Enhancing easy-plane anisotropy in bespoke Ni(II) quantum magnets

We examine the crystal structures and magnetic properties of several S = 1 Ni(II) coordination compounds, molecules and polymers, that include the bridging ligands HF2-, AF62- (A = Ti, Zr) and pyrazine or non-bridging ligands F-, SiF62-, glycine, H2O, 1-vinylimidazole, 4-methylpyrazole and 3-hydroxypyridine. Pseudo-octahedral NiN4F2, NiN4O2 or NiN4OF cores consist of equatorial Ni-N bonds that are equal to or slightly longer than the axial Ni-Lax bonds. By design, the zero-field splitting (D) is large in these systems and, in the presence of substantial exchange interactions (J), can be difficult to discriminate from magnetometry measurements on powder samples. Thus, we relied on pulsed-field magnetization in those cases and employed electron-spin resonance (ESR) to confirm D when J 0) and range from ≈ 8-25 K. This work reveals a linear correlation between the ratio d(Ni-Lax)/d(Ni-Neq) and D although the ligand spectrochemical properties may also be important. We assert that this relationship allows us to predict the type of magnetocrystalline anisotropy in tailored Ni(II) quantum magnets

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

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

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

DESNT: A Poor Prognosis Category of Human Prostate Cancer.

BACKGROUND: A critical problem in the clinical management of prostate cancer is that it is highly heterogeneous. Accurate prediction of individual cancer behaviour is therefore not achievable at the time of diagnosis leading to substantial overtreatment. It remains an enigma that, in contrast to breast cancer, unsupervised analyses of global expression profiles have not currently defined robust categories of prostate cancer with distinct clinical outcomes. OBJECTIVE: To devise a novel classification framework for human prostate cancer based on unsupervised mathematical approaches. DESIGN, SETTING, AND PARTICIPANTS: Our analyses are based on the hypothesis that previous attempts to classify prostate cancer have been unsuccessful because individual samples of prostate cancer frequently have heterogeneous compositions. To address this issue, we applied an unsupervised Bayesian procedure called Latent Process Decomposition to four independent prostate cancer transcriptome datasets obtained using samples from prostatectomy patients and containing between 78 and 182 participants. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Biochemical failure was assessed using log-rank analysis and Cox regression analysis. RESULTS AND LIMITATIONS: Application of Latent Process Decomposition identified a common process in all four independent datasets examined. Cancers assigned to this process (designated DESNT cancers) are characterized by low expression of a core set of 45 genes, many encoding proteins involved in the cytoskeleton machinery, ion transport, and cell adhesion. For the three datasets with linked prostate-specific antigen failure data following prostatectomy, patients with DESNT cancer exhibited poor outcome relative to other patients (p=2.65×10-5, p=4.28×10-5, and p=2.98×10-8). When these three datasets were combined the independent predictive value of DESNT membership was p=1.61×10-7 compared with p=1.00×10-5 for Gleason sum. A limitation of the study is that only prediction of prostate-specific antigen failure was examined. CONCLUSIONS: Our results demonstrate the existence of a novel poor prognosis category of human prostate cancer and will assist in the targeting of therapy, helping avoid treatment-associated morbidity in men with indolent disease. PATIENT SUMMARY: Prostate cancer, unlike breast cancer, does not have a robust classification framework. We propose that this failure has occurred because prostate cancer samples selected for analysis frequently have heterozygous compositions (individual samples are made up of many different parts that each have different characteristics). Applying a mathematical approach that can overcome this problem we identify a novel poor prognosis category of human prostate cancer called DESNT.This work was funded by the Bob Champion Cancer Trust, The Masonic Charitable Foundation successor to The Grand Charity, The King Family, and The University of East Anglia. We acknowledge support from Movember, from Prostate Cancer UK, Callum Barton, and from The Andy Ripley Memorial Fund. The research presented in this paper was carried out on the High Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia. Cancer Research UK Grant 10047 funded the generation of the prostate CancerMap expression microarray dataset. We would like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge UK

Postnatal Changes in the Expression Pattern of the Imprinted Signalling Protein XLαs Underlie the Changing Phenotype of Deficient Mice

The alternatively spliced trimeric G-protein subunit XLαs, which is involved in cAMP signalling, is encoded by the Gnasxl transcript of the imprinted Gnas locus. XLαs deficient mice show neonatal feeding problems, leanness, inertia and a high mortality rate. Mutants that survive to weaning age develop into healthy and fertile adults, which remain lean despite elevated food intake. The adult metabolic phenotype can be attributed to increased energy expenditure, which appears to be caused by elevated sympathetic nervous system activity. To better understand the changing phenotype of Gnasxl deficient mice, we compared XLαs expression in neonatal versus adult tissues, analysed its co-localisation with neural markers and characterised changes in the nutrient-sensing mTOR1-S6K pathway in the hypothalamus. Using a newly generated conditional Gnasxl lacZ gene trap line and immunohistochemistry we identified various types of muscle, including smooth muscle cells of blood vessels, as the major peripheral sites of expression in neonates. Expression in all muscle tissues was silenced in adults. While Gnasxl expression in the central nervous system was also developmentally silenced in some midbrain nuclei, it was upregulated in the preoptic area, the medial amygdala, several hypothalamic nuclei (e.g. arcuate, dorsomedial, lateral and paraventricular nuclei) and the nucleus of the solitary tract. Furthermore, expression was detected in the ventral medulla as well as in motoneurons and a subset of sympathetic preganglionic neurons of the spinal cord. In the arcuate nucleus of Gnasxl-deficient mice we found reduced activity of the nutrient sensing mTOR1-S6K signalling pathway, which concurs with their metabolic status. The expression in these brain regions and the hypermetabolic phenotype of adult Gnasxl-deficient mice imply an inhibitory function of XLαs in energy expenditure and sympathetic outflow. By contrast, the neonatal phenotype of mutant mice appears to be due to a transient role of XLαs in muscle tissues