Biology subjects

Cao, L.

Publications and source records attributed to Cao, L..

At least 19 recordsLinked to original sources

bioRxiv2026

Profiling Siglec-7 and Siglec-9 ligands across the LuCaP PDX series: Implications for glyco-immune checkpoint inhibition in advanced prostate cancer

Advanced prostate cancer exhibits profound cellular and molecular heterogeneity, frequently becoming resistant to androgen receptor (AR) targeting through lineage plasticity and neuroendocrine differentiation. Immunotherapies have shown limited efficacy in prostate cancer, largely due to its immunosuppressive tumour microenvironment. Hypersialylation contributes to immune evasion by engaging sialic acid-binding immunoglobulin-like lectins (Siglecs) on immune cells, forming glyco-immune checkpoints. Although this pathway represents a promising therapeutic target, the distribution of Siglec ligands across diverse prostate cancer phenotypes and their response to standard-of-care hormone therapy remain poorly understood. Here, we utilised high-affinity engineered sialoglycan-binding reagents (HYDRA) to perform comprehensive immunohistochemical profiling of Siglec-7 and Siglec-9 ligands across a panel of 40 Washington Carcinoma of the Prostate (LuCaP) patient-derived xenograft (PDX) models. Ligand expression was evaluated in relation to AR status and neuroendocrine phenotype. To determine the impact of androgen deprivation on the tumour glycome, ligand expression was compared between matched PDX lines grown in intact and castrated mice. Our findings reveal widespread but heterogeneous expression of Siglec-7 and Siglec-9 ligands across the LuCaP cohort. Expression levels were comparable between AR-positive adenocarcinoma models and AR-negative neuroendocrine variants, demonstrating that this glyco-immune checkpoint is maintained across distinct prostate cancer lineages. Under castration conditions, glycan remodelling occurred in a model-dependent manner. A subset of PDX models exhibited reduced Siglec ligand expression following castration, suggesting partial AR dependence. In contrast, other models displayed increased ligand expression, consistent with adaptive immune evasion in response to therapeutic stress, while a third group remained largely unchanged. Collectively, our study demonstrates that the Siglec-7/9 glyco-immune checkpoint axis is broadly maintained across the spectrum of prostate cancer lineage plasticity but is dynamically remodelled by androgen deprivation in a patient-specific manner. These findings support the sialoglycan-Siglec axis as a lineage-independent immunotherapeutic target and suggest that strategies aimed at disrupting Siglec-mediated immune suppression, such as tumour desialylation, may be most effective when combined with androgen deprivation therapy to enhance anti-tumour immunity.

cancer biology↗

bioRxiv2026

De novo design of ligand binding and sensing with a physics based generative approach

The de novo design of ligand-binding proteins has tremendous potential to revolutionize biosensor technology, yet converting these designs into functional sensors remains a major challenge due to the need for ligand-induced conformational changes or modulation of protein-protein interactions. Here, we introduce a physics-based generative approach for the de novo creation of proteins that bind small molecules and metal ions. Our method achieves customizable ligand-binding pocket formation in parallel with simulated protein folding, allowing for precise architectural control of the protein-ligand complex and facilitating the development of biosensors based on either ligand-triggered protein reassociation via split-protein reassembly or ligand-induced protein folding. We demonstrate the versatility of our computational method through successful designs targeting five small molecules, including the very small neurotransmitters serotonin and dopamine, and two metal ions. Biophysical characterization confirmed correct ligand binding, and crystal structures closely matched computational models. We demonstrated the biosensor engineering potential of these designs by constructing serotonin and dopamine sensors using a split protein strategy and explored several approaches to enhance sensor activity. Additionally, we developed a zinc sensor through a zinc-induced protein folding mechanism. Overall, our physics-based generative approach provides a robust framework for the de novo design of ligand-binding proteins, opening new avenues for the development of ligand-responsive biosensors.

bioinformatics↗

bioRxiv2026

New genes play a prominent role in evolution of new sperm classes of Drosophila

The widespread and regulated production of infertile parasperm assisting fertilization of eusperm provides a compelling model for elucidating the mechanisms of cellular innovation and altruism. Here we identify two specific parasperm lineages in Drosophila pseudoobscura that are segregated in development from the eusperm lineage by their single-cell transcriptomes. Most X-linked genes, except for species-specific new genes, show testis-specific repressive epigenetic modifications and become downregulated upon meiotic entry, supporting meiotic X chromosome inactivation. Between sperm classes, nearly half of the known meiotic arrest genes and their downstream targets are differentially transcribed, with over 200 genes displaying a gradient of transcription levels correlated with that of tail lengths. New genes are overrepresented throughout the hierarchical regulatory network of sperm divergence and over 60% of them exhibit a new cell-level expression compared to their parental copies. These results together indicate that new genes play a prominent role in the emergence of low-cost parasperm that shield the eusperm until fertilization.

evolutionary biology↗

bioRxiv2026

Integrating Machine-learning and Ultra-high-throughput Screening for Enzyme spaces exploration

AbstractThe systematic navigation of biocatalyst space is constrained by elusive structure-activity rules and a lack of evolutionary history. Here, we present IMUSE, a strategy integrating machine learning with ultra-high-throughput screening. By screening millions of droplet-encapsulated de novo enzymes, we generated massive synthetic sequence-structure datasets to train models that capture their complex fitness landscapes and biophysical principles. These models effectively guide functional exploration across both sequence and novel structure spaces. IMUSE identified synergistic triple mutations yielding [~]5-fold activity improvements and discovered active second-generation designs with novel catalytic pockets, boosting the experimental success rate >4.9-fold ([~]30%). This work demonstrates how synthetic fitness landscapes bridge the data gap in de novo enzyme space, transforming stochastic search into deterministic navigation to unlock highly proficient biocatalysts beyond natural boundaries.

biochemistry↗

bioRxiv2026

RepGene: Toward a Unified Gene Representation Space Robust to Missing Biological Views

This study evaluates how multi-view gene representations should be compared under a matched contract. Each of 18,460 genes is described by five aligned views: DNA sequence-derived features (D), RNA sequence-derived features (R), protein language-model embeddings (P), curated text knowledge (K), and single-cell expression (X). The contract fixes the gene universe, the 256-D output, label-free outer-training-only fitting, one random-forest probe, and task-equal Macro-F1 over nine registered binary tasks, and varies only the fusion operator across four protocol-defined input states: Core (DNA+RNA+protein), Core+K, Core+X, and Core+K+X. Under these states, the top-scoring operator changes with the available view combination and all task-bootstrap intervals overlap, establishing a condition-dependent rather than universal ranking pattern. An independently configured external RF track provides a separate check of the numerical range, while a gene-to-cell boundary diagnostic shows that gene-level differences attenuate toward a dimension-matched random control under expression-weighted aggregation, as predicted by a dilution identity. Historical log-derived multiplicative-interaction screening is retained only as magnitude-only supplementary evidence because fold-level records are unavailable. The contribution is therefore the matched contract and its audit trail: an evidence-graded protocol for turning fusion claims into comparable, condition-bounded measurements.

bioinformatics↗

bioRxiv2026

HalluDesign-NA: Extending HalluDesign for De Novo Nucleic Acid Design

AlphaFold3 has revolutionized the prediction of biomolecular structures and interactions, including atomic-level modeling of nucleic acids. However, the de novo design of structured and functional nucleic acids remains a significant challenge. Here, we extend our HalluDesign framework to nucleic acid design by integrating NA-MPNN for nucleic acid sequence optimization and design. This new framework, HalluDesign-NA, enables iterative sequence-structure co-optimization, facilitating the de novo design of nucleic acids. Computational benchmarking across ssDNA, ssRNA, and aptamer design tasks demonstrates consistent improvements in confidence scores (pLDDT, ipTM), supporting the feasibility of de novo nucleic acid design under various constraints, such as sequence length, symmetry, and protein structure context. We anticipate that HalluDesign-NA will accelerate the de novo design of functional nucleic acids for applications in biotechnology and medicine. The source code for HalluDesign-NA is available at https://github.com/MinchaoFang/HalluDesign_NA.

bioinformatics↗

bioRxiv2026

Covalent tumor anchoring spatially orchestrates antitumor immunity

Protein immunotherapies can elicit potent tumor rejection, but reversible target engagement, incomplete tumor retention, and systemic leakage often erode spatial control. Here, we develop covalently anchored tumor immunotherapeutic proteins (CATIPs), a modular platform that uses proximity-enabled covalent chemistry to immobilize immune cues on tumor-cell surfaces after intratumoral administration. CATIPs combine tumor-targeting nanobodies with payloads for T cell engagement, co-stimulation, and cytokine support. In human PBMC-reconstituted NSG mice, CATIPs completely eradicated treated EGFR-positive tumors, outperforming matched non-covalent proteins while limiting redistribution, systemic T cell activation, cytokine release, xGVHD-associated morbidity, and on-target, off tumor toxicity. In immunocompetent melanoma models, CATIPs remodeled the tumor microenvironment, expanded antigen-specific CD8+ T cells, induced antigen-restricted abscopal control, and generated durable protection against local and metastatic rechallenge. CATIP-engineered tumor cells further functioned as whole-cell vaccines. Thus, covalent tumor anchoring converts local protein delivery into tumor-surface immune programming, enabling systemic, tumor-specific, durable antitumor immunity while limiting systemic immunopathology.

synthetic biology↗

bioRxiv2026

N-3 Polyunsaturated Fatty Acids Ameliorate Post-infarction Cardiac Dysfunction Through Modulation Of Adiponectin-Ceramide Metabolism

BackgroundIt has been shown that n-3 polyunsaturated fatty acids (n-3 PUFA) of marine origin exert significant beneficial effects on myocardial infarction (MI); however, the underlying mechanisms remained unclear. Ceramides play a vital role in the regulation of energy metabolism, mitochondrial function, and apoptosis. Through the integration of clincial studies and animal experiments, this study aimed to determine whether n-3 PUFA improved myocardial function by modulating ceramide metabolism. MethodsIn a case-control study, 100 patients with AMI and 100 healthy pariticipants were enrolled to measure serum ceramide concentrations. Meanwhile, mice were randomly allocated into 4 groups and administrated to a 3-week intervention with n-3 PUFA in triglyceride and phospholipid forms. A mouse model of MI was then established, followed by an additional 4 weeks of continuous intervention. Subsequent comprehensive assessments of cardiac function were performed in the mice. Finally, the mice were euthanized to conduct targeted ceramide lipidomic analysis and other relevant assays. ResultsThe levels of serum C16:0-, C18:0-, C20:0-, C24:1-ceramides and total ceramides in patients with acute myocardial infarction (AMI) were significantly higher compared with the healthy controls. In the murine model of myocardial infarction, pathological analysis via TTC staining demonstrated that interventions with fish oil (triglyceride form) and krill oil (phospholipid form) both significantly reduced myocardial infarct size. Concomitant echocardiographic assessment confirmed that both treatments markedly elevated left ventricular ejection fraction (LVEF), with the magnitude of improvement being significantly superior to that of the model control group. Concurrently, compared with the model group, the concentrations of ceramides in cardiac tissue and serum were significantly lower in the groups with fish oil and krill oil intervention. Western blot analysis further confirmed that n-3 PUFA intervention upregulated adiponectin expression, reduced ceramide accumulation in myocardial tissue, and inhibited mitochondria-mediated cardiomyocyte apoptosis, thereby improving cardiac function and prognosis following myocardial infarction. ConclusionsThis work demonstrates that n-3 PUFA exert cardioprotective effects following MI mediated by adiponectin-ceramide axis. However, there is no significant difference regarding therapeutic efficacy of n-3 PUFA in triglyceride or phospholipid forms.

pharmacology and toxicology↗

bioRxiv2026

The world's first cloned golden wild yak via interspecific SCNT: 4800m donor origin and 4200m vitrified blastocyst transfer

Primarily inhabiting the harsh, high-altitude environment of the Qiangtang National Nature Reserve exceeding 5,000 meters above the sea (m.a.s.l.), the golden wild yak is critically endangered, with fewer than 300 individuals remaining in the world, a situation exacerbated by the significant challenges of conducting research and conservation of their genetic resources. Somatic cell nuclear transfer (SCNT) can be an effective method for their preservation, but facing several obstacles in this context, including the hypoxic stress at high altitude that impairs embryonic development due to in vitro manipulation, and constraints of long-distance embryo transport. In the present study, the ear tissue was collected from a childhood male golden wild yak at Xizang Geye Wildlife Rescue Station (4800 m.a.s.l.) and send to Institute of Animal Science at Beijing to derive fibroblast cells. Using fibroblast cells of the golden wild yak as nuclear donors, and bovine oocytes from a local slaughterhouse at Beijing as recipients, the interspecific SCNT (iSCNT) embryos were generated and in vitro developed to blastocysts. To maintain the embryonic viability after long-distance transportation from Beijing to Xizang, iSCNT blastocysts were subjected to cryopreservation by vitrification method. Thawing of vitrified iSCNT blastocysts were completed at Xizang Dangxiong Yak Breeding Innovation Base (4200 m.a.s.l.), and transferred into the uterine horn of domestic yaks. 257 days after blastocyst transfer, a cloned golden wild yak was successfully harvested on January 10, 2026. This work demonstrates, for the first time, that interspecies somatic cell nuclear transfer can successfully produce a cloned offspring under extreme conditions, spanning 4800 m.a.s.l. donor origin, long-distance vitrified embryo transportation, and high-altitude blastocyst transfer at 4200 m.a.s.l., establishing a viable strategy for conserving critically endangered high-altitude species.

genetics↗

bioRxiv2026

Molecular Glue-Induced Homodimerization Drives Targeted CRBN Autodegradation

Molecular glue degraders (MGDs) offer a sophisticated, proximity-based approach to protein modulation. In this study, we introduce LJY-3-60, a novel proximity-inducing agent that unexpectedly triggers the potent and selective autodegradation of CRBN. Evidence from CRISPR-Cas9 screening and IP-MS reveals that this degradation process is strictly governed by the intrinsic CRL4CRBN machinery, independent of any extrinsic E3 recruitment. Through a combination of cellular and biophysical characterizations, we demonstrate that LJY-3-60 acts as a molecular bridge to template CRBN homodimerization. This mechanism is unequivocally elucidated by the atomic-resolution co-crystal structure of the CRBNMidi-LJY-3-60 complex. The structure explicitly delineates the homodimerization interface, revealing how the ligand reorganizes the protein surface to stabilize a non-canonical architecture that drives trans-autoubiquitination and subsequent proteasomal degradation. Furthermore, LJY-3-60 serves as a highly effective, controllable off-switch to mitigate PROTAC-induced toxicity. Ultimately, this work delivers a robust chemical tool for modulating CRBN stability. By demonstrating how a small molecule can functionally mimic an endogenous E3 substrates degron to catalyse targeted autodegradation, this study establishes a rational structural framework for designing the next generation of self-destructive modulators in targeted protein degradation (TPD) therapeutics.

biochemistry↗

bioRxiv2026

The Combinatorial Capacity and Robustness of Hierarchical Concept Coding in the Human Medial Temporal Lobe

The human brain encodes a virtually infinite repertoire of semantic concepts using a finite number of neurons, a feat that defies the capacity limits of classical attractor networks. While "Concept Cells" in the medial temporal lobe (MTL) exhibit extreme sparsity, the information-theoretic principles governing their collective robustness remain elusive. Here, we present a hierarchical coding framework that resolves this paradox. We rigorously prove that while uniform sparse coding is bound by a polynomial "Exclusion Volume" limit--leading to catastrophic interference--a hierarchically partitioned architecture unlocks an exponential combinatorial capacity. We demonstrate that this "locally dense, globally sparse" topology mirrors the distance-dependent connectivity of the hippocampal CA3 region. Crucially, we derive a "Supply-Demand" theoretical model for Cognitive Reserve, which quantitatively predicts the "Silent Phase" of neurodegeneration and the mathematical inevitability of the clinical "Cliff Edge" collapse in Alzheimers Disease. Furthermore, our findings identify the lack of topological sparsity as the root cause of catastrophic forgetting in artificial neural networks, offering a blueprint for next-generation, biologically plausible AI architectures.

neuroscience↗

bioRxiv2026

Critical assessment of intratumor and low-biomass microbiome using long-read sequencing

The detection of low-biomass microbial DNA in human tissues is often confounded by contamination, as demonstrated in the debates over the existence of microbiomes in the placenta, brain, blood, and tumors. Here we show that genomic DNA fragment length serves as a discriminator: while genuine microbiome genomes have long genomic DNA fragments, contaminant DNA is typically short. Using germ-free mouse tissues with bacterial spike-ins and human cell lines, we developed a metric that normalizes microbial read length to host read length. Across multiple human tumor and normal tissues, we found genuine microbiome signals are largely limited to tissues with natural microbial exposure (e.g., gastrointestinal tract, cervix, vagina, skin), while other tissues (e.g. kidney, brain, blood, and placenta) showed no evidence of resident microbiome. These findings support DNA fragment length as a metric for quality controlling low-biomass microbiome profiling, clarifying the debates and strengthen future studies of resident microbiome in tissues.

genomics↗

bioRxiv2026

Nab-paclitaxel fused with the de novo designed receptor binder exhibits enhanced tumor targeting and therapeutic efficacy

Chemotherapy has been widely used in cancer treatment, but most of the chemotherapeutic drugs rely mainly on passive accumulation due to lack of target specificity, which may lead to systemic toxicity and limited clinical utility. Recent advances in artificial intelligence-based protein design provide new opportunities for developing precision therapeutics. Here we modify the albumin-bound paclitaxel (Nab-PTX), one of the most widely used drugs in chemotherapies, by applying the fusion proteins of albumin with the de novo designed protein binders targeting human EGFR or HER2. The resulting particles, EGFRmb-Nab-PTX and HER2mb-Nab-PTX, retain the similar physicochemical properties of Nab-PTX while acquiring the receptor-specific binding capacities. The in vitro assays show that both binder-modified Nab-PTX particles have increased uptake and inhibitory effects significantly in the cancer cell lines with high receptor expression levels. Furthermore, the data from a xenograft model, including tumor growth, excised tumor analysis, organ histology, and fluorescence imaging, show that the binder-modified Nab-PTX enhances tumor accumulation, improves tumor suppression, and reduces off-target toxicity compared with the conventional Nab-PTX, suggesting that they may have promising clinical potential in cancer treatment. Overall, this strategy provides an adaptable modular platform for generating albumin-based chemotherapeutic drugs with target specificities, which can be readily customized with diverse target binders to enable precise cancer therapies.

cancer biology↗

bioRxiv2026

BiOmics: A Foundational Agent for Grounded and Autonomous Multi-omics Interpretation

While AI has automated bioinformatic workflows, biological interpretation remains fragmented and often disconnected from mechanistic insights. Existing AI is bifurcated between statistical "black-box" models that lack logical grounding and simple agents restricted to shallow knowledge retrieval. To bridge this divide, we introduce BiOmics, a foundational agent that synthesizes multi-omics data with adaptive knowledge for biological interpretation. BiOmics introduces a novel dual-track architecture comprising a harmonized explicit reasoning space for grounded logic and a unified latent embedding space for high-dimensional association mapping. This architecture enables a transformative "Retrieving-Reasoning-Predicting" paradigm for purposeful, cross-scale inference traversing the biological hierarchy, from molecular variants to disease phenotypes. Empirical evaluations demonstrate that BiOmics surpasses state-of-the-art AI agents and specialized algorithms, markedly augmenting the granularity and depth of biological insights. Specifically, BiOmics exhibits unique superiority in uncovering indirect pathogenic variants, achieving reference-free cell annotation, and prioritizing drug repurposing candidates tailored to specific datasets. BiOmics further enriches the interpretive landscape of biological entities, leveraging its reasoning-grounded knowledge graph to uncover deep functional contexts. Ultimately, BiOmics provides a versatile engineering foundation to transition AI for Science from descriptive "data fitting" to autonomous, knowledge-driven interpretation.

bioinformatics↗

bioRxiv2026

Standard treatment against paediatric BRAF-V600E glioma promotes senescence and sensitizes tumours to BCL-xL inhibition

BackgroundChemo-, radio-, and targeted therapies can induce senescence in tumour cells, a process called therapy-induced senescence (TIS), which can be exploited therapeutically using compounds that kill senescent cells (senolytics). Children with BRAF-V600E activated brain tumours are commonly treated with Dabrafenib, Trametinib or Vinblastine (alone or in combination) with good responses. However, a subset of patients experiences tumour regrowth upon treatment withdrawal. Here, we explore the role of TIS and senolytic therapies in preclinical models of paediatric BRAF-V600E driven brain tumours. MethodsHuman BT-40 tumour cells derived from pleomorphic xanthoastrocytoma are used in vitro or in vivo orthotopically transplanted into mice and treated with either Dabrafenib, Trametinib or Vinblastine. Senescence is assessed by immunostaining and RNA sequencing. Sensitivity to senolytics is determined in vitro in dose response assays and in vivo. ResultsTrametinib treatment induces a senescent phenotype in BT-40 cells in vivo with activation of a senescence-associated secretory phenotype (SASP) and expansion of IBA-1 microglia. Senescence is induced in BT-40 cells in vitro when treated not only with Trametinib, but also with Dabrafenib and Vinblastine. In vitro testing identifies Navitoclax as a potent senolytic against BT-40 senescent cells, mostly through inhibition of the anti-apoptotic protein BCL-xL. In BT-40 tumour bearing mice, combination of Trametinib and Navitoclax causes the ablation of senescent BT-40 cells with significant reduction in tumour regrowth after treatment withdrawal and increased mouse survival. ConclusionsThis study shows that Navitoclax enhances the anti-tumour efficacy of Trametinib and limits tumour regrowth following treatment withdrawal. Key PointsO_LITrametinib, Dabrafenib and Vinblastine induce senescence in BT-40 cells in vitro C_LIO_LISenescent BT-40 cells are sensitive to BCL-xL inhibition C_LIO_LICombination of Trametinib and Navitoclax reduces rebound tumour growth in vivo C_LI Importance of the StudyChildren with BRAF-V600E activated glioma are frequently treated with Dabrafenib, Trametinib or Vinblastine with good responses. However, a subset of patients shows tumour regrowth when the treatment is stopped. To prevent this rebound growth, patients must continue treatment with potential aggravation in quality of life and risk of malignant progression. Our research demonstrates that these therapies induce BT-40 tumour cells to enter a non-proliferative state that shows features of cellular senescence. We identify that senescent tumour cells can be killed using Navitoclax, and potent inhibitor of the anti-apoptotic protein BCL-xL and a well-studied senolytic. We demonstrate that the combination of Trametinib and Navitoclax reduces tumour regrowth after treatment withdrawal. Our research provides a strong rationale supporting the combined use of senolytics with current conventional and targeted therapies against BRAF-V600E mutated brain tumours.

cancer biology↗

bioRxiv2026

De novo design of metalloproteases for targeted amyloid-β cleavage

De novo protein design has not yet achieved the creation of proteases capable of selectively cleaving any desired peptide bond within a native protein with high precision. Here, we report the use of the flow-based generative model Proteus2 to design metalloproteases by generating enzyme-substrate complexes conditioned on a target peptide sequence and a predefined catalytic motif. Our approach employs a two-step encapsulation strategy to create clamp-like metalloproteases that bind the target peptide in a manner that maximizes substrate sequence specificity. The generative process simultaneously optimizes the precise positioning of the target peptide bond in a catalytically competent configuration and accurately scaffolds the transition state catalytic residues--both essential for specific and efficient catalysis. Using this strategy, we designed zinc metalloproteases targeting three distinct cleavage sites within the aggregation-prone regions of amyloid-{beta} (A{beta}), a key pathogenic factor in Alzheimers disease. Experimental characterization validated five enzymes, each capable of precise cleavage at the intended sites with high specificity and minimal or undetectable activity on non-cognate substrates. On average, these enzymes accelerated peptide bond hydrolysis by more than 107-fold relative to the uncatalyzed reaction, and enabled efficient digestion of the A{beta} peptide into smaller segments when enzymes targeting different sites were combined. Cryo-EM structures of three designed enzymes in complex with A{beta} peptide, each targeting a distinct cleavage site, revealed close agreement with the design models. Together, these results demonstrate the potential of sequence-guided, generative approaches for developing programmable, sequence-specific proteolysis and lay the groundwork for future applications in basic research and therapeutic development.

synthetic biology↗

bioRxiv2026

The combination of BCL-xL PROTAC and mTOR inhibitor sensitizes pancreatic ductal adenocarcinoma to KRASG12D inhibitor treatment by enhancing apoptosis induction

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with a five-year survival rate of approximately 13%, partly because of limited treatment options and resistance to therapies. Although the recently discovered KRAS G12D inhibitor MRTX1133 has shown promise for PDAC treatment in preclinical studies, its clinical efficacy as a single agent is expected to be limited, as is the case with KRAS G12C inhibitors. Therefore, in this study, we evaluated potential combination strategies to enhance the therapeutic effect of MRTX1133. We rationally combined MRTX1133 with the BCL-xL proteolysis-targeting chimera (PROTAC) DT2216 and the mTOR inhibitor everolimus, which significantly potentiated the anti-tumor activity of MRTX1133 in multiple G12D-mutated PDAC cells in vitro by enhancing apoptosis induction. Mechanistically, MRTX1133 treatment increased BIM and decreased NOXA levels, while the combination of DT2216/everolimus was shown to simultaneously enhance BIM release and stabilize NOXA. In vivo, DT2216/everolimus combination significantly potentiated the anti-tumor activity of MRTX1133 in AsPC1 PDAC xenograft model. Furthermore, the triple combination of MRTX1133, DT2216, and everolimus effectively overcame acquired resistance to MRTX1133 in AsPC1 cells in vitro and in xenograft model. Collectively, our findings suggest that the single-agent efficacy of MRTX1133 is limited by apoptosis inhibition, and that its combination with DT2216/everolimus can enhance apoptosis and potentially overcome resistance in KRAS G12D-mutated PDAC. SIGNIFICANCEKRAS inhibitors, including KRAS G12D inhibitor MRTX1133, are promising therapeutics against KRAS-mutated pancreatic ductal adenocarcinoma (PDAC), but drug resistance limits their efficacy. Our study reveals that robust induction of apoptosis using a combination of BCL-xL PROTAC degrader and an mTOR inhibitor, significantly enhances MRTX1133 efficacy in PDAC models without increasing toxicity to normal tissues.

cancer biology↗

bioRxiv2025

OmniCell: Unified Foundation Modeling of Single-Cell and Spatial Transcriptomics for Cellular and Molecular Insights

A cells transcriptional programme is not fully defined by gene expression alone, but by the tissue context in which that programme is enacted. Single-cell RNA sequencing resolves molecular identity after dissociation, whereas spatial transcriptomics preserves tissue architecture but remains constrained by assay-specific sparsity and gene coverage. Here we present OmniCell, a tissue-contextual transcriptomic foundation model pretrained on 67 million dissociated and spatially resolved profiles. By integrating gene identity, expression magnitude and tissue context, OmniCell links transcriptional programmes to the cellular neighbourhoods and anatomical contexts in which they operate. OmniCell organised transcriptomes across molecular, cellular and tissue scales. It recovered cell-type-specific programmes and tissue-aligned gene modules, preserved robust cell-state structure across batches, species and rare populations, and improved the reconstruction of spatial cell identity, anatomical domains and cell-type composition. In human liver cancer Stereo-seq data, OmniCell resolved a tumour-margin transition zone characterised by immune infiltration, acute-phase inflammation, coagulation/complement activity and metallothionein-linked metal-ion detoxification. Contextual gene-embedding similarity analysis showed that gene relationships differed across tumour core, transition-zone and paratumour/adjacent non-malignant niches, indicating that OmniCell captures tissue-dependent gene function rather than expression similarity alone. In mouse brain development and macaque cortex, spatial virtual perturbations mapped regulatory genes onto stage- and region-specific anatomical programmes. Together, these results establish tissue context as a primary axis of transcriptomic representation and provide a framework for studying how cellular programmes acquire context-dependent biological meaning in intact tissues.

bioinformatics↗