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

Expression of N-acetylglucosaminyltransferase V in endometrial cancer correlates with poor prognosis

N-acetylglucosaminyltransferase V (GnT-V) is an enzyme that catalyses β1–6 branching of N-acetylglucosamine on asparagine-linked oligosaccharides of cell proteins. The present study aimed to investigate GnT-V expression and its prognostic significance in endometrial cancer. N-acetylglucosaminyltransferase V expression was studied by immunohistochemistry in 74 surgically resected endometrial cancers, and the staining intensity was evaluated. High GnT-V expression in tumour cells was found in 43 (58.1%) of the 74 cases, and was positively correlated with advanced patient age, histological grade, and lymph vascular space involvement. Patients with high GnT-V expression had significantly impaired overall survival and progression-free survival (PFS) (P=0.0041 and P=0.0023, respectively) compared to patients with low expression of GnT-V. On multivariate analysis, GnT-V expression was an independent prognostic factor for PFS (P=0.0364). β1–6 branching of asparagine-linked oligosaccharides was also detected in GnT-V-positive endometrial cancer cells by leukoagglutinating phytohaemagglutinin (L4-PHA) staining, and the molecular size of the major glycoproteins recognised by L4-PHA was approximately 60–200 kDa by lectin blot analysis. These results suggested that high GnT-V expression was correlated with an unfavourable clinical outcome, and that GnT-V is involved in the malignant potential of endometrial cancer by increasing the synthesis of β1–6 branching of asparagine-linked oligosaccharides

New Dual Mode Gadolinium Nanoparticle Contrast Agent for Magnetic Resonance Imaging

BACKGROUND: Liposomal-based gadolinium (Gd) nanoparticles have elicited significant interest for use as blood pool and molecular magnetic resonance imaging (MRI) contrast agents. Previous generations of liposomal MR agents contained gadolinium-chelates either within the interior of liposomes (core-encapsulated gadolinium liposomes) or presented on the surface of liposomes (surface-conjugated gadolinium liposomes). We hypothesized that a liposomal agent that contained both core-encapsulated gadolinium and surface-conjugated gadolinium, defined herein as dual-mode gadolinium (Dual-Gd) liposomes, would result in a significant improvement in nanoparticle-based T1 relaxivity over the previous generations of liposomal agents. In this study, we have developed and tested, both in vitro and in vivo, such a dual-mode liposomal-based gadolinium contrast agent. METHODOLOGY/PRINCIPAL FINDINGS: THREE TYPES OF LIPOSOMAL AGENTS WERE FABRICATED: core-encapsulated, surface-conjugated and dual-mode gadolinium liposomes. In vitro physico-chemical characterizations of the agents were performed to determine particle size and elemental composition. Gadolinium-based and nanoparticle-based T1 relaxivities of various agents were determined in bovine plasma. Subsequently, the agents were tested in vivo for contrast-enhanced magnetic resonance angiography (CE-MRA) studies. Characterization of the agents demonstrated the highest gadolinium atoms per nanoparticle for Dual-Gd liposomes. In vitro, surface-conjugated gadolinium liposomes demonstrated the highest T1 relaxivity on a gadolinium-basis. However, Dual-Gd liposomes demonstrated the highest T1 relaxivity on a nanoparticle-basis. In vivo, Dual-Gd liposomes resulted in the highest signal-to-noise ratio (SNR) and contrast-to-noise ratio in CE-MRA studies. CONCLUSIONS/SIGNIFICANCE: The dual-mode gadolinium liposomal contrast agent demonstrated higher particle-based T1 relaxivity, both in vitro and in vivo, compared to either the core-encapsulated or the surface-conjugated liposomal agent. The dual-mode gadolinium liposomes could enable reduced particle dose for use in CE-MRA and increased contrast sensitivity for use in molecular imaging

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

Long-term photometry of IC 348 with the Young Exoplanet Transit Initiative network

We present long-term photometric observations of the young open cluster IC 348 with a baseline time-scale of 2.4 yr. Our study was conducted with several telescopes from the Young Exoplanet Transit Initiative (YETI) network in the Bessel R band to find periodic variability of young stars. We identified 87 stars in IC 348 to be periodically variable; 33 of them were unreported before. Additionally, we detected 61 periodic non-members of which 41 are new discoveries. Our wide field of view was the key to those numerous newly found variable stars. The distribution of rotation periods in IC 348 has always been of special interest. We investigate it further with our newly detected periods but we cannot find a statistically significant bimodality. We also report the detection of a close eclipsing binary in IC 348 composed of a low-mass stellar component (M ≳ 0.09 M⊙) and a K0 pre-main-sequence star (M ≈ 2.7 M⊙). Furthermore, we discovered three detached binaries among the background stars in our field of view and confirmed the period of a fourth one

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 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

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