Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesi

Dialectics and difference: against Harvey's dialectical post-Marxism

David Harvey`s recent book, Justice, nature and the geography of difference (JNGD), engages with a central philosophical debate that continues to dominate human geography: the tension between the radical Marxist project of recent decades and the apparently disempowering relativism and `play of difference' of postmodern thought. In this book, Harvey continues to argue for a revised `post-Marxist' approach in human geography which remains based on Hegelian-Marxian principles of dialectical thought. This article develops a critique of that stance, drawing on the work of Jacques Derrida, Gilles Deleuze and Felix Guattari. I argue that dialectical thinking, as well as Harvey's version of `post-Marxism', has been undermined by the wide-ranging `post-' critique. I suggest that Harvey has failed to appreciate the full force of this critique and the implications it has for `post-Marxist' ontology and epistemology. I argue that `post-Marxism', along with much contemporary human geography, is constrained by an inflexible ontology which excessively prioritizes space in the theory produced, and which implements inflexible concepts. Instead, using the insights of several `post-' writers, I contend there is a need to develop an ontology of `context' leading to the production of `contextual theories'. Such theories utilize flexible concepts in a multilayered understanding of ontology and epistemology. I compare how an approach which produces a `contextual theory' might lead to more politically empowering theory than `post-Marxism' with reference to one of Harvey's case studies in JNGD

Population structures of Brazilian tall coconut (Cocos nucifera L.) by microsatellite markers

Coconut palms of the Tall group were introduced to Brazil from the Cape Verde Islands in 1553. The present study sought to evaluate the genetic diversity among and within Brazilian Tall coconut populations. Samples were collected of 195 trees from 10 populations. Genetic diversity was accessed by investigating 13 simple sequence repeats (SSR) loci. This provided a total of 68 alleles, ranging from 2 to 13 alleles per locus, with an average of 5.23. The mean values of gene diversity (He ) and observed heterozygosity (Ho ) were 0.459 and 0.443, respectively. The genetic differentiation among populations was estimated at θ^P=0.1600and the estimated apparent outcrossing rate was ta = 0.92. Estimates of genetic distances between the populations varied from 0.034 to 0.390. Genetic distance and the corresponding clustering analysis indicate the formation of two groups. The first consists of the Baía Formosa, Georgino Avelino, and São José do Mipibu populations and the second consists of the Japoatã, Pacatuba, and Praia do Forte populations. The correlation matrix between genetic and geographic distances was positive and significant at a 1% probability. Taken together, our results suggest a spatial structuring of the genetic variability among the populations. Geographically closer populations exhibited greater similarities

The Return of the Repressed: The Persistent and Problematic Claims of Long-Forgotten Trauma

Can purely psychological trauma lead to a complete blockage of autobiographical memories? This longstanding question about the existence of repressed memories has been at the heart of one of the most heated debates in modern psychology. These so-called memory wars originated in the 1990s and many scholars have assumed that they are over. We demonstrate that this assumption is incorrect and that the controversial issue of repressed memories is alive and well and may even be on the rise. We review converging research and data from legal cases indicating that the topic of repressed memories remains active in clinical, legal, and academic settings. We show that the belief in repressed memories occurs on a non-trivial-scale (58%) and appears to have increased among clinical psychologists since the 1990s. We also demonstrate that the scientifically controversial concept of dissociative amnesia, which we argue is a substitute term for memory repression, has gained in popularity. Finally, we review work onthe adverse side effects of certain psychotherapeutic techniques, some of which may be linked to the recovery of repressed memories. The memory wars have not vanished: They have continued to endure and contribute to potentially damaging consequences in clinical, legal, and academic contexts

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

Obesity, Metabolic Factors and Risk of Different Histological Types of Lung Cancer: A Mendelian Randomization Study

Background: Assessing the relationship between lung cancer and metabolic conditions is challenging because of the confounding effect of tobacco. Mendelian randomization (MR), or the use of genetic instrumental variables to assess causality, may help to identify the metabolic drivers of lung cancer. Methods and findings: We identified genetic instruments for potential metabolic risk factors and evaluated these in relation to risk using 29,266 lung cancer cases (including 11,273 adenocarcinomas, 7,426 squamous cell and 2,664 small cell cases) and 56,450 controls. The MR risk analysis suggested a causal effect of body mass index (BMI) on lung cancer risk for two of the three major histological subtypes, with evidence of a risk increase for squamous cell carcinoma (odds ratio (OR) [95% confidence interval (CI)] = 1.20 [1.01–1.43] and for small cell lung cancer (OR [95%CI] = 1.52 [1.15–2.00]) for each standard deviation (SD) increase in BMI [4.6 kg/m2]), but not for adenocarcinoma (OR [95%CI] = 0.93 [0.79–1.08]) (Pheterogeneity = 4.3x10-3). Additional analysis using a genetic instrument for BMI showed that each SD increase in BMI increased cigarette consumption by 1.27 cigarettes per day (P = 2.1x10-3), providing novel evidence that a genetic susceptibility to obesity influences smoking patterns. There was also evidence that low-density lipoprotein cholesterol was inversely associated with lung cancer overall risk (OR [95%CI] = 0.90 [0.84–0.97] per SD of 38 mg/dl), while fasting insulin was positively associated (OR [95%CI] = 1.63 [1.25–2.13] per SD of 44.4 pmol/l). Sensitivity analyses including a weighted-median approach and MR-Egger test did not detect other pleiotropic effects biasing the main results. Conclusions: Our results are consistent with a causal role of fasting insulin and low-density lipoprotein cholesterol in lung cancer etiology, as well as for BMI in squamous cell and small cell carcinoma. The latter relation may be mediated by a previously unrecognized effect of obesity on smoking behavior