Associations between maternal physical activity in early and late pregnancy and offspring birth size: remote federated individual level meta-analysis from eight cohort studies

OBJECTIVE

Evidence on the impact of leisure time physical activity (LTPA) in pregnancy on birth size is inconsistent. We aimed to examine the association between LTPA during early and late pregnancy and newborn anthropometric outcomes.

DESIGN

Individual level meta-analysis, which reduces heterogeneity across studies.

SETTING

A consortium of eight population-based studies (seven European and one US) comprising 72 694 participants.

METHODS

Generalised linear models with consistent inclusion of confounders (gestational age, sex, parity, maternal age, education, ethnicity, BMI, smoking, and alcohol intake) were used to test associations between self-reported LTPA at either early (8-18 weeks gestation) or late pregnancy (30+ weeks) and the outcomes. Results were pooled using random effects meta-analyses.

MAIN OUTCOME MEASURES

Birth weight, large-for-gestational age (LGA), macrosomia, small-for-gestational age (SGA), % body fat, and ponderal index at birth.

RESULTS

Late, but not early, gestation maternal moderate to vigorous physical activity (MVPA), vigorous activity, and LTPA energy expenditure were modestly inversely associated with BW, LGA, macrosomia, and ponderal index, without heterogeneity (all: I2  = 0%). For each extra hour/week of MVPA, RR for LGA and macrosomia were 0.97 (95% CI: 0.96, 0.98) and 0.96 (95% CI: 0.94, 0.98), respectively. Associations were only modestly reduced after additional adjustments for maternal BMI and gestational diabetes. No measure of LTPA was associated with risk for SGA.

CONCLUSIONS

Physical activity in late, but not early, pregnancy is consistently associated with modestly lower risk of LGA and macrosomia, but not SGA.

TWEETABLE ABSTRACT

In an individual participant meta-analysis, late pregnancy moderate to vigorous physical activity modestly reduced birth size outcomes.

A Novel CLCN5 Mutation Associated With Focal Segmental Glomerulosclerosis and Podocyte Injury

Introduction

Tubular dysfunction is characteristic of Dent’s disease; however, focal segmental glomerulosclerosis (FSGS) can also be present. Glomerulosclerosis could be secondary to tubular injury, but it remains uncertain whether the CLCN5 gene, which encodes an endosomal chloride and/or hydrogen exchanger, plays a role in podocyte biology. Here, we implicate a role for CLCN5 in podocyte function and pathophysiology.

Methods

Whole exome capture and sequencing of the proband and 5 maternally-related family members was conducted to identify X-linked mutations associated with biopsy-proven FSGS. Human podocyte cultures were used to characterize the mutant phenotype on podocyte function.

Results

We identified a novel mutation (L521F) in CLCN5 in 2 members of a Hispanic family who presented with a histologic diagnosis of FSGS and low-molecular-weight proteinuria without hypercalciuria. Presence of CLCN5 was confirmed in cultured human podocytes. Podocytes transfected with the wild-type or the mutant (L521F) CLCN5 constructs showed differential localization. CLCN5 knockdown in podocytes resulted in defective transferrin endocytosis and was associated with decreased cell proliferation and increased cell migration, which are hallmarks of podocyte injury.

Conclusions

The CLCN5 mutation, which causes Dent’s disease, may be associated with FSGS without hyercalcuria and nepthrolithiasis. The present findings supported the hypothesis that CLCN5 participates in protein trafficking in podocytes and plays a critical role in organizing the components of the podocyte slit diaphragm to help maintain normal cell physiology and a functional filtration barrier. In addition to tubular dysfunction, mutations in CLCN5 may also lead to podocyte dysfunction, which results in a histologic picture of FSGS that may be a primary event and not a consequence of tubular damage.

Earthworms are associated with subpopulations of Gammaproteobacteria irrespective of the total soil microbiota composition and stability

Soil represents one of the most complex microbial ecosystems on earth. It is well-known that invertebrates such as earthworms have a major impact on transformations of organic material in soil, while their effect on the soil microbiota remains largely unknown. The aim of our work was therefore to investigate the association of earthworms with temporal stability, composition and diversity in two soil microbiota experimental series. We found that earthworms were consistently associated with an increase in subgroups of Gammaproteobacteria, despite major differences in microbiota composition and temporal stability across the experimental series. Our results therefore suggest that earthworms can affect subpopulation dynamics in the soil microbiota, irrespective of the total microbiota composition. If the soil microbiota is comprised of independent microbiota components, this can contribute to our general understanding of the complexity of the soil microbiota.

Functional oncogene signatures guide rationally designed combination therapies to synergistically induce breast cancer cell death

A critical first step in the personalized approach to cancer treatment is the identification of activated oncogenes that drive each tumor. The Identification of driver oncogenes on a patient-by-patient basis is complicated by the complexity of the cancer genome and the fact that a particular genetic alteration may serve as a driver event only in a subset of tumors that harbor it. In this study, we set out to identify the complete set of functional oncogenes in a small panel of breast cancer cell lines. The cell lines in this panel were chosen because they each contain a known receptor tyrosine kinase (RTK) oncogene. To identify additional drivers, we integrated functional genetic screens with copy number and mutation analysis, and cancer genome knowledge databases. The resulting functional oncogene signatures were able to predict responsiveness of cell lines to targeted inhibitors. However, as single agents, these drugs had little effect on clonogenic potential. By contrast, treatment with drug combinations that targeted multiple oncogenes in the signatures, even at very low doses, resulted in the induction of apoptosis and striking synergistic effects on clonogenicity. In particular, targeting a driver oncogene that mediates AKT phosphorylation in combination with targeting the anti-apoptotic BCL2L1 protein had profound effects on cell viability. Importantly, because the synergistic induction of cell death was achieved using low levels of each individual drug, it suggests that a therapeutic strategy based on this approach could avoid the toxicities that have been associated with the combined use of multiple-targeted agents.

Human Orbitofrontal Cortex Represents a Cognitive Map of State Space

Although the orbitofrontal cortex (OFC) has been studied intensely for decades, its precise functions have remained elusive. We recently hypothesized that the OFC contains a "cognitive map" of task space in which the current state of the task is represented, and this representation is especially critical for behavior when states are unobservable from sensory input. To test this idea, we apply pattern-classification techniques to neuroimaging data from humans performing a decision-making task with 16 states. We show that unobservable task states can be decoded from activity in OFC, and decoding accuracy is related to task performance and the occurrence of individual behavioral errors. Moreover, similarity between the neural representations of consecutive states correlates with behavioral accuracy in corresponding state transitions. These results support the idea that OFC represents a cognitive map of task space and establish the feasibility of decoding state representations in humans using non-invasive neuroimaging.

A causal role for right frontopolar cortex in directed, but not random, exploration

The explore-exploit dilemma occurs anytime we must choose between exploring unknown options for information and exploiting known resources for reward. Previous work suggests that people use two different strategies to solve the explore-exploit dilemma: directed exploration, driven by information seeking, and random exploration, driven by decision noise. Here, we show that these two strategies rely on different neural systems. Using transcranial magnetic stimulation to inhibit the right frontopolar cortex, we were able to selectively inhibit directed exploration while leaving random exploration intact. This suggests a causal role for right frontopolar cortex in directed, but not random, exploration and that directed and random exploration rely on (at least partially) dissociable neural systems.

Complementary feature selection from alternative splicing events and gene expression for phenotype prediction

MOTIVATION

A central task of bioinformatics is to develop sensitive and specific means of providing medical prognoses from biomarker patterns. Common methods to predict phenotypes in RNA-Seq datasets utilize machine learning algorithms trained via gene expression. Isoforms, however, generated from alternative splicing, may provide a novel and complementary set of transcripts for phenotype prediction. In contrast to gene expression, the number of isoforms increases significantly due to numerous alternative splicing patterns, resulting in a prioritization problem for many machine learning algorithms. This study identifies the empirically optimal methods of transcript quantification, feature engineering and filtering steps using phenotype prediction accuracy as a metric. At the same time, the complementary nature of gene and isoform data is analyzed and the feasibility of identifying isoforms as biomarker candidates is examined.

RESULTS

Isoform features are complementary to gene features, providing non-redundant information and enhanced predictive power when prioritized and filtered. A univariate filtering algorithm, which selects up to the N highest ranking features for phenotype prediction is described and evaluated in this study. An empirical comparison of pipelines for isoform quantification is reported by performing cross-validation prediction tests with datasets from human non-small cell lung cancer (NSCLC) patients, human patients with chronic obstructive pulmonary disease (COPD) and amyotrophic lateral sclerosis (ALS) transgenic mice, each including samples of diseased and non-diseased phenotypes.

AVAILABILITY AND IMPLEMENTATION

https://github.com/clabuzze/Phenotype-Prediction-Pipeline.git

CONTACT

clabuzze@iastate.edu, antoniom@bc.edu, watsondk@musc.edu, andersonpe2@cofc.edu.

The effect of atomoxetine on random and directed exploration in humans

The adaptive regulation of the trade-off between pursuing a known reward (exploitation) and sampling lesser-known options in search of something better (exploration) is critical for optimal performance. Theory and recent empirical work suggest that humans use at least two strategies for solving this dilemma: a directed strategy in which choices are explicitly biased toward information seeking, and a random strategy in which decision noise leads to exploration by chance. Here we examined the hypothesis that random exploration is governed by the neuromodulatory locus coeruleus-norepinephrine system. We administered atomoxetine, a norepinephrine transporter blocker that increases extracellular levels of norepinephrine throughout the cortex, to 22 healthy human participants in a double-blind crossover design. We examined the effect of treatment on performance in a gambling task designed to produce distinct measures of directed exploration and random exploration. In line with our hypothesis we found an effect of atomoxetine on random, but not directed exploration. However, contrary to expectation, atomoxetine reduced rather than increased random exploration. We offer three potential explanations of our findings, involving the non-linear relationship between tonic NE and cognitive performance, the interaction of atomoxetine with other neuromodulators, and the possibility that atomoxetine affected phasic norepinephrine activity more so than tonic norepinephrine activity.

Molecular genetic analysis in 93 patients and 193 family members with classical congenital adrenal hyperplasia due to 21-hydroxylase deficiency in Croatia

Congenital adrenal hyperplasia owing to 21-hydroxylase deficiency is caused by mutation in the CYP21A2 gene. The frequency and spectrum of CYP21A2 mutations and genotype-phenotype correlations among different populations are variable. Aim of this study was to define mutation frequency and spectrum of CYP21A2 gene mutations in patients with classical 21-hydroxylase deficiency (21OHD) and their family members in Croatia and study genotype-phenotype correlation. Clinical features and mutations of CYP21A2 gene in 93 unrelated 21OHD patients and 193 family members were examined. In this cohort, 66 patients were affected with salt wasting (SW) form, and 27 were affected with simple virilizing (SV) form of the disease. Mutations were identified in both alleles (67% compound heterozygous and 33% homozygous) in 91 of 93 patients. Deletions and conversions were found in 18.8% and point mutations in 79.6% alleles. Mutations in 3 alleles (1.6%) remained unidentified (in one patient we found only one, while in other no mutations were found at all). The most common point mutations were Intron 2 splice mutation IVS2-13 A/C>G (35.5%) and p.R357W (16.7%). Genotypes were categorized into Groups 0, A, B and C according to the extent of enzyme impairment. Genotype-phenotype concordance was 100%, 85% and 75% for Groups 0, A and B, respectively. Since only classical 21OHD patients were studied, Group C comprised solely p.P31L mutation and had 73% patients with SV and 27% with SW phenotype. Intrafamilial phenotypic variability was found in two families. CYP21A2 genetic analysis in 193 family members showed that 126 parents were heterozygous carriers, 3 were newly discovered patients, 2 fathers were not biological parents, and mutations were not detected in 3. Among 59 siblings, 32 were heterozygous carriers, 15 carried normal alleles, and 12 were patients (4 newly diagnosed). Genotype-phenotype divergence observed in this study suggests caution in preconceptional counseling and prenatal diagnosis of CAH. High frequency of p.R357W mutation was found in Croatian patients with classical 21-OHD. Genotyping of family members discovered new patients and thus avoided pitfalls in genetic counseling when the parents were found to be affected.

Charting the expansion of strategic exploratory behavior during adolescence

Although models of exploratory decision making implicate a suite of strategies that guide the pursuit of information, the developmental emergence of these strategies remains poorly understood. This study takes an interdisciplinary perspective, merging computational decision making and developmental approaches to characterize age-related shifts in exploratory strategy from adolescence to young adulthood. Participants were 149 12-28-year-olds who completed a computational explore-exploit paradigm that manipulated reward value, information value, and decision horizon (i.e., the utility that information holds for future choices). Strategic directed exploration, defined as information seeking selective for long time horizons, emerged during adolescence and maintained its level through early adulthood. This age difference was partially driven by adolescents valuing immediate reward over new information. Strategic random exploration, defined as stochastic choice behavior selective for long time horizons, was invoked at comparable levels over the age range, and predicted individual differences in attitudes toward risk taking in daily life within the adolescent portion of the sample. Collectively, these findings reveal an expansion of the diversity of strategic exploration over development, implicate distinct mechanisms for directed and random exploratory strategies, and suggest novel mechanisms for adolescent-typical shifts in decision making. (PsycINFO Database Record

A novel mutation in HSD11B2 causes apparent mineralocorticoid excess in an Omani kindred

Apparent mineralocorticoid excess (AME) is a rare autosomal recessive genetic disorder causing severe hypertension in childhood due to a deficiency of 11β-hydroxysteroid dehydrogenase type 2 (11βHSD2), which is encoded by HSD11B2. Without treatment, chronic hypertension leads to early development of end-organ damage. Approximately 40 causative mutations in HSD11B2 have been identified in ∼100 AME patients worldwide. We have studied the clinical presentation, biochemical parameters, and molecular genetics in six patients from a consanguineous Omani family with AME. DNA sequence analysis of affected members of this family revealed homozygous c.799A>G mutations within exon 4 of HSD11B2, corresponding to a p.T267A mutation of 11βHSD2. The structural change and predicted consequences owing to the p.T267A mutation have been modeled in silico. We conclude that this novel mutation is responsible for AME in this family.

Systems analysis of the prostate transcriptome in African-American men compared with European-American men

AIM

African-Americans (AA) have increased prostate cancer risk and a greater mortality rate than European-Americans (EA). AA exhibit a high prevalence of vitamin D deficiency. We examined the global prostate transcriptome in AA and EA, and the effect of vitamin D₃ supplementation.

PATIENTS & METHODS

Twenty-seven male subjects (ten AA and 17 EA), slated to undergo prostatectomy were enrolled in the study. Fourteen subjects received vitamin D₃ (4000 IU daily) and 13 subjects received placebo for 2 months prior to surgery.

RESULTS

AA show higher expression of genes associated with immune response and inflammation.

CONCLUSION

Systems level analyses support the concept that Inflammatory processes may contribute to disease progression in AA. These transcripts can be modulated by a short course of vitamin D₃ supplementation.

Multivariate models from RNA-Seq SNVs yield candidate molecular targets for biomarker discovery: SNV-DA

BACKGROUND

It has recently been shown that significant and accurate single nucleotide variants (SNVs) can be reliably called from RNA-Seq data. These may provide another source of features for multivariate predictive modeling of disease phenotype for the prioritization of candidate biomarkers. The continuous nature of SNV allele fraction features allows the concurrent investigation of several genomic phenomena, including allele specific expression, clonal expansion and/or deletion, and copy number variation.

RESULTS

The proposed software pipeline and package, SNV Discriminant Analysis (SNV-DA), was applied on two RNA-Seq datasets with varying sample sizes sequenced at different depths: a dataset containing primary tumors from twenty patients with different disease outcomes in lung adenocarcinoma and a larger dataset of primary tumors representing two major breast cancer subtypes, estrogen receptor positive and triple negative. Predictive models were generated using the machine learning algorithm, sparse projections to latent structures discriminant analysis. Training sets composed of RNA-Seq SNV features limited to genomic regions of origin (e.g. exonic or intronic) and/or RNA-editing sites were shown to produce models with accurate predictive performances, were discriminant towards true label groupings, and were able to produce SNV rankings significantly different from than univariate tests. Furthermore, the utility of the proposed methodology is supported by its comparable performance to traditional models as well as the enrichment of selected SNVs located in genes previously associated with cancer and genes showing allele-specific expression. As proof of concept, we highlight the discovery of a previously unannotated intergenic locus that is associated with epigenetic regulatory marks in cancer and whose significant allele-specific expression is correlated with ER+ status; hereafter named ER+ associated hotspot (ERPAHS).

CONCLUSION

The use of models from RNA-Seq SNVs to identify and prioritize candidate molecular targets for biomarker discovery is supported by the ability of the proposed method to produce significantly accurate predictive models that are discriminant towards true label groupings. Importantly, the proposed methodology allows investigation of mutations outside of exonic regions and identification of interesting expressed loci not included in traditional gene annotations. An implementation of the proposed methodology is provided that allows the user to specify SNV filtering criteria and cross-validation design during model creation and evaluation.

Amplification of WHSC1L1 regulates expression and estrogen-independent activation of ERα in SUM-44 breast cancer cells and is associated with ERα over-expression in breast cancer

The 8p11‐p12 amplicon occurs in approximately 15% of breast cancers in aggressive luminal B‐type tumors. Previously, we identified WHSC1L1 as a driving oncogene from this region. Here, we demonstrate that over‐expression of WHSC1L1 is linked to over‐expression of ERα in SUM‐44 breast cancer cells and in primary human breast cancers. Knock‐down of WHSC1L1, particularly WHSC1L1‐short, had a dramatic effect on ESR1 mRNA and ERα protein levels. SUM‐44 cells do not require exogenous estrogen for growth in vitro; however, they are dependent on ERα expression, as ESR1 knock‐down or exposure to the selective estrogen receptor degrader fulvestrant resulted in growth inhibition. ChIP‐Seq experiments utilizing ERα antibodies demonstrated extensive ERα binding to chromatin in SUM‐44 cells under estrogen‐free conditions. ERα bound to ERE and FOXA1 motifs under estrogen‐free conditions and regulated expression of estrogen‐responsive genes. Short‐term treatment with estradiol enhanced binding of ERα to chromatin and influenced expression of many of the same genes to which ERα was bound under estrogen‐free conditions. Finally, knock‐down of WHSC1L1 in SUM‐44 cells resulted in loss of ERα binding to chromatin under estrogen‐free conditions, which was restored upon exposure to estradiol. These results indicate the SUM‐44 cells are a good model of a subset of luminal B breast cancers that have the 8p11‐p12 amplicon, over‐express WHSC1L1, and over‐express ERα, but are independent of estrogen for binding to chromatin and regulation of gene expression. Breast cancers such as these, that are dependent on ERα activity but independent of estradiol, are a major cause of breast cancer mortality.

SUM44 is a model cell line for ERα positive breast cancer with the 8p11 amplicon.

WHSC1L1 is a driving oncogene from the 8p11 amplicon in SUM44 cells.

SUM44 breast cancer cells have high ERα expression, regulated by WHSC1L1 knockdown.

ERα is required for growth and survival of SUM44 cells but is estrogen‐independent.

WHSC1L1 knock‐down re‐sensitizes ERα to estradiol for binding to essential genes.

Bayesian Modeling of the Dynamics of Phase Modulations and their Application to Auditory Event Related Potentials at Different Loudness Scales

We study the effect of long-term habituation signatures of auditory selective attention reflected in the instantaneous phase information of the auditory event-related potentials (ERPs) at four distinct stimuli levels of 60, 70, 80, and 90 dB SPL. The analysis is based on the single-trial level. The effect of habituation can be observed in terms of the changes (jitter) in the instantaneous phase information of ERPs. In particular, the absence of habituation is correlated with a consistently high phase synchronization over ERP trials. We estimate the changes in phase concentration over trials using a Bayesian approach, in which the phase is modeled as being drawn from a von Mises distribution with a concentration parameter which varies smoothly over trials. The smoothness assumption reflects the fact that habituation is a gradual process. We differentiate between different stimuli based on the relative changes and absolute values of the estimated concentration parameter using the proposed Bayesian model.

Is Model Fitting Necessary for Model-Based fMRI?

Model-based analysis of fMRI data is an important tool for investigating the computational role of different brain regions. With this method, theoretical models of behavior can be leveraged to find the brain structures underlying variables from specific algorithms, such as prediction errors in reinforcement learning. One potential weakness with this approach is that models often have free parameters and thus the results of the analysis may depend on how these free parameters are set. In this work we asked whether this hypothetical weakness is a problem in practice. We first developed general closed-form expressions for the relationship between results of fMRI analyses using different regressors, e.g., one corresponding to the true process underlying the measured data and one a model-derived approximation of the true generative regressor. Then, as a specific test case, we examined the sensitivity of model-based fMRI to the learning rate parameter in reinforcement learning, both in theory and in two previously-published datasets. We found that even gross errors in the learning rate lead to only minute changes in the neural results. Our findings thus suggest that precise model fitting is not always necessary for model-based fMRI. They also highlight the difficulty in using fMRI data for arbitrating between different models or model parameters. While these specific results pertain only to the effect of learning rate in simple reinforcement learning models, we provide a template for testing for effects of different parameters in other models.

In recent years, model-based fMRI has emerged as a powerful technique in psychology and neuroscience. With this method, computational models of behavior can be leveraged to identify where, whether and how different algorithms are implemented in the brain. Yet this approach seems to have an Achilles heel in that the models frequently have free parameters, and errors in setting these parameters could lead to errors in interpretation of the data. Here we asked whether this potential weakness, in theory, is an actual weakness in practice. In particular, we tested whether errors in estimating participants’ learning rate in a trial-and-error reinforcement learning setting would have adverse effects on identifying the neural substrates of the learning process. Amazingly, it turns out that even gross errors in the learning rate lead to only minute changes in the neural results. The good news is that precise identification of free parameters is not always necessary; the corollary bad news is that it may be harder to identify the precise computational roles of different brain areas than we had previously appreciated. Based on our analytical results, we offer suggestions for designing experiments that maximize or minimize sensitivity to model parameters, as needed.

Integrative "omic" analysis reveals distinctive cold responses in leaves and roots of strawberry, Fragaria × ananassa 'Korona'

To assess underlying metabolic processes and regulatory mechanisms during cold exposure of strawberry, integrative "omic" approaches were applied to Fragaria × ananassa Duch. 'Korona.' Both root and leaf tissues were examined for responses to the cold acclimation processes. Levels of metabolites, proteins, and transcripts in tissues from plants grown at 18°C were compared to those following 1-10 days of cold (2°C) exposure. When leaves and roots were subjected to GC/TOF-MS-based metabolite profiling, about 160 compounds comprising mostly structurally annotated primary and secondary metabolites, were found. Overall, 'Korona' showed a modest increase of protective metabolites such as amino acids (aspartic acid, leucine, isoleucine, and valine), pentoses, phosphorylated and non-phosphorylated hexoses, and distinct compounds of the raffinose pathway (galactinol and raffinose). Distinctive responses were observed in roots and leaves. By 2DE proteomics a total of 845 spots were observed in leaves; 4.6% changed significantly in response to cold. Twenty-one proteins were identified, many of which were associated with general metabolism or photosynthesis. Transcript levels in leaves were determined by microarray, where dozens of cold associated transcripts were quantitatively characterized, and levels of several potential key contributors (e.g., the dehydrin COR47 and GADb) to cold tolerance were confirmed by qRT-PCR. Cold responses are placed within the existing knowledge base of low temperature-induced changes in plants, allowing an evaluation of the uniqueness or generality of Fragaria responses in photosynthetic tissues. Overall, the cold response characteristics of 'Korona' are consistent with a moderately cold tolerant plant.

Humans use directed and random exploration to solve the explore-exploit dilemma

All adaptive organisms face the fundamental tradeoff between pursuing a known reward (exploitation) and sampling lesser-known options in search of something better (exploration). Theory suggests at least two strategies for solving this dilemma: a directed strategy in which choices are explicitly biased toward information seeking, and a random strategy in which decision noise leads to exploration by chance. In this work we investigated the extent to which humans use these two strategies. In our "Horizon task," participants made explore-exploit decisions in two contexts that differed in the number of choices that they would make in the future (the time horizon). Participants were allowed to make either a single choice in each game (horizon 1), or 6 sequential choices (horizon 6), giving them more opportunity to explore. By modeling the behavior in these two conditions, we were able to measure exploration-related changes in decision making and quantify the contributions of the two strategies to behavior. We found that participants were more information seeking and had higher decision noise with the longer horizon, suggesting that humans use both strategies to solve the exploration-exploitation dilemma. We thus conclude that both information seeking and choice variability can be controlled and put to use in the service of exploration.

Oncogenic signaling in amphiregulin and EGFR-expressing PTEN-null human breast cancer

A subset of triple negative breast cancer (TNBC) is characterized by overexpression of the epidermal growth factor receptor (EGFR) and loss of PTEN, and patients with these determinants have a poor prognosis. We used cell line models of EGFR‐positive/PTEN null TNBC to elucidate the signaling networks that drive the malignant features of these cells and cause resistance to EGFR inhibitors. In these cells, amphiregulin (AREG)‐mediated activation of EGFR results in up‐regulation of fibronectin (FN1), which is known to be a mediator of invasive capacity via interaction with integrin β1. EGFR activity in this PTEN null background also results in Wnt/beta‐catenin signaling and activation of NF‐κB. In addition, AKT is constitutively phosphorylated in these cells and is resistant to gefitinib. Expression profiling demonstrated that AREG‐activated EGFR regulates gene expression differently than EGF‐activated EGFR, and functional analysis via genome‐scale shRNA screening identified a set of genes, including PLK1 and BIRC5, that are essential for survival of SUM‐149 cells, but are uncoupled from EGFR signaling. Thus, our results demonstrate that in cells with constitutive EGFR activation and PTEN loss, critical survival genes are uncoupled from regulation by EGFR, which likely mediates resistance to EGFR inhibitors.

Activation of EGFR by AREG alters signaling and gene expression compared to EGF.

Activation of EGFR by AREG reduces mTORC1 pathway expression and phosphorylation.

EGF‐positive, PTEN‐null TNBC cells are poised for Wnt/beta‐catenin signaling.

Wnt/beta‐catenin activity occurs in a subset of cells and is enhanced in mammospheres.

Regulation of growth/survival genes is uncoupled from EGFR in PTEN‐null TNBC cells.

FLI1 expression is correlated with breast cancer cellular growth, migration, and invasion and altered gene expression

ETS factors have been shown to be dysregulated in breast cancer. ETS factors control the expression of genes involved in many biological processes, such as cellular proliferation, differentiation, and apoptosis. FLI1 is an ETS protein aberrantly expressed in retrovirus-induced hematological tumors, but limited attention has been directed towards elucidating the role of FLI1 in epithelial-derived cancers. Using data mining, we show that loss of FLI1 expression is associated with shorter survival and more aggressive phenotypes of breast cancer. Gain and loss of function cellular studies indicate the inhibitory effect of FLI1 expression on cellular growth, migration, and invasion. Using Fli1 mutant mice and both a transgenic murine breast cancer model and an orthotopic injection of syngeneic tumor cells indicates that reduced Fli1 contributes to accelerated tumor growth. Global expression analysis and RNA-Seq data from an invasive human breast cancer cell line with over expression of either FLI1 and another ETS gene, PDEF, shows changes in several cellular pathways associated with cancer, such as the cytokine-cytokine receptor interaction and PI3K-Akt signaling pathways. This study demonstrates a novel role for FLI1 in epithelial cells. In addition, these results reveal that FLI1 down-regulation in breast cancer may promote tumor progression.

Defective Kernel 1 (DEK1) is required for three-dimensional growth in Physcomitrella patens

Orientation of cell division is critical for plant morphogenesis. This is evident in the formation and function of meristems and for morphogenetic transitions. Mosses undergo such transitions: from two-dimensional tip-growing filaments (protonema) to the generation of three-dimensional leaf-like structures (gametophores). The Defective Kernel 1 (DEK1) protein plays a key role in the perception of and/or response to positional cues that specify the formation and function of the epidermal layer in developing seeds of flowering plants. The moss Physcomitrella patens contains the highly conserved DEK1 gene. Using efficient gene targeting, we generated a precise PpDEK1 deletion (∆dek1), which resulted in normal filamentous growth of protonema. Two distinct mutant phenotypes were observed: an excess of buds on the protonema, and abnormal cell divisions in the emerging buds resulting in developmental arrest and the absence of three-dimensional growth. Overexpression of a complete PpDEK1 cDNA, or the calpain domain of PpDEK1 alone, successfully complements both phenotypes. These results in P. patens demonstrate the morphogenetic importance of the DEK1 protein in the control of oriented cell divisions. As it is not for protonema, it will allow dissection of the structure/function relationships of the different domains of DEK1 using gene targeting in null mutant background.

Orbitofrontal cortex as a cognitive map of task space

Orbitofrontal cortex (OFC) has long been known to play an important role in decision making. However, the exact nature of that role has remained elusive. Here, we propose a unifying theory of OFC function. We hypothesize that OFC provides an abstraction of currently available information in the form of a labeling of the current task state, which is used for reinforcement learning (RL) elsewhere in the brain. This function is especially critical when task states include unobservable information, for instance, from working memory. We use this framework to explain classic findings in reversal learning, delayed alternation, extinction, and devaluation as well as more recent findings showing the effect of OFC lesions on the firing of dopaminergic neurons in ventral tegmental area (VTA) in rodents performing an RL task. In addition, we generate a number of testable experimental predictions that can distinguish our theory from other accounts of OFC function.

The catalytic domain CysPc of the DEK1 calpain is functionally conserved in land plants

DEK1, the single calpain of land plants, is a member of the ancient membrane bound TML-CysPc-C2L calpain family that dates back 1.5 billion years. Here we show that the CysPc-C2L domains of land plant calpains form a separate sub-clade in the DEK1 clade of the phylogenetic tree of plants. The charophycean alga Mesostigma viride DEK1-like gene is clearly divergent from those in land plants, suggesting that a major evolutionary shift in DEK1 occurred during the transition to land plants. Based on genetic complementation of the Arabidopsis thaliana dek1-3 mutant using CysPc-C2L domains of various origins, we show that these two domains have been functionally conserved within land plants for at least 450 million years. This conclusion is based on the observation that the CysPc-C2L domains of DEK1 from the moss Physcomitrella patens complements the A. thaliana dek1-3 mutant phenotype. In contrast, neither the CysPc-C2L domains from M. viride nor chimeric animal-plant calpains complement this mutant. Co-evolution analysis identified differences in the interactions between the CysPc-C2L residues of DEK1 and classical calpains, supporting the view that the two enzymes are regulated by fundamentally different mechanisms. Using the A. thaliana dek1-3 complementation assay, we show that four conserved amino acid residues of two Ca²⁺-binding sites in the CysPc domain of classical calpains are conserved in land plants and functionally essential in A. thaliana DEK1.