Biology subjects

Ho, W. J.

Publications and source records attributed to Ho, W. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer

Resistance to systemic therapy is a major unmet challenge in pancreatic cancer. To identify potential mechanisms of resistance, we developed a novel 3D pipeline in clinical samples that uses deep learning to classify sensitive and persistent tumor cell populations based on morphological features, enabling subsequent molecular characterization of intratumoral heterogeneity. We applied this automated 3D pipeline to a cohort of human pancreatic cancer samples treated with neoadjuvant chemotherapy, identifying heterogeneity in response to therapy both between and within tumors. Application of spatial proteomics to these sensitive and persistent regions identified enhanced epithelial-to-mesenchymal transition and non-classical cell states in persistent cells, confirming our morphological classification. Integration of spatial transcriptomics in multiple pancreatic cancer cohorts associated fibroblast-cancer crosstalk via syndecans with resistance to cytotoxic therapy. Our validated 3D multi-omic pipeline is now poised for application to clinical trials, enabling discovery of resistance mechanisms and design of new therapeutic combinations to circumvent resistance. Statement of significanceWe developed a novel 3D multi-omic pipeline to identify mechanisms of resistance to chemotherapy in clinical samples. This approach associated fibroblast-cancer crosstalk via syndecans with resistance to cytotoxic therapy and is poised for broader application in neoadjuvant clinical trials.

cancer biology↗

bioRxiv2025

Phase-targeting rapid cryofixation of the beating heart and histological analysis unveil contractile state-dependent sarcomere dynamics

The heart is a functional syncytium consisting of numerous cardiomyocytes that repetitively exhibit coordinated contractions/relaxations. However, the extent to which myocyte sarcomere arrangements in the heart differ across beats is unknown. To examine this, we conducted cardiac phase-targeting rapid cryofixation of Langendorff-perfused rat hearts. We adjusted the timepoint of cryogen exposure to the electrically paced heart and observed phase-dependent differences in the sarcomere length (SL) of subepicardial myocytes by -actinin immunohistochemistry, namely a significantly shorter SL during systole than during diastole. We detected spatially inhomogeneous SL distributions by generating a heatmap of the myocardium. For peak systole the SL heatmap exhibited nearly uniform SL shortening within and among the individual myocytes with some myocardia exhibiting nonuniform SLs. During diastole, the heart showed predominant SL elongation, which was also accompanied by patchy distributions of locally short-SL regions, reflecting inhomogeneous SLs. This SL inhomogeneity was attenuated by pharmacological relaxation by 2,3-butanedione monoxime. The heatmap of the rapidly-frozen heart during ventricular fibrillation also revealed inhomogeneous SLs within and among individual myocytes. Overall, cardiac phase-targeting cryofixation unveiled in-depth behaviors on SL in the heart. Our cryofixation strategy will open a new horizon to clarify precise spatiotemporal changes in sarcomere structures and understand cardiac functions.

biophysics↗

bioRxiv2025

Quantitative Calibration of a Spatial QSP Model Identifies Fibroblast Impact on HCC Immunotherapy

AbstractComputational models are increasingly used to predict treatment response and optimize cancer therapy strategies. Among these, quantitative systems pharmacology (QSP) models mechanistically simulate tumor progression and pharmacological interventions, enabling virtual clinical trials, model-informed drug development, and biomarker identification. Coupling QSP with an agent-based model yields a spatial QSP (spQSP) platform that captures tissue-level spatial organization of the tumor microenvironment (TME). However, parameterizing such models to represent tumor biology remains an open problem. In this study, we developed a calibration framework using the Approximate Bayesian Computation - Sequential Monte Carlo (ABC-SMC) approach to calibrate the spQSP model with a combination of clinical and spatial molecular data, reflecting the TME characteristics of human tumors. This calibration framework matches tumor architectures between spQSP model predictions and patient spatial molecular data by fitting statistical summaries of cellular neighborhoods. We demonstrate that model calibration using CODEX data from untreated HCC patients enables prediction of TME spatial molecular states in an independent cohort receiving immune-checkpoint inhibitor (ICI) and tyrosine kinase inhibitor (TKI) combination therapy. Finally, we identify spatial and non-spatial pretreatment biomarkers and assess their predictive power for therapeutic response. This workflow demonstrates how integrating spatial-omics with multiscale mechanistic models enables quantitative calibration, biological insight, and in silico biomarker discovery, providing a framework for personalized cancer therapy across tumor types. SignificanceDigital twins and computational models are increasingly used to simulate disease and guide therapy, but they often struggle to capture the immense complexity driving the spatiotemporal evolution of the TME. The challenge is compounded by clinical sample limitations, which typically provide measurements from only static snapshots of the TME for parameter estimation. We demonstrate how mechanistic modeling frameworks can overcome this limitation by enabling inference of spatiotemporal model parameters from static spatial data - an intractable task for purely data-driven approaches. Ultimately, our work presents a workflow that integrates spatial-omics with multiscale mechanistic models, enabling quantitative calibration, deeper biological insight, and in silico biomarker discovery.

bioinformatics↗

bioRxiv2025

Modeling cellular influence delineates functionally relevant cellular neighborhoods in primary and metastatic pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, with liver metastases significantly worsening outcomes. However, distinct features of the tumor microenvironment (TME) between primary and metastatic sites remain poorly defined. Cellular neighborhoods within the TME are recognized as functional units that influence tumor behavior. Conventional spatial methods, which assign equal weights to all cells in a region, fail to capture the nuances of cellular interactions. To address this, we developed Functional Cellular Neighborhood (FunCN) quantification, which integrates both the proportion and proximity of surrounding cells. Applying FunCN to PDAC imaging mass cytometry data, we identified neutrophil-enriched interactions in liver metastases compared to primary tumors, correlating with elevated VISTA expression by tumor cells. Additionally, FunCN clusters around CD8+ T cells in pancreas and liver were associated with higher TIGIT and LAG3, respectively. These findings demonstrate the importance of spatial immune landscapes in PDAC and identify potential therapeutic opportunities.

systems biology↗

bioRxiv2025

PIVOT: an open-source tool for multi-omic spatial data registration

Advances in spatial profiling have resulted in the generation of multi-omic atlases that span biological scales. In general, multiple workflows are required for image registration, coordinate registration, and spot deconvolution to integrate modalities. To improve the throughput of registration of multi-omic cohorts, we introduce PIVOT, a user-friendly and open-source interface for streamlined nonlinear registration. We demonstrate PIVOTs strengths through registration of three multi-omic datasets, and show comparison of its performance to existing workflows.

bioinformatics↗

bioRxiv2025

Antigen-presenting cancer-associated fibroblasts in murine pancreatic tumors differentially control regulatory T cell phenotype and function via CXCL9 and CCL22

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a complex tumor microenvironment (TME) including stromal cells that influence resistance to therapy. Recent studies have revealed that stromal cancer-associated fibroblasts (CAFs) are heterogeneous in origin, gene expression, and function. Antigen-presenting CAFs (apCAFs), are defined by major histocompatibility complex (MHC)-II expression and can activate effector CD4+ T cells that have the potential to contribute to the anti-cancer immune response, but also can induce regulatory T cell (Treg) differentiation. Whether apCAFs promote or restrain the antitumor response remains uncertain. Using tumor clones of the KPC murine PDAC model differing in sensitivity to immune checkpoint blockade (ICB), we found that immunosensitive (sKPC) tumors were characterized by higher immune cell and apCAF infiltration than resistant (rKPC) tumors. IMC analysis showed proximity of apCAFs and CD4+ T cells in both sKPC and rKPC tumors implicating interaction within the TME. apCAF-depleted sKPC tumor-bearing mice had diminished sensitivity to ICB. apCAFs from both sKPC and rKPC tumors activated tumor-infiltrating CD4+ T cells and induced Treg differentiation. However, transcriptomic analysis showed that Tregs induced by apCAFs were overexpressed for immunosuppressive genes in rKPCs relative to sKPCs, and that this is associated with differential chemokine signaling from apCAFs depending on tumor origin. Together these data implicate apCAFs as important mediators of the antitumor immune response, modulation of which could facilitate the development of more effective anti-tumor immune based approaches for PDAC patients.

cancer biology↗

bioRxiv2025

Cancer associated fibroblasts drive epithelial to mesenchymal transition and classical to basal change in pancreatic ductal adenocarcinoma cells with loss of IL-8 expression

Pancreatic ductal adenocarcinoma (PDAC) carries an extremely poor prognosis, in part resulting from cellular heterogeneity that supports overall tumorigenicity. Cancer associated fibroblasts (CAF) are key determinants of PDAC biology and response to systemic therapy. While CAF subtypes have been defined, the effects of patient-specific CAF heterogeneity and plasticity on tumor cell behavior remain unclear. Here, multi-omics was used to characterize the tumor microenvironment (TME) in tumors from patients undergoing curative-intent surgery for PDAC. In these same patients, matched tumor organoid and CAF lines were established to functionally validate the impact of CAFs on the tumor cells. CAFs were found to drive epithelial-mesenchymal transition (EMT) and a switch in tumor cell classificiaton from classical to basal subtype. Furthermore, we identified CAF-specific interleukin 8 (IL-8) as an important modulator of tumor cell subtype. Finally, we defined neighborhood relationships between tumor cell and T cell subsets. Statement of SignificanceThis multidimensional analysis highlights the diverse role CAFs have in influencing other cell types in the TME, including epithelial-derived tumor and infiltrating immune cells. Our methods provide a platform for evaluating emerging therapeutic approaches and for studying mechanisms that dictate tumor behavior in a manner that reflects patient-specific heterogeneity.

cancer biology↗

bioRxiv2024

Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancreatic cancer immunotherapy pathologic responders

Pancreatic adenocarcinoma (PDAC) is a rapidly progressing cancer that responds poorly to immunotherapies. Intratumoral tertiary lymphoid structures (TLS) have been associated with rare long-term PDAC survivors, but the role of TLS in PDAC and their spatial relationships within the context of the broader tumor microenvironment remain unknown. We generated a spatial multi-omics atlas encompassing 26 PDAC tumors from patients treated with combination immunotherapies. Using machine learning-enabled H&E image classification models and unsupervised gene expression matrix factorization methods for spatial transcriptomics, we characterized cellular states within TLS niches spanning across distinct morphologies and immunotherapies. Unsupervised learning generated a TLS-specific spatial gene expression signature that significantly associates with improved survival in PDAC patients. These analyses demonstrate TLS-associated intratumoral B cell maturation in pathological responders, confirmed with spatial proteomics and BCR profiling. Our study also identifies spatial features of pathologic immune responses, revealing TLS maturation colocalizing with IgG/IgA distribution and extracellular matrix remodeling. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=188 SRC="FIGDIR/small/613714v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@d5e1a5org.highwire.dtl.DTLVardef@1d14012org.highwire.dtl.DTLVardef@c57c6corg.highwire.dtl.DTLVardef@16baa56_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTSO_LIIntegrated multi-modal spatial profiling of human PDAC tumors from neoadjuvant immunotherapy clinical trials reveal diverse spatial niches enriched in TLS. C_LIO_LITLS maturity is influenced by tumor location and the cellular neighborhoods in which TLS immune cells are recruited. C_LIO_LIUnsupervised machine learning of genome-wide signatures on spatial transcriptomics data characterizes the TLS-enriched TME and associates TLS transcriptomes with survival outcomes in PDAC. C_LIO_LIInteractions of spatially variable gene expression patterns showed TLS maturation is coupled with immunoglobulin distribution and ECM remodeling in pathologic responders. C_LIO_LIIntratumoral plasma cell and immunoglobin gene expression spatial dynamics demonstrate trafficking of TLS-driven humoral immunity in the PDAC TME. C_LI SignificanceWe report a spatial multi-omics atlas of PDAC tumors from a series of immunotherapy neoadjuvant clinical trials. Intratumorally, pathologic responders exhibit mature TLS that propagate plasma cells into malignant niches. Our findings offer insights on the role of TLS-associated humoral immunity and stromal remodeling during immunotherapy treatment.

cancer biology↗

bioRxiv2024

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer for which few effective therapies exist. Immunotherapies specifically are ineffective in pancreatic cancer, in part due to its unique stromal and immune microenvironment. Pancreatic intraepithelial neoplasia, or PanIN, is the main precursor lesion to PDAC. Recently it was discovered that PanINs are remarkably abundant in the grossly normal pancreas, suggesting that the vast majority will never progress to cancer. Here, through construction of 48 samples of cm3-sized human pancreas tissue, we profiled the immune microenvironment of 1,476 PanINs in 3D and at single-cell resolution to better understand the early evolution of the pancreatic tumor microenvironment and to determine how inflammation may play a role in cancer progression. We found that bulk pancreatic inflammation strongly correlates to PanIN cell fraction. We found that the immune response around PanINs is highly heterogeneous, with distinct immune hotspots and cold spots that appear and disappear in a span of tens of microns. Immune hotspots generally mark locations of higher grade of dysplasia or locations near acinar atrophy. The immune composition at these hotspots is dominated by naive, cytotoxic, and regulatory T cells, cancer associated fibroblasts, and tumor associated macrophages, with little similarity to the immune composition around less-inflamed PanINs. By mapping FOXP3+ cells in 3D, we found that regulatory T cells are present at higher density in larger PanIN lesions compared to smaller PanINs, suggesting that the early initiation of PanINs may not exhibit an immunosuppressive response. This analysis demonstrates that while PanINs are common in the pancreases of most individuals, inflammation may play a pivotal role, both at the bulk and the microscopic scale, in demarcating regions of significance in cancer progression.

cancer biology↗

bioRxiv2024

High-motility pro-tumorigenic monocytes drive macrophage enrichment in the tumor microenvironment

Enrichment of tumor-associated macrophages (TAM{Phi}s) in the tumor microenvironment correlates with worse clinical outcomes in triple-negative breast cancer (TNBC) patients, prompting the development of therapies to inhibit TAM{Phi} infiltration. However, the lackluster efficacy of CCL2-based chemotaxis blockade in clinical trials suggests that a new understanding of monocyte/macrophage infiltration may be necessary. Here we demonstrate that random migration, and not only chemotaxis, drives macrophage tumor infiltration. We identified tumor- associated monocytes (TAMos) that display a dramatically enhanced migration capability, induced rapidly by the tumor microenvironment, that drives effective tumor infiltration, in contrast to low-motility differentiated macrophages. TAMo, not TAM{Phi}, promotes cancer cell proliferation through activation of the MAPK pathway. IL-6 secreted both by cancer cells and TAMo themselves enhances TAMo migration by increasing dendritic protrusion dynamics and myosin- based contractility via the JAK2/STAT3 signaling pathway. Independent from CCL2 mediated chemotaxis, IL-6 driven enhanced migration and pro-proliferative effect of TAMo were validated in a syngeneic TNBC mouse model. Depletion of IL-6 in cancer cells significantly attenuated monocyte infiltration and reversed TAMo-induced cancer cell proliferation. This work reveals the critical role random migration plays in monocyte driven TAM{Phi} enrichment in a tumor and pinpoints IL-6 as a potential therapeutic target in combination with CCL2 to ameliorate current strategies against TAM{Phi} infiltration.

immunology↗

bioRxiv2024

Natural killer cells associate with epithelial cells in the pancreatic ductal adenocarcinoma tumor microenvironment

Pancreatic ductal adenocarcinoma (PDAC) exhibits dense fibrosis and immune exclusion. While fibrosis has been studied globally and at the region-of-interest level, its impact on stromal-ductal architecture and immune cell localization remains unknown. Here, we establish cancer-associated fibroblast (CAF)-stratified ductal spatial architecture as a fundamental determinant of immune exclusion in PDAC. Focusing on malignant PDAC epithelial ductal regions, the critical interface where immune cells must access tumor epithelium, we demonstrate that periductal fibroblast organization dictates leukocyte proximity. Through integrative analysis of treatment-naive patient samples from three independent cohorts - including imaging mass cytometry, multiplex immunohistochemistry, and single-cell RNA sequencing - we uncovered that activated, pro-inflammatory leukocytes preferentially localized near malignant ducts in regions with low fibroblast density. Stratifying epithelial-ductal regions by CAF abundance revealed a graded constraint: increasing fibroblast content corresponded to reduced leukocyte-epithelial proximity and elevated collagen I deposition. Despite their exclusion in high-CAF ducts, leukocytes in low-CAF ducts retained functional competence. Mechanistically, ligand-receptor inference implicated collagen-CD44 signaling as an adhesion axis anchoring immune cells within fibroblast-rich zones, with CD44 blockade enhancing natural killer cell invasion and motility in fibrotic spheroid models. Thus, by establishing ductal regions as critical spatial units of immune exclusion, these findings provide a framework for dissecting stromal-immune interactions and reveal targetable "stromal checkpoints" that can be leveraged to overcome CAF-driven barriers to leukocyte motility and infiltration in PDAC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/593868v3_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@17df874org.highwire.dtl.DTLVardef@142c809org.highwire.dtl.DTLVardef@15af4a7org.highwire.dtl.DTLVardef@74183a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Mapping the breast tumor microenvironment: proximity analysis reveals spatial relationships between macrophage subtypes and metastasis-initiating cancer cells

The development of metastasis, responsible for the majority of cancer-related fatalities, is the most dangerous aspect of breast cancer, the predominant malignancy affecting women. We previously identified specific cancer cell populations responsible for metastatic events which are cytokeratin-14 (CK14) and E-cadherin positive in luminal tumors, and E-cadherin and vimentin positive in triple-negative tumors. Since cancer cells evolve within a complex ecosystem comprised of immune cells and stromal cells, we sought to decipher the spatial interactions of these aggressive cancer cell populations within the tumor microenvironment (TME). We used imaging mass cytometry to detect 36 proteins in tumor microarrays containing paired primary and metastatic lesions from luminal or triple-negative breast cancers (TNBC), resulting in a dataset of 1,477,337 annotated cells. Focusing on metastasis-initiating cell populations, we observed close proximity to specific fibroblast and macrophage subtypes, a relationship maintained between primary and metastatic tumors. Notably, high CK14 in luminal cancer cells and high vimentin in TNBC cells correlated with close proximity to specific macrophage subtypes (CD163intCD206intPDL1intHLA-DR+ or PDL1highARG1high). Our in-depth spatial analysis elucidates that metastasis-initiating cancer cells exhibit with distinct cell populations within the TME, implicating the role of these cell-cell interactions in promoting metastasis.

cancer biology↗

bioRxiv2023

Preventing NK cell activation in the damaged liver induced by cabozantinib/PD-1 blockade increases survival in hepatocellular carcinoma models

Combining multikinase inhibitors with immune checkpoint blockade improves tumor control in hepatocellular carcinoma (HCC), but survival benefits remain inconsistent. To define this discordance, we integrated COSMIC-312 with orthotopic and autochthonous murine HCC models with or without liver fibrosis. In patients treated with cabozantinib plus atezolizumab, baseline liver function stratified overall survival but not progression-free survival, indicating uncoupling of tumor control from survival. In contrast, sorafenib outcomes tracked with both endpoints, supporting a treatment-specific effect rather than a purely prognostic effect of liver status. In murine HCC models, cabozantinib plus PD-1 blockade induced comparable tumor regression regardless of liver condition, but improved survival only in mice with preserved liver function, whereas fibrotic hosts developed hepatotoxicity. Immune profiling revealed compartment-specific remodeling, with enhanced cytotoxic T-cell programs in tumors but expansion of NK-lineage innate lymphocytes with ILC1-like features in fibrotic liver. Depletion of NK1.1-positive cells reduced liver injury and restored survival without compromising antitumor efficacy, whereas CD4-positive or CD8-positive T-cell depletion did not protect from hepatotoxicity. Transcriptomic, single-cell, adoptive-transfer, and human in vitro studies supported a model in which the fibrotic liver niche promotes NK-to-ILC1-like reprogramming, hepatocyte stress signaling, and TNF/TRAIL-associated epithelial injury. Consistently, cabozantinib and nivolumab showed liver-predominant remodeling of CD56-positive innate lymphocyte-enriched populations in human HCC samples, and ex vivo TGF-beta induced ILC1-like phenotypic changes in human NK cells. These findings identify liver fibrosis as a host determinant that can limit the survival benefit of multikinase inhibitor immunotherapy by promoting innate immune-mediated hepatotoxicity despite preserved tumor control in HCC. One Sentence SummaryLiver fibrosis limits the survival benefit of multikinase inhibitor immunotherapy in hepatocellular carcinoma by promoting innate immune-mediated hepatotoxicity despite preserved tumor control.

cancer biology↗

bioRxiv2023

Immune landscape of tertiary lymphoid structures in hepatocellular carcinoma (HCC) treated with neoadjuvant immune checkpoint blockade

Neoadjuvant immunotherapy is thought to produce long-term remissions through induction of antitumor immune responses before removal of the primary tumor. Tertiary lymphoid structures (TLS), germinal center-like structures that can arise within tumors, may contribute to the establishment of immunological memory in this setting, but understanding of their role remains limited. Here, we investigated the contribution of TLS to antitumor immunity in hepatocellular carcinoma (HCC) treated with neoadjuvant immunotherapy. We found that neoadjuvant immunotherapy induced the formation of TLS, which were associated with superior pathologic response, improved relapse free survival, and expansion of the intratumoral T and B cell repertoire. While TLS in viable tumor displayed a highly active mature morphology, in areas of tumor regression we identified an involuted TLS morphology, which was characterized by dispersion of the B cell follicle and persistence of a T cell zone enriched for ongoing antigen presentation and T cell-mature dendritic cell interactions. Involuted TLS showed increased expression of T cell memory markers and expansion of CD8+ cytotoxic and tissue resident memory clonotypes. Collectively, these data reveal the circumstances of TLS dissolution and suggest a functional role for late-stage TLS as sites of T cell memory formation after elimination of viable tumor. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=128 SRC="FIGDIR/small/562104v2_fig0.gif" ALT="Figure 0"> View larger version (30K): org.highwire.dtl.DTLVardef@859572org.highwire.dtl.DTLVardef@169ed2org.highwire.dtl.DTLVardef@11510f0org.highwire.dtl.DTLVardef@b39a4_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LSTHighlightsC_LSTO_LIIn patients with hepatocellular carcinoma (HCC), tertiary lymphoid structures (TLS) are induced by neoadjuvant immunotherapy and are associated with favorable clinical outcomes. C_LIO_LITLS within the same tumor demonstrate extensive sharing of expanded granzyme K and granzyme B-expressing CD8+ T effector memory clonotypes, but the B cell repertoires of individual TLS are almost wholly distinct, consistent with independent germinal center reactions. C_LIO_LIWithin areas of viable tumor, mature TLS are characterized by high expression of CD21 and CD23, BCL6+ germinal center B cells, and close interactions between DCLAMP+ mature dendritic cells and CXCR5-CXCR3+ CD4 T peripheral helper cells within a T cell zone adjacent to the B cell follicle. C_LIO_LIWithin areas of tumor regression, an involuted TLS morphology is identified that is notable for dissolution of the B cell germinal center, retention of the T cell zone, and increased T cell memory. C_LI

immunology↗

bioRxiv2023

Informing virtual clinical trials of hepatocellular carcinoma with spatial multi-omics analysis of a human neoadjuvant immunotherapy clinical trial

Human clinical trials are important tools to advance novel systemic therapies improve treatment outcomes for cancer patients. The few durable treatment options have led to a critical need to advance new therapeutics in hepatocellular carcinoma (HCC). Recent human clinical trials have shown that new combination immunotherapeutic regimens provide unprecedented clinical response in a subset of patients. Computational methods that can simulate tumors from mathematical equations describing cellular and molecular interactions are emerging as promising tools to simulate the impact of therapy entirely in silico. To facilitate designing dosing regimen and identifying potential biomarkers, we developed a new computational model to track tumor progression at organ scale while reflecting the spatial heterogeneity in the tumor at tissue scale in HCC. This computational model is called a spatial quantitative systems pharmacology (spQSP) platform and it is also designed to simulate the effects of combination immunotherapy. We then validate the results from the spQSP system by leveraging real-world spatial multi-omics data from a neoadjuvant HCC clinical trial combining anti-PD-1 immunotherapy and a multitargeted tyrosine kinase inhibitor (TKI) cabozantinib. The model output is compared with spatial data from Imaging Mass Cytometry (IMC). Both IMC data and simulation results suggest closer proximity between CD8 T cell and macrophages among non-responders while the reverse trend was observed for responders. The analyses also imply wider dispersion of immune cells and less scattered cancer cells in responders samples. We also compared the model output with Visium spatial transcriptomics analyses of samples from post-treatment tumor resections in the original clinical trial. Both spatial transcriptomic data and simulation results identify the role of spatial patterns of tumor vasculature and TGF{beta} in tumor and immune cell interactions. To our knowledge, this is the first spatial tumor model for virtual clinical trials at a molecular scale that is grounded in high-throughput spatial multi-omics data from a human clinical trial.

bioengineering↗

bioRxiv2023

Reprogramming Intrahepatic Cholangiocarcinoma Immune Microenvironment by Chemotherapy and CTLA-4 Blockade Enhances Anti-PD1 Therapy

Intrahepatic cholangiocarcinoma (ICC) has limited therapeutic options and a dismal prognosis. Anti-PD-L1 immunotherapy combined with gemcitabine/cisplatin chemotherapy has recently shown efficacy in biliary tract cancers, but responses are seen only in a minority of patients. Here, we studied the roles of anti-PD1 and anti-CTLA-4 immune checkpoint blockade (ICB) therapies when combined with gemcitabine/cisplatin and the mechanisms of treatment benefit in orthotopic murine ICC models. We evaluated the effects of the combined treatments on ICC vasculature and immune microenvironment using flow cytometry analysis, immunofluorescence, imaging mass cytometry, RNA-sequencing, qPCR, and in vivo T-cell depletion and CD8+ T-cell transfer using orthotopic ICC models and transgenic mice. Combining gemcitabine/cisplatin with anti-PD1 and anti-CTLA-4 antibodies led to substantial survival benefits and reduction of morbidity in two aggressive ICC models, which were ICB-resistant. Gemcitabine/cisplatin treatment increased the frequency of tumor-infiltrating lymphocytes and normalized the ICC vessels, and when combined with dual CTLA-4/PD1 blockade, increased the number of activated CD8+Cxcr3+IFN-{gamma}+ T-cells. Depletion of CD8+ but not CD4+ T-cells compromised efficacy. Conversely, CD8+ T-cell transfer from Cxcr3-/- versus Cxcr3+/+ mice into Rag1-/- immunodeficient mice restored the anti-tumor effect of gemcitabine/cisplatin/ICB combination therapy. Finally, rational scheduling of the ICBs (anti-CTLA-4 "priming") with chemotherapy and anti-PD1 therapy achieved equivalent efficacy with continuous dosing while reducing overall drug exposure. In summary, gemcitabine/cisplatin chemotherapy normalizes vessel structure, increases activated T-cell infiltration, and enhances anti-PD1/CTLA-4 immunotherapy efficacy in aggressive murine ICC. This combination approach should be clinically tested to overcome resistance to current therapies in ICC patients. One Sentence SummaryImmune microenvironment reprogramming by chemotherapy and priming using CTLA-4 blockade render ICCs responsive to anti-PD-1 immunotherapy.

cancer biology↗

bioRxiv2022

Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces

Recent advances in spatial transcriptomics (ST) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor and its microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as occurs in tumor-immune interactions. We present SpaceMarkers, a novel bioinformatics algorithm to infer molecular changes from cell-cell interaction from latent space analysis of ST data. We apply this approach to infer molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.

bioinformatics↗

bioRxiv2021

Engineering CAR-NK cells to secrete IL15 sustains their anti-AML functionality, but is associated with systemic toxicities

BackgroundThe prognosis of patients with recurrent/refractory acute myelogenous leukemia (AML) remains poor and cell-based immunotherapies hold promise to improve outcomes. NK cells can elicit an anti-leukemic response via a repertoire of activating receptors that bind AML surface ligands. NK cell adoptive transfer is safe but thus far has shown limited anti-AML efficacy. Here, we aimed to overcome this limitation by engineering NK cells to express chimeric antigen receptors (CARs) to boost their anti-AML activity, and interleukin-15 (IL15) to enhance their persistence. MethodsWe characterized in detail NK cell populations expressing a panel of AML (CD123)-specific CARs and/or IL15 in vitro and in AML xenograft models. ResultsCARs with 2B4.{zeta} or 4-1BB.{zeta} signaling domains demonstrated greater cell surface expression and endowed NK cells with improved anti-AML activity in vitro. Initial in vivo testing revealed that only 2B4.{zeta} CAR-NK cells had improved anti-AML activity in comparison to untransduced (UTD) and 4-1BB.{zeta} CAR-NK cells. However, the benefit was transient due to limited CAR-NK cell persistence. Transgenic expression of secretory (s)IL15 in 2B4.{zeta} CAR and UTD NK cells improved their effector function in the setting of chronic antigen simulation in vitro. Multiparameter flow analysis after chronic antigen exposure identified the expansion of unique NK cell subsets. 2B4.{zeta}/sIL15 CAR and sIL15 NK cells maintained an overall activated NK cell phenotype. This was confirmed by transcriptomic analysis, which revealed a highly proliferative and activated signature in these NK cell groups. In vivo, 2B4.{zeta}/sIL15 CAR-NK cells had potent anti-AML activity in one model, while 2B4.{zeta}/sIL15 CAR and sIL15 NK cells induced lethal toxicity in a second model. ConclusionTransgenic expression of CD123-CARs and sIL15 enabled NK cells to function in the setting of chronic antigen exposure but was associated with systemic toxicities. Thus, our study provides the impetus to explore inducible and controllable expression systems to provide cytokine signals to AML-specific CAR-NK cells before embarking on early phase clinical testing. O_FIG O_LINKSMALLFIG WIDTH=161 HEIGHT=200 SRC="FIGDIR/small/461509v1_ufig1.gif" ALT="Figure 1"> View larger version (42K): org.highwire.dtl.DTLVardef@4d09eaorg.highwire.dtl.DTLVardef@1c61411org.highwire.dtl.DTLVardef@14f8097org.highwire.dtl.DTLVardef@8375ac_HPS_FORMAT_FIGEXP M_FIG C_FIG In BriefSecretion of IL15 from anti-CD123.2B4.CD3{zeta} CAR-NK cells enhances their activation and killing potential against Acute Myelogenous Leukemia, but carries the risk of severe systemic toxicity.

immunology↗