Biology subjects

Kim, W.

Publications and source records attributed to Kim, W..

At least 19 recordsLinked to original sources

bioRxiv2026

FateDriver: Weakly supervised dual-view graph learning for transition-specific prioritization of candidate regulators in cellular reprogramming

Cellular reprogramming supports regenerative medicine, yet the endogenous regulators of a specified source-to-target transition remain incompletely defined. Existing computational methods rank candidate regulators from network topology, trajectory dynamics, or cell-state labels, leaving unused the factors experimentally delivered to induce the transition. We present FateDriver, a weakly supervised dual-view graph neural network that jointly represents cells and genes from single-cell transcriptomes, treats the delivered factors as sparse gene-level labels, and ranks the remaining genes for a specified transition under a positive--unlabeled formulation. Across two OSKM datasets and one GMT dataset, FateDriver ranked first or second among six methods in recovering externally curated reference genes, exceeded a supervision-matched non-graph model despite weaker co-expression with the delivered factors, and achieved the highest recovery of protein targets of pluripotency-inducing chemical cocktails in both OSKM datasets. Holding either the source or the endpoint fixed yielded distinct candidate programs, including a DDX58--interferon axis associated with cells lacking endogenous pluripotency markers. Applying the same framework to candidate source--target pairs prioritized distinct candidate origins for two in vivo partially reprogrammed intestinal populations. FateDriver converts sparse experimental knowledge into transition-specific hypotheses for regulator prioritization from single-cell trajectories.

bioinformatics↗

bioRxiv2026

Variable sparsity non-negative matrix and tensor factorization algorithms and their applications in cancer genomics

The field of oncology has experienced significant advancements in novel therapies and molecular diagnostics to personalize initial cancer treatments. However, cancer's propensity for evolution and resistance to therapies remains a formidable challenge due to its dynamic nature. Cancer's complex and adaptive behavior surpasses the capabilities of simple models, complicating our comprehension at every level, from basic sciences to clinical practices, highlighting the urgent need for innovative approaches to improve the modeling and classification of cancer. In this context, matrix factorization algorithms have been used to generate transcriptional signatures that summarize the most salient patterns of behaviors in cancer datasets. For example, the standard non-negative matrix factorization algorithm (NMF) generates a dimensionality-reduced representation that encodes a significant amount of data relationships as a mixture of positive components and provides a working summary of the input data. The resulting NMF factor matrices, W and H, display some degree of sparseness; however, this sparseness is often a byproduct rather than an explicit objective of the NMF algorithm, and the user has limited control over the degree of sparseness of the representation and the corresponding balance between local versus global structures in the NMF results. Some sparse versions of NMF have been introduced but still do not allow a fine-grained control on the sparsity constraints. We present here a novel variable-sparsity Non-negative Matrix Factorization algorithm (vsNMF), where instead of imposing sparsity as a regularization constraint on the NMF objective function, sparsity is explicitly enforced by a projective step performed for each column of W and row of H after a standard NMF update. In this way, the algorithm takes as input the input matrix, plus two one-dimensional vectors, that specify the sparsity functions that will be imposed on the NMF solution. The more explicit control of sparsity, and the corresponding balance between local vs. global structure, at the level of individual components, allows the generation of NMF solutions that can be tuned to operate anywhere between a generative, parts-based encoding of overlapping features, and a partitional, soft-clustering model. This allows greater flexibility to represent biological subtypes, patterns of pathway activation or deregulation, and higher biological interpretability. These learned low-dimensionality representations can also be used to integrate and merge datasets, or to define groups of similar cancer samples representing putative cellular or tumor states. Adjustable/tunable NMF representations of biological data can greatly help advance our fundamental understanding of cancer biology, provide more interpretable computational models of cancer, and better functional cancer taxonomies and precision oncology paradigms. We apply the same approach to tensors and introduce a variable-sparsity Non-Negative Tensor Factorization algorithm (vsNTF) that can take an input tensor and sparsity functions for each of the tensor dimensions.

bioinformatics↗

bioRxiv2026

The Multi-scale Copula Index (MCI): a new information-theoretic measure of association and its applications in functional cancer genomics

Cancer genomic analyses increasingly involve large, complex datasets representing diverse omics variables, such as gene expression, mutations, copy number alterations, genetic perturbations (e.g. CRISPR or iRNA), drug sensitivity, and clinical phenotypes, making it crucial to accurately measure associations among these variables. Traditional correlation-based methods, like the Pearson correlation coefficient, often assume linearity, Gaussian distributions, and independence among variables, leading to oversimplified assumptions, less sensitive readouts and less accurate significance estimation. Information-theoretic measures overcome these limitations by being one step removed from the data and assessing dependencies at the level of probability distributions, thus providing a more data-agnostic, robust measure for identifying associations in common analysis tasks such as feature selection, pattern recognition, and predictive modeling. Building on these foundations, we introduce the Multi-scale Copula Index (MCI), a novel information-theoretic measure of association. The MCI offers significant advantages over existing methods by eliminating the need for density estimation and parameter tuning, thereby ensuring consistent estimation with reduced computational complexity. Furthermore, it enhances statistical power at lower sample sizes, exhibits strong robustness to outliers, and successfully captures both directionality and important symmetries under input-data transformations, such as reflection or complementation. Due to these strengths, the MCI is particularly useful for functional cancer genomic applications involving, e.g., transcriptional and perturbational data, with different statistical properties across a wide range of dataset sizes and complexity. Contextual associations often arise in functional genomics datasets: two genomic variables show little or no correlation in most samples, yet display a strong linkage within the subset that reflects the active biological context. These situations are ideal for quantifying associations with the MCI. We illustrate the performance of the MCI in a variety of benchmarks and cancer genomic examples and applications. We also introduce the Cumulative Entropy Diagram (CED), a graphical display that allows the visualization of the MCI between a reference vector, such as a phenotype, pathway activation or drug response, and a complete set of genomic features.

bioinformatics↗

bioRxiv2026

Surfactant-Enhanced Hybridization Capture for Direct Sequence-Specific RNA Extraction from Plasma and Whole Blood

Direct recovery of low-abundance RNA from complex biological samples remains a major challenge for ultrasensitive detection. Sequence-specific hybridization capture enables selective enrichment, but recovery from crude samples is compromised by RNA degradation, protein interference, RNA secondary structure, and target sequence variation. Here, we address these limitations with a sodium dodecyl sulfate (SDS)-based formulation that not only lyses virions and protects RNA, but also directly accelerates hybridization kinetics, substantially reducing the need for thermal denaturation. This enabled direct RNA capture from crude plasma or whole blood with near-quantitative recovery, outperforming a widely used silica-based kit at low input. Without centrifugation or plasma separation, we detected HIV RNA by RT-qPCR at 25 copies/mL directly from whole blood. We further developed a free energy ({Delta}G)-guided algorithm for mutation-robust probe design, achieving >85% mean recovery across HIV-1 subtypes with a single probe. This work opens low-abundance RNA biomarkers in crude biofluids to ultrasensitive detection, addressing a major barrier to early diagnosis.

bioengineering↗

bioRxiv2026

Achieving near single-molecule sensitivity in separation-free protein detection using engineered kinetic proofreading

Unlike nucleic acids, proteins cannot be directly amplified. Ultrasensitive detection must therefore couple efficient analyte-to-signal conversion with strong suppression of target-independent background. Consistently detecting ~100 molecules (below which Poisson sampling noise alone causes CV to exceed 10%) across protein targets in a format as scalable and accessible as PCR remains unsolved. Separation-based ultrasensitive immunoassays require target binding stable enough to survive stringent washing and are therefore constrained by wash-induced signal loss and, more fundamentally, the relative scarcity of exceptionally tight binders. Performance consequently varies across targets; detection limits below 1,000 molecules remain rare. Conventional separation-free proximity assays avoid washing but incur background from random probe collisions, with reported detection limits frequently exceeding 100,000 molecules. Here we introduce Successive Proximity Extension Amplification Reaction (SPEAR), a separation-free architecture in which autonomous engineered DNA nanodevices emulate biological kinetic proofreading. Two successive irreversible proximity-extension steps compound discrimination between analyte-dependent and background reactions, suppressing spurious signals while preserving efficient analyte-to-signal conversion. This design reduces reliance on high-affinity binders and enables sub-fM detection from 1 uL samples through simple 3-step mixing followed by standard qPCR readout. Across 11 biomarkers tested, SPEAR consistently achieved sub-100-molecule detection limits. Where compared, it outperformed ultrasensitive separation-based platforms, analytically and clinically, including for low-abundance Alzheimer's disease biomarkers. SPEAR also precisely quantified SARS-CoV-2 neutralizing antibody titers from finger-prick dried blood spots, concordant with the cell-based reference assay on venous blood. It detected a distinct mixed phosphorylation state of Tau, and targeting this state resolved previously observed capillary-venous discordance and improved amyloid-status discrimination. These results establish engineered autonomous successive molecular discrimination as a practical strategy for near-single-molecule protein detection, extending the sensitivity, scalability and accessibility of PCR-based testing to non-amplifiable analytes.

bioengineering↗

bioRxiv2026

Cascaded Nano-ring Dialyzer for Continuous Regenerative Peritoneal Dialysis

End-stage kidney disease (ESKD) requires lifelong kidney replacement therapy, yet conventional hemodialysis and peritoneal dialysis remain limited by intermittent treatment, restricted mobility, and repeated dialysate exchange. Here, we developed a continuous regenerative peritoneal dialysis platform based on a nano-ring-assisted nanoelectrokinetic dialyzer for portable artificial kidney applications. We first identified key geometric and electrokinetic parameters governing the removal performance of nano-ring meshes, including mesh dimension, nano-ring coating thickness, the number of cascaded nano-rings, and the relative orientation between fluid flow and the applied electric field. We then developed a single nano-ring dialyzer operating at 1.33 mL/min and scaled the treatment capacity to approximately 10 mL min/min through parallel integration of multiple modules. In a canine model, the closed-loop system achieved approximately 10 % reduction in circulating uremic toxin levels during continuous treatment. We further improved the biocompatibility of the regenerated dialysate by integrating plate-type electrodes, activated carbon, bicarbonate buffering, and UV-C treatment. In an unanesthetized canine model, the improved system sustained continuous toxin removal for 4 h while major hepatic and inflammatory markers remained within recoverable ranges. These results demonstrate that cascaded nano-ring enables continuous dialysate regeneration with scalable throughput, reduced dependence on fresh dialysate, and in vivo control of uremic toxins, providing a technological foundation for portable or wearable regenerative peritoneal dialysis systems.

bioengineering↗

bioRxiv2026

Functional importance and paralog-specificity of the intrinsically disordered RsmE C-terminus region in Pseudomonas fluorescens Pf0-1

RsmE and its homologs function as RNA-binding post-transcriptional regulators that control the production of diverse secondary metabolites. Pseudomonads harbor varying numbers of RsmE paralogs that are often generalized to overlap in function. However, recent studies indicate that these paralogs bind to both overlapping and unique sets of mRNA. In Pseudomonas fluorescens Pf0-1, RsmE exclusively regulates the production of multiple extracellular secretions, distinguishing it from its paralogs, RsmA and RsmI. While the majority of the three paralogs core sequences are highly conserved, each possesses a vastly different C-terminus region. The C-terminus tails are generalized to be functionless, as they are intrinsically disordered and devoid of known mRNA binding sites. Here, we challenge this notion through analyses of various naturally emergent RsmE variants that differentially impact repressive function solely from changes in the C-terminus tail. Engineered Rsm chimeras containing the various paralog cores and tails further confirmed the functional importance of the C-terminus tail, as neither replacing the RsmE tail with the RsmA tail nor attaching the RsmE tail to a different paralog core restored repression. However, the RsmI tail complemented function in the presence of the RsmE core, indicating that RsmEs functional specificity lies within the core despite the essentiality of the C-terminus. Bioinformatic analyses also revealed that the C-terminus tail composition of RsmA to be the most unique among the paralogs and each tail sequence is uniquely and highly conserved across diverse proteins, not only in bacteria, but also in eukaryotic species.

microbiology↗

bioRxiv2026

Functional impact of a type VI secretion system on RsmE-mediated spatial structure formation in Pseudomonas fluorescens Pf0-1

Bacteria naturally form densely structured populations wherein both space and nutrients become locally limited. In densely populated Pseudomonas fluorescens Pf0-1 colonies, spatiogenetic patches with drastically reduced cellular density naturally emerge through spontaneous mutations in rsmE. RsmE is a posttranscriptional regulator that binds to specific mRNAs, including those that consequently repress the production of extracellular secretions. We have previously shown that {Delta}rsmE produces an extracellular polysaccharide (EPS) and biosurfactant that collectively function to define the spatiogenetic structure and locally outcompete the WT. Here, we identify additional RsmE-regulated secretions through a combination of RNA-sequencing and LC-MS/MS. In particular, a type VI secretion system (T6SS) was exclusively produced by {Delta}rsmE. Confocal microscopy imaging of WT and genetically modified {Delta}rsmE cocultures showed that the T6SS kills WT cells that invade the low- density spatiogenetic structure. However, its impact on competition with the WT was both quantifiably and spatially limited in the absence of the normally co-produced EPS and biosurfactant, largely due to the consequently altered spatial structure. These results highlight the importance of understanding both the individual and collective spatial functions of extracellular secretions, especially in the ecological context of densely structured microbial populations. IMPORTANCEIn crowded wild type (WT) Pseudomonas fluorescens Pf0-1 colonies, rsmE mutants spontaneously emerge by forming a low cellular density spatial structure that is devoid of WT cells. RsmE functions primarily to repress the production of various extracellular secretions, including an extracellular polysaccharide and biosurfactant, that collectively form the unique spatial structure. Here, we describe an RsmE-regulated type VI secretion system that kills the invading WT cells and protect the low-density structure. Importantly, individual RsmE-regulated secretions carry out unique functions, but their efficacies largely depend on other co-regulated products. Extracellular secretions that are mechanistically similar to those described here are co- produced across diverse biofilm-forming and virulent bacterial species, where they also likely play complex molecular and ecological roles.

microbiology↗

bioRxiv2026

Solanum americanum Bs2 and ZAR1 homologs recognize Xanthomonas euvesicatoria effectors essential for infection.

Multiple recognition events of pathogen-secreted effectors by immune receptors confer robust disease resistance in plants. Understanding the underlying mechanisms facilitates the discovery and deployment of valuable resistance genes for crop protection. Xanthomonas euvesicatoria causes devastating bacterial spot disease in solanaceous crops but cannot infect the wild relative Solanum americanum. Here, we identified X. euvesicatoria type III effectors (T3Es) that induce cell death in S. americanum when transiently expressed in leaf. By quantifying immune responses of the S. americanum SP2273 accession to X. euvesicatoria multiple-T3E knockout mutants, we demonstrated that at least nine T3Es (AvrBs2, XopAP, XopAU, XopE1, XopJ3, XopM, XopN, XopX, and XopZ1) collectively contribute to effector-triggered immunity (ETI). Among these, AvrBs2 and XopJ3 were the primary drivers of ETI, eliciting robust cell death and defense gene expression when naturally delivered into plant cells. We next generated S. americanum lines concomitantly edited at the corresponding immune receptor loci, SaBs2 and SaZAR1 (SP2273-bz). Genetic complementation of SP2273-bz confirmed that AvrBs2 and XopJ3 are specifically recognized by each of the four SaBs2 homologs and by SaZAR1, respectively. Moreover, enhanced growth of X. euvesicatoria on the characterized SP2273-bz line indicated that both effectors are required for bacterial multiplication in S. americanum. Together, our findings provide a framework for understanding the mechanisms of ETI-mediated resistance and establish a genetic foundation for resistance breeding in solanaceous crops.

plant biology↗

bioRxiv2026

Frontolimbic Functional Connectivity Development from Birth to Emerging Adulthood

Frontolimbic circuits connecting the frontal cortex with the amygdala and the hippocampus are critical for emotion and learning. These connections undergo major changes throughout childhood and adolescence, yet the principles guiding their maturation remain unclear. Analyzing large developmental cohorts, we show that fronto-hippocampus connectivity develops rapidly in early childhood and stabilizes thereafter. In contrast, fronto-amygdala connectivity becomes progressively differentiated from fronto-hippocampus connectivity, with development most pronounced during adolescence. This entailed hippocampus and amygdala respectively becoming preferentially tethered to association-related regions and sensorimotor-related regions. Greater adversity exposure was associated with more differentiated fronto-amygdala connectivity for a given age. Higher cognitive ability was associated with less differentiated fronto-hippocampus connectivity. These findings suggest that frontolimbic connectivity development follows a principle of differentiation, with circuit-specific timing and sensitivity to stress and learning. This work provides a foundation for understanding typical and atypical frontolimbic circuitry development from birth to emerging adulthood. Significance StatementThe frontolimbic circuit, especially the fronto-hippocampus and fronto-amygdala circuitry, is integral for cognitive and affective processes. Yet its maturation has been challenging to characterize due to variable connectivity growth across the frontal cortex. Here, we reveal that this variability follows a principle of differentiation, where the hippocampus and the amygdala acquire respectively unique connectivity profiles with the frontal cortex at disparate developmental stages. Deviations from these normative trajectories were linked to cognitive ability and cumulative adversity, respectively. This approach provides a framework to unify inconsistent findings while serving as a foundation for identifying circuit-specific windows of plasticity and vulnerability.

neuroscience↗

bioRxiv2026

Immunodominance Hierarchy of Endogenous BBN963 Bladder Cancer Antigens Remains Stable Under Anti-PD1 and Anti-CTLA4 Immunotherapy

Immune checkpoint inhibition (ICI) is clinically active against multiple cancers, including urothelial cancer at the non-muscle invasive, muscle-invasive, and metastatic stages. Despite this, large numbers of patients experience disease progression and relapse after treatment with ICI-containing regimens. Tumor antigen-specific T cells are critical to ICI response, however few studies have evaluated the breadth and magnitude of tumor antigen-specific T cell responses with ICI therapy. In this study, we mapped the tumor antigen immunodominance hierarchy in the BBN963 model of murine basal-like bladder cancer for endogenous tumor neoantigens expressed physiologically. We used a high-throughput matrixed ELISpot assay to detect CD8+ T cell responses to predicted BBN963 tumor antigens derived from multiple mutational genomic sources. We found CD8+ T cell responses were directed against a subset of tumor antigens forming a stable and reproducible immunodominance hierarchy across individual mice. Treatment with anti-PD-1 or anti-CTLA-4 did not substantially reshape this hierarchy or broadly shift dominant responses to previously defined subdominant epitopes. Predicted peptide MHC binding stability and affinity was associated with antigen immunogenicity. Cancer-testis antigens, endogenous retroviral antigens, and SNV-derived tumor antigens that were immunogenic were found across tumor subclones. By diversifying the immunogenic antigen repertoire beyond SNVs, we achieved nearly 100% tumor subclone coverage, suggesting that broader antigen selection could help immunotherapy target more tumor subclones. In conclusion, this study supports the stability of the immunodominance hierarchy under ICI therapy and a role for broadening antigen discovery to multiple expressional sources in immunotherapy design.

cancer biology↗

bioRxiv2026

Decoy diversification underpins the regulation of an NLR-mediated autoimmunity

Appropriate activation of innate immune receptors is vital for the plant immune system. Immune activation must be strong and robust upon invasion by rapidly evolving pathogen species, while staying inactive in the absence of a pathogen to avoid constitutive defense responses that inhibit plant growth. Nucleotide-binding leucine-rich repeat receptors (NLRs) are intracellular proteins that surveil for pathogen invasion, often by direct or indirect perception of pathogen effector proteins. Indirect recognition of pathogen effector proteins, through monitoring the integrity of guardee or decoy proteins, can allow for a single NLR to detect a wide range of pathogen effectors. In this work, we investigated how the Solanaceae NLR NbPtr1 can recognize six different effector proteins from the bacterial pathogens Pseudomonas syringae, Xanthomonas perforans, and Ralstonia pseudosolanacearum. We identified several NOI-domain containing proteins that are guarded by NbPtr1. These NOI proteins share homology with, but are distinct from, RPM1 INTERACTING PROTEIN 4 (RIN4), a well-known guardee in Arabidopsis. Virus-induced gene silencing and CRISPR/Cas9-assisted deletion of NbNOI genes resulted in stunted growth dependent on NbPtr1 activity. Negative regulation of NbPtr1 requires the interaction between NbPtr1 and the suppressor NbNOIs. A conserved threonine residue of the NOI proteins is required for this interaction and fits into a putative binding pocket of NbPtr1 based on protein modeling. This threonine residue is modified by some of the recognized effector proteins. Our study uncovers the regulatory mechanism of an autoactive NLR and highlights the importance of decoy diversification in establishing compatibility with NLRs.

plant biology↗

bioRxiv2026

Display functions of dinosaur proto-wings before powered flight

Pennaceous feathers are fundamental to avian flight, yet their early function in non-volant dinosaurs remains unknown. Early-diverging pennaraptorans had simple pennaceous feathers on proto-wings and tails, which were unsuitable for flight but may have enhanced visual signals. However, the visual display hypothesis has not been empirically tested. To address this, we used computer animations of early pennaraptoran displays to measure responses in a well-established animal model of a visually sensitive neural pathway. We show that pennaceous proto-wings and tails enhance the efficiency of motion-based displays across a range of anatomically plausible movements. Integrating these results with comparative and paleontological evidence, we suggest that early pennaceous feathers functioned in diverse signaling contexts and were subsequently exapted for aerodynamic use.

evolutionary biology↗

bioRxiv2026

Bioactivity-driven discovery of repurposable antivirals as OSCAR inhibitors that promote cartilage protection via transcriptomic reprogramming

Osteoarthritis (OA) is a progressive degenerative joint disorder characterized by cartilage degradation, chronic pain, and impaired joint function. The avascular nature of cartilage isolates chondrocytes from systemic circulation, presenting significant challenges for therapeutic intervention. Despite extensive efforts, no clinically effective disease-modifying osteoarthritis drugs (DMOADs) are currently available. Targeting chondrocyte-specific receptors has therefore emerged as a promising strategy. The osteoclast-associated receptor (OSCAR), expressed on chondrocytes, has been implicated in the regulation of cartilage homeostasis and OA pathogenesis. Here, we applied sBEAR (Structurally similar Bioactive compound Enrichment by Assay Repositioning), a bioactivity-driven virtual screening framework independent of target structural information, to identify small-molecule inhibitors of the OSCAR-collagen interaction. By mining large-scale bioactivity profiles, we identified adefovir (ADV) and brivudine (BRV), as candidate OSCAR inhibitors. Molecular docking analyses indicated that both compounds occupy the collagen-recognition pocket within the OSCAR D2 domain. Intra-articular administration of these compounds in a post-traumatic OA mouse model significantly attenuated OA progression and enhanced chondrocyte regeneration. Both compounds increased Sox9 expression, and transcriptomic analyses revealed that BRV reverses inflammatory and extracellular matrix-degrading transcriptional programs. Together, these findings establish OSCAR as a therapeutically actionable target in OA and highlight ADV and BRV as potential DMOAD candidates.

bioinformatics↗

bioRxiv2026

TACE reprograms RANKL-mediated differentiation of macrophages by activating the non-canonical pathway of IRF3

Inflammation is associated with an influx of inflammatory macrophages and increased activation and differentiation of osteoclasts. Receptor activator of NF-kB ligand (RANKL) is a key driver for osteoclast differentiation. However, the pathogenic mechanisms augmenting RANKL-induced osteoclast differentiation in inflammatory conditions are not fully elucidated. Here, we show that TNF- converting enzyme (TACE) plays a critical role in pathological bone erosion and enhances osteoclast differentiation in inflammatory conditions. Myeloid cell-specific TACE deletion in a murine arthritis model attenuates joint inflammation and bone destruction. TACE deficiency suppresses distal RANKL signaling in macrophages by increasing IRF3 activation, while enhancing proximal RANKL signaling, leading to the suppression of osteoclast differentiation. Mechanistically, IRF3 activation limits macrophage reprogramming by suppressing NFATc1 and HB-EGF in response to RANKL through a non-canonical pathway. HB-EGF, a TACE substrate, activates EGFR signaling and promotes osteoclastogenesis by inhibiting IRF3 activation. TACE regulates the reciprocal inhibition of the IRF3-HBEGF axis. Our study highlights a role for TACE as a rheostat, balancing both pro- and anti-osteoclastogenic signals.

cell biology↗

bioRxiv2026

Computational design of orthogonal TCR α/β interfaces for dual-TCR therapeutics

T-cell receptors (TCRs) recognize peptides presented by MHC, enabling access to intracellular targets that are largely inaccessible to antibodies and difficult to target with small molecules. Despite this potential, their inherent cross-reactivity limits tumor specificity, while single-antigen targeting provides limited coverage of intratumoral heterogeneity. Dual-TCR therapeutics comprising two distinct TCRs could enhance tumor specificity via combinatorial recognition while broadening coverage across heterogeneous antigens. However, practical development of dual-TCR therapeutics has been limited by /{beta} subunit mispairing that prevents efficient production and creates undesired binding properties. Here, we develop orthogonal TCR /{beta} interfaces that prevent subunit mispairing. Using computational multistate design and second-site suppressor strategies implemented in Rosetta, we identified over 250 TCR variants for experimental screening to assess protein stability and pairing fidelity. The top-performing designs achieved approximately 95% correct pairing, as validated by mass spectrometry and X-ray crystallography. Focusing mutations on constant domains and conserved framework regions of variable domains enabled broad applicability across diverse TCRs while preserving antigen recognition. Using these orthogonal interfaces, we developed trispecific T-cell engagers (TriTEs) that target two cancer-testis antigens and CD3 on T cells, demonstrating enhanced potency under dual-antigen engagement (EC50 of 380 fM) while maintaining high activity when targeting cells displaying a single antigen (EC50s of 48 pM and 20 pM). This orthogonal TCR interface technology establishes a generalizable platform for engineering multi-specific immune therapeutics targeting diverse cancer antigens.

bioengineering↗

bioRxiv2025

Genetic Drivers of Sensitivity or Resistance to RAS(ON) Multi-Selective Inhibitors in NRAS-Mutated Melanoma

Most patients with advanced BRAF or NRAS-driven melanoma receive front-line immunotherapy. However, if immunotherapy fails, BRAF-mutated patients have effective second-line therapies, whereas NRAS-mutated patients lack pathway-targeted options. Recently, RAS(ON) multi-selective inhibitors like RMC-7977, and the investigational agent daraxonrasib, were described that, in partnership with cyclophilin-A (CYPA), inhibit RAS[GTP] signaling. Both compounds demonstrate potent anti-proliferative activity against NRAS-mutated melanoma cell lines and robust anti-tumor activity against preclinical melanoma models. However, in preclinical models, resistance to RMC-7977 monotherapy arose through mutations in Ppia (encoding CYPA) or Map2k1 (encoding MEK1). Moreover, two clinical case studies in patients with NRAS-mutated melanoma treated with daraxonrasib demonstrated clear anti-tumor activity in one patient, but progressive disease in another with co-occurring NRAS and MAP2K1 mutations at baseline. These findings support the potential for daraxonrasib in treatment of patients with NRAS-mutated melanoma, and reveal candidate mechanisms of monotherapy resistance, underscoring the need for combination therapies to improve outcomes. SIGNIFICANCEThere are no pathway-targeted therapies for patients with NRAS-mutated melanoma. Here we demonstrate that direct pharmacological inhibition of RAS[GTP] with RMC-7977 or daraxonrasib (RMC-6236) has profound inhibitory effects in preclinical models of NRAS-mutated melanoma. Furthermore, we identify mechanisms of resistance to RMC-7977 through mutational inactivation of CYPA or mutational activation of MEK1.

cancer biology↗

bioRxiv2025

A Cross-scale Causal Mapping Framework Pinpoints Macrophage Orchestrators of Balanced Arterial Development

Postnatal pulmonary arteries experience an abrupt surge in flow that demands tightly coordinated remodeling of vascular structure and mechanical compliance. However, the cellular programs orchestrating these multiscale adaptation remain poorly defined, partly due to the absence of analytical tools integrating gene-cell-tissue scales. Here, we present CausaLink, a cross-scale causal mapping framework that predicts how altered gene expression propagates through gene-cell-tissue networks by integrating time-course transcriptomic and tissue morpho-mechanical data. We constructed a single-cell transcriptomic atlas of 11,143 proximal pulmonary artery-derived cells from C57BL/6J mice across five developmental stages (P2, P10, P21, P42, and P84), revealing dynamic lineage transitions and transient mesenchymal population specifying into fibroblasts and smooth muscle cells from P2 to P21. Using this framework, we identified Mgl2 macrophages as central regulators promoting lumen expansion while preventing pathological wall thinning or thickening. To validate these predictions, we established a human induced pluripotent stem cell-derived arterial assembloid enriched in MGLhigh macrophages. In this model, MGLhigh macrophages supported lumen enlargement while maintaining overall wall thickness and induced formation of an adventitia-like fibroblast layer that recapitulated approximately 80% of the native adventitial fraction with balanced collagen-elastin remodeling. By linking predictive modeling to human organoid validation, this study establishes a cross-scale workflow for tracing how gene programs shape vascular architecture, offering mechanistic insights and a foundation for predictive regenerative medicine.

bioengineering↗