RESUMO
Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.
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Biologia Computacional , Proteômica , Humanos , Proteômica/métodos , Biologia Computacional/métodos , Biomarcadores Tumorais/metabolismo , Neoplasias/metabolismo , Neoplasias/imunologia , Algoritmos , Biomarcadores , Processamento de Imagem Assistida por Computador/métodosRESUMO
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 iNOS in immunosuppressive myeloid cells and enhance immunity against immune-sensitive tumors including head and neck cancers. We show for the first time that combining a PDE5 inhibitor, tadalafil, with a mesothelin-specific vaccine, anti-PD1, and anti-CTLA4 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 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.
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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
Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable, but is hindered by the limited performance of existing biomarkers. Here, we leveraged in-silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We tested 90 biomarker candidates, including various cellular and molecular species, by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pre-treatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.
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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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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 .
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Carcinoma Hepatocelular , Neoplasias Hepáticas , Vacinas , Humanos , Carcinoma Hepatocelular/tratamento farmacológico , Neoplasias Hepáticas/tratamento farmacológico , Anticorpos Monoclonais Humanizados/efeitos adversos , Vacinas/uso terapêuticoRESUMO
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.
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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
The US National Cancer Act of 1971 designated the director of the National Cancer Institute as responsible for coordinating federal agencies and nonfederal organizations to make progress against cancer. As part of her role, the immediate past director of the National Cancer Institute (MMB) led the development of a National Cancer Plan that was formally released on April 3, 2023. The plan includes 8 aspirational goals "to achieve a society where every person with cancer lives a full and active life and to prevent most cancers so that few people need to face this diagnosis." Research findings provide a foundation for each goal, and research gaps are included in the strategies for meeting each goal. The President's Cancer Panel, also created by the National Cancer Act, conducted an initial assessment of progress toward the plan goals by hearing from 12 organizations at a virtual public meeting on September 7, 2023. The purpose of this commentary is to orient the scientific community to the plan and call attention to related knowledge gaps that could benefit from research.
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National Cancer Institute (U.S.) , Neoplasias , Humanos , Estados Unidos/epidemiologia , Neoplasias/epidemiologia , Neoplasias/prevenção & controle , Neoplasias/terapia , Pesquisa Biomédica/organização & administraçãoRESUMO
We report the results of 24 women, 50% (N = 12) with hormone receptor-positive breast cancer and 50% (N = 12) with advanced triple-negative breast cancer, treated with entinostat + nivolumab + ipilimumab from the dose escalation (N = 6) and expansion cohort (N = 18) of ETCTN-9844 ( NCT02453620 ). The primary endpoint was safety. Secondary endpoints were overall response rate, clinical benefit rate, progression-free survival and change in tumor CD8:FoxP3 ratio. There were no dose-limiting toxicities. Among evaluable participants (N = 20), the overall response rate was 25% (N = 5), with 40% (N = 4) in triple-negative breast cancer and 10% (N = 1) in hormone receptor-positive breast cancer. The clinical benefit rate was 40% (N = 8), and progression-free survival at 6 months was 50%. Exploratory analyses revealed that changes in myeloid cells may contribute to responses; however, no correlation was noted between changes in CD8:FoxP3 ratio, PD-L1 status and tumor mutational burden and response. These findings support further investigation of this treatment in a phase II trial.
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Protocolos de Quimioterapia Combinada Antineoplásica , Benzamidas , Ipilimumab , Nivolumabe , Piridinas , Receptor ErbB-2 , Humanos , Feminino , Pessoa de Meia-Idade , Piridinas/administração & dosagem , Piridinas/uso terapêutico , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Nivolumabe/uso terapêutico , Nivolumabe/administração & dosagem , Adulto , Receptor ErbB-2/metabolismo , Benzamidas/uso terapêutico , Benzamidas/administração & dosagem , Idoso , Ipilimumab/uso terapêutico , Ipilimumab/administração & dosagem , Neoplasias de Mama Triplo Negativas/tratamento farmacológico , Neoplasias da Mama/tratamento farmacológico , Neoplasias da Mama/mortalidade , Intervalo Livre de ProgressãoRESUMO
PURPOSE: Targeting solid tumors with chimeric antigen receptor (CAR) T cells remains challenging due to heterogenous target antigen expression, antigen escape, and the immunosuppressive tumor microenvironment (TME). Pancreatic cancer is characterized by a thick stroma generated by cancer-associated fibroblasts (CAF), which may contribute to the limited efficacy of mesothelin-directed CAR T cells in early-phase clinical trials. To provide a more favorable TME for CAR T cells to target pancreatic ductal adenocarcinoma (PDAC), we generated T cells with an antimesothelin CAR and a secreted T-cell-engaging molecule (TEAM) that targets CAF through fibroblast activation protein (FAP) and engages T cells through CD3 (termed mesoFAP CAR-TEAM cells). EXPERIMENTAL DESIGN: Using a suite of in vitro, in vivo, and ex vivo patient-derived models containing cancer cells and CAF, we examined the ability of mesoFAP CAR-TEAM cells to target PDAC cells and CAF within the TME. We developed and used patient-derived ex vivo models, including patient-derived organoids with patient-matched CAF and patient-derived organotypic tumor spheroids. RESULTS: We demonstrated specific and significant binding of the TEAM to its respective antigens (CD3 and FAP) when released from mesothelin-targeting CAR T cells, leading to T-cell activation and cytotoxicity of the target cell. MesoFAP CAR-TEAM cells were superior in eliminating PDAC and CAF compared with T cells engineered to target either antigen alone in our ex vivo patient-derived models and in mouse models of PDAC with primary or metastatic liver tumors. CONCLUSIONS: CAR-TEAM cells enable modification of tumor stroma, leading to increased elimination of PDAC tumors. This approach represents a promising treatment option for pancreatic cancer.
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Complexo CD3 , Endopeptidases , Proteínas Ligadas por GPI , Imunoterapia Adotiva , Mesotelina , Neoplasias Pancreáticas , Receptores de Antígenos Quiméricos , Microambiente Tumoral , Ensaios Antitumorais Modelo de Xenoenxerto , Humanos , Animais , Camundongos , Neoplasias Pancreáticas/imunologia , Neoplasias Pancreáticas/terapia , Neoplasias Pancreáticas/patologia , Neoplasias Pancreáticas/metabolismo , Microambiente Tumoral/imunologia , Imunoterapia Adotiva/métodos , Receptores de Antígenos Quiméricos/imunologia , Receptores de Antígenos Quiméricos/metabolismo , Complexo CD3/imunologia , Complexo CD3/metabolismo , Proteínas Ligadas por GPI/imunologia , Proteínas Ligadas por GPI/metabolismo , Linhagem Celular Tumoral , Carcinoma Ductal Pancreático/imunologia , Carcinoma Ductal Pancreático/terapia , Carcinoma Ductal Pancreático/patologia , Carcinoma Ductal Pancreático/metabolismo , Linfócitos T/imunologia , Linfócitos T/metabolismo , Fibroblastos Associados a Câncer/metabolismo , Fibroblastos Associados a Câncer/imunologia , Proteínas de Membrana/imunologia , Proteínas de Membrana/metabolismo , Serina Endopeptidases/imunologia , Serina Endopeptidases/metabolismo , Adenocarcinoma/imunologia , Adenocarcinoma/terapia , Adenocarcinoma/patologiaRESUMO
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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Radiotherapy is hypothesized to have an immune-modulating effect on the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) to sensitize it to anti-PD-1 antibody (a-PD-1) treatment. We collected paired pre- and posttreatment specimens from a clinical trial evaluating combination treatment with GVAX vaccine, a-PD-1, and stereotactic body radiation (SBRT) following chemotherapy for locally advanced PDACs (LAPC). With resected PDACs following different neoadjuvant therapies as comparisons, effector cells in PDACs were found to skew toward a more exhausted status in LAPCs following chemotherapy. The combination of GVAX/a-PD-1/SBRT drives TME to favor antitumor immune response including increased densities of GZMB+CD8+ T cells, TH1, and TH17, which are associated with longer survival, however increases immunosuppressive M2-like tumor-associated macrophages (TAMs). Adding SBRT to GVAX/a-PD-1 shortens the distances from PD-1+CD8+ T cells to tumor cells and to PD-L1+ myeloid cells, which portends prolonged survival. These findings have guided the design of next radioimmunotherapy studies by targeting M2-like TAM in PDACs.
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Terapia Neoadjuvante , Neoplasias Pancreáticas , Humanos , Linfócitos T CD8-Positivos/patologia , Radioimunoterapia , Receptor de Morte Celular Programada 1 , Neoplasias Pancreáticas/terapia , Neoplasias Pancreáticas/patologia , Microambiente TumoralRESUMO
Pancreatic cancer is more prevalent in older individuals and often carries a poorer prognosis for them. The relationship between the microenvironment and pancreatic cancer is multifactorial, and age-related changes in nonmalignant cells in the tumor microenvironment may play a key role in promoting cancer aggressiveness. Because fibroblasts have profound impacts on pancreatic cancer progression, we investigated whether age-related changes in pancreatic fibroblasts influence cancer growth and metastasis. Proteomics analysis revealed that aged fibroblasts secrete different factors than young fibroblasts, including increased growth/differentiation factor 15 (GDF-15). Treating young mice with GDF-15 enhanced tumor growth, whereas aged GDF-15 knockout mice showed reduced tumor growth. GDF-15 activated AKT, rendering tumors sensitive to AKT inhibition in an aged but not young microenvironment. These data provide evidence for how aging alters pancreatic fibroblasts and promotes tumor progression, providing potential therapeutic targets and avenues for studying pancreatic cancer while accounting for the effects of aging. SIGNIFICANCE: Aged pancreatic fibroblasts secrete GDF-15 and activate AKT signaling to promote pancreatic cancer growth, highlighting the critical role of aging-mediated changes in the pancreatic cancer microenvironment in driving tumor progression. See related commentary by Isaacson et al., p. 1185.
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Fibroblastos Associados a Câncer , Neoplasias Pancreáticas , Animais , Camundongos , Fator 15 de Diferenciação de Crescimento/genética , Fator 15 de Diferenciação de Crescimento/uso terapêutico , Proteínas Proto-Oncogênicas c-akt , Neoplasias Pancreáticas/patologia , Pâncreas/patologia , Fibroblastos/patologia , Microambiente Tumoral , Linhagem Celular Tumoral , Fibroblastos Associados a Câncer/patologiaRESUMO
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
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
Axon guidance molecules were found to be the gene family most frequently altered in pancreatic ductal adenocarcinoma (PDA) through mutations and copy number changes. However, the exact molecular mechanism regarding PDA development remained unclear. Using genetically engineered mouse models to examine one of the axon guidance molecules, semaphorin 3D (SEMA3D), we found a dual role for tumor-derived SEMA3D in malignant transformation of pancreatic epithelial cells and a role for nerve-derived SEMA3D in PDA development. This was demonstrated by the pancreatic-specific knockout of the SEMA3D gene from the KRAS G12D and TP53 R 172 H mutation knock-in, PDX1-Cre (KPC) mouse model which demonstrated a delayed tumor initiation and growth comparing to the original KPC mouse model. Our results showed that SEMA3D knockout skews the macrophages in the pancreas away from M2 polarization, providing a potential mechanistic role of tumor-derived SEMA3D in PDA development. The KPC mice with the SEMA3D knockout remained metastasis-free, however, died from primary tumor growth. We then tested the hypothesis that a potential compensation mechanism could result from SEMA3D which is naturally expressed by the intratumoral nerves. Our study further revealed that nerve-derived SEMA3D does not reprogram macrophages directly, but reprograms macrophages indirectly through ARF6 signaling and lactate production in PDA tumor cells. SEMA3D increases tumor-secreted lactate which is sensed by GPCR132 on macrophages and subsequently stimulates pro-tumorigenic M2 polarization in vivo. Tumor intrinsic- and extrinsic-SEMA3D induced ARF6 signaling through its receptor Plexin D1 in a mutant KRAS-dependent manner. Consistently, RNA sequencing database analysis revealed an association of higher KRAS MUT expression with an increase in SEMA3D and ARF6 expression in human PDAs. Moreover, multiplex immunohistochemistry analysis showed an increased number of M2-polarized macrophages proximal to nerves in human PDA tissue expressing SEMA3D. Thus, this study suggests altered expression of SEMA3D in tumor cells lead to acquisition of cancer-promoting functions and the axon guidance signaling originating from nerves is "hijacked" by tumor cells to support their growth. Other axon guidance and neuronal development molecules may play a similar dual role which is worth further investigation. One sentence summary: Tumor- and nerve-derived SEMA3D promotes tumor progression and metastasis through macrophage reprogramming in the tumor microenvironment. STATEMENT OF SIGNIFICANCE: This study established the dual role of axon guidance molecule, SEMA3D, in the malignant transformation of pancreatic epithelial cells and of nerve-derived SEMA3D in PDA progression and metastasis. It revealed macrophage reprogramming as the mechanism underlying bothroles. Together, this research elucidated how inflammatory responses promote invasive PDA progression and metastasis through an oncogenic process.
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Non-negative matrix factorization (NMF) is an unsupervised learning method well suited to high-throughput biology. However, inferring biological processes from an NMF result still requires additional post hoc statistics and annotation for interpretation of learned features. Here, we introduce a suite of computational tools that implement NMF and provide methods for accurate and clear biological interpretation and analysis. A generalized discussion of NMF covering its benefits, limitations and open questions is followed by four procedures for the Bayesian NMF algorithm Coordinated Gene Activity across Pattern Subsets (CoGAPS). Each procedure will demonstrate NMF analysis to quantify cell state transitions in a public domain single-cell RNA-sequencing dataset. The first demonstrates PyCoGAPS, our new Python implementation that enhances runtime for large datasets, and the second allows its deployment in Docker. The third procedure steps through the same single-cell NMF analysis using our R CoGAPS interface. The fourth introduces a beginner-friendly CoGAPS platform using GenePattern Notebook, aimed at users with a working conceptual knowledge of data analysis but without a basic proficiency in the R or Python programming language. We also constructed a user-facing website to serve as a central repository for information and instructional materials about CoGAPS and its application programming interfaces. The expected timing to setup the packages and conduct a test run is around 15 min, and an additional 30 min to conduct analyses on a precomputed result. The expected runtime on the user's desired dataset can vary from hours to days depending on factors such as dataset size or input parameters.
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Algoritmos , Linguagens de Programação , Teorema de Bayes , Análise de Célula ÚnicaRESUMO
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.