Biology subjects

Hwang, Y.

Publications and source records attributed to Hwang, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

RADIAL AND TANGENTIAL FIBER COMPONENTS IN HUMAN SUPERFICIAL WHITE MATTER AND THEIR ASSOCIATIONS WITH MACROSCALE FUNCTION

The superficial white matter (SWM), a thin layer of white matter beneath the cortex, contains a complex arrangement of short- and long-range fiber systems that support communication between cortical regions. These fiber populations include subcortical U-shaped fibers (U-fibers) that predominantly follow a tangential trajectory along the gray matter-white matter interface and long-range fibers that extend more radially through the deeper white matter to connect distant cortical regions. Here, we developed a surface-based framework to dissociate radial and tangential fiber components within the human SWM and investigated their microstructural properties and functional relevance using in-vivo high-field MRI. These components were quantified using apparent fiber density (AFD), fractional anisotropy (FA), and mean diffusivity (MD). We further contextualized SWM fiber architecture by examining depth-dependent microstructural profiles and their relationship with normative patterns of cortical organization and hierarchical specialization. The anatomical assessment of the proposed fiber orientation separation was supported by tractography-based bundle analyses, while the anatomical accuracy of tractography reconstructions was confirmed through comparison with post-mortem white matter dissection data. To assess their functional relevance, the fiber predominance map derived from radial and tangential AFD was related to spatial patterns of functional variability across the cortex. Regions with greater radially oriented fiber contribution exhibited more gradual changes in functional similarity across geodesic distance, whereas tangentially oriented fiber-enriched regions showed more rapid local functional differentiation. These findings reveal distinct structural and functional signatures of radial and tangential SWM fiber components and provide a framework for investigating their contributions to cortical organization and functional specialization. SIGNIFICANCE STATEMENTThe human cerebral cortex is organized into specialized regions that support diverse functions, but the structural principles underlying this organization remain incompletely understood. The superficial white matter (SWM), a thin layer of white matter beneath the cortex, contains intermingled short- and long-range fiber systems that support communication between cortical regions. However, these fiber populations have remained difficult to characterize because they are closely intertwined within the SWM. By developing a reproducible framework for mapping and quantifying distinct SWM fiber systems, this work provides a foundation for systematic investigation of this complex compartment. Integration of multimodal datasets, together with open sharing of analytical tools and standardized features, promotes transparency, reproducibility, enabling future studies of how superficial connectivity supports brain organization.

neuroscience↗

bioRxiv2026

Generative Design of New-to-nature Biosynthetic Assembly Lines with Genomic Language Modeling

Reprogramming biosynthetic assembly lines can extend biosynthesis beyond the chemical space explored by nature. However, this remains difficult because assembly-line function depends on coordinated interactions across large multidomain enzymes. Here, we couple gLM2, a genomic language model trained on metagenomic sequences, with discrete diffusion and domain-level conditioning to enable generative design and optimization of biosynthetic gene clusters. We apply this approach to a chimeric type I polyketide synthase (PKS) engineered to produce {delta}-valerolactam, a molecule not naturally synthesized by PKSs. Through iterative redesign of two multi-domain regions in the context of the full PKS sequence, gLM2 progressively improved {delta}-valerolactam production, yielding variants with up to 9.4-fold higher titer than the starting enzyme. Together, these results demonstrate that evolutionary sequence information can be learned and applied to complex, multi-domain enzyme design problems, expanding biosynthetic assembly lines to produce molecules outside their natural biosynthetic repertoire.

bioengineering↗

bioRxiv2026

Discovery of microbial intergenic features with genomic language modeling and multimodal search

Systematic characterization of microbial noncoding regions is limited by two distinct challenges: discovery of conserved sequence features without predefined motifs and functional interpretation of newly identified elements. We address these challenges by training a sparse autoencoder on genomic language model (gLM2) representations to identify intergenic sequence features without prior annotation, and by implementing multimodal search to generate functional hypotheses from conserved associations with neighboring proteins, RNA families, and genomic organization. This framework uncovered divergent, previously uncharacterized noncoding elements, including candidate regulatory DNA sequences and structured RNAs not captured by existing annotation models. gLM2-derived intergenic features can be explored through SeqHub's multimodal search, freely available for academic use at seqhub.org.

microbiology↗

bioRxiv2026

HippoGenes: A robust workflow for subregional transcriptomic profiling of the human hippocampus

The human hippocampus is a unique cortical structure central to brain function, plasticity, and disease. Unravelling its complex organization requires the integration of multiscale data, linking molecular features to mesoscale anatomy and macroscale functional patterns. Gene expression is a fundamental microscale phenotype, and its profiling can provide a reference description of how molecular features are distributed across the brain. Capitalizing on recent imaging-transcriptomic analyses, we introduce HippoGenes, a repository of fine-grained gene expression patterns across human hippocampal subregions. We leveraged spatial statistical models and hippocampal surface mapping to reconstruct dense transcriptomic maps from sparse post-mortem tissue samples of the Allen Human Brain Atlas, generating continuous expression estimates for thousands of genes aligned to a common surface-based coordinate system. We illustrate the utility of HippoGenes to (i) map medial-lateral and anterior-posterior transcriptomic gradients that align with subfield and tripartite subdivisions of the hippocampal formation, (ii) examine associations between gene expression and canonical microstructural and functional features of the hippocampus, and (iii) perform a molecular decoding of subregional alterations in neurological patients with hippocampal pathology. HippoGenes provides a framework for exploring the molecular organization of the hippocampus, opening avenues for multiscale integration in health and disease, and is openly available on https://hippogenes.readthedocs.io/.

neuroscience↗

bioRxiv2026

Loss of Arginase 2 Promotes Lung Metastasis in immune-competent hosts via Nitric Oxide Synthase 2-Dependent Th17 Response

Distant metastasis is the leading cause of mortality in many cancers. Although metabolic reprogramming is recognized as a hallmark of cancer, how tumor-intrinsic metabolic enzymes regulate tumor-immune crosstalk during metastatic progression remains poorly understood. Here, using a high-throughput functional CRISPR-Cas9 screen targeting metabolic genes in an orthotopic 4T1 murine mammary carcinoma model of spontaneous lung metastasis, we identify a selective enrichment of arginase 2 (ARG2)-deficient tumor cells in metastatic lungs of immunocompetent but not RAG1-deficient mice, indicating a lymphocyte-dependent mechanism. Loss of ARG2 enhances spontaneous lung metastasis without affecting primary tumor growth. Further, metastatic outgrowth in the lung is not affected when tumor cells are injected intravenously, indicating that ARG2 regulates an early stage of the metastatic cascade. Mechanistically, ARG2 deficiency upregulates nitric oxide synthase 2 (NOS2), resulting in increased nitric oxide production, accumulation of cytosolic DNA, and activation of the cGAS-STING-NF-{kappa}B pathway, leading to upregulation of inflammatory cytokines. ARG2-deficient tumors exhibit an immunosuppressive tumor microenvironment characterized by enrichment of Th17 cells and reduced anti-tumor immune populations. Functionally, Th17 cells enhance tumor cell migration in vitro and promote spontaneous lung metastasis in vivo. Genetic deletion of NOS2 attenuates cytosolic DNA accumulation, reduces STING-NF-{kappa}B activation, restores anti-tumor immunity, and suppresses ARG2 deficiency-driven metastatic burden in vivo. Collectively, these findings define a tumor cell-intrinsic ARG2-NOS2 axis that regulates inflammatory signaling and the tumor microenvironment to promote metastasis, highlighting a targetable vulnerability in metastatic breast cancer.

cancer biology↗

bioRxiv2026

MICAFlow: Fast and Robust MRI Preprocessing Bridging Research Neuroimaging and Clinical Practice

MICAFlow is a fully automated MRI preprocessing pipeline designed to translate advanced neuroimaging workflows from research into routine clinical practice. The pipeline emphasizes speed, robustness, and ease of use, focusing on structural and diffusion MRI. Key innovations include a Label-Augmented Modality-Agnostic Registration (LAMAReg) technique driven by deep learning segmentations for reliable cross-modal alignment, integration of state-of-the-art distortion corrections, and adherence to reproducible standards (Snakemake workflow, BIDSApp specifications). We describe the design of MICAFlow and evaluate its performance across heterogeneous datasets. First, accessibility: MICAFlow processes a multimodal MRI exam in minutes with clinically accessible hardware and without requiring GPU access, making it feasible for same-day clinical use. Second, registration accuracy: LAMAReg achieves cutting-edge multi-modal registration accuracy, yielding accurate alignment of diffusion MRI, FLAIR, and intra-subject T1-weighted images while remaining generally robust to common artifacts. Third, data reliability: Using identifiability, we show MICAFlow maintains consistent performance across diverse datasets, including subjects with pathology, and is closely comparable to contemporary pipelines. In sum, MICAFlows combination of machine learning and efficient workflows produces research-grade data quality with clinical-grade speed. This work demonstrates that advanced MRI preprocessing can be done fast and robustly, helping close the gap between research neuroimaging and broad clinical application of quantitative MRI techniques. The source code for MICAFlow is available here: https://github.com/MICA-MNI/micaflow, and for LAMAReg here: https://github.com/MICA-MNI/LAMAReg.

bioinformatics↗

bioRxiv2026

CPT1A loss promotes lung metastasis in immune-competent mice via a mechanism of mtDNA release and chronic activation of STING pathway

The metastatic progression of breast cancer involves complex interactions between tumor cells and immune cells, including T cells that exert cytotoxic pressure to limit metastasis. Tumor cells reprogram their metabolism to evade immune surveillance, a critical step to achieving metastatic outgrowth. Using an unbiased CRISPR screen targeting metabolism-related genes and a clinically relevant spontaneous metastasis mouse model, we identified CPT1A, the rate-limiting enzyme in fatty acid {beta}-oxidation, as a suppressor of immune-dependent metastasis. Loss of CPT1A enhances lung metastasis in immunocompetent mice, but not Rag1 KO mice that lack mature lymphocytes. Loss of CPT1A triggers cytosolic mitochondrial DNA (mtDNA) release via the mPTP pore. Cytosolic mtDNA release triggers a STING-dependent inflammatory response, creating an environment that impairs CD8+ T cell function, promoting metastatic outgrowth. Among breast cancer patients, low CPT1A expression correlates with poor survival when CD8+ T cell infiltration is high. These findings reveal an extrinsic role for CPT1A in immune-tumor dynamics and suggest therapeutic opportunities targeting inflammation in metastatic breast cancer.

cancer biology↗

bioRxiv2026

A Rapidly Excretable, ROS-Scavenging Ionizable Lipid Decouples mRNA Delivery Potency from Toxicity

The broader clinical application of mRNA therapeutics remains constrained by dose-limiting toxicities, vector-associated immunogenicity, and prolonged tissue retention of lipid nanoparticles (LNPs) in vivo. Here, we report a class of ionizable lipids incorporating a sulfur-bearing hexyl 2-hydroxyethyl sulfide (HHES) motif that decouples mRNA delivery potency from these safety liabilities through dual functionality: the sulfur moiety acts as an intrinsic reactive oxygen species scavenger to suppress oxidative stress, while undergoing oxidative conversion into hydrophilic metabolites to promote rapid systemic clearance. HHES-based LNPs demonstrated a 3.3-fold shorter hepatic half-life and 29-fold lower total hepatic exposure than MC3, while maintaining robust protein expression including functional monoclonal antibody production in vivo. Repeated dosing in non-human primates confirmed negligible systemic, hepatic, or hematological toxicity. Leveraging this safety profile, subretinal HHES LNP delivery achieved up to 57% genome editing efficiency in retinal pigment epithelium, suppressing choroidal neovascularization by [~]65% in a wet age-related macular degeneration model without structural damage or microglial activation. This dual-function design provides a generalizable framework for safe, transient, non-accumulative mRNA nanomedicines.

bioengineering↗

bioRxiv2026

NPannotator: a genome- and chemistry- constrained automation for type I polyketide synthase pathway elucidation

Natural products (NPs) are structurally diverse bioactive compounds whose biosynthesis is encoded within biosynthetic gene clusters (BGCs). Although databases such as the Minimum Information about a Biosynthetic Gene Cluster (MiBIG) repository now catalog thousands of experimentally validated NP structures, the full biosynthetic pathway connecting individual domain sequences to specific chemical features on final NP structures remains largely unannotated. This gap is especially pronounced for type I polyketide synthases (PKSs). These are modular assembly lines in which multiple enzymatic domains work in concert to condense acyl-CoA building blocks into complex polyketide scaffolds. Within these systems, acyltransferase (AT) domains govern which starter and extender units are incorporated at each elongation step, yet the substrate specificities of AT domains are known for only a fraction of cataloged clusters. Moreover, the catalytic order of genes encoding PKS modules is not immediately apparent from existing database entries, leaving the correct module ordering for observed product structures uncertain. Here, we present NPannotator, an automated, genomic context-aware cheminformatics pipeline that infers both the catalytic ordering of PKS domains and the substrate specificities of a given PKSs AT domains. NPannotator loads a precomputed database of synthetically generated polyketide backbones, iteratively replaces default malonyl-CoA substrates with candidate starter and extender units via SMARTS-based substructure matching against the target NP, and selects the arrangement that maximizes chemical similarity. When benchmarked on the type I PKSs annotated within the expert-reviewed ClusterCAD dataset, NPannotator recovered 62.0% of both correct gene orderings and AT substrate annotations, and achieved 80.0% accuracy on gene ordering alone. By bridging gene-level architecture with chemical outcomes, NPannotator represents a step toward systematically decoding how protein sequence and genomic organization encode chemical structure in the world of natural products.

biochemistry↗

bioRxiv2026

Linear-time prediction of proteome-scale microbial protein interactions

Protein-protein interactions (PPIs) underpin biological function, yet proteome-scale interaction prediction remains bottlenecked by the quadratic computational complexity of all-vs-all pairwise comparisons. Here, we present FlashPPI, a contrastive learning framework, grounded in residue-level interactions, that enables linear-time prediction of physical protein interfaces across a microbial proteome. By leveraging a genomic language model that captures cross-protein co-evolutionary signals from metagenomic sequences, FlashPPI aligns interacting partners in a shared latent space. We demonstrate a four-fold performance increase over existing sequence-based methods, while reducing proteome-wide screening time from days to minutes. Crucially, FlashPPI achieves comparable screening performance to state-of-the-art structure-folding models at a fraction of the computational cost. Finally, we integrate FlashPPI into seqhub.org, an interactive web platform that combines predicted networks with functional annotations and genomic context, making proteome-wide network analysis rapid and accessible for microbial discovery.

molecular biology↗

bioRxiv2026

Hierarchical Signatures of Language in the Human Brain

Language relies on a hierarchy of sensory and cognitive processes, yet how different levels of this hierarchy are supported by distinct neural architectures remains unclear. Here we show that semantic processing, compared with phonological processing, is associated with higher-level brain networks, as characterized by resting-state fMRI connectivity, in vivo measures of cortical myelin, and cortical types derived from a cytoarchitecture-defined reference atlas. These relationships were established using individualized ultra-high field fMRI in both English and French speakers leveraging a multi-session, multi-modal 7T MRI protocol including a language localizer. For comparison, we developed an artificial neural network, in which a representational hierarchy spontaneously emerged where phonological information was captured in earlier layers and semantic information in later layers. By integrating individualized functional mapping, neuroanatomical characterization and artificial intelligence, this study advances understanding of the neural basis of language and provides a framework for linking biological and artificial systems of communication. Significance StatementLanguage is widely described as hierarchical, yet how this functional organization is implemented in the brains biological architecture remains unclear. By combining ultra-high field, individualized neuroimaging with in vivo measures of cortical microstructure and large-scale connectivity, this study establishes a framework for linking distinct levels of linguistic computation to the brains structural and functional organization. Integrating these findings with artificial neural network modeling further reveals shared principles between biological and machine systems. Together, this work advances a biologically grounded account of language, bridges cognitive neuroscience and artificial intelligence, and provides a roadmap for understanding how complex cognition emerges from structured brain architecture.

neuroscience↗

bioRxiv2026

OmniDetect: a plant-produced universal IgG binder replacing secondary antibodies in immunoassays

High sensitivity in immunodetection technologies has long been a priority for both diagnostic kit development and routine laboratory research. We developed a recombinant fusion protein, OmniDetect-G3, as an alternative to conventional HRP-conjugated secondary antibodies, and successfully produced it in plants. OmniDetect-G3 binds to primary IgG antibodies regardless of host species, and also recognizes chicken IgY. In comparative analyses, OmniDetect-G3 exhibits 165-381% higher sensitivity than commercial secondary antibodies in western blot analysis and 30%-1145% higher sensitivity in ELISA, depending on commercial products tested. Moreover, OmniDetect-G3 showed robust performance when used with sera from vaccinated animals (porcine and bovine). The chemiluminescence signal generated by OmniDetect-G3 remained stable up to 30 minutes after reaction initiation. These findings indicate that plant-produced OmniDetect-G3 has strong potential as a universal mimetic to animal-derived HRP-conjugated secondary antibodies, offering simplified immunoassay workflows and improved detection efficiency.

immunology↗

bioRxiv2025

Optimizing methods for virome analysis based on studies of a synthetic viral community

Studies of whole viral populations--the "virome"--are yielding exciting new insights into biological systems, but methods are still being optimized. Here we describe generation and use of a synthetic viral community to assess several technical challenges important in virome analysis. Our mock community was comprised of phages lambda, T4, M13, MS2, and phi6, together with adeno-associated virus (AAV), murine hepatitis virus (MHV), and vaccinia virus (VV). We spiked the mock community into different human sample types, including stool, saliva, oropharyngeal (OP) wash, and bronchoalveolar lavage (BAL), then passed the samples through different virus enrichment protocols and analyzed by Illumina sequencing. Compared to direct metagenomic sequencing, VLP enrichment protocols greatly increased viral read yields from virus-rich samples such as from stool and saliva. Three VLP enrichment work flows were compared, and each was found to have strengths and weaknesses. Four methods for DNA amplification were compared, with three showing over-amplification of small circular ssDNA viruses, most notably GenomiPhi. Studies of viral particle stability in the presence of nuclease showed that most viral genomes were stable when protected in viral particles, but phage MS2 RNA was unexpectedly labile under some of the conditions tested. Comparison of Illumina 1000-cycle sequencing versus 300-cycle sequencing showed that longer reads supported generation of longer viral genome assemblies. Bacteriophage DNA can be modified by at least 12 different chemistries, raising the question of whether these modifications might block recovery in virome analytical protocols. We tested bacteriophage T4 DNA modified with glucosyl-hydroxymethylcytosine (ghmC) and hydroxymethylcytosine (hmC), and found that both were readily detected, though the recovery of ghmC-modified DNA was reduced. These studies together with published data help provide guidance for virome researchers optimizing analytical protocols.

microbiology↗

bioRxiv2025

Intracortical microstructure profiling: a versatile method for indexing cortical lamination

Intracortical microstructure profiling represents a powerful, scalable approach for investigating the laminar organisation of the human cortex on both in vivo and post-mortem datasets. Building upon a long tradition of histological analysis, this method leverages surface-based intracortical sampling to generate profiles of tissue properties across cortical depths. The present work outlines a standardised workflow for intracortical microstructural profiling, newly packaged as an open-source toolbox "CortPro" (https://github.com/caseypaquola/cortpro). Here, we explore the utility of central moments as descriptors of profile shape. Using these measures, we quantify (i) the extent to which in vivo MRI can capture laminar differentiation, (ii) the test-retest reliability of profiles, and (iii) their replicability across sites and studies. Our results demonstrate that intracortical profiles are remarkably robust and effectively mitigate bias-field related limitations of non-quantitative MRI. As applications of microstructure-sensitive imaging expand across development, aging, and disease, microstructure profiling provides a principled means of linking microstructural neuroanatomy with systems-level brain organisation.

neuroscience↗

bioRxiv2025

State dependent shifts in large scale functional topographies

Although functional networks can be consistently identified across cognitive states, they also undergo dynamic reconfigurations across different contexts. For example, naturalistic movie watching paradigms amplify activity in sensory systems compared to resting conditions. However, it remains unclear how these different states affect large-scale brain organization. The current study leveraged high-resolution in vivo 7T fMRI data from the Human Connectome Project (HCP) and the Precision NeuroImaging (PNI) datasets to examine large scale functional connectivity changes between resting and movie-watching conditions. To understand these changes within topographic and geometric principles of brain organization, connectivity shifts were stratified relative to macroscale cortical hierarchy and geodesic distance. Our results revealed that primary sensory areas showed increased local connectivity and reduced long-range interactions during movie watching relative to resting conditions, whereas the default mode network (DMN) exhibited an opposing pattern characterized by reduced within-network long-range connectivity and enhanced connectivity with distant regions outside the DMN. Together, these findings demonstrate that different cognitive states involve geometry-and hierarchy-informed reorganization of large-scale functional networks.

neuroscience↗

bioRxiv2025

Mutation-Agnostic Base Editing of the Progerin Farnesylation Site Rescues Hutchinson-Gilford Progeria Syndrome Phenotypes in Neuromuscular Organoids

Hutchinson Gilford progeria syndrome (HGPS) is a fatal premature aging disorder caused by pathogenic farnesylated lamin A variants that disrupt nuclear architecture and DNA repair. Current therapies, including farnesyltransferase inhibitors, provide only modest survival benefits and lack molecular specificity, while mutation-specific genome-editing strategies cannot address atypical laminopathies. Here, we develop Farnesylation Amino acid Targeted Editing (FATE), a mutation-agnostic base-editing platform that selectively disrupts the LMNA farnesylation motif without affecting other farnesylated proteins. Using isogenic human pluripotent stem cell derived neuromuscular organoids (NMOs), we reveal muscle-specific progerin accumulation that sequesters 53BP1 and abolishes DNA damage foci formation. FATE eliminates perinuclear progerin, restores 53BP1 mobility, reconstitutes DNA repair foci, and normalizes heterochromatin architecture. Importantly, transient delivery of FATE mRNA conjugated with lipid nanoparticles to HGPS NMOs achieves efficient base editing and phenotypic rescue. These findings establish FATE as a mutation-independent therapeutic strategy targeting a fundamental pathogenic mechanism in HGPS and provide a proof-of-concept for RNA-based in situ genome editing in progeroid disease.

pathology↗

bioRxiv2025

A unified imaging-histology framework for superficial white matter architecture studies in the human brain

The superficial white matter (SWM), immediately beneath the cortical mantle, is thought to play a major role in cortico-cortical connectivity as well as large-scale brain function. Yet, this compartment remains rarely studied due to its complex organization. Our objectives were to develop and disseminate a robust computational framework to study SWM organization based on 3D histology and high-field 7T MRI. Using data from the BigBrain and Ahead 3D histology initiatives, we first interrogated variations in cell staining intensities across different cortical regions and different SWM depths. These findings were then translated to in-vivo 7T quantitative myelin-sensitive MRI, including T1 relaxometry (T1 map) and magnetization transfer saturation (MTsat). As indicated by the statistical moments of the SWM intensity profiles, the first 2 mm below the cortico-subcortical boundary were characterized by high structural complexity. We quantified SWM microstructural variation using a non-linear dimensionality reduction method and examined the relationship of the resulting microstructural gradients with indices of cortical geometry, as well as structural and functional connectivity. Our results showed correlations between SWM microstructural gradients, as well as curvature and cortico-cortical functional connectivity. Our study provides novel insights into the organization of SWM in the human brain and underscores the potential of SWM mapping to advance fundamental and applied neuroscience research. HighlightsO_LIDeveloped an anatomy-based open science framework to study SWM organization based on 3D post-mortem histology and/or in-vivo high-field MRI C_LIO_LIThe first 2 mm into the white matter are characterized by high structural complexity C_LIO_LIInter-regional trends in SWM microstructural variation, which related to cortical geometry, as well as cortico-cortical connectivity C_LI

neuroscience↗

bioRxiv2025

Targeting mTORC2 in lung squamous cell carcinoma improves anti-tumor immunity through the PSGL-1-VISTA axis

Targeted therapies have improved survival for lung adenocarcinoma patients. However, similar advances are lacking for lung squamous carcinoma (LUSC). Advances in immunotherapy have shown some promise, but the overall response rate remains low in LUSC. Here, we demonstrate that the mTORC2 signaling pathway represents an actionable target in LUSC to improve anti-tumor immune responses. We show that genetic alterations affecting the mTORC2 pathway are common among patients with LUSC tumors, and targeting mTORC2 reduces LUSC tumor growth in mouse models. Transcriptomics reveal that mTORC2-deficient LUSC cells exhibit reduced expression of glycolytic and hypoxia-related genes. In agreement, loss of mTORC2 signaling decreases lactate levels in tumor-interstitial fluid, creating reduced acidity within the tumor microenvironment. Interestingly, mTORC2-deficient LUSC cells also exhibited reduced expression of the pH-sensitive VISTA ligand PSGL-1 in a HIF-2 dependent mechanism. LUSC patients, but not those with LUAD, display a positive correlation in expression between HIF-2 and PSGL-1, suggesting a distinct association among mTORC2, HIF-2, and immune responses in LUSC. Indeed, mTORC2 loss-of-function enhanced CD8+ T cell activation in tumors, while use of anti-VISTA immunotherapy reduced LUSC tumor burden only in the presence of intact mTORC2 signaling. Collectively, these data describe an important role of mTORC2 signaling in LUSC tumors and demonstrate the therapeutic potential of targeting the mTORC2/PSGL-1/VISTA axis in patients that are non-responsive to current therapies.

cancer biology↗