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Hypoxia occurs in 90% of solid tumors and is associated with metastasis and mortality. Breast cancer cells that experience intratumoral hypoxia are 5x more likely to develop lung metastasis in animal models. Using spatial transcriptomics, we determine that hypoxic cells localized in more oxygenated tumor regions (termed 'post-hypoxic') retain expression of hypoxia-inducible and NF-kB-regulated genes, even in the oxygen-rich bloodstream. This cellular response is reproduced in vitro under chronic hypoxic conditions followed by reoxygenation. A subset of genes remains increased in reoxygenated cells. MUC1/MUC1-C is upregulated by both HIF-1α and NF-kB-p65 during chronic hypoxia. Abrogating MUC1 decreases the expression of superoxide dismutase enzymes, causing reactive oxygen species (ROS) production and cell death. A hypoxia-dependent genetic deletion of MUC1, or MUC1-C inhibition by GO-203, increases ROS levels in circulating tumor cells (CTCs), reducing the extent of metastasis. High MUC1 expression in tumor biopsies is associated with recurrence, and MUC1+ CTCs have lower ROS levels than MUC1- CTCs in patient-derived xenograft models. This study demonstrates that therapeutically targeting MUC1-C reduces hypoxia-driven metastasis.
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Neoplasias da Mama , Mucina-1 , Espécies Reativas de Oxigênio , Mucina-1/metabolismo , Mucina-1/genética , Humanos , Animais , Espécies Reativas de Oxigênio/metabolismo , Feminino , Linhagem Celular Tumoral , Camundongos , Neoplasias da Mama/patologia , Neoplasias da Mama/metabolismo , Neoplasias da Mama/genética , Regulação Neoplásica da Expressão Gênica , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Subunidade alfa do Fator 1 Induzível por Hipóxia/genética , Células Neoplásicas Circulantes/metabolismo , Células Neoplásicas Circulantes/patologia , Neoplasias Pulmonares/secundário , Neoplasias Pulmonares/metabolismo , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Oxigênio/metabolismo , Fator de Transcrição RelA/metabolismo , Metástase Neoplásica , Hipóxia/metabolismo , Hipóxia CelularRESUMO
Pancreatic ductal adenocarcinoma (PDAC) is highly lethal and resistant to immunotherapy. Although immune recognition can be enhanced with immunomodulatory agents including checkpoint inhibitors and vaccines, few patients experience clinical efficacy because the tumor immune microenvironment (TiME) is dominated by immunosuppressive myeloid cells that impose T cell inhibition. Inhibition of phosphodiesterase-5 (PDE5) was reported to downregulate metabolic regulators arginase and inducible NOS in immunosuppressive myeloid cells and enhance immunity against immune-sensitive tumors, including head and neck cancers. We show for the first time to our knowledge that combining a PDE5 inhibitor, tadalafil, with a mesothelin-specific vaccine, anti-programmed cell death protein 1, and anti-cytotoxic T lymphocyte-associated protein 4 yields antitumor efficacy even against immune-resistant PDAC. To determine immunologic advantages conferred by tadalafil, we profiled the TiME using mass cytometry and single-cell RNA-sequencing analysis with Domino to infer intercellular signaling. Our analyses demonstrated that tadalafil reprograms myeloid cells to be less immunosuppressive. Moreover, tadalafil synergized with the vaccine, enhancing T cell activation including mesothelin-specific T cells. Tadalafil treatment was also associated with myeloid/T cell signaling axes important for antitumor responses (e.g., Cxcr3, Il12). Our study shows that PDE5 inhibition combined with vaccine-based immunotherapy promotes pro-inflammatory states of myeloid cells, activation of T cells, and enhanced myeloid/T cell crosstalk to yield antitumor efficacy against immune-resistant PDAC.
Assuntos
Vacinas Anticâncer , Carcinoma Ductal Pancreático , Imunoterapia , Células Mieloides , Neoplasias Pancreáticas , Inibidores da Fosfodiesterase 5 , Tadalafila , Microambiente Tumoral , Carcinoma Ductal Pancreático/imunologia , Carcinoma Ductal Pancreático/terapia , Carcinoma Ductal Pancreático/tratamento farmacológico , Carcinoma Ductal Pancreático/patologia , Células Mieloides/imunologia , Células Mieloides/efeitos dos fármacos , Tadalafila/farmacologia , Tadalafila/uso terapêutico , Vacinas Anticâncer/uso terapêutico , Vacinas Anticâncer/farmacologia , Humanos , Camundongos , Imunoterapia/métodos , Animais , Inibidores da Fosfodiesterase 5/farmacologia , Inibidores da Fosfodiesterase 5/uso terapêutico , Microambiente Tumoral/imunologia , Microambiente Tumoral/efeitos dos fármacos , Neoplasias Pancreáticas/imunologia , Neoplasias Pancreáticas/terapia , Neoplasias Pancreáticas/tratamento farmacológico , Linhagem Celular Tumoral , MesotelinaRESUMO
This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.
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Fibroblastos Associados a Câncer , Carcinogênese , Carcinoma Ductal Pancreático , Neoplasias Pancreáticas , Humanos , Neoplasias Pancreáticas/genética , Carcinogênese/genética , Fibroblastos Associados a Câncer/metabolismo , Carcinoma Ductal Pancreático/genética , Microambiente Tumoral/genética , Análise de Célula Única/métodos , Transcriptoma/genética , Regulação Neoplásica da Expressão Gênica/genética , Carcinoma in Situ/genética , Carcinoma in Situ/patologiaRESUMO
Due to the lack of treatment options, there remains a need to advance new therapeutics in hepatocellular carcinoma (HCC). The traditional approach moves from initial molecular discovery through animal models to human trials to advance novel systemic therapies that improve treatment outcomes for patients with cancer. Computational methods that simulate tumors mathematically to describe cellular and molecular interactions are emerging as promising tools to simulate the impact of therapy entirely in silico, potentially greatly accelerating delivery of new therapeutics to patients. To facilitate the design of dosing regimens and identification of potential biomarkers for immunotherapy, we developed a new computational model to track tumor progression at the organ scale while capturing the spatial heterogeneity of the tumor in HCC. This computational model of spatial quantitative systems pharmacology was designed to simulate the effects of combination immunotherapy. The model was initiated using literature-derived parameter values and fitted to the specifics of HCC. Model validation was done through comparison with spatial multiomics data from a neoadjuvant HCC clinical trial combining anti-PD1 immunotherapy and a multitargeted tyrosine kinase inhibitor cabozantinib. Validation using spatial proteomics data from imaging mass cytometry demonstrated that closer proximity between CD8 T cells and macrophages correlated with nonresponse. We also compared the model output with Visium spatial transcriptomics profiling of samples from posttreatment tumor resections in the clinical trial and from another independent study of anti-PD1 monotherapy. Spatial transcriptomics data confirmed simulation results, suggesting the importance of spatial patterns of tumor vasculature and TGFß in tumor and immune cell interactions. Our findings demonstrate that incorporating mathematical modeling and computer simulations with high-throughput spatial multiomics data provides a novel approach for patient outcome prediction and biomarker discovery. Significance: Incorporating mathematical modeling and computer simulations with high-throughput spatial multiomics data provides an effective approach for patient outcome prediction and biomarker discovery.
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Biomarcadores Tumorais , Carcinoma Hepatocelular , Imunoterapia , Neoplasias Hepáticas , Humanos , Anilidas/uso terapêutico , Anilidas/farmacologia , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/imunologia , Carcinoma Hepatocelular/patologia , Carcinoma Hepatocelular/terapia , Ensaios Clínicos como Assunto , Simulação por Computador , Inibidores de Checkpoint Imunológico/uso terapêutico , Inibidores de Checkpoint Imunológico/farmacologia , Imunoterapia/métodos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/imunologia , Neoplasias Hepáticas/patologia , Neoplasias Hepáticas/terapia , Multiômica , Piridinas/uso terapêutico , Piridinas/farmacologia , Microambiente Tumoral/imunologiaRESUMO
Metastatic disease results from the dissemination of tumor cells beyond their organ of origin to grow in distant organs and is the primary cause of death in patients with advanced breast cancer. Preclinical murine models in which primary tumors spontaneously metastasize are valuable tools for studying metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. The NT2.5-lung metastasis (-LM) cell line was derived from serial passaging of tumor cells that were macro-dissected from spontaneous lung metastases after orthotopic mammary implantation of parental NT2.5 cells. Within one week of NT2.5-LM implantation, metastases are observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. We demonstrate that NT2.5-LM metastases are positive for NeuN-the murine equivalent of human epidermal growth factor 2 (HER2). We further demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT), suggestive of their enhanced metastatic potential. Genomic analyses support these findings and reveal enrichment in EMT-regulating pathways. In addition, the metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. The new NT2.5-LM model provides certain advantages over the parental NT2/NT2.5 model, given its more rapid and spontaneous development of metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses.
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Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by an immunosuppressive tumor microenvironment enriched with cancer-associated fibroblasts (CAF). This study used a convergence approach to identify tumor cell and CAF interactions through the integration of single-cell data from human tumors with human organoid coculture experiments. Analysis of a comprehensive atlas of PDAC single-cell RNA sequencing data indicated that CAF density is associated with increased inflammation and epithelial-mesenchymal transition (EMT) in epithelial cells. Transfer learning using transcriptional data from patient-derived organoid and CAF cocultures provided in silico validation of CAF induction of inflammatory and EMT epithelial cell states. Further experimental validation in cocultures demonstrated integrin beta 1 (ITGB1) and vascular endothelial factor A (VEGFA) interactions with neuropilin-1 mediating CAF-epithelial cell cross-talk. Together, this study introduces transfer learning from human single-cell data to organoid coculture analyses for experimental validation of discoveries of cell-cell cross-talk and identifies fibroblast-mediated regulation of EMT and inflammation. SIGNIFICANCE: Adaptation of transfer learning to relate human single-cell RNA sequencing data to organoid-CAF cocultures facilitates discovery of human pancreatic cancer intercellular interactions and uncovers cross-talk between CAFs and tumor cells through VEGFA and ITGB1.
Assuntos
Fibroblastos Associados a Câncer , Carcinoma Ductal Pancreático , Técnicas de Cocultura , Transição Epitelial-Mesenquimal , Inflamação , Integrina beta1 , Neoplasias Pancreáticas , Análise de Célula Única , Microambiente Tumoral , Humanos , Carcinoma Ductal Pancreático/patologia , Carcinoma Ductal Pancreático/metabolismo , Carcinoma Ductal Pancreático/genética , Fibroblastos Associados a Câncer/metabolismo , Fibroblastos Associados a Câncer/patologia , Neoplasias Pancreáticas/patologia , Neoplasias Pancreáticas/metabolismo , Neoplasias Pancreáticas/genética , Inflamação/patologia , Inflamação/metabolismo , Integrina beta1/metabolismo , Integrina beta1/genética , Organoides/patologia , Organoides/metabolismo , Fator A de Crescimento do Endotélio Vascular/metabolismo , Fator A de Crescimento do Endotélio Vascular/genética , Neuropilina-1/metabolismo , Neuropilina-1/genética , Regulação Neoplásica da Expressão Gênica , Linhagem Celular Tumoral , Comunicação CelularRESUMO
Programmed cell death protein 1 (PD-1) inhibitors have modest efficacy as a monotherapy in hepatocellular carcinoma (HCC). A personalized therapeutic cancer vaccine (PTCV) may enhance responses to PD-1 inhibitors through the induction of tumor-specific immunity. We present results from a single-arm, open-label, phase 1/2 study of a DNA plasmid PTCV (GNOS-PV02) encoding up to 40 neoantigens coadministered with plasmid-encoded interleukin-12 plus pembrolizumab in patients with advanced HCC previously treated with a multityrosine kinase inhibitor. Safety and immunogenicity were assessed as primary endpoints, and treatment efficacy and feasibility were evaluated as secondary endpoints. The most common treatment-related adverse events were injection-site reactions, observed in 15 of 36 (41.6%) patients. No dose-limiting toxicities or treatment-related grade ≥3 events were observed. The objective response rate (modified intention-to-treat) per Response Evaluation Criteria in Solid Tumors 1.1 was 30.6% (11 of 36 patients), with 8.3% (3 of 36) of patients achieving a complete response. Clinical responses were associated with the number of neoantigens encoded in the vaccine. Neoantigen-specific T cell responses were confirmed in 19 of 22 (86.4%) evaluable patients by enzyme-linked immunosorbent spot assays. Multiparametric cellular profiling revealed active, proliferative and cytolytic vaccine-specific CD4+ and CD8+ effector T cells. T cell receptor ß-chain (TCRß) bulk sequencing results demonstrated vaccination-enriched T cell clone expansion and tumor infiltration. Single-cell analysis revealed posttreatment T cell clonal expansion of cytotoxic T cell phenotypes. TCR complementarity-determining region cloning of expanded T cell clones in the tumors following vaccination confirmed reactivity against vaccine-encoded neoantigens. Our results support the PTCV's mechanism of action based on the induction of antitumor T cells and show that a PTCV plus pembrolizumab has clinical activity in advanced HCC. ClinicalTrials.gov identifier: NCT04251117 .
Assuntos
Carcinoma Hepatocelular , Neoplasias Hepáticas , Vacinas , Humanos , Carcinoma Hepatocelular/tratamento farmacológico , Neoplasias Hepáticas/tratamento farmacológico , Anticorpos Monoclonais Humanizados/efeitos adversos , Vacinas/uso terapêuticoRESUMO
Preclinical murine models in which primary tumors spontaneously metastasize to distant organs are valuable tools to study metastatic progression and novel cancer treatment combinations. Here, we characterize a novel syngeneic murine breast tumor cell line, NT2.5-lung metastasis (-LM), that provides a model of spontaneously metastatic neu-expressing breast cancer with quicker onset of widespread metastases after orthotopic mammary implantation in immune-competent NeuN mice. Within one week of orthotopic implantation of NT2.5-LM in NeuN mice, distant metastases can be observed in the lungs. Within four weeks, metastases are also observed in the bones, spleen, colon, and liver. Metastases are rapidly growing, proliferative, and responsive to HER2-directed therapy. We demonstrate altered expression of markers of epithelial-to-mesenchymal transition (EMT) and enrichment in EMT-regulating pathways, suggestive of their enhanced metastatic potential. The new NT2.5-LM model provides more rapid and spontaneous development of widespread metastases. Besides investigating mechanisms of metastatic progression, this new model may be used for the rationalized development of novel therapeutic interventions and assessment of therapeutic responses targeting distant visceral metastases.
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The immune system defines a complex network of tissues and cell types that orchestrate responses across the body in a dynamic manner. The local and systemic interactions between immune and cancer cells contribute to disease progression. Lymphocytes are activated in lymph nodes, traffic through the periphery, and impact cancer progression through their interactions with tumor cells. As a result, therapeutic response and resistance are mediated across tissues, and a comprehensive understanding of lymphocyte dynamics requires a systems-level approach. In this review, we highlight experimental and computational methods that can leverage the study of leukocyte trafficking through an immunomics lens and reveal how adaptive immunity shapes cancer.
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Imunoinformática , Neoplasias , Humanos , Linfócitos , Neoplasias/terapia , Leucócitos , LinfonodosRESUMO
Personalized cancer vaccines aim to activate and expand cytotoxic antitumor CD8+ T cells to recognize and kill tumor cells. However, the role of CD4+ T cell activation in the clinical benefit of these vaccines is not well defined. We previously established a personalized neoantigen vaccine (PancVAX) for the pancreatic cancer cell line Panc02, which activates tumor-specific CD8+ T cells but required combinatorial checkpoint modulators to achieve therapeutic efficacy. To determine the effects of neoantigen-specific CD4+ T cell activation, we generated a vaccine (PancVAX2) targeting both major histocompatibility complex class I- (MHCI-) and MHCII-specific neoantigens. Tumor-bearing mice vaccinated with PancVAX2 had significantly improved control of tumor growth and long-term survival benefit without concurrent administration of checkpoint inhibitors. PancVAX2 significantly enhanced priming and recruitment of neoantigen-specific CD8+ T cells into the tumor with lower PD-1 expression after reactivation compared with the CD8+ vaccine alone. Vaccine-induced neoantigen-specific Th1 CD4+ T cells in the tumor were associated with decreased Tregs. Consistent with this, PancVAX2 was associated with more proimmune myeloid-derived suppressor cells and M1-like macrophages in the tumor, demonstrating a less immunosuppressive tumor microenvironment. This study demonstrates the biological importance of prioritizing and including CD4+ T cell-specific neoantigens for personalized cancer vaccine modalities.
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Vacinas Anticâncer , Neoplasias Pancreáticas , Camundongos , Animais , Linfócitos T CD4-Positivos , Antígenos de Neoplasias , Eficácia de Vacinas , Neoplasias Pancreáticas/metabolismo , Microambiente TumoralRESUMO
Genomic and transcriptomic analysis has furthered our understanding of many tumors. Yet, thyroid cancer management is largely guided by staging and histology, with few molecular prognostic and treatment biomarkers. Here, we utilize a large cohort of 251 patients with 312 samples from two tertiary medical centers and perform DNA/RNA sequencing, spatial transcriptomics, and multiplex immunofluorescence to identify biomarkers of aggressive thyroid malignancy. We identify high-risk mutations and discover a unique molecular signature of aggressive disease, the Molecular Aggression and Prediction (MAP) score, which provides improved prognostication over high-risk mutations alone. The MAP score is enriched for genes involved in epithelial de-differentiation, cellular division, and the tumor microenvironment. The MAP score also identifies aggressive tumors with lymphocyte-rich stroma that may benefit from immunotherapy. Future clinical profiling of the stromal microenvironment of thyroid cancer could improve prognostication, inform immunotherapy, and support development of novel therapeutics for thyroid cancer and other stroma-rich tumors.
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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.
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BACKGROUND: Novel immunotherapy combination therapies have improved outcomes for patients with hepatocellular carcinoma (HCC), but responses are limited to a subset of patients. Little is known about the inter- and intra-tumor heterogeneity in cellular signaling networks within the HCC tumor microenvironment (TME) that underlie responses to modern systemic therapy. METHODS: We applied spatial transcriptomics (ST) profiling to characterize the tumor microenvironment in HCC resection specimens from a prospective clinical trial of neoadjuvant cabozantinib, a multi-tyrosine kinase inhibitor that primarily blocks VEGF, and nivolumab, a PD-1 inhibitor in which 5 out of 15 patients were found to have a pathologic response at the time of resection. RESULTS: ST profiling demonstrated that the TME of responding tumors was enriched for immune cells and cancer-associated fibroblasts (CAF) with pro-inflammatory signaling relative to the non-responders. The enriched cancer-immune interactions in responding tumors are characterized by activation of the PAX5 module, a known regulator of B cell maturation, which colocalized with spots with increased B cell marker expression suggesting strong activity of these cells. HCC-CAF interactions were also enriched in the responding tumors and were associated with extracellular matrix (ECM) remodeling as there was high activation of FOS and JUN in CAFs adjacent to the tumor. The ECM remodeling is consistent with proliferative fibrosis in association with immune-mediated tumor regression. Among the patients with major pathologic responses, a single patient experienced early HCC recurrence. ST analysis of this clinical outlier demonstrated marked tumor heterogeneity, with a distinctive immune-poor tumor region that resembles the non-responding TME across patients and was characterized by HCC-CAF interactions and expression of cancer stem cell markers, potentially mediating early tumor immune escape and recurrence in this patient. CONCLUSIONS: These data show that responses to modern systemic therapy in HCC are associated with distinctive molecular and cellular landscapes and provide new targets to enhance and prolong responses to systemic therapy in HCC.
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Carcinoma Hepatocelular , Neoplasias Hepáticas , Humanos , Carcinoma Hepatocelular/tratamento farmacológico , Carcinoma Hepatocelular/genética , Terapia Neoadjuvante , Nivolumabe/uso terapêutico , Estudos Prospectivos , Transcriptoma , Neoplasias Hepáticas/tratamento farmacológico , Neoplasias Hepáticas/genética , Microambiente Tumoral/genéticaRESUMO
Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells' characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This allows us to systematically integrate biological knowledge and multi-omics data to make them computable. We can then perform virtual "thought experiments" that challenge and extend our understanding of multicellular systems, and ultimately generate new testable hypotheses. In this paper, we motivate and describe the grammar, provide a reference implementation, and demonstrate its potential through a series of examples in tumor biology and immunotherapy. Altogether, this approach provides a bridge between biological, clinical, and systems biology researchers for mathematical modeling of biological systems at scale, allowing the community to extrapolate from single-cell characterization to emergent multicellular behavior.
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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 TGFß 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.
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Recent advances in spatial transcriptomics (STs) 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 as well as the tumor 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 it occurs in tumor-immune interactions. We present SpaceMarkers, a bioinformatics algorithm to infer molecular changes from cell-cell interactions from latent space analysis of ST data. We apply this approach to infer the 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.
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Algoritmos , Microambiente Tumoral , Comunicação Celular , Biologia Computacional , Perfilação da Expressão GênicaRESUMO
Novel immunotherapy combination therapies have improved outcomes for patients with hepatocellular carcinoma (HCC), but responses are limited to a subset of patients and recurrence can also occur. Little is known about the inter- and intra-tumor heterogeneity in cellular signaling networks within the HCC tumor microenvironment (TME) that underlie responses to modern systemic therapy. We applied spatial transcriptomics (ST) profiling to characterize the tumor microenvironment in HCC resection specimens from a clinical trial of neoadjuvant cabozantinib, a multi-tyrosine kinase inhibitor that primarily blocks VEGF, and nivolumab, a PD-1 inhibitor in which 5 out of 15 patients were found to have a pathologic response. ST profiling demonstrated that the TME of responding tumors was enriched for immune cells and cancer associated fibroblasts (CAF) with pro-inflammatory signaling relative to the non-responders. The enriched cancer-immune interactions in responding tumors are characterized by activation of the PAX5 module, a known regulator of B cell maturation, which colocalized with spots with increased B cell markers expression suggesting strong activity of these cells. Cancer-CAF interactions were also enriched in the responding tumors and were associated with extracellular matrix (ECM) remodeling as there was high activation of FOS and JUN in CAFs adjacent to tumor. The ECM remodeling is consistent with proliferative fibrosis in association with immune-mediated tumor regression. Among the patients with major pathologic response, a single patient experienced early HCC recurrence. ST analysis of this clinical outlier demonstrated marked tumor heterogeneity, with a distinctive immune-poor tumor region that resembles the non-responding TME across patients and was characterized by cancer-CAF interactions and expression of cancer stem cell markers, potentially mediating early tumor immune escape and recurrence in this patient. These data show that responses to modern systemic therapy in HCC are associated with distinctive molecular and cellular landscapes and provide new targets to enhance and prolong responses to systemic therapy in HCC.
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BACKGROUND AND AIMS: The treatment of hepatocellular carcinoma (HCC) has been transformed by the use of immune checkpoint inhibitors. However, most patients with HCC do not benefit from treatment with immunotherapy. There is an urgent need to understand the mechanisms that underlie response or resistance to immunotherapy for patients with HCC. The use of syngeneic mouse models that closely recapitulate the heterogeneity of human HCC will provide opportunities to examine the complex interactions between cancer cells and nonmalignant cells in the tumor microenvironment. APPROACH AND RESULTS: We leverage a multifaceted approach that includes imaging mass cytometry and suspension cytometry by time of flight to profile the tumor microenvironments of the Hep53.4, Hepa 1-6, RIL-175, and TIBx (derivative of TIB-75) syngeneic mouse HCC models. The immune tumor microenvironments vary across these four models, and various immunosuppressive pathways exist at baseline in orthotopic liver tumors derived from these models. For instance, TIBx, which is resistant to anti-programmed cell death protein 1 therapy, contains a high proportion of "M2-like" tumor-associated macrophages with the potential to diminish antitumor immunity. Investigation of The Cancer Genome Atlas reveals that the baseline immunologic profiles of Hep53.4, RIL-175, and TIBx are broadly representative of human HCCs; however, Hepa 1-6 does not recapitulate the immune tumor microenvironment of the vast majority of human HCCs. CONCLUSIONS: There is a wide diversity in the immune tumor microenvironments in preclinical models and in human HCC, highlighting the need to use multiple syngeneic HCC models to improve the understanding of how to treat HCC through immune modulation.