Evaluation of somatic copy number variation detection by NGS technologies and bioinformatics tools on a hyper-diploid cancer genome.

BACKGROUND: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome. RESULTS: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395). CONCLUSIONS: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

3D genomic mapping reveals multifocality of human pancreatic precancers.

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.

Ginsenoside Rg3: A Review of its Anticancer Mechanisms and Potential Therapeutic Applications.

BACKGROUND: Traditional Chinese Medicine (TCM) has a long history of treating various diseases and is increasingly being recognized as a complementary therapy for cancer. A promising natural compound extracted from the Chinese herb ginseng is ginsenoside Rg3, which has demonstrated significant anticancer effects. It has been tested in a variety of cancers and tumors and has proven to be effective in suppressing cancer. OBJECTIVES: This work covers various aspects of the role of ginsenoside Rg3 in cancer treatment, including its biological functions, key pathways, epigenetics, and potential for combination therapies, all of which have been extensively researched and elucidated. The study aims to provide a reference for future research on ginsenoside Rg3 as an anticancer agent and a support for the potential application of ginsenoside Rg3 in cancer treatment.

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions.

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

Estimation of cancer cell fractions and clone trees from multi-region sequencing of tumors.

MOTIVATION: Multi-region sequencing of solid tumors can improve our understanding of intratumor subclonal diversity and the evolutionary history of mutational events. Due to uncertainty in clonal composition and the multitude of possible ancestral relationships between clones, elucidating the most probable relationships from bulk tumor sequencing poses statistical and computational challenges. RESULTS: We developed a Bayesian hierarchical model called PICTograph to model uncertainty in assigning mutations to subclones, to enable posterior distributions of cancer cell fractions (CCFs) and to visualize the most probable ancestral relationships between subclones. Compared with available methods, PICTograph provided more consistent and accurate estimates of CCFs and improved tree inference over a range of simulated clonal diversity. Application of PICTograph to multi-region whole-exome sequencing of tumors from individuals with pancreatic cancer precursor lesions confirmed known early-occurring mutations and indicated substantial molecular diversity, including 6-12 distinct subclones and intra-sample mixing of subclones. Using ensemble-based visualizations, we highlight highly probable evolutionary relationships recovered in multiple models. PICTograph provides a useful approximation to evolutionary inference from cross-sectional multi-region sequencing, particularly for complex cases. AVAILABILITY AND IMPLEMENTATION: https://github.com/KarchinLab/pictograph. The data underlying this article will be shared on reasonable request to the corresponding author. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multiregion whole-exome sequencing of intraductal papillary mucinous neoplasms reveals frequent somatic KLF4 mutations predominantly in low-grade regions.

OBJECTIVE: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive precursor lesions that can progress to invasive pancreatic cancer and are classified as low-grade or high-grade based on the morphology of the neoplastic epithelium. We aimed to compare genetic alterations in low-grade and high-grade regions of the same IPMN in order to identify molecular alterations underlying neoplastic progression. DESIGN: We performed multiregion whole exome sequencing on tissue samples from 17 IPMNs with both low-grade and high-grade dysplasia (76 IPMN regions, including 49 from low-grade dysplasia and 27 from high-grade dysplasia). We reconstructed the phylogeny for each case, and we assessed mutations in a novel driver gene in an independent cohort of 63 IPMN cyst fluid samples. RESULTS: Our multiregion whole exome sequencing identified KLF4, a previously unreported genetic driver of IPMN tumorigenesis, with hotspot mutations in one of two codons identified in >50% of the analyzed IPMNs. Mutations in KLF4 were significantly more prevalent in low-grade regions in our sequenced cases. Phylogenetic analyses of whole exome sequencing data demonstrated diverse patterns of IPMN initiation and progression. Hotspot mutations in KLF4 were also identified in an independent cohort of IPMN cyst fluid samples, again with a significantly higher prevalence in low-grade IPMNs. CONCLUSION: Hotspot mutations in KLF4 occur at high prevalence in IPMNs. Unique among pancreatic driver genes, KLF4 mutations are enriched in low-grade IPMNs. These data highlight distinct molecular features of low-grade and high-grade dysplasia and suggest diverse pathways to high-grade dysplasia via the IPMN pathway.

Integrated Informatics Analysis of Cancer-Related Variants.

PURPOSE: The modern researcher is confronted with hundreds of published methods to interpret genetic variants. There are databases of genes and variants, phenotype-genotype relationships, algorithms that score and rank genes, and in silico variant effect prediction tools. Because variant prioritization is a multifactorial problem, a welcome development in the field has been the emergence of decision support frameworks, which make it easier to integrate multiple resources in an interactive environment. Current decision support frameworks are typically limited by closed proprietary architectures, access to a restricted set of tools, lack of customizability, Web dependencies that expose protected data, or limited scalability. METHODS: We present the Open Custom Ranked Analysis of Variants Toolkit1 (OpenCRAVAT) a new open-source, scalable decision support system for variant and gene prioritization. We have designed the resource catalog to be open and modular to maximize community and developer involvement, and as a result, the catalog is being actively developed and growing every month. Resources made available via the store are well suited for analysis of cancer, as well as Mendelian and complex diseases. RESULTS: OpenCRAVAT offers both command-line utility and dynamic graphical user interface, allowing users to install with a single command, easily download tools from an extensive resource catalog, create customized pipelines, and explore results in a richly detailed viewing environment. We present several case studies to illustrate the design of custom workflows to prioritize genes and variants. CONCLUSION: OpenCRAVAT is distinguished from similar tools by its capabilities to access and integrate an unprecedented amount of diverse data resources and computational prediction methods, which span germline, somatic, common, rare, coding, and noncoding variants.

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex (MHC) proteins can be used to predict patient response to cancer immunotherapy. Current neoantigen predictors focus on in silico estimation of MHC binding affinity and are limited by low predictive value for actual peptide presentation, inadequate support for rare MHC alleles, and poor scalability to high-throughput data sets. To address these limitations, we developed MHCnuggets, a deep neural network method that predicts peptide-MHC binding. MHCnuggets can predict binding for common or rare alleles of MHC class I or II with a single neural network architecture. Using a long short-term memory network (LSTM), MHCnuggets accepts peptides of variable length and is faster than other methods. When compared with methods that integrate binding affinity and MHC-bound peptide (HLAp) data from mass spectrometry, MHCnuggets yields a 4-fold increase in positive predictive value on independent HLAp data. We applied MHCnuggets to 26 cancer types in The Cancer Genome Atlas, processing 26.3 million allele-peptide comparisons in under 2.3 hours, yielding 101,326 unique predicted immunogenic missense mutations (IMM). Predicted IMM hotspots occurred in 38 genes, including 24 driver genes. Predicted IMM load was significantly associated with increased immune cell infiltration (P < 2 × 10-16), including CD8+ T cells. Only 0.16% of predicted IMMs were observed in more than 2 patients, with 61.7% of these derived from driver mutations. Thus, we describe a method for neoantigen prediction and its performance characteristics and demonstrate its utility in data sets representing multiple human cancers.

Intraductal Papillary Mucinous Neoplasms Arise From Multiple Independent Clones, Each With Distinct Mutations.

BACKGROUND & AIMS: Intraductal papillary mucinous neoplasms (IPMNs) are lesions that can progress to invasive pancreatic cancer and constitute an important system for studies of pancreatic tumorigenesis. We performed comprehensive genomic analyses of entire IPMNs to determine the diversity of somatic mutations in genes that promote tumorigenesis. METHODS: We microdissected neoplastic tissues from 6-24 regions each of 20 resected IPMNs, resulting in 227 neoplastic samples that were analyzed by capture-based targeted sequencing. Somatic mutations in genes associated with pancreatic tumorigenesis were assessed across entire IPMN lesions, and the resulting data were supported by evolutionary modeling, whole-exome sequencing, and in situ detection of mutations. RESULTS: We found a high prevalence of heterogeneity among mutations in IPMNs. Heterogeneity in mutations in KRAS and GNAS was significantly more prevalent in IPMNs with low-grade dysplasia than in IPMNs with high-grade dysplasia (P < .02). Whole-exome sequencing confirmed that IPMNs contained multiple independent clones, each with distinct mutations, as originally indicated by targeted sequencing and evolutionary modeling. We also found evidence for convergent evolution of mutations in RNF43 and TP53, which are acquired during later stages of tumorigenesis. CONCLUSIONS: In an analysis of the heterogeneity of mutations throughout IPMNs, we found that early-stage IPMNs contain multiple independent clones, each with distinct mutations, indicating their polyclonal origin. These findings challenge the model in which pancreatic neoplasms arise from a single clone. Increasing our understanding of the mechanisms of IPMN polyclonality could lead to strategies to identify patients at increased risk for pancreatic cancer.

Single-cell sequencing defines genetic heterogeneity in pancreatic cancer precursor lesions.

Intraductal papillary mucinous neoplasms (IPMNs) are precursors to pancreatic cancer; however, little is known about genetic heterogeneity in these lesions. The objective of this study was to characterize genetic heterogeneity in IPMNs at the single-cell level. We isolated single cells from fresh tissue from ten IPMNs, followed by whole genome amplification and targeted next-generation sequencing of pancreatic driver genes. We then determined single-cell genotypes using a novel multi-sample mutation calling algorithm. Our analyses revealed that different mutations in the same driver gene frequently occur in the same IPMN. Two IPMNs had multiple mutations in the initiating driver gene KRAS that occurred in unique tumor clones, suggesting the possibility of polyclonal origin or an unidentified initiating event preceding this critical mutation. Multiple mutations in later-occurring driver genes were also common and were frequently localized to unique tumor clones, raising the possibility of convergent evolution of these genetic events in pancreatic tumorigenesis. Single-cell sequencing of IPMNs demonstrated genetic heterogeneity with respect to early and late occurring driver gene mutations, suggesting a more complex pattern of tumor evolution than previously appreciated in these lesions. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Role of copper in regression of cardiac hypertrophy.

Pressure overload causes an accumulation of homocysteine in the heart, which is accompanied by copper depletion through the formation of copper-homocysteine complexes and the excretion of the complexes. Copper supplementation recovers cytochrome c oxidase (CCO) activity and promotes myocardial angiogenesis, along with the regression of cardiac hypertrophy and the recovery of cardiac contractile function. Increased copper availability is responsible for the recovery of CCO activity. Copper promoted expression of angiogenesis factors including vascular endothelial growth factor (VEGF) in endothelial cells is responsible for angiogenesis. VEGF receptor-2 (VEGFR-2) is critical for hypertrophic growth of cardiomyocytes and VEGFR-1 is essential for the regression of cardiomyocyte hypertrophy. Copper, through promoting VEGF production and suppressing VEGFR-2, switches the VEGF signaling pathway from VEGFR-2-dependent to VEGFR-1-dependent, leading to the regression of cardiomyocyte hypertrophy. Copper is also required for hypoxia-inducible factor-1 (HIF-1) transcriptional activity, acting on the interaction between HIF-1 and the hypoxia responsible element and the formation of HIF-1 transcriptional complex by inhibiting the factor inhibiting HIF-1. Therefore, therapeutic targets for copper supplementation-induced regression of cardiac hypertrophy include: (1) the recovery of copper availability for CCO and other critical cellular events; (2) the activation of HIF-1 transcriptional complex leading to the promotion of angiogenesis in the endothelial cells by VEGF and other factors; (3) the activation of VEGFR-1-dependent regression signaling pathway in the cardiomyocytes; and (4) the inhibition of VEGFR-2 through post-translational regulation in the hypertrophic cardiomyocytes. Future studies should focus on target-specific delivery of copper for the development of clinical application.

Backtracking RAS mutations in high hyperdiploid childhood acute lymphoblastic leukemia.

High hyperdiploidy is the single largest subtype of childhood acute lymphoblastic leukemia (ALL) and is defined by the presence of 51-68 chromosomes in a karyotype. The 5 or more extra chromosomes characterizing this subtype are known to occur in a single mitotic event, prenatally. We screened for RAS mutations among 517 acute childhood leukemias (including 437 lymphocytic, of which 393 were B-cell subtypes) and found mutations in 30% of high hyperdiploids compared to only 10% of leukemias of other subtypes (P<0.0001). We assessed whether KRAS mutations occurred before birth using a PCR-restriction enzyme-mediated Taqman quantitative PCR reaction, and found no evidence for prenatal KRAS mutations in 14 patients tested. While RAS mutations were previously associated with prior chemical exposures in childhood and adult leukemias, in this study RAS-mutated cases were not significantly associated with parental smoking when compared to study controls. IGH rearrangements were backtracked in three RAS-positive patients (which were negative for KRAS mutation at birth) and found to be evident before birth, confirming a prenatal origin for the leukemia clone. We posit a natural history for hyperdiploid leukemia in which prenatal mitotic catastrophe is followed by a postnatal RAS mutation to produce the leukemic cell phenotype.

Effect of acid on the aggregation of poly(ethylene xide)-poly(propylene oxide)-poly(ethylene oxide) block copolymers.

The acid effect on the aggregation of poly(ethylene oxide)-poly(propylene oxide)-poly(ethylene oxide) block copolymers EO(20)PO(70)EO(20) has been investigated by transmission electron microscopy (TEM), particle size analyzer (PSA), Fourier transformed infrared, and fluorescence spectroscopy. The critical micellization temperature for Pluronic P123 in different HCl aqueous solutions increases with the increase of acid concentration. Additionally, the hydrolysis degradation of PEO blocks is observed in strong acid concentrations at higher temperatures. When the acid concentration is low, TEM and PSA show the increase of the micelle mean diameter and the decrease of the micelle polydispersity at room temperature, which demonstrate the extension of EO corona and tendency of uniform micelle size because of the charge repulsion. When under strong acid conditions, the aggregation of micelles through the protonated water bridges was observed.