Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning

Multi-task neural network architectures provide a mechanism that jointly integrates information from distinct sources. It is ideal in the context of MR-only radiotherapy planning as it can jointly regress a synthetic CT (synCT) scan and segment organs-at-risk (OAR) from MRI. We propose a probabilistic multi-task network that estimates: 1) intrinsic uncertainty through a heteroscedastic noise model for spatially-adaptive task loss weighting and 2) parameter uncertainty through approximate Bayesian inference. This allows sampling of multiple segmentations and synCTs that share their network representation. We test our model on prostate cancer scans and show that it produces more accurate and consistent synCTs with a better estimation in the variance of the errors, state of the art results in OAR segmentation and a methodology for quality assurance in radiotherapy treatment planning.Comment: Early-accept at MICCAI 2018, 8 pages, 4 figure

Suppression of Tumourigenicity 2 in Heart Failure With Preserved Ejection Fraction

Heart failure (HF), with steadily increasing incidence rates and mortality in an ageing population, represents a major challenge. Evidence suggests that more than half of all patients with a diagnosis of HF suffer from HF with preserved ejection fraction (HFpEF). Emerging novel biomarkers to improve and potentially guide the treatment of HFpEF are the subject of discussion. One of these biomarkers is suppression of tumourigenicity 2 (ST2), a member of the interleukin (IL)-1 receptor family, binding to IL-33. Its two main isoforms – soluble ST2 (sST2) and transmembrane ST2 (ST2L) – show opposite effects in cardiovascular diseases. While the ST2L/IL-33 interaction is considered as being cardioprotective, sST2 antagonises this beneficial effect by competing for binding to IL-33. Recent studies show that elevated levels of sST2 are associated with increased mortality in HF with reduced ejection fraction. Nevertheless, the significance of sST2 in HFpEF remains uncertain. This article aims to give an overview of the current evidence on sST2 in HFpEF with an emphasis on prognostic value, clinical association and interaction with HF treatment. The authors conclude that sST2 is a promising biomarker in HFpEF. However, further research is needed to fully understand underlying mechanisms and ultimately assess its full value

Exploring and interpreting spatiotemporal interactions between native and invasive carnivores across a gradient of rainforest degradation

Studies of elusive carnivores often rely on passive sampling when investigating either spatial or temporal interactions. However, inference on behavioral mechanisms are usually lacking. We present an analysis that combines previously published spatial co-occurrence estimates and temporal kernel density estimates to explore spatiotemporal interspecific interactions. We do so by deriving a spatiotemporal value (STV) that is a relative measure of potential interaction in both niche dimensions, across a gradient of degradation, for rainforest carnivore pairs in Madagascar. We also use a conceptual framework to provide insight into the potential behavioral mechanisms of habitat selection. Of the six native and three invasive carnivores, we estimate the spatiotemporal interactions for twelve pairings, which range from no spatial/temporal relationship (n = 5) to spatiotemporal aggregation or segregation (n = 7). We visualized these spatiotemporal interactions along a fragmentation gradient and demonstrate that these interactions are not static, as STV overlap increases with increasing anthropogenic disturbance. Of the three invasive carnivores (free-ranging dogs Canis familiaris, cats Felis species, and small Indian civets Viverricula indica) the latter had the highest number of spatial occurrence (n = 4) and spatiotemporal overlap (n = 4) relationships with native carnivores. Our results highlight the potential for increasing direct and indirect interactions between native and invasive species as forest degradation and invasive predators increase. Our approach allows us to better understand adaptive behaviors, plasticity in temporal activity, community assemblage, and to develop targeted conservation strategies to manage ecological communities in rapidly changing ecosystems

The Highly Energetic Expansion of SN2010bh Associated with GRB 100316D

We present the spectroscopic and photometric evolution of the nearby (z = 0.059) spectroscopically confirmed type Ic supernova, SN 2010bh, associated with the soft, long-duration gamma-ray burst (X-ray flash) GRB 100316D. Intensive follow-up observations of SN 2010bh were performed at the ESO Very Large Telescope (VLT) using the X-shooter and FORS2 instruments. Owing to the detailed temporal coverage and the extended wavelength range (3000--24800 A), we obtained an unprecedentedly rich spectral sequence among the hypernovae, making SN 2010bh one of the best studied representatives of this SN class. We find that SN 2010bh has a more rapid rise to maximum brightness (8.0 +/- 1.0 rest-frame days) and a fainter absolute peak luminosity (L_bol~3e42 erg/s) than previously observed SN events associated with GRBs. Our estimate of the ejected (56)Ni mass is 0.12 +/- 0.02 Msun. From the broad spectral features we measure expansion velocities up to 47,000 km/s, higher than those of SNe 1998bw (GRB 980425) and 2006aj (GRB 060218). Helium absorption lines He I lambda5876 and He I 1.083 microm, blueshifted by ~20,000--30,000 km/s and ~28,000--38,000 km/s, respectively, may be present in the optical spectra. However, the lack of coverage of the He I 2.058 microm line prevents us from confirming such identifications. The nebular spectrum, taken at ~186 days after the explosion, shows a broad but faint [O I] emission at 6340 A. The light-curve shape and photospheric expansion velocities of SN 2010bh suggest that we witnessed a highly energetic explosion with a small ejected mass (E_k ~ 1e52 erg and M_ej ~ 3 Msun). The observed properties of SN 2010bh further extend the heterogeneity of the class of GRB supernovae.Comment: 37 pages and 12 figures (one-column pre-print format), accepted for publication in Ap

A randomized controlled phase III study of VB-111 combined with bevacizumab vs bevacizumab monotherapy in patients with recurrent glioblastoma (GLOBE).

BackgroundOfranergene obadenovec (VB-111) is an anticancer viral therapy that demonstrated in a phase II study a survival benefit for patients with recurrent glioblastoma (rGBM) who were primed with VB-111 monotherapy that was continued after progression with concomitant bevacizumab.MethodsThis pivotal phase III randomized, controlled trial compared the efficacy and safety of upfront combination of VB-111 and bevacizumab versus bevacizumab monotherapy. Patients were randomized 1:1 to receive VB-111 1013 viral particles every 8 weeks in combination with bevacizumab 10 mg/kg every 2 weeks (combination arm) or bevacizumab monotherapy (control arm). The primary endpoint was overall survival (OS), and secondary endpoints were objective response rate (ORR) by Response Assessment in Neuro-Oncology (RANO) criteria and progression-free survival (PFS).ResultsEnrolled were 256 patients at 57 sites. Median exposure to VB-111 was 4 months. The study did not meet its primary or secondary goals. Median OS was 6.8 versus 7.9 months in the combination versus control arm (hazard ratio, 1.20; 95% CI: 0.91-1.59; P = 0.19) and ORR was 27.3% versus 21.9% (P = 0.26). A higher rate of grades 3-5 adverse events was reported in the combination arm (67% vs 40%), mainly attributed to a higher rate of CNS and flu-like/fever events. Trends for improved survival with combination treatment were seen in the subgroup of patients with smaller tumors and in patients who had a posttreatment febrile reaction.ConclusionsIn this study, upfront concomitant administration of VB-111 and bevacizumab failed to improve outcomes in rGBM. Change of treatment regimen, with the lack of VB-111 monotherapy priming, may explain the differences from the favorable phase II results.Clinical trials registrationNCT02511405

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

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

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