Biology subjects

Wu, C. J.

Publications and source records attributed to Wu, C. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Programmable antigen-presenting scaffolds expand rare tumor-antigen-specific T cells from peripheral blood

Adoptive cellular therapies can be effective against solid tumors but rely on the identification and expansion of rare tumor-reactive T cells (TRTs). Here, we utilize antigen-presenting cell-mimetic scaffolds (APC-ms), a modular biomaterial platform that presents defined peptide-HLA and co-stimulatory ligands on a fluid lipid bilayer to selectively recover rare antigen-specific T cells from peripheral blood. Independent variation of peptide-HLA, co-stimulatory ligands, and cytokine support defined a formulation that enriched MART-1-specific T cells to above 2% of CD8+ T cells in 35 of 50 HLA-A*02:01+ healthy donors from low or undetectable baseline frequencies. Compared with mo-DCs, APC-ms achieved greater fold expansion of MART-1-specific T cells with increased functional avidity and preservation of an early differentiation phenotype, and generated a higher number of MART-1-specific clonotypes. In five of eight patients with treatment-naive melanoma, APC-ms could enrich MART-1-specific T cells to a median of 13.7% of CD8+ cells (range 0.30 - 57.2%) Moreover, APC-ms could expand T cells specific for an HLA-A*24:01-restricted personal neoantigen that were previously undetectable in peripheral blood of a patient with melanoma. These findings establish APC-ms as a tunable platform for the recovery of rare TRTs from peripheral blood, supporting its further development for therapeutic TCR discovery and personalized adoptive cell therapy.

immunology↗

bioRxiv2026

PAIR-Scan: Single-step identification of highly potent TCR-neoantigen pairs through library-on-library screening

Tumors contain a mixture of T cells with bystander reactivities and reactivities towards different, frequently patient-specific, cancer (neo)antigens. The one-step identification of highly active TCR-antigen pairs in human tumors would be valuable, both as a monitoring tool and to boost T cell reactivities of interest. Here, we develop PAIR-Scan, an HLA-agnostic library-on-library screening technology that identifies functionally active TCR-neoantigen pairs among tens of thousands of candidate pairs in a single step. We demonstrate the value of PAIR-Scan on a range of tumor samples and for the direct identification of TCR-recognized minimal peptides. In addition, we demonstrate that PAIR-Scan correctly ranks TCRs reactive to the same antigen by their relative tumor-killing efficiency. Together, these data demonstrate the value of PAIR-Scan for both the dissection of T cell responses in clinical samples and to generate large-scale datasets for the development of predictive models of TCR reactivity.

immunology↗

bioRxiv2026

Tumor-tropic E. coli engineered as living T and NK cell engagers

Despite advances in immunotherapy, most solid tumors remain resistant to treatment. Immune cell engagers redirect cytotoxic lymphocytes against cancer, but limited tumor access, immunosuppressive microenvironments and systemic immune activation limit efficacy. Here we develop live immune modulating engagers (LIME), a modular platform where non-pathogenic, tumor-tropic Escherichia coli display tandem single-chain variable fragments targeting a tumor-associated antigen and an activating receptor on T or natural killer cells. LIME bridged effector and tumor cells, induced transcriptional programs of T cell activation, metabolism and proliferation, and enhanced cytotoxicity across cancer cell lines and patient-derived organoids. In mouse models, LIME safely accumulated in tumors, outperformed tarlatamab in small cell lung cancer, and induced durable immunity in lymphoma. RAS inhibition and PD-L1 blockade enhanced LIME activity in pancreatic cancer and induced humoral responses. Multi-lineage immune modulation remained tumor-confined, without organ toxicity. These findings establish LIME as a versatile living therapeutic platform for programmable, tumor-restricted immune orchestration.

bioengineering↗

bioRxiv2025

Early persistence of recipient stem-cells and T-cell dysregulation are associated with relapse after transplant in AML/MDS

Hematopoietic stem cell transplantation (HSCT) offers the best curative option for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), yet relapse remains common. Current relapse detection methods are often too late for effective intervention. To identify earlier predictors and therapeutic targets, we performed longitudinal single-cell RNA and T cell receptor (TCR) sequencing of bone marrow from 33 AML/MDS patients during post-transplant immune reconstitution, comparing those who relapsed to those who remained in remission. Persistence of recipient hematopoietic stem and progenitor cells (HSPCs) in the marrow was associated with relapse months later. These residual recipient HSPCs harbored copy number variations (CNVs), supporting their leukemic origin, and overexpressed PRAME and CALCRL compared to coexisting donor HSPCs. Further, in a subset of TP53-mutant disease, low TCR diversity with skewing toward dominant clonotypes foreshadowed relapse. These findings lay the groundwork for improved relapse prediction and nominate therapeutic targets for early post-transplant intervention.

cancer biology↗

bioRxiv2024

CoREST Complex Inhibition Alters RNA Splicing to Promote Neoantigen Expression and Enhance Tumor Immunity

ABSTRACTEpigenetic complexes tightly regulate gene expression and colocalize with RNA splicing machinery; however, the consequences of these interactions are uncertain. Here, we identify unique interactions of the CoREST repressor complex with RNA splicing factors and their functional consequences in tumorigenesis. Using mass spectrometry, in vivo binding assays, and cryo-EM we find that CoREST complex-splicing factor interactions are direct and perturbed by the CoREST complex inhibitor, corin, leading to extensive changes in RNA splicing in melanoma and other malignancies. Using predictive machine learning models and MHC IP-MS, we identify thousands of corin-induced neopeptides derived from unannotated splice sites which generate immunogenic splice-neoantigens. Furthermore, corin reactivates the response to immune checkpoint blockade and promotes dramatic expansion of cytotoxic T cells in an immune cold melanoma model. CoREST complex inhibition thus represents a unique therapeutic opportunity in cancer which creates tumor-associated neoantigens that enhance the immunogenicity of current therapeutics. Statement of SignificanceWe identify a novel role of the CoREST transcriptional repressor complex in regulating pre-mRNA splicing and find that the small molecule inhibitor, corin, promotes alternative splicing events in cancer leading to neoantigen expression and T cell-mediated immunity. This represents a potential approach to promote immunoreactive neoantigen expression in immune-cold tumors.

cancer biology↗

bioRxiv2024

Coordinated Immune Cell Networks in the Bone Marrow Microenvironment Define the Graft versus Leukemia Response with Adoptive Cellular Therapy

Understanding how intra-tumoral immune populations coordinate to generate anti-tumor responses following therapy can guide precise treatment prioritization. We performed systematic dissection of an established adoptive cellular therapy, donor lymphocyte infusion (DLI), by analyzing 348,905 single-cell transcriptomes from 74 longitudinal bone-marrow samples of 25 patients with relapsed myeloid leukemia; a subset was evaluated by protein-based spatial analysis. In acute myelogenous leukemia (AML) responders, diverse immune cell types within the bone-marrow microenvironment (BME) were predicted to interact with a clonally expanded population of ZNF683+GZMB+ CD8+ cytotoxic T lymphocytes (CTLs) which demonstrated in vitro specificity for autologous leukemia. This population, originating predominantly from the DLI product, expanded concurrently with NK and B cells. AML nonresponder BME revealed a paucity of crosstalk and elevated TIGIT expression in CD8+ CTLs. Our study highlights recipient BME differences as a key determinant of effective anti-leukemia response and opens new opportunities to modulate cell-based leukemia-directed therapy.

cancer biology↗

bioRxiv2023

DIISCO: A Bayesian framework for inferring dynamic intercellular interactions from time-series single-cell data

Characterizing cell-cell communication and tracking its variability over time is essential for understanding the coordination of biological processes mediating normal development, progression of disease, or responses to perturbations such as therapies. Existing tools lack the ability to capture time-dependent intercellular interactions, such as those influenced by therapy, and primarily rely on existing databases compiled from limited contexts. We present DIISCO, a Bayesian framework for characterizing the temporal dynamics of cellular interactions using single-cell RNA-sequencing data from multiple time points. Our method uses structured Gaussian process regression to unveil time-resolved interactions among diverse cell types according to their co-evolution and incorporates prior knowledge of receptor-ligand complexes. We show the interpretability of DIISCO in simulated data and new data collected from CAR-T cells co-cultured with lymphoma cells, demonstrating its potential to uncover dynamic cell-cell crosstalk. AvailabilityDIISCO is publicly accessible at https://github.com/azizilab/DIISCO_public. All data will be deposited to GEO upon publication.

bioinformatics↗

bioRxiv2023

Design of Cytotoxic T Cell Epitopes by Machine Learning of Human Degrons

Antigen processing is critical for producing epitope peptides that are presented by HLA molecules for T cell recognition. Therapeutic vaccines aim to harness these epitopes for priming cytotoxic T cell responses against cancer and pathogens, but insufficient processing often reduces vaccine efficacy through limiting the quantity of epitopes released. Here, we set out to improve antigen processing by harnessing protein degradation signals called degrons from the ubiquitin-proteasome system. We used machine learning to generate a computational model that ascribes a proteasomal degradation score between 0 and 100. Epitope peptides with varying degron activities were synthesized and translocated into cells using nontoxic anthrax proteins: protective antigen (PA) and the N-terminus of lethal factor (LFN). Immunogenicity studies revealed epitope sequences with a low score (<25) show pronounced T-cell activation but epitope sequences with a higher score (>75) provide limited activation. This work sheds light on the sequence-activity relationships between proteasomal degradation and epitope immunogenicity, through conserving the epitope region but varying the flanking sequence. We anticipate that future efforts to incorporate proteasomal degradation signals into vaccine designs will lead to enhanced cytotoxic T cell priming by vaccine therapeutics in clinical settings.

immunology↗

bioRxiv2023

Slide-tags: scalable, single-nucleus barcoding for multi-modal spatial genomics

Recent technological innovations have enabled the high-throughput quantification of gene expression and epigenetic regulation within individual cells, transforming our understanding of how complex tissues are constructed. Missing from these measurements, however, is the ability to routinely and easily spatially localise these profiled cells. We developed a strategy, Slide-tags, in which single nuclei within an intact tissue section are tagged with spatial barcode oligonucleotides derived from DNA-barcoded beads with known positions. These tagged nuclei can then be used as input into a wide variety of single-nucleus profiling assays. Application of Slide-tags to the mouse hippocampus positioned nuclei at less than 10 micron spatial resolution, and delivered whole-transcriptome data that was indistinguishable in quality from ordinary snRNA-seq. To demonstrate that Slide-tags can be applied to a wide variety of human tissues, we performed the assay on brain, tonsil, and melanoma. We revealed cell-type-specific spatially varying gene expression across cortical layers and spatially contextualised receptor-ligand interactions driving B-cell maturation in lymphoid tissue. A major benefit of Slide-tags is that it is easily adaptable to virtually any single-cell measurement technology. As proof of principle, we performed multiomic measurements of open chromatin, RNA, and T-cell receptor sequences in the same cells from metastatic melanoma. We identified spatially distinct tumour subpopulations to be differentially infiltrated by an expanded T-cell clone and undergoing cell state transition driven by spatially clustered accessible transcription factor motifs. Slide-tags offers a universal platform for importing the compendium of established single-cell measurements into the spatial genomics repertoire.

genomics↗

bioRxiv2022

Genomic heterogeneity and ploidy identify patients with intrinsic resistance to PD-1 blockade in metastatic melanoma

While the introduction of immune checkpoint blockade (ICB) has dramatically improved clinical outcomes for patients with advanced melanoma, a significant proportion of patients develop resistance to therapy, and mechanisms of resistance are poorly elucidated in most cases. Further, while combination ICB has higher response rates and improved progression free survival compared to single agent therapy in the front line setting, there is significantly increased toxicity with combination ICB, and biomarkers to identify patients who would disproportionately benefit from combination therapy vs aPD-1 ICB are poorly characterized. To understand resistance mechanisms to single vs combination ICB therapy, we analyze whole-exome-sequencing (WES) of pre-treatment tumor and matched normals of 4 cohorts (n=140) of previously ICB-naive aPD-1 ICB treated patients. We find that high intratumoral genomic heterogeneity and low ploidy identify patients with intrinsic resistance to aPD-1 ICB. Comparing to a melanoma cohort from a pre-targeted therapy and ICB time period ("untreated" cohort), we find that genomic heterogeneity specifically predicts response and survival in the ICB treated cohorts, but not in the untreated cohort, while ploidy is also prognostic of overall survival in the "untreated" (by targeted therapy or ICB) group. To establish clinically actionable predictions, we optimize a simple decision tree using genomic ploidy and heterogeneity to identify with high confidence (90% PPV) a subset of patients with intrinsic resistance to and significantly worse survival on aPD1 ICB treatment. We then validate this model in independent cohorts, and further show that a significant proportion of patients predicted to have intrinsic resistance to single agent aPD-1 ICB respond to combination ICB, which suggests that nominated patients may benefit disproportionately from combination ICB. We further show that the features and predictions of the model are independent of known clinical features and previously nominated molecular biomarkers. These findings highlight the clinical and biological importance of genomic heterogeneity and ploidy, and sets a concrete framework towards clinical actionability, broadly advancing precision medicine in oncology.

cancer biology↗

bioRxiv2022

Treg cells drive MYCN-mediated immunosuppression and tumor aggressiveness in high-risk neuroblastoma

Solid tumors, especially those with aberrant MYCN activation, harbor an immunosuppressive microenvironment to fuel malignant growth and trigger treatment resistance1,2, yet the underlying mechanisms are elusive and effective strategies to tackle this challenge are lacking. Here we demonstrated the crucial role of T regulatory (Treg) cells in MYCN-mediated immune repression and tumor aggression using high-risk neuroblastoma (NB) as a model system. Human MYCN-activated NB attracts CD4+ Treg cells, which are also found enriched in MYCN-high primary patient samples. Zebrafish MYCN-overexpressing neural crests recruit Cd4+ cells before tumor formation and induce an immunosuppressive microenvironment, thereby promoting tumor onset and progression. Strikingly, disruption of Treg cells through depletion of forkhead box protein 3a restores anti-tumor immunity and impairs NB development. Together, our studies establish Treg cells as the key driver of MYCN-mediated immunosuppression and tumor aggressiveness, providing mechanistic insights and therapeutic implications.

cancer biology↗

bioRxiv2022

Latent human herpesvirus 6 is reactivated in chimeric antigen receptor T cells

Cell therapies have yielded durable clinical benefits for patients with cancer, but the risks associated with the development of therapies from manipulated human cells are still being understood. For example, we currently lack a comprehensive understanding of the mechanisms of neurotoxicity observed in patients receiving T cell therapies, including recent reports of encephalitis caused by human herpesvirus 6 (HHV-6) reactivation1. Here, via petabase-scale viral RNA data mining, we examine the landscape of human latent viral reactivation and demonstrate that HHV-6B can become reactivated in human CD4+ T cells in standard in vitro cultures. Using single-cell sequencing, we identify a rare population of HHV-6 super-expressors (~1 in 300-10,000 cells) that possess high viral transcriptional activity in chimeric antigen receptor (CAR) T cell culture before spreading to infect other cells in vitro. Through the analysis of single-cell sequencing data from patients receiving cell therapy products that are FDA-approved2 or used in clinical studies3,4, we identify the presence of CAR+, HHV-6 super-expressor T cells in vivo. Together, our study implicates cell therapy products as a source of lytic HHV-6 reported in clinical trials1,5-7 and has broad implications for the design, production, and monitoring of cell therapies.

immunology↗

bioRxiv2022

Detection of alternative isoforms of gene fusions from long-read RNA-seq with FLAIR-fusion

Gene fusions are important cancer drivers and drug targets, but are difficult to reliably identify with short-read RNA-sequencing. Long-read RNA sequencing data are more likely to span a fusion breakpoint and provide more sequence context around the breakpoint. This allows for more reliable identification of gene fusions and for detecting alternative splicing in gene fusions. Notably, alternative splicing of fusions has been shown to be a mechanism for drug resistance and altered levels of oncogenicity. Here, we present FLAIR-fusion, a computational tool to identify gene fusions and their isoforms from long-read RNA-sequencing data. FLAIR-fusion can detect fusions and their isoforms with high precision and recall, even with error-prone reads. We also investigated different library preparation methods and found that direct-cDNA has a higher incidence of artifactual chimeras than direct-RNA and PCR-cDNA methods. FLAIR-fusion is able to filter these technical artifacts from all of these library prep methods and consistently identify known fusions and their isoforms across cell lines. We ran FLAIR-fusion on amplicon sequencing from multiple tumor samples and cell lines and detected alternative splicing in the previously validated fusion GUCYA2-PIWIL4, which shows that long-read sequencing can detect novel splicing events from cancer gene panels. We also detect fusion isoforms from long-read sequencing in chronic lymphocytic leukemias with the splicing factor mutation SF3B1 K700E, and find that up to 10% of gene fusions had more than one unique isoform. We also compared long-read fusion detection tools with short-read fusion detection tools on the same samples and found greater consensus in the long-read tools. Our results demonstrate that gene fusion isoforms can be effectively detected from long-read RNA-sequencing and are important in the characterization of the full complexity of cancer transcriptomes.

bioinformatics↗

bioRxiv2021

Robust integration of single-cell cytometry datasets

Combining single-cell cytometry datasets increases the analytical flexibility and the statistical power of data analyses. However, in many cases the full potential of co-analyses is not reached due to technical variance between data from different experimental batches. Here, we present cyCombine, a method to robustly integrate cytometry data from different batches, experiments, or even different experimental techniques, such as CITE-seq, flow cytometry, and mass cytometry. We demonstrate that cyCombine maintains the biological variance and the structure of the data, while minimizing the technical variance between datasets. cyCombine does not require technical replicates across datasets, and computation time scales linearly with the number of cells, allowing for integration of massive datasets. Robust, accurate, and scalable integration of cytometry data enables integration of multiple datasets for primary data analyses and the validation of results using public datasets.

bioinformatics↗

bioRxiv2021

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

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

biochemistry↗

bioRxiv2021

Integrative Clinical and Molecular Characterization of Translocation Renal Cell Carcinoma

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

cancer biology↗

bioRxiv2020

Comprehensive and Integrated Genomic Characterization of Human Immunome in Cancer

Genetic alterations in immune-related pathways are common hallmarks of cancer. However, to realize the full potential of immunotherapy, a comprehensive understanding of immune networks and how mutations impact network structure and functional output across cancer types is instrumental. Herein we systematically interrogated somatic mutations that could express neoantigens and alter immune responses in cancer patients compared to wild-type controls. To do so, we developed a network-based immunogenomics model (NIPPER) with scoring systems to prioritize critical genes and mutations eliciting differential HLA binding affinity and alternate responses to immunotherapy. These mutations are enriched in essential protein domains and often alter tumor infiltration by immune cells, affecting T cell receptor repertoire and B cell clonal expansion. Furthermore, we devised an interactome network propagation framework integrated with drug associated gene signatures to identify potential immunomodulatory drug candidates. Together, our systems-level analysis results help interpret the heterogeneous immune responses among patients, and serve as a resource for future functional studies and targeted therapeutics. SignificanceCancer cells induce specific immune-related pathway perturbations by mutations, transcriptional dysregulation, and integration of multi-omics data can help identify critical molecular determinants for effective targeted therapeutics.

immunology↗

bioRxiv2020

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

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

cancer biology↗