Biology subjects

White, S. R.

Publications and source records attributed to White, S. R..

18 recordsLinked to original sources

bioRxiv2025

RHOV is a Detachment-Responsive Rho GTPase Necessary for Ovarian Cancer Peritoneal Metastasis

All ovarian cancer subtypes spread via transcoelomic metastasis, where cells disseminate into the peritoneal fluid, resist anoikis, and form multicellular aggregates that invade the peritoneum. This represents the main driver of morbidity and mortality for peritoneal cancer patients. Mechanisms necessary for cancer cells to survive matrix detachment and initiate transcoelomic metastasis remain poorly defined. To address this, we identified a conserved detachment-sensitive gene signature activated shortly after matrix-detachment across multiple ascites-derived cancer cell lines. RHOV, an atypical, constitutively active and understudied member of the Rho GTPase family, emerged as a top upregulated transcript, which was confirmed in patient ascites-derived tumor cells. Functionally, loss of RHOV impairs anoikis resistance, multicellular aggregate integrity, migration and invasion, and completely abolishes transcoelomic tumor progression in vivo. RHOV enhances c-Jun signaling and cytoskeletal remodeling, which is dependent on both RHOV GTP-binding and membrane localization. These findings define RHOV as a novel detachment-sensitive Rho GTPase and establish RHOV as a critical regulator of peritoneal metastasis for the first time.

cancer biology↗

bioRxiv2025

Charting structural brain asymmetry across the human lifespan

Lateralization is a fundamental principle of structural brain organization. In vivo imaging of brain asymmetry is essential for deciphering lateralized brain functions and their disruption in neurodevelopmental and neurodegenerative disorders. Here, we present a normative framework for benchmarking brain asymmetry across the lifespan, developed from an aggregated sample of 128 primary neuroimaging studies, including 177,701 scans from 138,231 individuals, jointly spanning the age range from 20 post menstrual weeks to 102 years. This resource includes comprehensive, hemisphere-specific brain growth charts for multiple neuroimaging phenotypes: regional cortical grey matter volume, thickness, surface area, and subcortical volumes. Our findings reveal distinct spatial patterns of asymmetry, with early leftward asymmetry observed in association cortices and late rightward asymmetry in sensory regions. These trajectories support theories of the neuroplasticity of asymmetry and the role of both genetic and environmental factors in shaping brain lateralization. Additionally, we provide tools to generate asymmetry centile scores, which allow the quantification of individual deviations from typical asymmetry throughout the lifespan and can be applied to unseen data or clinical populations. We demonstrate the utility of these models by highlighting group-level differences in asymmetry in autism spectrum disorder, schizophrenia, and Alzheimers disease, and exploring genetic correlations with hemispheric specialization. To facilitate further research, we have made this normative framework freely available as an interactive open-access resource (upon publication), offering an essential tool to advance both basic and clinical neuroscience.

neuroscience↗

bioRxiv2024

Loss of the predicted cell adhesion molecule MPZL3 promotes EMT and chemoresistance in ovarian cancer

Myelin protein zero-like 3 (MPZL3) is an Immunoglobulin-containing transmembrane protein with predicted cell adhesion molecule function. Loss of 11q23, where the MPZL3 gene resides, is frequently observed in cancer, and MPZL3 copy number alterations are frequently detected in tumor specimens. Yet the role and consequences of altered MPZL3 expression have not been explored in tumor development and progression. We addressed this in ovarian cancer, where both MPZL3 amplification and deletions are observed in respective subsets of high-grade serous specimens. While high and low MPZL3 expressing populations were similarly observed in primary ovarian tumors from an independent patient cohort, metastatic omental tumors largely displayed decreased MPZL3 expression, suggesting that MPZL3 loss is associated with metastatic progression. MPZL3 knock-down leads to strong upregulation of vimentin and an EMT gene signature that is associated with poor patient outcomes. Moreover, MPZL3 is necessary for homotypic cancer cell adhesion, and decreasing MPZL3 expression enhances invasion and clearance of mesothelial cell monolayers. In addition, MPZL3 loss abrogated cell cycle progression and proliferation. This was associated with increased resistance to Cisplatin and Olaparib and reduced DNA damage and apoptosis in response to these agents. Enhanced Cisplatin resistance was further validated in vivo. These data demonstrate for the first time that MPZL3 acts as an adhesion molecule and that MPZL3 loss results in EMT, decreased proliferation, and drug resistance in ovarian cancer. Our study suggests that decreased MPZL3 expression is a phenotype of ovarian cancer tumor progression and metastasis and may contribute to treatment failure in advanced-stage patients.

cancer biology↗

bioRxiv2024

The role of rat prelimbic cortex in decision making

The frontal cortex plays a critical role in decision-making. One specific frontal area, the anterior cingulate cortex, has been identified as crucial for setting a threshold for how much evidence is needed before a choice is made (Domenech & Dreher, 2010). Threshold is a key concept in drift diffusion models, a popular framework used to understand decision-making processes. Here, we investigated the role of the prelimbic cortex, part of the rodent cingulate cortex, in decision making. Male and female rats learned to choose between stimuli associated with high and low value rewards. Females learned faster, were more selective in their responses, and integrated information about the stimuli more quickly. By contrast, males learned more slowly and showed a decrease in their decision thresholds during choice learning. Inactivating the prelimbic cortex in female and male rats sped up decision making without affecting choice accuracy. Drift diffusion modeling found selective effects of prelimbic cortex inactivation on the decision threshold, which was reduced with increasing doses of the GABA-A agonist muscimol. Stimulating the prelimbic cortex through mu opioid receptors slowed the animals choice latencies and increased the decision threshold. These findings provide the first causal evidence that the prelimbic cortex directly influences decision processes. Additionally, they suggest possible sex-based differences in early choice learning.

neuroscience↗

bioRxiv2024

Learning to Choose: Behavioral Dynamics Underlying the Initial Acquisition of Decision Making

Current theories of decision making propose that decisions arise through competition between choice options. Computational models of the decision process estimate how quickly information about choice options is integrated and how much information is needed to trigger a choice. Experiments using this approach typically report data from well-trained participants. As such, we do not know how the decision process evolves as a decision-making task is learned for the first time. To address this gap, we used a behavioral design separating learning the value of choice options from learning to make choices. We trained male rats to respond to single visual stimuli with different reward values. Then, we trained them to make choices between pairs of stimuli. Initially, the rats responded more slowly when presented with choices. However, as they gained experience in making choices, this slowing reduced. Response slowing on choice trials persisted throughout the testing period. We found that it was specifically associated with increased exponential variability when the rats chose the higher value stimulus. Additionally, our analysis using drift diffusion modeling revealed that the rats required less information to make choices over time. Surprisingly, we observed reductions in the decision threshold after just a single session of choice learning. These findings provide new insights into the learning process of decision-making tasks. They suggest that the value of choice options and the ability to make choices are learned separately, and that experience plays a crucial role in improving decision-making performance.

neuroscience↗

bioRxiv2024

GPX3 supports ovarian cancer tumor progression in vivo and promotes expression of GDF15

ObjectiveWe previously reported that high expression of the extracellular glutathione peroxidase GPX3 is associated with poor patient outcome in ovarian serous adenocarcinomas, and that GPX3 protects ovarian cancer cells from oxidative stress in culture. Here we tested if GPX3 is necessary for tumor establishment in vivo and to identify novel downstream mediators of GPX3s pro-tumorigenic function. MethodsGPX3 was knocked-down in ID8 ovarian cancer cells by shRNA to test the role of GPX3 in tumor establishment using a syngeneic IP xenograft model. RNA sequencing analysis was carried out in OVCAR3 cells following shRNA-mediated GPX3 knock-down to identify GPX3-dependent gene expression signatures. ResultsGPX3 knock-down abrogated clonogenicity and intraperitoneal tumor development in vivo, and the effects were dependent on the level of GPX3 knock-down. RNA sequencing showed that loss of GPX3 leads to decreased gene expression patterns related to pro-tumorigenic signaling pathways. Validation studies identified GDF15 as strongly dependent on GPX3. GDF15, a member of the TGF-{beta} growth factor family, has known oncogenic and immune modulatory activities. Similarly, GPX3 expression positively correlated with pro-tumor immune cell signatures, including regulatory T-cell and macrophage infiltration, and displayed significant correlation with PD-L1 expression. ConclusionsWe show for the first time that tumor produced GPX3 is necessary for ovarian cancer growth in vivo and that it regulates expression of GDF15. The immune profile associated with GPX3 expression in serous ovarian tumors suggests that GPX3 may be an alternate marker of ovarian tumors susceptible to immune check-point inhibitors.

cancer biology↗

bioRxiv2023

Alternate splice variants of the mitochondrial fission protein DNM1L/Drp1 regulate mitochondrial dynamics and cell fate in ovarian cancer.

Aberrant mitochondrial fission/fusion dynamics have been reported in cancer cells. While post translational modifications are known regulators of the mitochondrial fission/fusion machinery, we show that alternative splice variants of the fission protein Drp1 (DNM1L) have specific and unique roles in cancer, adding to the complexity of mitochondrial fission/fusion regulation in tumor cells. Ovarian cancer specimens express an alternative splice transcript variant of Drp1 lacking exon 16 of the variable domain, and high expression of this splice variant relative to other transcripts is associated with poor patient outcome. Unlike the full-length variant, expression of Drp1 lacking exon 16 leads to decreased association of Drp1 to mitochondrial fission sites, more fused mitochondrial networks, enhanced respiration, and TCA cycle metabolites, and is associated with a more metastatic phenotype in vitro and in vivo. These pro-tumorigenic effects can also be inhibited by specific siRNA-mediated inhibition of the endogenously expressed transcript lacking exon 16. Moreover, lack of exon 16 abrogates mitochondrial fission in response to pro-apoptotic stimuli and leads to decreased sensitivity to chemotherapeutics. These data emphasize the significance of the pathophysiological consequences of Drp1 alternative splicing and divergent functions of Drp1 splice variants, and strongly warrant consideration of Drp1 splicing in future studies.

cancer biology↗

bioRxiv2023

Human adolescent brain network development is different for paralimbic versus neocortical systems

Adolescent development of human brain structural and functional networks is increasingly recognised as fundamental to emergence of typical and atypical adult cognitive and emotional processes. We analysed multimodal magnetic resonance imaging (MRI) data collected from N [~] 300 healthy adolescents (51%; female; 14-26 years) each scanned repeatedly in an accelerated longitudinal design, to provide an analyzable dataset of 469 structural scans and 448 functional MRI scans. We estimated the morphometric similarity between each possible pair of 358 cortical areas on a feature vector comprising six macro- and micro-structural MRI metrics, resulting in a morphometric similarity network (MSN) for each scan. Over the course of adolescence, we found that morphometric similarity increased in paralimbic cortical areas, e.g., insula and cingulate cortex, but generally decreased in neocortical areas; and these results were replicated in an independent developmental MRI cohort (N [~] 304). Increasing hubness of paralimbic nodes in MSNs was associated with increased strength of coupling between their morphometric similarity and functional connectivity. Decreasing hubness of neocortical nodes in MSNs was associated with reduced strength of structure-function coupling and increasingly diverse functional connections in the corresponding fMRI networks. Neocortical areas became more structurally differentiated and more functionally integrative in a metabolically expensive process linked to cortical thinning and myelination; whereas paralimbic areas specialised for affective and interoceptive functions became less differentiated, as hypothetically predicted by a developmental transition from peri-allocortical to pro-isocortical organization of cortex. Cytoarchitectonically distinct zones of human cortex undergo distinct neurodevelopmental programmes during typical adolescence.

neuroscience↗

bioRxiv2022

The rostral medial frontal cortex is crucial for engagement in consummatory behavior

The medial frontal cortex (MFC) in rodents emits rhythmic activity that is entrained to the animals licking cycle during consumption and encodes the value of consumed fluids (Horst and Laubach, 2013; Amarante et al., 2017; Amarante and Laubach, 2021). These signals are especially prominent in the rostral half of the MFC. This region is located above an orbitofrontal region where mu opioid receptors regulate intake (Mena et al., 2011; Castro and Berridge, 2017) and reversible inactivation reduces behavioral measures associated with the incentive value and palatability of liquid sucrose (Parent et al., 2015a). Here, we examined the effects of reversible inactivation and stimulation of mu opioid receptors in rostral MFC on behavior in an incentive contrast licking task. Adult male rats licked to receive access to liquid sucrose, which alternated between high (16%) and low (4%) values over 30 sec periods. Bilateral infusion of muscimol reduced the total number of licks emitted over the 30 min test sessions, the time spent actively consuming sucrose, and the ratio of licks for the higher and lower value fluids. Inactivation did not alter licking frequency or variability or microstructural measures such as the duration of licking bouts that are classically associated with the palatability of a liquid reward. Infusions of DAMGO (1g/L) at the same sites had inconsistent behavioral effects across different subjects. Our findings suggest that the rostral MFC has a distinct role in the control of consummatory behavior and contributes to peristent consumption and not to the expression of palatability. SIGNIFICANCE STATEMENTThe medial frontal cortex (MFC) of rodents has received attention in recent years and is considered as a singular cortical region with a potential unitary function. Increasing evidence suggests that MFC is composed of distinct subregions, with unique roles in the control of behavior. The present study adds to this literature by showing unique effects of reversibly inactivating the most rostral part of the medial frontal cortex and a lack of consistent effects of stimulating mu opioid receptors in the subregion. Findings are in contrast to previous reports on the more ventral orbitofrontal cortex and caudal medial frontal cortex and are important for understanding the general role of the rodent frontal cortex and how opioids may act to control behavior.

neuroscience↗

bioRxiv2021

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here, we built an interactive resource to benchmark brain morphology, www.brainchart.io, derived from any current or future sample of magnetic resonance imaging (MRI) data. With the goal of basing these reference charts on the largest and most inclusive dataset available, we aggregated 123,984 MRI scans from 101,457 participants aged from 115 days post-conception through 100 postnatal years, across more than 100 primary research studies. Cerebrum tissue volumes and other global or regional MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3; showed high stability of individual centile scores over longitudinal assessments; and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared to non-centiled MRI phenotypes, and provided a standardised measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In sum, brain charts are an essential first step towards robust quantification of individual deviations from normative trajectories in multiple, commonly-used neuroimaging phenotypes. Our collaborative study proves the principle that brain charts are achievable on a global scale over the entire lifespan, and applicable to analysis of diverse developmental and clinical effects on human brain structure. Furthermore, we provide open resources to support future advances towards adoption of brain charts as standards for quantitative benchmarking of typical or atypical brain MRI scans.

neuroscience↗

bioRxiv2020

An open source platform for presenting dynamic visual stimuli

Operant behavior procedures often rely on visual stimuli to cue the initiation or secession of a response, and to provide a means for discriminating between two or more simultaneously available responses. While primate and human studies typically use LCD or OLED monitors and touch screens, rodent studies use a variety of methods to present visual cues ranging from traditional incandescent light bulbs, single LEDs, and, more recently, touch screen monitors. Commercially available systems for visual stimulus presentation are costly, challenging to customize, and are typically closed source. We developed an open-source, highly-modifiable visual stimulus presentation platform that can be combined with a 3D-printed operant response device. The device uses an eight by eight matrix of LEDs, and can be expanded to control much larger LED matrices. Implementing the platform is low-cost (<$70 USD per device in the year 2020). Using the platform, we trained rats to make nosepoke responses and discriminate between two distinct visual cues in a location-independent manner. This visual stimulus presentation platform is a cost-effective way to implement complex visually-guided operant behavior, including the use of moving or dynamically changing visual stimuli. Significance StatementThe design of an open source and low cost device for presenting visual stimuli is described. It is capable of presenting complex visual patterns and dynamically changing stimuli. A practical demonstration of the device is also reported, from an experiment in which rats performed a luminance based visual discrimination. The device has utility for studying visual processing, psychophysics, and decision making in a variety of species.

neuroscience↗

bioRxiv2020

Asthma-associated variants induce IL33 differential expression through a novel regulatory region

Genome-wide association studies (GWAS) have implicated the IL33 locus in asthma, but the underlying mechanisms remain unclear. Here, we identify a 5 kb region within the GWAS-defined segment that acts as a strong regulatory element in vivo and in vitro. Chromatin conformation capture showed that this 5 kb region loops to the IL33 promoter, potentially regulating its expression. Supporting this notion, we show that genotype at an asthma-associated SNP, rs1888909, located within the 5 kb region, is associated with IL33 gene expression in human airway epithelial cells and IL-33 protein expression in human plasma, potentially through differential binding of OCT-1 (POU2F1) to the asthma-risk allele. Our data demonstrate that asthma-associated variants at the IL33 locus mediate allele-specific regulatory activity and IL33 expression, providing a novel mechanism through which a regulatory SNP contributes to genetic risk of asthma.

genomics↗

bioRxiv2020

BaseQTL: a Bayesian method to detect eQTLs from RNA-seq data with or without genotypes

Available methods to detect molecular quantitative trait loci (QTL) require study individuals to be genotyped. Here, we describe BaseQTL, a Bayesian method that exploits allele-specific expression to map molecular QTL from sequencing reads even when no genotypes are available. When used with genotypes, BaseQTL has lower error rates and increased power compared with existing QTL mapping methods. Running without genotypes limits how many tests can be performed, but due to the proximity of QTL variants to gene bodies, the 2.8% of variants within a 100kB-window that could be tested, contained 26% of QTL variants detectable with genotypes. eQTL effect estimates were invariably consistent between analyses performed with and without genotypes. Often, sequencing data may be generated in absence of genotypes on patients and controls in differential expression studies, and we identified an apparent psoriasis-specific effect for GSTP1 in one such dataset, providing new insights into disease-dependent gene regulation.

genomics↗

bioRxiv2020

Sexually dimorphic development of depression-related brain networks during healthy human adolescence

We hypothesized that there are sexual differences in human brain network development underlying the female > male divergence in adolescent depression. We tested for sex differences in parameters of brain network development (accelerated longitudinal fMRI, N=298 healthy adolescents, each scanned 1 to 3 times). Sexually divergent development of functional connectivity was located in default mode network (DMN), limbic cortex, and subcortical nuclei. Females had a more "disruptive" pattern of development, where weak functional connectivity at age 14 became stronger during adolescence. This fMRI-derived map of divergent adolescent development was co-located with (i) a map of functional dysconnectivity associated with adult major depressive disorder (MDD); and (ii) an adult brain gene expression pattern enriched for genes on the X chromosome, neurodevelopmental genes, and risk genes for MDD. Sexual divergence in disruptive development of DMN, limbic and subcortical functional networks is potentially relevant to the increased risk of depression in adolescent females.

neuroscience↗

bioRxiv2019

Characterising group-level brain connectivity: a framework using Bayesian exponential random graph models

The brain can be modelled as a network with nodes and edges derived from a range of imaging modalities: the nodes correspond to spatially distinct regions and the edges to the interactions between them. Whole-brain connectivity studies typically seek to determine how network properties change with a given categorical phenotype such as age-group, disease condition or mental state. To do so reliably, it is necessary to determine the features of the connectivity structure that are common across a group of brain scans. Given the complex interdependencies inherent in network data, this is not a straightforward task. Some studies construct a group-representative network (GRN), ignoring individual differences, while other studies analyse networks for each individual independently, ignoring information that is shared across individuals. We propose a Bayesian framework based on exponential random graph models (ERGM) extended to multiple networks to characterise the distribution of a entire population of networks. Using resting-state fMRI data from the Cam-CAN project, a study on healthy ageing, we demonstrate how our method can be used to characterise and compare the brains functional connectivity structure across a group of young individuals and a group of old individuals.

neuroscience↗

bioRxiv2018

Waves of maturation and senescence in micro-structural MRI markers of human cortical myelination over the lifespan

Seminal human brain histology work has demonstrated developmental waves of myelination. Here, using a micro-structural magnetic resonance imaging (MRI) marker linked to myelin, we studied fine-grained age differences to deduce waves of growth, stability, and decline of cortical myelination over the life-cycle. In 484 participants, aged 8-85 years, we fitted smooth growth curves to T1- to T2-weighted ratio in each of 360 regions from one of 7 cytoarchitectonic classes. From the first derivatives of these generally inverted-U trajectories, we defined three milestones: the age at peak growth; the age at onset of a stable plateau; and the age at the onset of decline. Age at peak growth had a bimodal distribution comprising an early (pre-pubertal) wave of primary sensory and motor cortices and a later (post-pubertal) wave of association, insular and limbic cortices. Most regions reached stability in the 30s but there was a second wave reaching stability in the 50s. Age at onset of decline was also bimodal: in some right hemisphere regions, the curve declined from the 60s, but in other left hemisphere regions, there was no significant decline from the stable plateau. These results are consistent with regionally heterogeneous waves of intracortical myelinogenesis and age-related demyelination.

neuroscience↗

bioRxiv2017

Gene co-expression networks in whole blood implicate multiple interrelated molecular pathways in obese asthma

BackgroundAsthmatic children who develop obesity have poorer outcomes compared to those that do not, including poorer control, more severe symptoms, and greater resistance to standard treatment. Gene expression networks are powerful statistical tools for characterizing the underpinnings of human disease that leverage the putative co-regulatory relationships of genes to infer biological pathways altered in disease states.\n\nObjectiveThe aim of this study was to characterize the biology of childhood asthma complicated by adult obesity.\n\nMethodsWe performed weighted gene co-expression network analysis (WGCNA) of gene expression data in whole blood from 514 adult subjects from the Childhood Asthma Management Program (CAMP). We then performed module preservation and association replication analyses in 418 subjects from two independent asthma cohorts (one pediatric and one adult).\n\nResultsWe identified a multivariate model in which four gene co-expression network modules were associated with incident obesity in CAMP (each P < 0.05). The module memberships were enriched for genes in pathways related to platelets, integrins, extracellular matrix, smooth muscle, NF-{kappa}B signaling, and Hedgehog signaling. The network structures of each of the four obese asthma modules were significantly preserved in both replication cohorts (permutation P = 9.999E-05). The corresponding module gene sets were significantly enriched for differential expression in obese subjects in both replication cohorts (each P < 0.05).\n\nConclusionsOur gene co-expression network profiles thus implicate multiple interrelated pathways in the biology of an important endotype of obese asthma.\n\nKey MessagesO_LIWe hypothesized that individuals with asthma complicated by obesity had distinct blood gene expression signatures.\nC_LIO_LIGene co-expression network analysis implicated several inflammatory biological pathways in one form of obese asthma.\nC_LI\n\nCapsule SummaryThis work addresses a knowledge gap about the molecular relationship between asthma and obesity, suggesting that an endotype of obese asthma, known as asthma complicated by obesity, is underpinned by coherent biological mechanisms.\n\nAbbreviations

genomics↗

bioRxiv2017

Assessing dynamic functional connectivity in heterogeneous samples

Several methods have been developed to measure dynamic functional connectivity (dFC) in fMRI data. These methods are often based on a sliding-window analysis, which aims to capture how the brains functional organization varies over the course of a scan. The aim of many studies is to compare dFC across groups, such as younger versus older people. However, spurious group differences in measured dFC may be caused by other sources of heterogeneity between people. For example, the shape of the haemodynamic response function (HRF) and levels of measurement noise have been found to vary with age. We use a generic simulation framework for fMRI data to investigate the effect of such heterogeneity on estimates of dFC. Our findings show that, despite no differences in true dFC, individual differences in measured dFC can result from other (non-dynamic) features of the data, such as differences in neural autocorrelation, HRF shape, connectivity strength and measurement noise. We also find that common dFC methods such as k-means and multilayer modularity approaches can detect spurious group differences in dynamic connectivity due to inappropriate setting of their hyperparameters. fMRI studies therefore need to consider alternative sources of heterogeneity across individuals before concluding differences in dFC.

neuroscience↗