PROviding Better ACcess To ORgans: A comprehensive overview of organ‐access initiatives from the ASTS PROACTOR Task Force

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138905/1/ajt14441_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138905/2/ajt14441.pd

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Radiation Tolerance of SiGe BiCMOS Monolithic Silicon Pixel Detectors without Internal Gain Layer

A monolithic silicon pixel prototype produced for the MONOLITH ERC Advanced project was irradiated with 70 MeV protons up to a fluence of 1 x 10^16 1 MeV n_eq/cm^2. The ASIC contains a matrix of hexagonal pixels with 100 {\mu}m pitch, readout by low-noise and very fast SiGe HBT frontend electronics. Wafers with 50 {\mu}m thick epilayer with a resistivity of 350 {\Omega}cm were used to produce a fully depleted sensor. Laboratory tests conducted with a 90Sr source show that the detector works satisfactorily after irradiation. The signal-to-noise ratio is not seen to change up to fluence of 6 x 10^14 n_eq /cm^2 . The signal time jitter was estimated as the ratio between the voltage noise and the signal slope at threshold. At -35 {^\circ}C, sensor bias voltage of 200 V and frontend power consumption of 0.9 W/cm^2, the time jitter of the most-probable signal amplitude was estimated to be 21 ps for proton fluence up to 6 x 10 n_eq/cm^2 and 57 ps at 1 x 10^16 n_eq/cm^2 . Increasing the sensor bias to 250 V and the analog voltage of the preamplifier from 1.8 to 2.0 V provides a time jitter of 40 ps at 1 x 10^16 n_eq/cm^2.Comment: Submitted to JINS

Characteristics of the Early Immune Response Following Transplantation of Mouse ES Cell Derived Insulin-Producing Cell Clusters

Background The fully differentiated progeny of ES cells (ESC) may eventually be used for cell replacement therapy (CRT). However, elements of the innate immune system may contribute to damage or destruction of these tissues when transplanted. Methodology/Principal Findings Herein, we assessed the hitherto ill-defined contribution of the early innate immune response in CRT after transplantation of either ESC derived insulin producing cell clusters (IPCCs) or adult pancreatic islets. Ingress of neutrophil or macrophage cells was noted immediately at the site of IPCC transplantation, but this infiltration was attenuated by day three. Gene profiling identified specific inflammatory cytokines and chemokines that were either absent or sharply reduced by three days after IPCC transplantation. Thus, IPCC transplantation provoked less of an early immune response than pancreatic islet transplantation. Conclusions/Significance Our study offers insights into the characteristics of the immune response of an ESC derived tissue in the incipient stages following transplantation and suggests potential strategies to inhibit cell damage to ensure their long-term perpetuation and functionality in CRT

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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

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

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

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

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

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