Fetal Metabolic Adaptations to Cardiovascular Stress in Twin-Twin Transfusion Syndrome

Monochorionic-diamniotic twin pregnancies are susceptible to unique complications arising from a single placenta shared by two fetuses. Twin-twin transfusion syndrome (TTTS) is a constellation of disturbances caused by unequal blood flow within the shared placenta giving rise to a major hemodynamic imbalance between the twins. Here, we applied TTTS as a model to uncover fetal metabolic adaptations to cardiovascular stress. We compared untargeted metabolomic analyses of amniotic fluid samples from severe TTTS cases vs. singleton controls. Amniotic fluid metabolites demonstrated alterations in fatty acid, glucose, and steroid hormone metabolism in TTTS. Among TTTS cases, unsupervised principal component analysis revealed two distinct clusters of disease defined by levels of glucose metabolites, amino acids, urea, and redox status. Our results suggest that the human fetal heart can adapt to hemodynamic stress by modulating its glucose metabolism and identify potential differences in the ability of individual fetuses to respond to cardiovascular stress

Cortical tracking of speech in noise accounts for reading strategies in children

Humans’ propensity to acquire literacy relates to several factors, including the ability to understand speech in noise (SiN). Still, the nature of the relation between reading and SiN perception abilities remains poorly understood. Here, we dissect the interplay between (1) reading abilities, (2) classical behavioral predictors of reading (phonological awareness, phonological memory, and rapid automatized naming), and (3) electrophysiological markers of SiN perception in 99 elementary school children (26 with dyslexia). We demonstrate that, in typical readers, cortical representation of the phrasal content of SiN relates to the degree of development of the lexical (but not sublexical) reading strategy. In contrast, classical behavioral predictors of reading abilities and the ability to benefit from visual speech to represent the syllabic content of SiN account for global reading performance (i.e., speed and accuracy of lexical and sublexical reading). In individuals with dyslexia, we found preserved integration of visual speech information to optimize processing of syntactic information but not to sustain acoustic/phonemic processing. Finally, within children with dyslexia, measures of cortical representation of the phrasal content of SiN were negatively related to reading speed and positively related to the compromise between reading precision and reading speed, potentially owing to compensatory attentional mechanisms. These results clarify the nature of the relation between SiN perception and reading abilities in typical child readers and children with dyslexia and identify novel electrophysiological markers of emergent literacy

Myogenic cell proliferation and generation of a reversible tumorigenic phenotype are triggered by preirradiation of the recipient site

Environmental influences have profound yet reversible effects on the behavior of resident cells. Earlier data have indicated that the amount of muscle formed from implanted myogenic cells is greatly augmented by prior irradiation (18 Gy) of the host mouse muscle. Here we confirm this phenomenon, showing that it varies between host mouse strains. However, it is unclear whether it is due to secretion of proliferative factors or reduction of antiproliferative agents. To investigate this further, we have exploited the observation that the immortal myogenic C2 C12 cell line forms tumors far more rapidly in irradiated than in nonirradiated host muscle. We show that the effect of preirradiation on tumor formation is persistent and dose dependent. However, C2 C12 cells are not irreversibly compelled to form undifferentiated tumor cells by the irradiated muscle environment and are still capable of forming large amounts of muscle when reimplanted into a nonirradiated muscle. In a clonal analysis of this effect, we discovered that C2 C12 cells have a bimodal propensity to form tumors; some clones form no tumors even after extensive periods in irradiated graft sites, whereas others rapidly form extensive tumors. This illustrates the subtle interplay between the phenotype of implanted cells and the factors in the muscle environment

A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response

Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ∼100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.National Human Genome Research Institute (U.S.) (Grant P50HG006193

The Effects of a Problem Solving-Based Intervention on Depressive Symptoms and HIV Medication Adherence Are Independent

Depression and depressive symptoms predict poor adherence to medical therapy, but the association is complex, nonspecific, and difficult to interpret. Understanding this association may help to identify the mechanism explaining the results of interventions that improve both medical therapy adherence and depressive symptoms as well as determine the importance of targeting depression in adherence interventions. We previously demonstrated that Managed Problem Solving (MAPS) focused on HIV medication adherence improved adherence and viral load in patients initiating a new antiretroviral regimen. Here, we assessed whether MAPS improved depressive symptoms and in turn, whether changes in depressive symptoms mediated changes in adherence and treatment outcomes. We compared MAPS to usual care with respect to presence of depressive symptoms during the trial using logistic regression. We then assessed whether MAPS' effect on depressive symptoms mediated the relationship between MAPS and adherence and virologic outcomes using linear and logistic regression, respectively. Mediation was defined by the disappearance of the mathematical association between MAPS and the outcomes when the proposed mediator was included in regression models. Although MAPS participants had a lower rate of depressive symptoms (OR = 0.45, 95% confidence interval 0.21-0.93), there was no evidence of mediation of the effects of MAPS on adherence and virological outcome by improvements in depression. Thus, interventions for medication adherence may not need to address depressive symptoms in order to impact both adherence and depression; this remains to be confirmed, however, in other data

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