Demo Faculty

Background and aimsEpstein–Barr virus (EBV) is associated with solid and hematopoietic malignancies. After allogeneic stem cell transplantation, EBV infection or reactivation represents a potentially life-threatening condition with no specific treatment available in clinical routine. In vitro expansion of naturally occurring EBV-specific T cells for adoptive transfer is time-consuming and influenced by the donor's T-cell receptor (TCR) repertoire and requires a specific memory compartment that is non-existent in seronegative individuals.The authors present highly efficient identification of EBV-specific TCRs that can be expressed on human T cells and recognize EBV-infected cells.Methods and ResultsMononuclear cells from six stem cell grafts were expanded in vitro with three HLA-B*35:01- or four HLA-A*02:01-presented peptides derived from six EBV proteins expressed during latent and lytic infection. Epitope-specific …

Giant congenital melanocytic nevi are NRAS-driven proliferations that may cover up to 80% of the body surface. Their most dangerous consequence is progression to melanoma. This risk often triggers preemptive extensive surgical excisions in childhood, producing severe lifelong challenges. We have presented preclinical models, including multiple genetically engineered mice and xenografted human lesions, which enabled testing locally applied pharmacologic agents to avoid surgery. The murine models permitted the identification of proliferative versus senescent nevus phases and treatments targeting both. These nevi recapitulated the histologic and molecular features of human giant congenital nevi, including the risk of melanoma transformation. Cutaneously delivered MEK, PI3K, and c-KIT inhibitors or proinflammatory squaric acid dibutylester (SADBE) achieved major regressions. SADBE triggered innate …

Purpose Cancer-associated fibroblasts (CAF) have been implicated as potential mediators of checkpoint immunotherapy response. However, the extensive heterogeneity of these cells has precluded rigorous understanding of their immunoregulatory role in the tumor microenvironment. Experimental Design We performed high-dimensional single-cell RNA sequencing (scRNA-seq) on four patient tumors pretreatment and posttreatment from a neoadjuvant trial of patients with advanced-stage head and neck squamous cell carcinoma that were treated with the αPD-1 therapy, nivolumab. The head and neck CAF (HNCAF) protein activity profiles, derived from this cohort of paired scRNA-seq, were used to perform protein activity enrichment analysis on the 28-patient parental cohort of clinically annotated bulk transcriptomic profiles. Ex vivo coculture assays were used to test …

Acute myeloid leukemia (AML) remains difficult to treat and requires new therapeutic approaches. Potent inhibitors of the chromatin-associated protein MENIN have recently entered human clinical trials, opening new therapeutic opportunities for some genetic subtypes of this disease. Using genome-scale functional genetic screens, we identified IKAROS (encoded by IKZF1) as an essential transcription factor in KMT2A (MLL1)-rearranged (MLL-r) AML that maintains leukemogenic gene expression while also repressing pathways for tumor suppression, immune regulation and cellular differentiation. Furthermore, IKAROS displays an unexpected functional cooperativity and extensive chromatin co-occupancy with mixed lineage leukemia (MLL)1–MENIN and the regulator MEIS1 and an extensive hematopoietic transcriptional complex involving homeobox (HOX)A10, MEIS1 and IKAROS. This dependency could be …

Giant congenital melanocytic nevi are NRAS-driven proliferations that may cover up to 80% of the body surface. Their most dangerous consequence is progression to melanoma. This risk often triggers preemptive extensive surgical excisions in childhood, producing severe lifelong challenges. We have presented preclinical models, including multiple genetically engineered mice and xenografted human lesions, which enabled testing locally applied pharmacologic agents to avoid surgery. The murine models permitted the identification of proliferative versus senescent nevus phases and treatments targeting both. These nevi recapitulated the histologic and molecular features of human giant congenital nevi, including the risk of melanoma transformation. Cutaneously delivered MEK, PI3K, and c-KIT inhibitors or proinflammatory squaric acid dibutylester (SADBE) achieved major regressions. SADBE triggered innate …

PurposeAlthough local tissue-based immune responses are critical for elucidating direct tumor-immune cell interactions, peripheral immune responses are increasingly recognized as occupying an important role in anti-cancer immunity. We evaluated serial blood samples from patients with epithelial ovarian cancer (EOC) undergoing standard-of-care neoadjuvant carboplatin and paclitaxel chemotherapy (including dexamethasone for prophylaxis of paclitaxel-associated hypersensitivity reactions) to characterize the evolution of the peripheral immune cell function and composition during therapy.

PurposeAlthough local tissue-based immune responses are critical for elucidating direct tumor-immune cell interactions, peripheral immune responses are increasingly recognized as occupying an important role in anti-cancer immunity. We evaluated serial blood samples from patients with epithelial ovarian cancer (EOC) undergoing standard-of-care neoadjuvant carboplatin and paclitaxel chemotherapy (including dexamethasone for prophylaxis of paclitaxel-associated hypersensitivity reactions) to characterize the evolution of the peripheral immune cell function and composition during therapy.

PurposeAlthough local tissue-based immune responses are critical for elucidating direct tumor-immune cell interactions, peripheral immune responses are increasingly recognized as occupying an important role in anti-cancer immunity. We evaluated serial blood samples from patients with epithelial ovarian cancer (EOC) undergoing standard-of-care neoadjuvant carboplatin and paclitaxel chemotherapy (including dexamethasone for prophylaxis of paclitaxel-associated hypersensitivity reactions) to characterize the evolution of the peripheral immune cell function and composition during therapy.

In this issue of Immunity, Meylan et al. (2022) uses spatial transcriptomics to examine B cell immunity within intratumoral tertiary lymphoid structures (TLSs). They find that B cells expand and mature into plasma cells (PCs) within the TLS, migrate along fibroblastic tracks to tumor beds, and produce IgG antibodies that target cancer cells.

Syngeneic mouse models are tumors derived from murine cancer cells engrafted on genetically identical mouse strains. They are widely used tools for studying tumor immunity and immunotherapy response in the context of a fully functional murine immune system. Large volumes of syngeneic mouse tumor expression profiles under different immunotherapy treatments have been generated, although a lack of systematic collection and analysis makes data reuse challenging. We present Tumor Immune Syngeneic MOuse (TISMO), a database with an extensive collection of syngeneic mouse model profiles with interactive visualization features. TISMO contains 605 in vitro RNA-seq samples from 49 syngeneic cancer cell lines across 23 cancer types, of which 195 underwent cytokine treatment. TISMO also includes 1518 in vivo RNA-seq samples from 68 syngeneic mouse tumor models across 19 cancer types, of …

Recent advances in single-cell RNA sequencing have revealed heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can reveal common cell types and states in the tumor microenvironment (TME). We developed a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.

c-MYC (MYC) is a major driver of prostate cancer tumorigenesis and progression. Although MYC is overexpressed in both early and metastatic disease and associated with poor survival, its impact on prostate transcriptional reprogramming remains elusive. We demonstrate that MYC overexpression significantly diminishes the androgen receptor (AR) transcriptional program (the set of genes directly targeted by the AR protein) in luminal prostate cells without altering AR expression. Analyses of clinical specimens reveal that concurrent low AR and high MYC transcriptional programs accelerate prostate cancer progression toward a metastatic, castration-resistant disease. Data integration of single-cell transcriptomics together with ChIP-seq uncover an increase in RNA polymerase II (Pol II) promoter-proximal pausing at AR-dependent genes following MYC overexpression without an accompanying deactivation of AR …

BackgroundImmune checkpoint blockade (ICB) response in recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) is limited to 15%–20% of patients and underpinnings of resistance remain undefined.MethodsStarting with an anti-PD1 sensitive murine HNSCC cell line, we generated an isogenic anti-PD1 resistant model. Mass cytometry was used to delineate tumor microenvironments of both sensitive parental murine oral carcinoma (MOC1) and resistant MOC1esc1 tumors. To examine heterogeneity and clonal dynamics of tumor infiltrating lymphocytes (TILs), we applied paired single-cell RNA and TCR sequencing in three HNSCC models.ResultsAnti-PD1 resistant MOC1esc1 line displayed a conserved cell intrinsic immune evasion signature. Immunoprofiling showed distinct baseline tumor microenvironments of MOC1 and MOC1esc1, as well as the remodeling of immune compartments on …

Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell’s endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by TPD approaches, termed “degradability”, is largely unknown. Here, we developed a machine learning model, model-free analysis of protein degradability (MAPD), to predict degradability from features intrinsic to protein targets. MAPD shows accurate performance in predicting kinases that are degradable by TPD compounds [with an area under precision recall curve (AUPRC) of 0.759 and area under the receiver operating characteristic curve (AUROC) of 0.775] and is likely generalizable to independent non-kinase proteins. We found five features with statistical significance to achieve optimal prediction, with ubiquitination potential being the most predictive. By …

Background Immune checkpoint blockade (ICB) response in recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) is limited to 15%–20% of patients and underpinnings of resistance remain undefined.Methods Starting with an anti-PD1 sensitive murine HNSCC cell line, we generated an isogenic anti-PD1 resistant model. Mass cytometry was used to delineate tumor microenvironments of both sensitive parental murine oral carcinoma (MOC1) and resistant MOC1esc1 tumors. To examine heterogeneity and clonal dynamics of tumor infiltrating lymphocytes (TILs), we applied paired single-cell RNA and TCR sequencing in three HNSCC models.Results Anti-PD1 resistant MOC1esc1 line displayed a conserved cell intrinsic immune evasion signature. Immunoprofiling showed distinct baseline tumor microenvironments of MOC1 and MOC1esc1, as well as the remodeling of immune compartments on …

Drugs that block the activity of the methyltransferase EZH2 are in clinical development for the treatment of non-Hodgkin lymphomas harboring EZH2 gain-of-function mutations that enhance its polycomb repressive function. We have previously reported that EZH2 can act as a transcriptional activator in castration-resistant prostate cancer (CRPC). Now we show that EZH2 inhibitors can also block the transactivation activity of EZH2 and inhibit the growth of CRPC cells. Gene expression and epigenomics profiling of cells treated with EZH2 inhibitors demonstrated that in addition to derepressing gene expression, these compounds also robustly down-regulate a set of DNA damage repair (DDR) genes, especially those involved in the base excision repair (BER) pathway. Methylation of the pioneer factor FOXA1 by EZH2 contributes to the activation of these genes, and interaction with the transcriptional coactivator P300 …

Purpose: Predictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. Methods: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. Results: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. Conclusion: This DREAM …

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences to serve as personal natural barcodes and review technical implementations in single-cell analysis workflows. Applications of these methodologies include the study of acquired therapeutic resistance and the dissection of donor- and host cellular interactions in the context of allogeneic hematopoietic stem cell transplantation.

Purpose: Predictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. Methods: Participants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. Results: A total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The best-performing models showed improved predictive power over reference variables, including TMB or PD-L1. Conclusion: This DREAM …

Recent advances in single-cell RNA sequencing have revealed heterogeneous cell types and gene expression states in the non-cancerous cells in tumors. The integration of multiple scRNA-seq datasets across tumors can reveal common cell types and states in the tumor microenvironment (TME). We developed a data driven framework, MetaTiME, to overcome the limitations in resolution and consistency that result from manual labelling using known gene markers. Using millions of TME single cells, MetaTiME learns meta-components that encode independent components of gene expression observed across cancer types. The meta-components are biologically interpretable as cell types, cell states, and signaling activities. By projecting onto the MetaTiME space, we provide a tool to annotate cell states and signature continuums for TME scRNA-seq data. Leveraging epigenetics data, MetaTiME reveals critical transcriptional regulators for the cell states. Overall, MetaTiME learns data-driven meta-components that depict cellular states and gene regulators for tumor immunity and cancer immunotherapy.

Blood malignancies provide unique opportunities for longitudinal tracking of disease evolution following therapeutic bottlenecks and for the monitoring of changes in anti-tumor immunity. The expanding development of multi-modal single-cell sequencing technologies affords newer platforms to elucidate the mechanisms underlying these processes at unprecedented resolution. Furthermore, the identification of molecular events that can serve as in-vivo barcodes now facilitate the tracking of the trajectories of malignant and of immune cell populations over time within primary human samples, as these permit unambiguous identification of the clonal lineage of cell populations within heterogeneous phenotypes. Here, we provide an overview of the potential for chromosomal copy number changes, somatic nuclear and mitochondrial DNA mutations, single nucleotide polymorphisms, and T and B cell receptor sequences …