Biology subjects

Lazar, A.

Publications and source records attributed to Lazar, A..

15 recordsLinked to original sources

bioRxiv2026

Spatially Anchored Regulatory State Inference in Melanoma

Spatial transcriptomics (ST) captures gene expression within tissue architecture but lacks direct regulatory information, while single-cell multiome assays profile transcriptional and chromatin states without spatial context. We present a framework for spatially anchored regulatory inference that integrates Visium ST with single-cell multiome data to infer spatially resolved regulatory programs. Building upon GraphST, we introduce spatially regularized cell-to-spot mapping and propagate chromatin accessibility and transcription factor motif activity into tissue space. Regulatory analysis is performed at the spatial domain level via joint differential expression and accessibility testing, along with quantitative concordance assessment. Applied to melanoma tissue sections, the framework reveals spatially localized regulatory programs and shows that assignment strategy substantially affects downstream regulatory stability. This modular approach enables interpretable gene-, peak-, and transcription factor-level outputs for multimodal spatial analysis.

bioinformatics↗

bioRxiv2025

EWS::WT1 Isoform-Dependent Regulation of Neogenes in Desmoplastic Small Round Cell Tumors

Desmoplastic small round cell tumor (DSRCT) is a rare, aggressive sarcoma characterized by the pathognomonic EWS::WT1 fusion protein (FP), an oncogenic chimeric transcription factor (OCTF) resulting from the t(11;22)(p13;q12) translocation. Recent studies have identified "neogenes" (NGs), genes normally silent in normal tissues but transcriptionally activated by OCTFs, as potential tumor-specific markers in fusion-driven cancers. In this study, we investigated the expression and regulation of DSRCT-specific NGs (DSRCT_NGs) using multimodal data across different cohorts of patients, PDX, and cell line data. We evaluated bulk and single-nucleus RNA sequencing of patient specimens from MD Anderson Cancer Center, revealing the robust ability for DSRCT_NGs to distinguish FP-positive DSRCT from samples failing detection of the EWS::WT1 FP. To elucidate the regulatory role of the EWS::WT1 FP in driving NG expression, we performed knockdown experiments in four DSRCT cell lines. This consistently resulted in a reduction of DSRCT_NG expression. Isoform-specific expression of EWS::WT1 in LP9 and MeT-5A mesothelial cells revealed that the E-KTS isoform of EWS::WT1 predominantly drives DSRCT_NG expression. Mechanistically, ATAC-seq and ChIP-seq analyses demonstrated that EWS::WT1 directly binds to accessible chromatin regions near NG transcription start sites, enriched for WT1 motifs and active histone marks. Integration of Hi-ChIP data further revealed that EWS::WT1 facilitates long-range enhancer-promoter looping at DSRCT_NG loci, promoting the expression of nearby genes. Collectively, these findings establish DSRCT_NGs as direct transcriptional outputs of the EWS::WT1 FP and implicate their loci as regulatory regions of the DSRCT transcriptome. Their fusion-dependent expression, chromatin accessibility, and promoter-enhancer connectivity underscore their potential utility as highly specific biomarkers and therapeutic targets in DSRCT.

genomics↗

bioRxiv2024

Spatial Transcriptomics Reveals Inflammation and Trans-differentiation States of Acute Myeloid Leukemia in Extramedullary and Medullary Tissues

Acute myeloid leukemia (AML) is a heterogeneous disease of the bone marrow (medullary) but can also involve extramedullary tissues. While single cell dynamics of AML in suspension are previously explored, a comprehensive spatial transcriptomic assessment in AML remain underexplored. Here, we used Visium spatial transcriptomics to resolve medullary and extramedullary AML environments. We reveal spatial co-localization of monocytes and granulocyte-monocyte progenitors with leukemic populations in the bone marrow, sharing molecular signatures with extramedullary sites. Cell-cell communication via the CXCL12- CXCR4 axis correlated with PI3K/AKT/mTOR signaling in high inflammatory niches. Trans- differentiation states were concentrated in AML-infiltrated regions, with committed-like AML populations present in inflammatory niches and away from the trabeculae, while primitive-like AML cells localized near the endosteal niche. We validated these findings in GeoMx-based Digital Spatial profiling (DSP). Our study applied multimodal spatial transcriptomic approaches to characterize the spatial hierarchy and microenvironmental dynamics of AML differentiation states. We also demonstrated the feasibility of applying Visium-based spatial transcriptomics in decalcified bone tissues.

cancer biology↗

bioRxiv2024

MorphLink: Bridging Cell Morphological Behaviors and Molecular Dynamics in Multi-modal Spatial Omics

Multi-modal spatial omics data are invaluable for exploring complex cellular behaviors in diseases from both morphological and molecular perspectives. Current analytical methods primarily focus on clustering and classification, and do not adequately examine the relationship between cell morphology and molecular dynamics. Here, we present MorphLink, a framework designed to systematically identify disease-related morphological-molecular interplays. MorphLink has been evaluated across a wide array of datasets, showcasing its effectiveness in extracting and linking interpretable morphological features with various molecular measurements in multi-modal spatial omics analyses. These linkages provide a transparent depiction of cellular behaviors that drive transcriptomic heterogeneity and immune diversity across different regions within diseased tissues, such as cancer. Additionally, MorphLink is scalable and robust against cross-sample batch effects, making it an efficient method for integrative spatial omics data analysis across samples, cohorts, and modalities, and enhancing the interpretation of results for large-scale studies.

bioinformatics↗

bioRxiv2024

Lack of TGFβ signaling competency predicts immune poor cancer conversion to immune rich and response to checkpoint blockade

BackgroundThe efficacy of immune checkpoint blockade (ICB) depends on restoring immune recognition of cancer cells that have evaded immune surveillance. At the time of diagnosis, patients with lymphocyte-infiltrated cancers are the most responsive to ICB, yet a considerable fraction of patients have immune-poor tumors. MethodsWe analyzed transcriptomic data from IMvigor210, TCGA, and TISMO datasets to evaluate the predictive value of {beta}Alt, a score representing the negative correlation of signatures consisting of transforming growth factor beta (TGF{beta}) targets and genes involved in error-prone DNA repair. The immune context of {beta}Alt was assessed by evaluating tumor-educated immune signatures. An ICB-resistant, high {beta}Alt preclinical tumor model was treated with a TGF{beta} inhibitor, radiation, and/or ICB and assessed for immune composition and tumor control. ResultsHere, we show that high {beta}Alt is associated with an immune-poor context yet is predictive of ICB response in both humans and mice. A high {beta}Alt cancer in which TGF{beta} signaling is compromised generates a TGF{beta} rich, immunosuppressive tumor microenvironment. Accordingly, preclinical modeling showed that TGF{beta} inhibition followed by radiotherapy could convert an immune-poor, ICB-resistant tumor to an immune-rich, ICB-responsive tumor. Mechanistically, TGF{beta} blockade in irradiated tumors activated natural killer cells that were required to recruit lymphocytes to respond to ICB. In support of this, natural killer cell activation signatures were also increased in immune-poor mouse and human tumors that responded to ICB. ConclusionsThese studies suggest that loss of TGF{beta} competency identifies a subset of cold tumors that are candidates for ICB. Our mechanistic studies show that inhibiting TGF{beta} activity converts high {beta}Alt, cold tumors into ICB-responsive tumors via NK cells. Thus, a biomarker consisting of combined TGF{beta}, DNA repair, and immune context signatures provides a means to prospectively identify patients whose cancers may be converted from cold to hot, which could be exploited for therapeutic treatment. O_LIWhat is already known on this topic - For some cancer patients, response to ICB provides durable tumor control. Current biomarkers are insufficient to reliably predict the immunotherapy response for most patients, particularly those whose tumors lack lymphocytic infiltration. C_LIO_LIWhat this study adds - The {beta}Alt score, which reports a DNA damage deficiency caused by lack of TGF{beta} signaling, predicts response to ICB in clinical trial data from IMvigor210 metastatic bladder cancer patients and for melanoma patients. Notably, transcriptomic assessment of the immune context shows that these are immune-poor, so-called "cold" tumors. Preclinical modeling indicates that alleviating TGF{beta} inhibition of NK cells is critical to relieving immunosuppression. C_LIO_LIHow this study might affect research, practice or policy - Our work identifies a novel tumor phenotype consisting of cancer cells that have lost TGF{beta} signaling and gained error-prone DNA repair embedded in a TGF{beta} rich, immune-poor microenvironment, which is conserved across cancer types in humans and among preclinical tumor models. Patients whose immune-poor tumors have high {beta}Alt scores are strong candidates for ICB and radiotherapy combinations that may be further augmented by TGF{beta} inhibition. Hence, the {beta}Alt score can be used to stratify immune-poor cancer patients for optimal therapeutic strategies. C_LI

cancer biology↗

bioRxiv2023

Dynamic Fading Memory and Expectancy Effects in Monkey Primary Visual Cortex

In order to investigate the involvement of primary visual cortex (V1) in working memory (WM), parallel, multisite recordings of multiunit activity were obtained from monkey V1 while the animals performed a delayed match-to-sample (DMS) task. During the delay period, V1 population firing rate vectors maintained a lingering trace of the sample stimulus that could be reactivated by intervening impulse stimuli that enhanced neuronal firing. This fading trace of the sample did not require active engagement of the monkeys in the DMS task and likely reflects the intrinsic dynamics of recurrent cortical networks in lower visual areas. This renders an active, attention-dependent involvement of V1 in the maintenance of working memory contents unlikely. By contrast, population responses to the test stimulus depended on the probabilistic contingencies between sample and test stimuli. Responses to tests that matched expectations were reduced which agrees with concepts of predictive coding.

neuroscience↗

bioRxiv2023

Paying attention to natural scenes in area V1

Natural scene responses in the primary visual cortex are modulated simultaneously by attention and by contextual signals about scene statistics stored across the connectivity of the visual processing hierarchy. Here, we hypothesized that attentional and contextual top-down signals interact in V1, in a manner that primarily benefits the representation of natural visual stimuli, rich in high-order statistical structure. Recording from two macaques engaged in a spatial attention task, we found that attention enhanced the decodability of stimulus identity from population responses evoked by natural scenes but, critically, not by synthetic stimuli in which higher-order statistical regularities were eliminated. Population analysis revealed that neuronal responses converged to a low dimensional subspace for natural but not for synthetic images. Critically, we determined that the attentional enhancement in stimulus decodability was captured by the dominant low dimensional subspace, suggesting an alignment between the attentional and natural stimulus variance. The alignment was pronounced for late evoked responses but not for early transient responses of V1 neurons, supporting the notion that top-down feedback was required. We argue that attention and perception share top-down pathways, which mediate hierarchical interactions optimized for natural vision.

neuroscience↗

bioRxiv2022

Enhancer Reprogramming in Melanoma Immune Checkpoint Therapy Resistance

Immune checkpoint blockade (ICB) therapy has improved long-term survival for patients with advanced melanoma. However, there is critical need to identify potential biomarkers of response and actionable strategies to improve response rates. Through generation and analysis of 148 chromatin modification maps for 36 melanoma samples from patients treated with anti-PD- 1, we identified significant enrichment of active enhancer states in non-responders at baseline. Analysis of an independent cohort of 20 samples identified a set of 437 enhancers that predicted response to anti-PD-1 therapy (Area Under the Curve of 0.8417). The activated non-responder enhancers marked a group of key regulators of several pathways in melanoma cells (including c- MET, TGF{beta}, EMT and AKT) that are known to mediate resistance to ICB therapy and several checkpoint receptors in T cells. Epigenetic editing experiments implicated involvement of c-MET enhancers in the modulation of immune response. Finally, inhibition of enhancers and repression of these pathways using bromodomain inhibitors along with anti-PD-1 therapy significantly decreased melanoma tumor burden and increased T-cell infiltration. Together, these findings identify a potential enhancer-based biomarker of resistance to anti-PD-1 and suggest enhancer blockade in combination with ICB as a potential strategy to improve responses.

cancer biology↗

bioRxiv2022

Landscape scale ecology of Tetracladium spp. fungal root endophytes

BackgroundThe genus Tetracladium has been traditionally regarded as an Ingoldian fungus or aquatic hyphomycete - a group of phylogenetically diverse, polyphyletic fungi which grow on decaying leaves and plant litter in streams. Recent sequencing evidence has shown that Tetracladium spp. may also exist as root endophytes in terrestrial environments, and furthermore may have beneficial effects on the health and growth of their host. However, the diversity of Tetracladium spp. communities in terrestrial systems and the factors which shape their distribution are largely unknown. ResultsUsing a fungal community internal transcribed spacer amplicon dataset from 37 UK Brassica napus fields we found that soils contained diverse Tetracladium spp., most of which represent previously uncharacterised clades. The two most abundant OTUs, related to previously described aquatic T. furcatum and T. maxilliforme, were enriched in roots relative to bulk and rhizosphere soil. For both taxa, relative abundance in roots, but not rhizosphere or bulk soil was correlated with B. napus yield. The relative abundance of T. furcatum and T. maxilliforme OTUs across compartments showed very similar responses with respect to agricultural management practices and soil characteristics. The factors shaping the relative abundance of T. furcatum and T. maxilliforme OTUs in roots was assessed using linear regression and structural equation modelling. Relative abundance of Tetracladium maxilliforme and Tetracladium furcatum in roots increased with pH, concentrations of phosphorus, and increased rotation frequency of OSR. While it decreased with increased soil water content, concentrations of extractable phosphorus, chromium, and iron. ConclusionsThe genus Tetracladium as a root colonising endophyte is a diverse and wildly distributed part of the oilseed rape microbiome that positively correlates to crop yield. The main drivers of its community composition are crop management practices and soil nutrients.

microbiology↗

bioRxiv2020

Cortical resonance selects coherent input

Synchronization has been implicated in neuronal communication, but causal evidence remains indirect. We used optogenetics to generate depolarizing currents in pyramidal neurons of cat visual cortex, emulating excitatory synaptic inputs under precise temporal control, while measuring spike output. Cortex transformed constant excitation into strong gamma-band synchronization, revealing the well-known cortical resonance. Increasing excitation with ramps increased the strength and frequency of synchronization. Slow, symmetric excitation profiles revealed hysteresis of power and frequency. Crucially, white-noise input sequences enabled causal analysis of network transmission, establishing that cortical resonance selectively transmits coherent input components. Models composed of recurrently coupled excitatory and inhibitory units uncovered a crucial role of feedback inhibition and suggest that hysteresis can arise through spike-frequency adaptation. The presented approach provides a powerful means to investigate the resonance properties of local circuits and probe how these properties transform input and shape transmission.

neuroscience↗

bioRxiv2020

Predictability in natural images determines V1 firing rates and synchronization: A deep neural network approach

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that neural activity results from an integration and comparison of bottom-up inputs with contextual predictions, a process in which firing rates and synchronization may play distinct roles. Here, we quantified stimulus predictability for natural images based on self-supervised, generative neural networks. When the precise pixel structure of a stimulus falling into the V1 receptive field (RF) was predicted by the spatial context, V1 exhibited characteristic{gamma} -synchronization (30-80Hz), despite no detectable modulation of firing rates. In contrast to{gamma} , {beta}-synchronization emerged exclusively for unpredictable stimuli. Natural images with high structural predictability were characterized by high compressibility and low dimensionality. Yet, perceptual similarity was mainly determined by higher-level features of natural stimuli, not by the precise pixel structure. When higher-level features of the stimulus in the receptive field were predicted by the context, neurons showed a strong reduction in firing rates and an increase in surround suppression that was dissociated from synchronization patterns. These findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.

neuroscience↗

bioRxiv2020

A GTP-state specific cyclic peptide inhibitor of the GTPase Gαs

The G protein-coupled receptor (GPCR) cascade leading to production of the second messenger cAMP is replete with pharmacologically targetable receptors and enzymes with the exception of the G subunit, Gs. GTPases remain largely undruggable given the difficulty of displacing high-affinity guanine nucleotides and the lack of other drug binding sites. We explored a chemical library of 1012 cyclic peptides in order to expand the chemical search for inhibitors of this enzyme class. We identified two macrocyclic peptides, GN13 and GD20, that antagonize the active and inactive states of Gs, respectively. Both macrocyclic peptides fine-tune Gs activity with high nucleotide-binding-state selectivity and G protein class-specificity. Co-crystal structures reveal that GN13 and GD20 distinguish the conformational differences within the switch II/3 pocket and block effector interactions. The Gs inhibitors showed strong activity in cellular contexts through binding to crystallographically defined pockets. The discovery of cyclic peptide inhibitors targeting Gs provides a path for further development of state-dependent GTPase inhibitors.

biochemistry↗

bioRxiv2018

Enhancer Reprogramming Confers Dependence on Glycolysis and IGF signaling in KMT2D Mutant Melanoma

Epigenetic modifiers have emerged as important regulators of tumor progression. We identified histone methyltransferase KMT2D as a potent tumor-suppressor through an in vivo epigenome-focused pooled RNAi screen in melanoma. KMT2D harbors frequent somatic point mutations in multiple tumor types. How these events contribute to tumorigenesis and whether they impart therapeutic vulnerability are poorly understood. To address these questions, we generated a genetically engineered mouse model of melanoma based on conditional and melanocyte-specific deletion of KMT2D. We demonstrate KMT2D as a bona fide tumor suppressor which cooperates with activated BRAF. KMT2D-deficient tumors showed substantial reprogramming of key metabolic pathways including glycolysis. Glycolysis enzymes, intermediate metabolites and glucose consumption rate were aberrantly upregulated in KMT2D mutant cells. The pharmacological inhibition of glycolysis reduced proliferation and tumorigenesis preferentially in KMT2D mutant cells. Mechanistically, KMT2D loss caused drastic reduction of H3K4me1-marked active enhancer states. Loss of distal enhancer and subsequent reduction in expression of IGFBP5 activated IGF1R-AKT to increase glycolysis in KMT2D-deficient cells. We conclude that KMT2D loss promotes tumorigenesis by facilitating increased usage of glycolysis pathway for enhanced biomass needs via enhancer reprogramming. Our data imply that inhibition of glycolysis or IGFR pathway could be a potential therapeutic strategy in KMT2D mutant tumors.

cancer biology↗

bioRxiv2018

Visual exposure optimizes stimulus encoding in primary visual cortex

The brain adapts to the sensory environment. For example, simple sensory exposure can modify the response properties of early sensory neurons. How these changes affect the overall encoding and maintenance of stimulus information across neuronal populations remains unclear. We perform parallel recordings in the primary visual cortex of anesthetized cats and find that brief, repetitive exposure to structured visual stimuli enhances stimulus encoding by decreasing the selectivity and increasing the range of the neuronal responses that persist after stimulus presentation. Low-dimensional projection methods and simple classifiers demonstrate that visual exposure increases the segregation of persistent neuronal population responses into stimulus-specific clusters. These observed refinements preserve the representational details required for stimulus reconstruction and are detectable in post-exposure spontaneous activity. Assuming response facilitation and recurrent network interactions as the core mechanisms underlying stimulus persistence, we show that the exposure-driven segregation of stimulus responses can arise through strictly local plasticity mechanisms, also in the absence of firing rate changes. Our findings provide evidence for the existence of an automatic, unguided optimization process that enhances the encoding power of neuronal populations in early visual cortex, thus potentially benefiting simple readouts at higher stages of visual processing.

neuroscience↗

bioRxiv2017

Stimulus content shapes cortical response statistics

Spike count correlations (SCCs) are ubiquitous in sensory cortices, are characterized by rich structure and arise from structured internal interactions. Yet, most theories of visual perception focus exclusively on the mean responses of individual neurons. Here, we argue that feedback interactions in primary visual cortex (V1) establish the context in which individual neurons process complex stimuli and that changes in visual context give rise to stimulus-dependent SCCs. Measuring V1 population responses to natural scenes in behaving macaques, we show that the fine structure of SCCs is stimulus-specific and variations in response correlations across-stimuli are independent of variations in response means. Moreover, we demonstrate that stimulus-specificity of SCCs in V1 can be directly manipulated by controlling the high-order structure of synthetic stimuli. We propose that stimulus-specificity of SCCs is a natural consequence of hierarchical inference where inferences on the presence of high-level image features modulate inferences on the presence of low-level features.

neuroscience↗