Development of B-1 cells: segregation of phosphatidyl choline-specific B cells to the B-1 population occurs after immunoglobulin gene expression

Adult mice have two easily recognizable subsets of B cells: the predominant resting population of the spleen, called B-2, and those called B-1, which predominate in coelomic cavities and can express CD5. Some antibody specificities appear to be unique to the B-1 population. Cells expressing antibody specific for phosphatidyl choline (PtC) are the most frequent, comprising 2-10% of peritoneal B cells in normal mice. To understand the basis for the segregation of the anti-PtC specificity to this population, we have produced transgenic (Tg) mice expressing the rearranged VH12 and V kappa 4 genes of a PtC-specific B- 1 cell lymphoma. We find that VH12-Tg and VH12/V kappa 4 double-Tg mice develop very high numbers of PtC-specific peritoneal and splenic B cells. These cells have the characteristics of B-1 cells; most are CD5+, and are all IgMhi, B220lo, and CD23-. In the peritoneum these cells are also CD11b+. In addition, adult mice have many splenic B cells (up to one third of Tg+ cells) that express the VH12 Tg but do not bind PtC, presumably because they express a V kappa gene other than V kappa 4. These cells appear to be B-2 cells; they are CD23+, CD11b-, IgMlo, B220hi, and CD5-. Thus, mice given either the VH12 Tg alone or together with the V kappa 4 Tg develop a large population of PtC- specific B cells which belong exclusively to the B-1 population. Since B-2 cells can express the VH12 and V kappa 4 gene separately, we interpret these data to indicate that the events leading to the segregation of PtC-specific B cells to the B-1 population in normal mice are initiated after Ig gene rearrangement and expression. These data are discussed with regard to hypotheses of the origin of B-1 cells. We also find that VH12-Tg mice have a marked decrease in the generation of Tg-expressing B cells in adult bone marrow, but not newborn liver. We speculate that this may be related to positive selection of VH12-expressing B cells during differentiation

ALK Status Testing in Non–Small-Cell Lung Carcinoma by FISH on ThinPrep Slides with Cytology Material

Introduction:Oncogenic anaplastic lymphoma kinase (ALK) gene rearrangements in non–small-cell lung carcinomas (NSCLC) provide the basis for targeted therapy with crizotinib and other specific ALK inhibitors. Treatment eligibility is conventionally determined by the Food and Drug Administration–approved companion diagnostic fluorescence in situ hybridization (FISH) assay on paraffin-embedded tissue (PET). On limited samples such as fine needle aspiration–derived cytoblocks, FISH for ALK is often uninformative. FISH performed on liquid-based ThinPrep slides (ThinPrep-FISH) may represent a robust alternative.Methods:Two hundred thirty cytology samples from 217 patients with advanced NSCLC, including a consecutive series of 179 specimens, were used to generate matched ThinPrep slides and paraffin cytoblocks. The same ThinPrep slides used for cytologic diagnosis were assessed by standard ALK break-apart two-color probe FISH, after etching of tumor areas. Ultrasensitive ALK immunohistochemistry (IHC) on corresponding cytoblocks [D5F3 antibody, OptiView signal amplification] served as the reference data set.Results:ThinPrep-FISH ALK signals were robust in 228 of 230 cases and not compromised by nuclear truncation inherent in paraffin-embedded tissue–FISH; only two samples displayed no signals. Nine of 178 informative cases (5%) in the consecutive series and 18 of 228 informative cases (7.8%) overall were ALK rearranged by ThinPrep-FISH. In 154 informative matched ThinPrep-FISH and cytoblock-IHC samples, 152 were concordant (10, 6.5% ALK status positive; 142, 92.2% ALK status negative), and two (1.3%) were ThinPrep-FISH positive but IHC negative (sensitivity 100%, specificity 98.6%, overall agreement 98.7%).Conclusion:Detection of ALK gene rearrangements in liquid cytology ThinPrep slides derived from patients with NSCLC can be confidently used for clinical ALK molecular testing

Changes in refractive error during young adulthood: the effects of longitudinal screen time, ocular sun exposure, and genetic predisposition

Purpose: Changes in refractive error during young adulthood is common yet risk factors at this age are largely unexplored. This study explored risk factors for these changes, including gene–environmental interactions. Methods: Spherical equivalent refraction (SER) and axial length (AL) for 624 community-based adults were measured at 20 (baseline) and 28 years old. Participants were genotyped and their polygenic scores (PGS) for refractive error calculated. Self-reported screen time (computer, television, and mobile devices) from 20 to 28 years old were collected prospectively and longitudinal trajectories were generated. Past sun exposure was quantified using conjunctival ultraviolet autofluorescence (CUVAF) area. Results: Median change in SER and AL were −0.023 diopters (D)/year (interquartile range [IQR] = −0.062 to –0.008) and +0.01 mm/year (IQR = 0.000 to 0.026), respectively. Sex, baseline myopia, parental myopia, screen time, CUVAF, and PGS were significantly associated with myopic shift. Collectively, these factors accounted for approximately 20% of the variance in refractive error change, with screen time, CUVAF, and PGS each explaining approximately 1% of the variance. Four trajectories for total screen time were found: “consistently low” (n = 148), “consistently high” (n = 250), “consistently very high” (n = 76), and “increasing” (n = 150). Myopic shift was faster in those with “consistently high” or “consistently very high” screen time compared to “consistently-low” (P ≤ 0.031). For each z-score increase in PGS, changes in SER and AL increased by −0.005 D/year and 0.002 mm/year (P ≤ 0.045). Of the three types of screen time, only computer time was associated with myopic shift (P ≤ 0.040). There was no two- or three-way interaction effect between PGS, CUVAF, or screen time (P ≥ 0.26). Conclusions: Higher total or computer screen time, less sun exposure, and genetic predisposition are each independently associated with greater myopic shifts during young adulthood. Given that these factors explained only a small amount of the variance, there are likely other factors driving refractive error change during young adulthood

Simple uncertainty frameworks for selecting weighting schemes and interpreting multimodel ensemble climate change experiments

Future climate change projections are often derived from ensembles of simulations from multiple global circulation models using heuristic weighting schemes. This study provides a more rigorous justification for this by introducing a nested family of three simple analysis of variance frameworks. Statistical frameworks are essential in order to quantify the uncertainty associated with the estimate of the mean climate change response. The most general framework yields the “one model, one vote” weighting scheme often used in climate projection. However, a simpler additive framework is found to be preferable when the climate change response is not strongly model dependent. In such situations, the weighted multimodel mean may be interpreted as an estimate of the actual climate response, even in the presence of shared model biases. Statistical significance tests are derived to choose the most appropriate framework for specific multimodel ensemble data. The framework assumptions are explicit and can be checked using simple tests and graphical techniques. The frameworks can be used to test for evidence of nonzero climate response and to construct confidence intervals for the size of the response. The methodology is illustrated by application to North Atlantic storm track data from the Coupled Model Intercomparison Project phase 5 (CMIP5) multimodel ensemble. Despite large variations in the historical storm tracks, the cyclone frequency climate change response is not found to be model dependent over most of the region. This gives high confidence in the response estimates. Statistically significant decreases in cyclone frequency are found on the flanks of the North Atlantic storm track and in the Mediterranean basin

C-Terminal Substitution of MDM2 Interacting Peptides Modulates Binding Affinity by Distinctive Mechanisms

The complex between the proteins MDM2 and p53 is a promising drug target for cancer therapy. The residues 19–26 of p53 have been biochemically and structurally demonstrated to be a most critical region to maintain the association of MDM2 and p53. Variation of the amino acid sequence in this range obviously alters the binding affinity. Surprisingly, suitable substitutions contiguous to this region of the p53 peptides can yield tightly binding peptides. The peptide variants may differ by a single residue that vary little in their structural conformations and yet are characterized by large differences in their binding affinities. In this study a systematic analysis into the role of single C-terminal mutations of a 12 residue fragment of the p53 transactivation domain (TD) and an equivalent phage optimized peptide (12/1) were undertaken to elucidate their mechanistic and thermodynamic differences in interacting with the N-terminal of MDM2. The experimental results together with atomistically detailed dynamics simulations provide insight into the principles that govern peptide design protocols with regard to protein-protein interactions and peptidomimetic design

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

Mega-evolutionary dynamics of the adaptive radiation of birds

The origin and expansion of biological diversity is regulated by both developmental trajectories and limits on available ecological niches. As lineages diversify, an early and often rapid phase of species and trait proliferation gives way to evolutionary slow- downs as new species pack into ever more densely occupied regions of ecological niche space. Small clades such as Darwin’s finches demonstrate that natural selection is the driving force of adaptive radiations, but how microevolutionary processes scale up to shape the expansion of phenotypic diversity over much longer evolutionary timescales is unclear. Here we address this problem on a global scale by analysing a crowd-sourced dataset of three-dimensional scanned bill morphology from more than 2,000 species. We find that bill diversity expanded early in extant avian evolutionary history, before transitioning to a phase dominated by packing of morphological space. However, this early phenotypic diversification is decoupled from temporal variation in evolutionary rate: rates of bill evolution vary among lineages but are comparatively stable through time. We find that rare, but major, discontinuities in phenotype emerge from rapid increases in rate along single branches, sometimes leading to depauperate clades with unusual bill morphologies. Despite these jumps between groups, the major axes of within-group bill-shape evolution are remarkably consistent across birds. We reveal that macroevolutionary processes underlying global-scale adaptive radiations support Darwinian and Simpsonian ideas of microevolution within adaptive zones and accelerated evolution between distinct adaptive peaks

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