Biology subjects

Braun, D. A.

Publications and source records attributed to Braun, D. A..

14 recordsLinked to original sources

bioRxiv2026

Molecular orchestration of global actin remodelling by INF2

The actin cytoskeleton rapidly reorganizes in response to intracellular calcium signals, driving cellular morphogenesis and wound healing. Among actin regulators, the formin INF2 uniquely mediates the "Calcium-mediated Actin Reset" (CaAR) reaction, orchestrating transient and global actin remodeling upon calcium influx. Excessive INF2 activity is linked to kidney and neuronal diseases, underscoring the need for its tight control. Combining live cell imaging with single molecule tracking, biochemistry and structural analysis we discover that INF2 activity is tightly controlled by two interlinked mechanisms: canonical intramolecular autoinhibition and binding of the INF2 N-terminus to the side of actin filaments. Side-binding limits actin elongation and supports re-establishment of autoinhibition. Disruption of this negative feedback prolongs INF2 activity, affecting plasma membrane organization and repair as well as transcriptional control. Our findings uncover a novel product-inhibition mechanism that limits INF2 function and offer important insight into disease mechanisms linked to actin dysregulation.

cell biology↗

bioRxiv2026

VDJdive and ECLIPSE enhance single-cell TCR sequencing analysis through the probabilistic resolution of ambiguous clonotypes

Single-cell T cell receptor sequencing (scTCR-seq) has transformed our ability to track individual T cell clones and has been instrumental in advancing our understanding of human T cell differentiation. However, current computational pipelines for analysis, which require precise matching of CDR3 sequences from exactly 2 heterodimeric TCR chains to define the clonotype for each cell, are inherently limited because of the substantial proportion of cells possessing "ambiguous" clonotypes driven by missing (undetected from the technical issue of chain "dropout") or extra chains (present from either true biological expression or due to technical artifacts such as cellular doublets and ambient TCR contamination). As a result, clone sizes are artificially reduced, impeding the tracking of clones across conditions and differentiation states. Here we introduce VDJdive and ECLIPSE (Enhanced CLonotypic Inference via Prediction of Single-cell Expression), two computational methods that, together, resolve this clonal ambiguity by utilizing the expectation-maximization algorithm for the clonal prediction of ambiguous cells. These methods consider chain pairings across the sample, allowing for high-fidelity prediction of chains lost due to dropout and the discernment of biological expression of extra chains from technical artifacts. Consequently, clone sizes are augmented and cells without clonotype assignments are minimized. Our approach facilitates enhanced clonal tracking through these elevated clone sizes and is easily implementable, compatible with standard single-cell transcriptomic workflows, and broadly applicable across biological contexts and T cell subsets.

immunology↗

bioRxiv2025

Perturbational single-cell profiling of patient tumors defines lineage- and context-specific programs of innate immune resistance

AbstractDespite promise in preclinical models, most immuno-oncology drug candidates fail in clinical trials. These failures reflect limitations in our ability to directly model the response of human tumor and immune cells to immunotherapies. To address this gap and test the effect of innate immune agonists, we developed PERCEPT, an approach that uses ex vivo perturbational single-cell RNA sequencing to compare the response of immunomodulatory treatments with unstimulated controls directly in patient samples. Using PERCEPT, we tested cytokines and innate immune agonists in melanoma and Merkel cell carcinoma (MCC) and identified the dsRNA mimetic, RIG-I agonist, Stem Loop RNA (SLR) 14 as a powerful inducer of anti-viral states and enhancer of T cell activation. We compared transcriptional responder and non-responder patient samples and identified midkine (MDK), a multifunctional cytokine, as a potent repressor of IFN signaling in both tumor and immune cells. MDK expression dampened MHC-I presentation in human tumor cells and reduced activation of antigen-presenting cells, disrupting tumor immunity at multiple levels. In contrast to prior studies, we identified MDK as specifically enriched in neuroendocrine cancers such as MCC and small cell lung cancer compared with melanoma, suggesting the importance of lineage- and context-specific targeting. Our results demonstrate the utility of high-dimensional controlled perturbation of patient samples to identify mechanisms of innate immune response and resistance and demonstrate an actionable path towards clinical development of MDK-inhibiting therapies including FDA-approved ALK inhibitors in neuroendocrine cancers.

cancer biology↗

bioRxiv2025

Pan-cancer prediction of tumor immune activation and response to immune checkpoint blockade from tumor transcriptomics and histopathology

Accurately predicting which patients will respond to immune checkpoint blockade (ICB) remains a major challenge. Here, we present TIME_ACT, an unsupervised 66-gene transcriptomic signature of tumor immune activation derived from TCGA (The Cancer Genome Atlas) melanoma data. First, we demonstrate that TIME_ACT scores accurately identify tumors with activated immune microenvironments across different cancer types. Further, analysis of spatial features reveals that tumor microenvironment regions with dense lymphocyte infiltration near tumor cells have high TIME_ACT scores, successfully marking localized immune activation. Second, across 25 transcriptomic ICB cohorts encompassing nine cancer types, TIME_ACT achieves a mean AUC of 0.76 and a mean odds ratio of 5.77, significantly outperforming 30 established transcriptomic signatures and prediction methods for ICB response, including a recently developed foundation model for immunotherapy response prediction. Third, we show that TIME_ACT scores can be accurately inferred from routine tumor histopathology slides and that slide-inferred TIME_ACT scores predict ICB response across nine new independent patient cohorts spanning eight cancer types, achieving a mean AUC of 0.72 and a mean odds ratio of 4.99. These findings establish TIME_ACT as a robust, pan-cancer biomarker that enables accurate, low-cost, and clinically scalable prediction of ICB response from routine histopathology.

cancer biology↗

bioRxiv2025

CRISPR-Cas9 HDR Optimization: RAD52, Denatured and 5'-Modified DNA Templates in Knock-In Mice Generation

AbstractCRISPR/Cas9-mediated genome editing is a powerful tool for producing animal models of human diseases. However, it often encounters challenges related to low efficiency of donor DNA templates insertion through homology-directed repair (HDR) pathway or unwanted insertions and/or multiplications. Here, we present findings from multiple targeting experiments aimed at generating a Nup93 conditional knockout (cKO) mouse model. Injection of CRISPR/Cas9 components into over two thousand zygotes, resulted in 270 founder animals. Our study revealed various obstacles associated with the use of single-stranded (ssDNA) and double-stranded DNA (dsDNA) templates during cKO generation, highlighting the critical role of denaturation of long 5-monophosphorylated dsDNA templates in enhancing precise genome editing and reducing template multiplications. Application of RAD52 protein increased HDR efficiency of ssDNA integration almost 4-fold, albeit with an associated increase in template multiplication. Targeting the antisense strand of DNA using two crRNAs demonstrated better efficacy in HDR-mediated precise genome editing when compared to targeting the sense or sense-antisense strands. In addition, the application of 5-end biotin-modified donor DNA resulted in up to a 8-fold increase in HDR-mediated single-copy template integration compered to unmodified dsDNA donor. Furthermore, application of 5-end C3 spacer modified template resulted in up to a 20-fold increase in correctly HDR modified mice independent from ssDNA or dsDNA template employment. This study underscores potential pitfalls in CRISPR/Cas9-mediated genome editing and offers simple practical solutions to refine this potent tool. These findings highlight various strategies to enhance CRISPR/Cas9 HDR efficiency, providing a framework for improving precision in the generation of conditional knockout models.

molecular biology↗

bioRxiv2023

Epigenomic signatures as circulating and predictive biomarkers in sarcomatoid renal cell carcinoma

Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are (1) a limited understanding of its gene regulatory programs and (2) difficulty identifying sarcomatoid differentiation on tumor biopsies due to spatial heterogeneity. To address these challenges, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries in tissue and plasma samples from 50 patients with RCC and healthy volunteers. We identified highly recurrent epigenomic reprogramming, as assessed by histone modifications and DNA methylation, that distinguishes sRCC from non-sarcomatoid RCC. Computational analysis of RCC epigenomic profiles and CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs. Analysis of two randomized clinical trials identified FOSL1 expression as a predictive biomarker of response to ICIs in RCC. Finally, we demonstrate that epigenomic signatures of sRCC are detectable in patient plasma, establishing an approach for blood-based diagnosis of this clinically important phenotype. These findings provide a framework for the discovery and non-invasive detection of epigenomic correlates of tumor histology via liquid biopsy.

genomics↗

bioRxiv2023

FGF-21 Conducts a Liver-Brain-Kidney Axis to Promote Renal Cell Carcinoma

Metabolic homeostasis is one of the most exquisitely tuned systems in mammalian physiology. Metabolic homeostasis requires multiple redundant systems to cooperate to maintain blood glucose concentrations in a narrow range, despite a multitude of physiological and pathophysiological pressures. Cancer is one of the canonical pathophysiological settings in which metabolism plays a key role. In this study, we utilized REnal Gluconeogenesis Analytical Leads (REGAL), a liquid chromatography-mass spectrometry/mass spectrometry-based stable isotope tracer method that we developed to show that in conditions of metabolic stress, the fasting hepatokine fibroblast growth factor-21 (FGF-21)1, 2 coordinates a liver-brain-kidney axis to promote renal gluconeogenesis. FGF-21 promotes renal gluconeogenesis by enhancing {beta}2 adrenergic receptor (Adrb2)-driven, adipose triglyceride lipase (ATGL)-mediated intrarenal lipolysis. Further, we show that this liver-brain-kidney axis promotes gluconeogenesis in the renal parenchyma in mice and humans with renal cell carcinoma (RCC). This increased gluconeogenesis is, in turn, associated with accelerated RCC progression. We identify Adrb2 blockade as a new class of therapy for RCC in mice, with confirmatory data in human patients. In summary, these data reveal a new metabolic function of FGF-21 in driving renal gluconeogenesis, and demonstrate that inhibition of renal gluconeogenesis by FGF-21 antagonism deserves attention as a new therapeutic approach to RCC.

physiology↗

bioRxiv2023

Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states

Background Abstract Background Results Discussion Methods Data Availability Code Availability Author Contributions Competing Interests Extended Data References Renal cell carcinoma (RCC) is among the 10 most common cancers worldwide and is comprised of several histological subtypes1. The clear cell histological subtype (ccRCC) is the most common form of RCC and accounts for the vast majority (75-80%) of metastatic cases1. In addition to highly recurrent mutations in hypoxia (VHL) and chromatin regulator genes (e.g. PBRM1, BAP1, SETD2), ccRCC exhibits extensive genomic intratumoral heterogeneity (ITH)2, which wa ...

cancer biology↗

bioRxiv2021

Gauging the capacity for concurrent motor planning in human fMRI with information constraints in bounded rational decision-making models

While traditional theories of sensorimotor processing have often assumed a serial decision-making pipeline, more recent approaches have suggested that multiple actions may be planned concurrently and vie for execution. Evidence for the latter almost exclusively stems from electrophysiological studies in posterior parietal and premotor cortex of monkeys. Here we study concurrent prospective motor planning in humans by recording functional magnetic resonance imaging (fMRI) during a delayed response task engaging movement sequences towards multiple potential targets. We find that also in human posterior parietal and premotor cortex delay activity modulates both with sequence complexity and the number of potential targets. We tested the hypothesis that this modulation is best explained by concurrent prospective planning as opposed to the mere maintenance of potential targets in memory. We devise a bounded rationality model with information constraints that optimally assigns information resources for planning and memory for this task and determine predicted information profiles according to the two hypotheses. When regressing delay activity on these model predictions, we find that the concurrent prospective planning strategy provides a significantly better explanation of the fMRI-signal modulations. Moreover, we find that concurrent prospective planning is more costly and thus limited for most subjects, as expressed by the best fitting information capacities. We conclude that bounded rational decision-making models allow relating both behavior and neural representations to utilitarian task descriptions based on bounded optimal information-processing assumptions. Author summaryWhen the future is uncertain, it can be beneficial to concurrently plan several action possibilities in advance. Electrophysiological research found evidence in monkeys that brain regions in posterior parietal and promotor cortex are indeed capable of planning several actions in parallel. We now used fMRI to study brain activity in these brain regions in humans. For our analyses we applied bounded rationality models that optimally assign information resources to fMRI activity in a complex motor planning task. We find that theoretical information costs of concurrent prospective planning explained fMRI activity profiles significantly better than assuming alternative memory-based strategies. Moreover, exploiting the model allowed us to quantify the individual capacity limit for concurrent planning and to relate these individual limits to both subjects behavior and to their neural representations of planning.

neuroscience↗

bioRxiv2021

Nash equilibria in human sensorimotor interactions explained by Q-Learning

The Nash equilibrium concept has previously been shown to be an important tool to understand human sensorimotor interactions, where different actors vie for minimizing their respective effort while engaging in a multi-agent motor task. However, it is not clear how such equilibria are reached. Here, we compare different reinforcement learning models based on haptic feedback to human behavior in sensorimotor versions of three classic games, including the Prisoners Dilemma, and the symmetric and asymmetric matching pennies games. We find that a discrete analysis that reduces the continuous sensorimotor interaction to binary choices as in classical matrix games does not allow to distinguish between the different learning algorithms, but that a more detailed continuous analysis with continuous formulations of the learning algorithms and the game-theoretic solutions affords different predictions. In particular, we find that Q-learning with intrinsic costs that disfavor deviations from average behavior explains the observed data best, even though all learning algorithms equally converge to admissible Nash equilibrium solutions. We therefore conclude that it is important to study different learning algorithms for understanding sensorimotor interactions, as such behavior cannot be inferred from a game-theoretic analysis alone, that simply focuses on the Nash equilibrium concept, as different learning algorithms impose preferences on the set of possible equilibrium solutions due to the inherent learning dynamics.

neuroscience↗

bioRxiv2021

Optimized liquid and gas phase fractionation increase HLA-peptidome coverage for primary cell and tissue samples

Mass spectrometry is the most effective method to directly identify peptides presented on HLA molecules. However, current standard approaches often require many millions of cells for input material to achieve high coverage of the immunopeptidome and are therefore not compatible with the often limited amounts of tissue available from clinical tumor samples. Here, we evaluated microscaled basic reversed-phase fractionation to separate HLA peptide samples off-line followed by ion mobility coupled to LC-MS/MS for analysis. The combination of these two separation methods enabled identification of 20% to 50% more peptides compared to samples analyzed without either prior fractionation or use of ion mobility alone. We demonstrate coverage of HLA immunopeptidomes with up to 8,107 distinct peptides starting with as few as 100 million cells or 150 milligrams of wet weight tumor tissue. This increased sensitivity can improve HLA binding prediction algorithms and enable detection of clinically relevant epitopes such as neoantigens.

biochemistry↗

bioRxiv2021

Integrative Clinical and Molecular Characterization of Translocation Renal Cell Carcinoma

ABSTRACTTranslocation renal cell carcinoma (tRCC) is an aggressive and poorly-characterized subtype of kidney cancer driven by MiT/TFE gene fusions. Here, we define the landmarks of tRCC through an integrative analysis of 152 tRCC patients identified across multiple genomic, clinical trial, and retrospective cohorts. Most tRCCs harbor few somatic alterations apart from MiT/TFE fusions and homozygous deletions at chromosome 9p21.3 (19.2% of cases). Transcriptionally, tRCCs display a heightened NRF2-driven antioxidant response that is associated with resistance to many targeted therapies. Consistently, we find that outcomes for tRCC patients treated with vascular endothelial growth factor receptor inhibitors (VEGFR-TKI) are worse than those treated with immune checkpoint inhibition (ICI). Multiparametric immunofluorescence confirmed the presence of CD8 + tumor-infiltrating T cells compatible with a clinical benefit from ICI and revealed an exhaustion immunophenotype distinct from clear cell RCC. Our findings comprehensively define the clinical and molecular features of tRCC and may inspire new therapeutic hypotheses.

cancer biology↗

bioRxiv2020

Integrative Molecular Characterization of Sarcomatoid and Rhabdoid Renal Cell Carcinoma Reveals Determinants of Poor Prognosis and Response to Immune Checkpoint Inhibitors

Sarcomatoid and rhabdoid (S/R) renal cell carcinoma (RCC) are highly aggressive tumors with limited molecular and clinical characterization. Emerging evidence suggests immune checkpoint inhibitors (ICI) are particularly effective for these tumors1-3, although the biological basis for this property is largely unknown. Here, we evaluate multiple clinical trial and real-world cohorts of S/R RCC to characterize their molecular features, clinical outcomes, and immunologic characteristics. We find that S/R RCC tumors harbor distinctive molecular features that may account for their aggressive behavior, including BAP1 mutations, CDKN2A deletions, and increased expression of MYC transcriptional programs. We show that these tumors are highly responsive to ICI and that they exhibit an immune-inflamed phenotype characterized by immune activation, increased cytotoxic immune infiltration, upregulation of antigen presentation machinery genes, and PD-L1 expression. Our findings shed light on the molecular drivers of aggressivity and responsiveness to immune checkpoint inhibitors of S/R RCC tumors.

cancer biology↗

bioRxiv2020

Cystin gene mutations cause autosomal recessive polycystic kidney disease associated with altered Myc expression

Mutation of the Cys1 gene underlies the renal cystic disease in the Cys1cpk/cpk (cpk) mouse that phenocopies human autosomal recessive polycystic kidney disease (ARPKD). Cystin, the protein product of Cys1, is expressed in the primary apical cilia of renal ductal epithelial cells. In previous studies, we showed that cystin regulates Myc expression via interaction with the tumor suppressor, necdin. Here, we demonstrate rescue of the cpk renal phenotype by kidney-specific expression of a cystin-GFP fusion protein encoded by a transgene integrated into the Rosa26 locus. In addition, we show that expression of the cystin-GFP fusion protein in collecting duct cells down-regulates expression of Myc in cpk kidneys. Finally, we report the first human patient with an ARPKD phenotype due to homozygosity for a predicted deleterious splicing defect in CYS1. These findings suggest that mutations in the Cys1 mouse and CYS1 human orthologues cause an ARPKD phenotype that is driven by overexpression of the Myc proto-oncogene. Translational StatementThe cystin-deficient cpk mouse is a model for the study of autosomal recessive polycystic kidney disease (ARPKD). We show that the cpk mouse phenotype is associated with altered Myc expression. To date, the clinical relevance of cystin deficiency to human disease was unclear, due to the absence of ARPKD cases associated with CYS1 mutations. We report the first case of ARPKD linked to a CYS1 mutation disrupting normal splicing. These findings confirm the relevance of cystin deficiency to human ARPKD, implicate Myc in disease initiation or progression, and validate the cpk mouse as a translationally relevant disease model.

molecular biology↗