Biology subjects

Brown, C.

Publications and source records attributed to Brown, C..

11 recordsLinked to original sources

bioRxiv2026

Patient-Derived Glioma Models Preserve Tumor Heterogeneity and Identify Stearoyl-CoA Desaturase1 (SCD1) as a Candidate Biomarker for Precision Immunotherapy

Background: Pediatric and adult brain tumors, including glioblastoma, astrocytoma, ependymoma, and medulloblastoma, remain associated with poor prognosis despite advances in surgery, radiation, and chemotherapy. Therapeutic resistance, tumor heterogeneity, and treatment-related toxicity highlight the need for clinically relevant models that enable precision medicine and immunotherapy development. Methods: Freshly dispersed tumors (FDTs), low-passage patient-derived brain tumor (PBT) spheroid lines, and matched patient-derived xenograft (PDX) models were established from patients with primary brain tumors. Models were characterized using single-cell and bulk RNA sequencing, whole-exome sequencing, multiparameter flow cytometry, and immunohistochemistry. PBTs were compared with matched FDTs to evaluate model fidelity. Results: PBT lines were established in approximately 68% of cases and retained key patient-specific genomic alterations, including IDH1, MGMT, TP53, and PTEN, with expression of therapeutically relevant targets, including IL13R2, EGFR, HER2, WNT1, JAK1/2, and NOTCH1-4. Gene expression profiles of PBTs closely correlated with matched FDTs (R = 0.38, P = 0.0038). PBT and PDX models preserved intratumoral heterogeneity and non-clonal populations, enabling identification of therapy-resistant subclones during in vitro selection. Molecular analyses identified Stearoyl-CoA Desaturase1 (SCD1) as an overexpressed biomarker across glioma PBTs and matched patient tumors. Ingenuity Pathway Analysis identified SCD1 as an upstream regulator of EGFR-, TP53-, and CYCS-associated signaling networks implicated in tumor progression and immune suppression. Conclusions: Clinically relevant PBT and matched PDX models recapitulate molecular, transcriptional, and histopathological characteristics of primary brain tumors. These platforms provide tools for biomarker discovery, therapeutic testing, and precision immunotherapy development, while identifying SCD1 as a biomarker and therapeutic target in glioma.

cancer biology↗

bioRxiv2018

Life-history traits inform on population trends when assessing the conservation status of a declining tiger shark population

The assessment of the conservation status of wide ranging species depends on estimates of the magnitude of their population trends. The accuracy of trend estimates will depend on where and how many locations within a species range are sampled. We ask how the spatial extent of sampling interacts with non-linear patterns in long-term trends to affect estimates of decline in standardised catch of tiger sharks (Galeocerdo cuvier) on the east coast of Australia. We apply a Bayesian trend model that uses prior information on life-history traits to estimate trends where we use data from all regions versus spatial subsets of the data. As more regions were included in the model the trend estimates converged towards an overall decline of 71% over three generations. Trends estimated from data only from northern regions or southern regions underestimated and overestimated the regional decline, respectively. When a subset of regions was modelled, rather than the full data-set, the prior informed by life-history traits performed well, as did a weakly informed prior that allowed for high variation. The rate of decline in tiger sharks is consistent with a listing East Coast Australia tiger sharks as endangered under local legislation. Monitoring programs that aim to estimate population trends should attempt to cover the extremes and mid-points of a populations range. Life-history information can be used to inform priors for population variation and may give more accurate estimates of trends that can be justified in debates about the status of threatened species, particularly when sampling is limited.

ecology↗

bioRxiv2018

Hippo Pathway Deregulation Drives Tissue Stiffness and Cancer Stem-like Cells in Lung Adenocarcinoma

Lung cancer remains the leading cause of cancer-related death due to poor treatment responses arising from tumor heterogeneity and epigenetic aberrations. Here we show that adverse prognosis associated with epigenetically silenced tumour suppressor RASSF1A is a consequence of increased extracellular matrix, tumour stiffness and metastatic dissemination in vivo and in vitro. We find that lung cancer cells with methylated RASSF1A display constitutive nuclear YAP1 and expression of prolyl4hydroxylase2 (P4HA2) into extracellular matrix that correlates with increases collagen deposition. Furthermore, we identify an epigenetic axis in tumour cells where elevated ECM impedes the intrinsic suppression of WNT signaling (via TPBG/5T4) triggering b-catenin-YAP1 activation and thus results in a cancer stem-like programming. As key drivers, we identified RASSF1A and P4HA2 mediating the ECM-dependent stemness and metastatic dissemination in vivo. Re-expression of RASSF1A or inhibition of P4HA2 activity reverse these effects and increase levels of lung differentiation markers (TTF-1, Mucin5B) in vivo and in vitro. Our study identifies an epigenetic program to cancer stemness and metastatic progression of lung adenocarcinoma and P4HA2 as potential target for uncoupling ECM signals towards cancer stemness.

cancer biology↗

bioRxiv2018

Neural representations of aversive value encoding in pain catastrophizers

Chronic pain is exacerbated by maladaptive cognition such as pain catastrophizing (PC). Biomarkers of PC mechanisms may aid precision medicine for chronic pain. Here, we investigate EEG biomarkers using mass univariate and multivariate (machine learning) approaches. We test theoretical notions that PC results from a combination of augmented aversive-value encoding (\"magnification\") and persistent expectations of pain (\"rumination\"). Healthy individuals with high or low levels of PC underwent an experimental pain model involving nociceptive laser stimuli preceded by cues predicting forthcoming pain intensity. Analysis of EEG acquired during the cue and laser stimulation provided event-related potentials (ERPs) identifying spatially and temporally-extended neural representations associated with pain catastrophizing. Specifically, differential neural responses to cues predicting high vs. low intensity pain (i.e. aversive value encoding) were larger in the high PC group, largely originating from mid-cingulate and superior parietal cortex. Multivariate spatiotemporal EEG patterns evoked from cues with high aversive value selectively and significantly differentiated the high PC from low PC group (64.6% classification accuracy). Regression analyses revealed that neural patterns classifying groups could be partially predicted (R2 = 28%) from those neural patterns classifying the aversive value of cues. In contrast, behavioural and EEG analyses did not provide evidence that PC modifies more persistent effects of prior expectation on pain perception and nociceptive responses. These findings support the hypothesis of magnification of aversive value encoding but not persistent expression of expectation in pain catastrophizers. Multivariate patterns of aversive value encoding provide promising biomarkers of maladaptive cognitive responses to chronic pain that have future potential for psychological treatment development and clinical stratification.

neuroscience↗

bioRxiv2018

Transposable elements generate regulatory novelty in a tissue specific fashion

BackgroundTransposable elements (TE) are an important source of evolutionary novelty in gene regulation. However, the mechanisms by which TEs contribute to gene expression are largely uncharacterized.\n\nResultsHere, we leverage Roadmap and GTEx data to investigate the association of TEs with active and repressed chromatin in 24 tissues. We find 112 human TE types enriched in active regions of the genome across tissues. SINEs and DNA transposons are the most frequently enriched classes, while LTRs are often enriched in a tissue-specific manner. We report across-tissue variability in TE enrichment in active regions. Genes with consistent expression across tissues are less likely to be associated with TE insertions. TE presence in repressed regions similarly follows tissue-specific patterns. Moreover, different TE classes correlate with different repressive marks: Long Terminal Repeat Retrotransposons (LTRs) and Long Interspersed Nuclear Elements (LINEs) are overrepresented in regions marked by H3K9me3, while the other TEs are more likely to overlap regions with H3K27me3. Young TEs are typically enriched in repressed regions and depleted in active regions. We detect multiple instances of TEs that are enriched in tissue-specific active regulatory regions. Such TEs contain binding sites for transcription factors that are master regulators for the given tissue. These TEs are enriched in intronic enhancers, and their tissue-specific enrichment correlates with tissue-specific variations in the expression of the nearest genes.\n\nConclusionsWe provide an integrated overview of the contribution of TEs to human gene regulation. Expanding previous analyses, we demonstrate that TEs can potentially contribute to the turnover of regulatory sequences in a tissue-specific fashion.

genomics↗

bioRxiv2018

Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease

PurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.\n\nMethodsUsing a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.\n\nResultsWe found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing of de-novo CNVs.\n\nConclusionRobust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.

genomics↗

bioRxiv2017

The cost of enforcing marine protected areas to achieve ecological targets

Protected areas are the primary management tool for conserving ecosystems, yet their intended outcomes may often be compromised by poaching. Consequently, many protected areas are ineffective paper parks that contribute little towards conserving ecosystems. Poaching can be prevented through enforcement and engaging with community members so they support protected areas. It is not clear how much needs to be spent on enforcement and engagement to ensure they are frequent enough to be effective at conserving biodiversity. We develop models of enforcement against illegal fishing in marine protected areas. We apply the models to data on fishing rates and fish biomass from a marine protected area in Raja Ampat, Indonesia and explore how frequent enforcement patrols need to be to achieve targets for coral reef fish biomass. Achieving pristine levels of reef fish biomass required almost year-round enforcement of the protected area. Surveillance of the protected area may also be enhanced if local fishers who support the reserve report on poaching. The opportunity for local fishing boats to participate in surveillance was too small for it to have much benefit for total reef fish biomass, which increases slowly. However, specific functional groups of fish have much higher population growth rates and their biomass was predicted to increase markedly with community surveillance. We conclude that budgets for park management must balance the cost of conducting frequent patrols against supporting alternative activities, like education to build community support. Optimized budgets will be much more likely to achieve ecological targets for recovering fish biomasses and will contribute to fiscal sustainability of protected areas.

ecology↗

bioRxiv2017

Estimating the footprint of pollution on coral reefs using models of species turn-over

Ecological communities typically change along gradients of human impact, though it is difficult to estimate the footprint of impacts for diffuse threats like pollution. Here we develop a joint model of benthic habitats on lagoonal coral reefs and use it to infer change in benthic composition along a gradient of distance from logging operations. The model estimates both changes in abundances of benthic groups and their compositional turn-over, a type of beta-diversity. We detect compositional turnover across the gradient and use the model to predict the footprint of turbidity impacts from logging. We then apply the model to predict impacts of recent logging activities, finding recent impacts to be small, because recent logging has occurred far from lagoonal reefs. Our model can be used more generally to estimate the footprint of human impacts on ecosystems and evaluate the benefits of conservation actions for ecosystems.

ecology↗

bioRxiv2017

A dementia-associated risk variant near TMEM106B alters chromatin architecture and gene expression

Neurodegenerative diseases pose an extraordinary threat to the worlds aging population, yet no disease-modifying therapies are available. While genome-wide association studies (GWAS) have identified hundreds of novel risk loci for neurodegeneration, the mechanisms by which these loci influence disease risk are largely unknown. Indeed, of the many thousands of SNP-trait associations identified by GWAS over the past ~10 years, very few are understood mechanistically. Here, we investigate the association of common genetic variants at the 7p21 locus with risk for the neurodegenerative disease frontotemporal lobar degeneration. We show that variants associated with disease risk correlate with increased brain expression of the 7p21 gene TMEM106B, and no other genes. Furthermore, incremental increases in TMEM106B levels result in incremental increases in lysosomal phenotypes and cell toxicity. We then combine fine-mapping, bioinformatics, and bench-based approaches to functionally characterize all candidate causal variants at this locus. This approach identified a noncoding variant, rs1990620, which differentially recruits CTCF, influencing CTCF-mediated long-range chromatin looping interactions between multiple cis-regulatory elements, including the TMEM106B promoter. Our findings thus provide an in-depth analysis of the 7p21 locus linked by GWAS to frontotemporal lobar degeneration, nominating a causal variant and a causal mechanism for allele-specific expression and disease association at this locus. Finally, we show that genetic variants associated with risk for neurodegenerative diseases beyond frontotemporal lobar degeneration are enriched in brain CTCF-binding sites genome-wide, implicating CTCF-mediated gene regulation in risk for neurodegeneration more generally.

genetics↗

bioRxiv2017

Altered neurocognitive processing of tactile stimuli in patients with Complex Regional Pain Syndrome (CRPS)

Chronic pain in CRPS has been linked to tactile misperceptions and deficits in somatotopic representation of the affected limb. Here, we identify altered cognitive processing of tactile stimuli in CRPS patients that we propose marks heterogeneity in tactile decision-making mechanisms. In a case-control design, we compared middle and late-latency somatosensory-evoked potentials (SEPs) in response to pseudo-randomised mechanical stimulation of the digits of both hands (including CRPS-affected and non-affected sides) between 13 CRPS patients and 13 matched healthy controls. During a task to discriminate the digit simulated, patients (compared to controls) had significantly lower accuracy and slowed response times but with high between-subject variability. At middle latencies (124-132 ms), tactile processing in patients relative to controls showed decrements in superior parietal lobe and precuneus (that were independent of task demands) but enhanced activity in superior frontal lobe (that were task-dependent). At late latencies, patients showed an augmented P300-like response under task demands that localised to supplementary motor area (SMA). Source activity in SMA correlated with slowed response times, while its scalp representation intriguingly correlated with better functioning of the affected limb, suggesting a compensatory mechanism. Future research should investigate the clinical utility of these putative markers of tactile decision-making mechanisms in CRPS.\n\nDisclosuresThe research was supported by funding from Cambridge Arthritis Research Endeavour (CARE). The study was sponsored by Cambridge University Hospitals NHS Foundation Trust and supported by its Rheumatology department. The authors report no conflicts of interest.\n\nPerspectiveWe present evidence of altered but highly variable cognitive processing (124 - 268ms latency) in response to mechanical tactile stimuli in patients with CRPS compared to healthy controls. Such mid-to-late latency responses could potentially provide convenient and robust biomarkers of abnormal perceptual decision-making mechanisms in CRPS to aid in clinical detection and treatment.

neuroscience↗

bioRxiv2017

QuASAR-MPRA: Accurate allele-specific analysis for massively parallel reporter assays

MotivationThe majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRA), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets.\n\nResultsWe have further developed our method for allele-specific analysis QuASAR (quantitative allele-specific analysis of reads) to analyze allele-specific signals in barcoded read counts data from MPRA. Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. The provided allelic skew estimate and its standard error also simplifies meta-analysis of replicate experiments. Additionally, we show that a beta-binomial distribution better models the variability present in the allelic imbalance of these synthetic reporters and results in a test that is statistically well calibrated under the null. Applying this approach to the MPRA data by Tewhey et al. (2016), we found 602 SNPs with significant (FDR 10%) allele-specific regulatory function in LCLs. We also show that we can combine MPRA with QuASAR estimates to validate existing experimental and computational annotations of regulatory variants. Our study shows that with appropriate data analysis tools, we can improve the power to detect allelic effects in high throughput reporter assays.\n\nAvailabilityhttp://github.com/piquelab/QuASAR/tree/master/mpra\n\nContactfluca@wayne.edu; rpique@wayne.edu

bioinformatics↗