Genomic Profiling of Childhood Tumor Patient-Derived Xenograft Models to Enable Rational Clinical Trial Design.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer

SUSTAIN drilling at Surtsey volcano, Iceland, tracks hydrothermal and microbiological interactions in basalt 50 years after eruption

The 2017 Surtsey Underwater volcanic System for Thermophiles, Alteration processes and INnovative concretes (SUSTAIN) drilling project at Surtsey volcano, sponsored in part by the International Continental Scientific Drilling Program (ICDP), provides precise observations of the hydrothermal, geochemical, geomagnetic, and microbiological changes that have occurred in basaltic tephra and minor intrusions since explosive and effusive eruptions produced the oceanic island in 1963–1967. Two vertically cored boreholes, to 152 and 192 m below the surface, were drilled using filtered, UV-sterilized seawater circulating fluid to minimize microbial contamination. These cores parallel a 181 m core drilled in 1979. Introductory investigations indicate changes in material properties and whole-rock compositions over the past 38 years. A Surtsey subsurface observatory installed to 181 m in one vertical borehole holds incubation experiments that monitor in situ mineralogical and microbial alteration processes at 25–124 ∘C. A third cored borehole, inclined 55∘ in a 264∘ azimuthal direction to 354 m measured depth, provides further insights into eruption processes, including the presence of a diatreme that extends at least 100 m into the seafloor beneath the Surtur crater. The SUSTAIN project provides the first time-lapse drilling record into a very young oceanic basaltic volcano over a range of temperatures, 25–141 ∘C from 1979 to 2017, and subaerial and submarine hydrothermal fluid compositions. Rigorous procedures undertaken during the drilling operation protected the sensitive environment of the Surtsey Natural Preserve

Polycystin-1 Surface Localization Is Stimulated by Polycystin-2 and Cleavage at the G Protein-coupled Receptor Proteolytic Site

The localization of polycystin (PC)1) to the plasma membrane requires coexpression with PC2 and cleavage at the PC1 G protein-coupled receptor proteolytic site. Neither the PC1 binding capacity of PC2 nor its channel function is required for this effect

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

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

Gradual caldera collapse at Bárdarbunga volcano, Iceland, regulated by lateral magma outflow

Large volcanic eruptions on Earth commonly occur with a collapse of the roof of a crustal magma reservoir, forming a caldera. Only a few such collapses occur per century, and the lack of detailed observations has obscured insight into the mechanical interplay between collapse and eruption.We usemultiparameter geophysical and geochemical data to show that the 110-squarekilometer and 65-meter-deep collapse of Bárdarbunga caldera in 2014-2015 was initiated through withdrawal of magma, and lateral migration through a 48-kilometers-long dike, from a 12-kilometers deep reservoir. Interaction between the pressure exerted by the subsiding reservoir roof and the physical properties of the subsurface flow path explain the gradual, nearexponential decline of both collapse rate and the intensity of the 180-day-long eruption.</p

NuSTAR and Chandra observations of new X-ray transients in the central parsec of the Galaxy

We report NuSTAR and Chandra observations of two X-ray transients, SWIFT J174540.7$-$290015 (T15) and SWIFT J174540.2$-$290037 (T37), which were discovered by the Neil Gehrels Swift Observatory in 2016 within $r\sim1$ pc of Sgr A*. NuSTAR detected bright X-ray outbursts from T15 and T37, likely in the soft and hard states, with 3-79~keV luminosities of $8\times10^{36}$ and $3\times10^{37}$ erg/s, respectively. No X-ray outbursts have previously been detected from the two transients and our Chandra ACIS analysis puts an upper limit of $L_X \lesssim 2 \times10^{31}$ erg/s on their quiescent 2-8 keV luminosities. No pulsations, significant QPOs, or type I X-ray bursts were detected in the NuSTAR data. While T15 exhibited no significant red noise, the T37 power density spectra are well characterized by three Lorentzian components. The declining variability of T37 above $\nu \sim 10$ Hz is typical of black hole (BH) transients in the hard state. NuSTAR spectra of both transients exhibit a thermal disk blackbody, X-ray reflection with broadened Fe atomic features, and a continuum component well described by Comptonization models. Their X-ray reflection spectra are most consistent with high BH spin ($a_{*} \gtrsim 0.9$) and large disk density ($n_e\sim10^{21}$ cm$^{-3}$). Based on the best-fit ionization parameters and disk densities, we found that X-ray reflection occurred near the inner disk radius, which was derived from the relativistic broadening and thermal disk component. These X-ray characteristics suggest the outbursting BH-LMXB scenario for both transients and yield the first BH spin measurements from X-ray transients in the central 100 pc region.Comment: 15 pages, 7 figures, accepted for publication in Ap

Mapping genetic variations to three- dimensional protein structures to enhance variant interpretation: a proposed framework

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods