / chloroform. We thus provide evidence for significant method-dependent bias in DNA isolation from human brain, as reported in rat tissues. This may contribute to array “waves”, and could affect copy number determination, particularly if mosaicism is being sought, and sequencing coverage. Variations in isolation protocol may also affect apparent mtDNA abundance.

Sequencing studies of breast tumour cohorts have identified many prevalent mutations, but provide limited insight into the genomic diversity within tumours. Here we developed a whole-genome and exome single cell sequencing approach called nuc-seq that uses G2/M nuclei to achieve 91% mean coverage breadth. We applied this method to sequence single normal and tumour nuclei from an oestrogen-receptor-positive (ER(+)) breast cancer and a triple-negative ductal carcinoma. In parallel, we performed single nuclei copy number profiling. Our data show that aneuploid rearrangements occurred early in tumour evolution and remained highly stable as the tumour masses clonally expanded. In contrast, point mutations evolved gradually, generating extensive clonal diversity. Using targeted single-molecule sequencing, many of the diverse mutations were shown to occur at low frequencies (10%) in the tumour mass. Using mathematical modelling we found that the triple-negative tumour cells had an increased mutation rate (13.3×), whereas the ER(+) tumour cells did not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer.

Background: The cyclin-dependent-kinase inhibitors (CDKN)/retinoblastoma (RB1) pathway has been implicated as having a role in medullary thyroid carcinoma (MTC) tumorigenesis. CDKN2C loss has been associated with RET-mediated MTC in humans but with minimal phenotypic correlation provided. The objective of this study was to evaluate the association between tumor RET mutation status, CDKN2C loss, and aggressiveness of MTC in a cohort of patients with sporadic disease. Methods: Tumors from patients with sporadic MTC treated at a single institution were evaluated for somatic RET(M918T) mutation and CDKN2C copy number loss. These variables were compared to patient demographics, pathology detail, clinical course, and disease-specific and overall survival. Results: Sixty-two MTC cases with an initial surgery date ranging from 1983 to 2009 met the inclusion criteria, of whom 36 (58%) were male. The median age at initial surgery was 53 years (range 22–81 years). The median tumor size was 30 mm (range 6–145 mm) with 29 (57%) possessing extrathyroidal extension. Nodal and/or distant metastasis at presentation was found in 47/60 (78%) and 12/61 (20%) patients, respectively. Median follow-up time was 10.5 years (range 1.1–27.8 years) for the censored observations. The presence of CDKN2C loss was associated with worse M stage and overall AJCC stage. Median overall survival of patients with versus without CDKN2C loss was 4.14 [confidence interval (CI) 1.93–NA] versus 18.27 [CI 17.24–NA] years (p

The rhesus macaque ( Macaca mulatta ) is an abundant primate species that diverged from the ancestors of Homo sapiens about 25 million years ago. Because they are genetically and physiologically similar to humans, rhesus monkeys are the most widely used nonhuman primate in basic and applied biomedical research. We determined the genome sequence of an Indian-origin Macaca mulatta female and compared the data with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families. A comparison of sequences from individual animals was used to investigate their underlying genetic diversity. The complete description of the macaque genome blueprint enhances the utility of this animal model for biomedical research and improves our understanding of the basic biology of the species.

Genetic heterogeneity in a mixed sample of tumor and normal DNA can confound characterization of the tumor genome. Numerous computational methods have been proposed to detect aberrations in DNA samples from tumor and normal tissue mixtures. Most of these require tumor purities to be at least 10–15%. Here, we present a statistical model to capture information, contained in the individual's germline haplotypes, about expected patterns in the B allele frequencies from SNP microarrays while fully modeling their magnitude, the first such model for SNP microarray data. Our model consists of a pair of hidden Markov models—one for the germline and one for the tumor genome—which, conditional on the observed array data and patterns of population haplotype variation, have a dependence structure induced by the relative imbalance of an individual's inherited haplotypes. Together, these hidden Markov models offer a powerful approach for dealing with mixtures of DNA where the main component represents the germline, thus suggesting natural applications for the characterization of primary clones when stromal contamination is extremely high, and for identifying lesions in rare subclones of a tumor when tumor purity is sufficient to characterize the primary lesions. Our joint model for germline haplotypes and acquired DNA aberration is flexible, allowing a large number of chromosomal alterations, including balanced and imbalanced losses and gains, copy-neutral loss-of-heterozygosity (LOH) and tetraploidy. We found our model (which we term J-LOH) to be superior for localizing rare aberrations in a simulated 3% mixture sample. More generally, our model provides a framework for full integration of the germline and tumor genomes to deal more effectively with missing or uncertain features, and thus extract maximal information from difficult scenarios where existing methods fail., Author Summary Allelic imbalance, or a deviation from the expected 1-to-1 ratio of alleles where both were present in the germline, can result when there has been an acquired deletion or duplication of part of a chromosome and is a hallmark of cancer genomes. Tumor genomic profiling studies often involve analysis of samples that contain aberrant tumor cells mixed with normal cells without these acquired mutations. Methods for detecting chromosomal aberrations that result in allelic imbalance within a heterogeneous sample have previously been proposed that use the dispersion of within-sample allele frequencies measured at germline heterozygous positions. Here we demonstrate that combining this information with a measure for the correlation in these dispersions, due to the imbalance of one of the chromosomes, provides the most powerful approach. Our method allows for sensitive identification of short allelic imbalance events (e.g. 10 Mb) contained in as few as 3% of the cells in a heterogeneous mixture. Applications include profiling tumor genomes following surgical resection where there exists high contamination of normal tissue and identifying aberrations in subclones. Our work provides a framework for further development of methods that use observed data and population genetic theory for inference of allelic imbalance.

Due to limitations of surgical dissection and tumor heterogeneity, tumor samples collected for cancer genomics studies are often heavily diluted with normal tissue or contain subpopulations of cells harboring important aberrations. Methods for profiling tumor-associated allelic imbalance in such scenarios break down at aberrant cell proportions of 10%–15% and below. Here, we present an approach that offers a vast improvement for detection of subtle allelic imbalance, or low proportions of cells harboring aberrant allelic ratio among nonaberrant cells, in unpaired tumor samples using SNP microarrays. We leverage the expected pattern of allele-specific intensity ratios determined by an individual's germline haplotypes, information that has been ignored in existing approaches. We demonstrate our method on real and simulated data from the CRL-2324 breast cancer cell line genotyped on the Illumina 370K array. Assuming a 5 million SNP array, we can detect the presence of aberrant cells in proportions lower than 0.25% in the breast cancer sample, approaching the sensitivity of some minimal residual disease assays. Further, we apply a hidden Markov model to identify copy-neutral LOH (loss of heterozygosity) events as short as 11 Mb in mixtures of only 4% tumor using 370K data. We anticipate our approach will offer a new paradigm for genomic profiling of heterogeneous samples.

Methotrexate is used to treat autoimmune diseases and malignancies, including acute lymphoblastic leukemia (ALL). Inter-individual variation in clearance of methotrexate results in heterogeneous systemic exposure, clinical efficacy, and toxicity. In a genome-wide association study of children with ALL, we identified SLCO1B1 as harboring multiple common polymorphisms associated with methotrexate clearance. The extent of influence of rare versus common variants on pharmacogenomic phenotypes remains largely unexplored. We tested the hypothesis that rare variants in SLCO1B1 could affect methotrexate clearance and compared the influence of common versus rare variants in addition to clinical covariates on clearance. From deep resequencing of SLCO1B1 exons in 699 children, we identified 93 SNPs, 15 of which were non-synonymous (NS). Three of these NS SNPs were common, with a minor allele frequency (MAF) >5%, one had low frequency (MAF 1%–5%), and 11 were rare (MAF SLCO1B1 haplotypes that were associated with reduced methotrexate clearance. In a multivariate stepwise regression analysis adjusting for other genetic and non-genetic covariates, SLCO1B1 variants accounted for 10.7% of the population variability in clearance. Of that variability, common NS variants accounted for the majority, but rare damaging NS variants constituted 17.8% of SLCO1B1's effects (1.9% of total variation) and had larger effect sizes than common NS variants. Our results show that rare variants are likely to have an important effect on pharmacogenetic phenotypes.

To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production. Fil: Bovine Genome Sequencing and Analysis Consortium. Bovine Genome Sequencing And Analysis Consortium; Estados Unidos Fil: Amadio, Ariel Fernando. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Santa Fe. Estación Experimental Agropecuaria Rafaela; Argentina Fil: Poli, Mario Andres. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Genética; Argentina

The phenomenon of field cancerization has been previously postulated and observed in various cancers, including those of the lung. We have recently demonstrated that normal-appearing airway cells carry expression profiles that are often characteristic of the adjacent tumor. A better understanding of the molecular mechanisms that drive these field changes may provide important biological insights into lung cancer pathogenesis. Loss-of-heterozygosity (LOH) and other forms of acquired chromosomal alterations (allelic imbalance; AI) have an established and profound role in oncogenesis. However, the relationship between AI and field cancerization has not been studied comprehensively across the genome. Here we address this void by interrogating a rich collection of normal-appearing airways from non-small cell lung cancer (NSCLC) patients. We applied Illumina 1M SNP arrays to characterize whole genome copy number alterations in 435 samples from 45 early-stage NSCLC patients [31 adenocarcinomas (ADCs), 14 squamous cell carcinomas (SCCs)]. Each patient set comprised samples from the primary tumor and adjacent normal-appearing airways paired with blood cells and/or uninvolved normal lung tissue. A subset of these included brushings from ipsilateral large airways (mainstem bronchi) and from the nasal cavities as well as multi-region tumor biopsies for intra-tumoral analysis (on 22, 27, and 20 patients, respectively). To characterize the field in normal-appearing airways at a genome-wide scale, we applied a haplotype-based computational program, hapLOH, to profile AI events (loss, gain, copy neutral LOH) in a paired mode contrasting signals in the blood or normal lung. We detected 198 AI events in normal-appearing airways of 24 of 45 patients; 92% of these events were represented in the paired tumor. Of the 24 patients, 23 had events in the adjacent airway, 3 had events in the large airway, and no events were observed in nasal brushings, indicating a pronounced AI field gradient. We detected AI in the airways of approximately 43% of ADCs regardless of smoking status (3 of 7 smokers, 10 of 24 non-smokers), and 79% (11 of 14) of SCCs, clearly indicating squamous histology as a greater predictor of observing a genomic field effect (P < 0.03). The most frequently observed airway alterations were in 9p and 9q, affecting 13 smoker patients; interestingly, these were not observed in the non-smokers. Finally, we note that AI events were present in the adjacent airways of 4/5 (80%) of patients with recurrence and only in 20/40 patients without recurrence, signaling a profound prognostic value in studying the field of cancerization in NSCLC. Although preliminary, our findings suggest that chromosomal aberrations are common in the normal-appearing airway field of cancerization and can potentially provide insights into the biology of lung cancer pathogenesis and progression. Citation Format: Yasminka Jakubek, Wenhua Lang, Selina Vattathil, Melinda Garcia, Lili Huang, Wei Lu, Chi-Wan Chow, Zachary Weber, Gareth E. Davies, Carmen Behrens, Neda Kalhor, Cesar Moran, Junya Fujimoto, Reza J. Mehran, Jerry Fowler, Erik A. Ehli, Ignacio I. Wistuba, Paul Scheet, Humam Kadara. The landscape of DNA allelic imbalance in the normal-appearing airway field of cancerization. [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 2993. doi:10.1158/1538-7445.AM2015-2993

Recent genome-wide surveys have revealed age-related genetic mosaicism and established a link between clonal mosaicism and risk of hematological and solid-tumor cancers (Laurie et al, 2012, Nat Genet, 44:642; Jacobs et al, 2012, Nat Genet, 44:651; Forsberg et al, 2012, AJHG, 90:217). Existing methods to identify chromosomal aberrations leading to mosaic allelic imbalance (AI) rely on the detection of increased variance of the estimated within-sample allele frequencies at heterozygous loci, ignoring the dependence among allele frequencies in regions of an AI-inducing event, such as a deletion or copy-neutral loss of heterozygosity (LOH), expected from the loss or gain of a chunk of an inherited chromosome. As a result, they break down when the proportion of DNA from an aberrant source is below 10-15%. Here we present a suite of new methods (hapLOH, J-LOH, hapLOHseq) that harness the important information contained in the germline haplotypes to help distinguish signal from noise, accommodate multiple samples of different tumor purities (to deconvolute aberration type and tumor purity) and infer co-occurrence of aberrations in heterogeneous mixtures. For example, our initial method, hapLOH (Vattathil & Scheet, 2013, Gen Res 23:152), can identify 10 Mb regions with just 4% of the signal coming from the tumor genome in data simulated from a series of experiments from a 317K SNP microarray. Application of hapLOH to data analyzed by Laurie et al (2012) indicates that we have substantially greater sensitivity to detect clonal mosaicism, particularly events harbored in a small proportion of cells (< 5-10%). We identify more than twice as many mosaic events, demonstrating the potential role for our methods to aid in profiling cancer risk. Our suite of tools is designed for both microarray and next-generation sequencing data and is available at scheet.org. Citation Format: Paul Scheet, Rui Xia, F. Anthony San Lucas, Christina Hahn, Jerry Fowler, Selina Vattathil. Novel computational methods reveal subtle clonal mosaicism. [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 5320. doi:10.1158/1538-7445.AM2014-5320

Human breast cancers often display intratumor genomic heterogeneity. This clonal diversity confounds the clinical diagnosis and basic research of cancer, because single samples may not represent that tumor as a whole. Sequencing breast tumor cohorts en masse has identified many prevalent mutations, but has limited ability for resolving subclonal diversity. Here, we developed a whole-genome and exome single-cell sequencing approach (Nuc-Seq) using G2/M cells. To validate our method, we applied Nuc-Seq to sequence the whole genomes of two single cells from a genetically monoclonal breast cancer cell line (SK-BR-3) at high coverage depth (61X ± 5 sem, n=2) and breadth (83.70% ± 3.40 sem, n=2) to detect somatic mutations. Our analysis suggests that Nuc-Seq generates low allelic dropout rates (9.73% ± 2.19%) and low false positive error rates for point mutations (FPR = 1.24e-6). We then applied this method to sequence single normal and tumor cells from an estrogen-receptor positive breast cancer and a triple-negative ductal carcinoma at base-pair resolution. In parallel, we performed single cell copy number profiling. In both tumors, we observed a large number of rare variants that were not detected by sequencing the bulk tumor en masse. In contrast, we find that single cell copy number profiles are highly similar. Our data suggest that aneuploid rearrangements occurred early in tumor evolution and remained highly stable as the tumor mass expanded. In contrast we find that point mutations evolved gradually, generating extensive clonal diversity. Many of the diverse mutations were shown to occur at low frequencies (0.03 -10%) in the tumor mass by targeted duplex sequencing. Mathematical modeling suggests that the triple-negative tumor cells have an increased mutation rate (13.3X), while the ER+ tumor cells do not. These findings have important implications for the diagnosis, therapeutic treatment and evolution of chemoresistance in breast cancer. Citation Format: Yong Wang, Nicholas Navin, Jill Waters, Marco Leung, Anna Unruh, Xiuqing Shi, Whijae Roh, Ken Chen, Paul Scheet, Selina Vattathil, Han Liang, Asha Multani, Hong Zhang, Funda Meric-Bernstam, Franziska Michor, Rui Zhao. Single cell genome sequencing reveals clonal stability and diversity in breast cancer. [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 LB-310. doi:10.1158/1538-7445.AM2014-LB-310

Abstract 571 Methotrexate is an antifolate chemotherapeutic drug commonly used to treat cancer, including acute lymphoblastic leukemia (ALL). Interindividual variation in clearance of methotrexate results in a vast range of exposure to the drug, which affects its clinical effectiveness and risk of toxicity. In a genome-wide association study of children with ALL, we identified the SLCO1B1 gene, encoding liver transporter OATP1B1, as harboring multiple common polymorphisms associated with methotrexate clearance (Trevino et al. J Clin Oncol, 27:5972-5978, 2009). Because these common polymorphisms could not account for the variation in methotrexate clearance entirely, we hypothesized that there may be rare variants in addition to the common polymorphisms in this gene that affect methotrexate disposition. To test this hypothesis, we sequenced SLCO1B1 exons in 699 pediatric leukemia patients, and compared the effects of common versus rare variants on methotrexate clearance (adjusting for clinical covariates). We identified 93 SNPs, 15 of which were non-synonymous (NS); 11 of the 15 NS SNPs were rare, with minor allele frequencies < 1%. We used four computational programs (SIFT, PMUT, SNPS3D, and Polyphen2) to predict whether the NS SNPs were damaging to the function of the protein. The 7 NS SNPs predicted to be functionally damaging (common or rare) were more likely to be found among patients with the lowest methotrexate clearance than patients with high clearance (p=2.4×10−8), including one SNP that was observed only once among nearly 1400 chromosomes. Four SLCO1B1 haplotypes were associated with reduced methotrexate clearance (p Disclosures: Evans: St. Jude Children's Research Hospital: Employment, Patents & Royalties; NIH NCI: Research Funding; Aldagen: Membership on an entity's Board of Directors or advisory committees. Relling:Sigma-Tau Pharmaceuticals, Inc: Investigator-initiated research; St. Jude Children's Research Hospital: Employment, Patents & Royalties; NIH: Research Funding.