179 research outputs found

    Profiling Heterogeneous Circulating Tumor Cells (CTC) Populations in Pancreatic Cancer Using a Serial Microfluidic CTC Carpet Chip

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    Although isolation of circulating tumor cells (CTCs) from pancreatic adenocarcinoma patients is feasible, investigating their clinical utility has proven less successful than other cancers due to the limitations of epithelial cellular adhesion molecule (EpCAM)‐only based CTC assays. An integrated technology‐ and biology‐based approach using a microfluidic “Carpet Chip” is presented to study the biological relevance of heterogeneous CTC populations. Both epithelial CTCs (EpCs) and epithelial‐to‐mesenchymal transition (EMT)‐like CTCs (EMTCs) are isolated simultaneously from the whole blood of pancreatic cancer (PaCa) patients (n = 35) by separately targeting two surface markers: EpCAM and CD133. Recovery of cancer cell lines spiked into whole blood is ≄97% with >76% purity. Thirty‐four patients had ≄5 EpCs mL−1 and 35 patients had ≄15 EMTCs mL−1. Overall, significantly higher numbers of EMTCs than EpCs are recovered, reflecting the aggressive nature of PaCa. Furthermore, higher numbers of EMTCs are observed in patients with lymph node involvement compared to patients without. Gene expression profiling of CTCs from 17 patients reveals that CXCR1 is significantly upregulated in EpCs, while known stem cell markers POU5F1/Oct‐4 and MYC are upregulated in EMTCs. In conclusion, successful isolation and genomic profiling of heterogeneous CTC populations are demonstrated, revealing genetic signatures relevant to patient outcomes.“Carpet Chip” uses sequential immunoaffinity‐based microfluidics to study the biological relevance of heterogeneous circulating tumor cell (CTCs). Both epithelial (EpCs) and epithelial‐to‐mesenchymal transition (EMT)‐like CTCs (EMTCs) are detectable from the blood of pancreatic cancer patients. Based on our observations of EMTCs and patient lymph node involvement, individualizing therapies targeting genes involved in EMT could reduce metastasis, thereby improving patient survival.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147173/1/adbi201800228-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147173/2/adbi201800228.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147173/3/adbi201800228_am.pd

    Assessing Reproducibility of Inherited Variants Detected With Short-Read Whole Genome Sequencing

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    Background: Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. Results: To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when \u3e 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30×. Conclusions: Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS

    Assessing reproducibility of inherited variants detected with short-read whole genome sequencing

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    Background: Reproducible detection of inherited variants with whole genome sequencing (WGS) is vital for the implementation of precision medicine and is a complicated process in which each step affects variant call quality. Systematically assessing reproducibility of inherited variants with WGS and impact of each step in the process is needed for understanding and improving quality of inherited variants from WGS. Results: To dissect the impact of factors involved in detection of inherited variants with WGS, we sequence triplicates of eight DNA samples representing two populations on three short-read sequencing platforms using three library kits in six labs and call variants with 56 combinations of aligners and callers. We find that bioinformatics pipelines (callers and aligners) have a larger impact on variant reproducibility than WGS platform or library preparation. Single-nucleotide variants (SNVs), particularly outside difficult-to-map regions, are more reproducible than small insertions and deletions (indels), which are least reproducible when > 5 bp. Increasing sequencing coverage improves indel reproducibility but has limited impact on SNVs above 30x. Conclusions: Our findings highlight sources of variability in variant detection and the need for improvement of bioinformatics pipelines in the era of precision medicine with WGS.Peer reviewe

    Hundreds of variants clustered in genomic loci and biological pathways affect human height

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    Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Recent advances in hydrothermal carbonisation:from tailored carbon materials and biochemicals to applications and bioenergy

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    Introduced in the literature in 1913 by Bergius, who at the time was studying biomass coalification, hydrothermal carbonisation, as many other technologies based on renewables, was forgotten during the "industrial revolution". It was rediscovered back in 2005, on the one hand, to follow the trend set by Bergius of biomass to coal conversion for decentralised energy generation, and on the other hand as a novel green method to prepare advanced carbon materials and chemicals from biomass in water, at mild temperature, for energy storage and conversion and environmental protection. In this review, we will present an overview on the latest trends in hydrothermal carbonisation including biomass to bioenergy conversion, upgrading of hydrothermal carbons to fuels over heterogeneous catalysts, advanced carbon materials and their applications in batteries, electrocatalysis and heterogeneous catalysis and finally an analysis of the chemicals in the liquid phase as well as a new family of fluorescent nanomaterials formed at the interface between the liquid and solid phases, known as hydrothermal carbon nanodots
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