Publications
Background: Schwannomas are nerve sheath tumors arising at cranial and peripheral nerves, either sporadically or in patients with a schwannomatosis-predisposition syndrome. There is limited understanding of the transcriptional heterogeneity of schwannomas across genetic backgrounds and anatomic locations. Methods: Here, we prospectively profile by single-cell full-length transcriptomics tumors from 22 patients with NF2-related schwannomatosis, non-NF2-related schwannomatosis, and sporadic schwannomas, resected from cranial and peripheral nerves. We profiled 11,373 cells (after QC), including neoplastic cells, fibroblasts, T cells, endothelial cells, myeloid cells, and pericytes. Results: We characterize the intra-tumoral genetic and transcriptional heterogeneity of schwannoma, identifying six distinct transcriptional metaprograms, with gene signatures related to stress, myelin production, antigen presentation, interferon signaling, glycolysis, and extracellular matrix. We demonstrate the robustness of our findings with analysis of an independent cohort. Conclusions: Overall, our atlas describes the spectrum of gene expression across schwannoma entities at the single-cell level and will serve as an important resource for the community.
Human papillomavirus (HPV)-related multiphenotypic sinonasal carcinoma (HMSC) is a rare tumor that morphologically resembles high-grade adenoid cystic carcinoma (ACC) but exhibits indolent clinical behavior. Both demonstrate MYB proto-oncogene upregulation, though HMSC lacks the MYB translocation characteristic of ACC. We performed single-cell RNA sequencing on an HMSC tumor and compared expression patterns with published ACC and oropharyngeal squamous cell carcinoma (OPSCC) datasets. Malignant HMSC cells clustered separately from ACC and lacked bicellular luminal and myoepithelial differentiation. A greater proportion of HMSC cells expressing HPV-related genes (HPVon) expressed MYB (83% vs. 62%, p = 0.022) and MYB targets (p = 6.4 × 10−6), supporting an HPV-MYB association. Validation in HPV + OPSCC revealed MYB upregulation in HPVon cells from 7/10 tumors (p
Despite decades of concerted research and clinical efforts, patient outcomes in glioblastoma (GBM) remain dismal. While chimeric antigen receptor (CAR)- T cell therapies in GBM have produced individual reports of efficacy, they have yet to meaningfully alter standard of care. Tumor heterogeneity, both inter- and intra-patient, likely contributes to these variable responses. Single-cell RNA sequencing (scRNA-seq) conducted in our lab has revealed that this transcriptional heterogeneity is organized along distinct cellular state axes. We sought to overcome this heterogeneity by designing CAR-T cells directed against these cellular states. We hypothesize that CAR-T cells targeting a defined GBM cell state will lead to a depletion of those populations. We report the development of a panel of cell state-targeting CAR-T cell candidates engineered for target-specific activity in vitro. To model the three-dimensional tumor environment, we developed patient-derived GBM organoids that recapitulate the cell state landscape seen in primary tumors. We treated GBM organoids with these cell state-targeting CAR-T cells and assessed cell states by scRNA seq. Unexpectedly, we observed convergent transcriptome shifts to a new cell state with overlapping features of mesenchymal (MES) and interferon-induced signatures. To target this dynamic, we designed a novel CAR-T cell directed against this population and observed feedforward target enrichment in response to therapy. We anticipate that our findings will inform rational design of translational CAR-T cell candidates for GBM patients.
Isocitrate dehydrogenase (IDH) gene mutations occur early among the genetic alterations that lead to the formation of lower-grade adult-type diffuse gliomas. Mutant IDH enzymes synthesize the oncometabolite (R)-2-hydroxyglutarate (2HG), which inhibits α-ketoglutarate-dependent dioxygenases, including those involved in DNA and histonedemethylation. Although this epigenetic dysregulation is thought to play a central role in gliomagenesis, the precise mechanisms linking mutant IDH to glioma initiation remain incompletely understood. To address this, we developed a genetically engineered mouse model of astrocytoma driven by the IDH1-R132H oncogene and performed time-resolved single-cell RNA and ATAC sequencing to capture the molecular and cellular dynamics of early glioma development. We found that mutant IDH activates neural progenitor cells (NPCs) and shifts their lineage priming toward a glial, as opposed to a neuronal, fate. Together, these effects caused expansion of oligodendrocyte precursor cells (OPCs) and depletion of interneurons and neuroblasts. Importantly, we observed that the malignant clone that drives glioma initiation preferentially arises among OPCs, but not neuronal cells. Our findings provide direct evidence that OPCs are the dominant cell type of origin for IDH-mutant gliomas, corroborating prior evidence for this idea based on comparative gene expression profiling and other approaches. Mechanistically, NPC fate reprogramming was associated with promoter hypermethylation and transcriptional silencing of Gsx2, a homeobox transcription factor essential for interneuron specification. Ablating Gsx2 in IDH-wildtype NPCs recapitulated mutant IDH-induced lineage switching and OPC expansion, indicating that Gsx2 repression is a key consequence of mutant IDH activity during glioma initiation. Our findings define a developmental and epigenetic mechanism through which IDH mutations rewire NPC fate to favor glioma-permissive lineages. By linking metabolic signaling to chromatin remodeling and altered cell fate specification, our study provides insight into how IDH mutations exploit neurodevelopmental programs to promote gliomagenesis.
The diffusely infiltrative growth pattern of glioblastoma (GBM) is a major obstacle to effective therapy. A complex network of tumor intrinsic and microenvironmental features interact to shape the landscape of this growth pattern, but deciphering the molecular substrates of these interactions remains challenging. While single cell RNA sequencing has reshaped our understanding of GBM heterogeneity and uncovered cellular phenotypes of many cellular populations in these tumors, the spatial context of this heterogeneity could not be assessed with earlier technologies. By contrast, spatial transcriptomics platforms have the potential to map this transcriptome-wide information in situ. We recently reported the use of this technology to develop a layered model of spatial architecture in GBM and showed that hypoxia represents a key organizing feature of GBM heterogeneity. However, the limited resolution of this platform precluded assessment of whole-transcriptome features at truly cellular resolution. In this work, we now present our findings utilizing the next generation of this technology and showcase the ability to map whole transcriptome data in spatial context at true single cell resolution in primary patient GBM samples. We explore heterogeneous GBM phenotypes in the context of GBM spatial microarchitecture. Using copy number inference, we demonstrate the ability to assess clonal heterogeneity in situ and map the pattern of invasion of unique GBM clones. Finally, we discuss our progress to discover organizing principles underlying distinct patterns of GBM cell invasion. Taken together, we demonstrate the potential of single cell spatial transcriptomics to decipher the molecular heterogeneity of GBM microenvironment in situ and uncover the biology driving the aggressive infiltrative growth of this disease.
Isocitrate dehydrogenase (IDH)-mutant glioma is the most common primary brain tumor diagnosed in patients younger than 50 years old. While IDH inhibitors have shown promise for patients with low-grade disease, patients with higher-grade tumors still have limited treatment options and face poor clinical outcomes. Chimeric antigen receptor (CAR)-T cell therapies have demonstrated potential in other molecularly-distinct gliomas, but directing this immunotherapeutic strategy towards IDH-mutant glioma remains largely unexplored. Our prior work using single-cell RNA sequencing (scRNAseq) has defined a hierarchical model of transcriptional states in IDH-mutant glioma, including a central stem-like population that is enriched for cycling cells and drives overall disease progression. We hypothesize that targeting this stem-like population in IDH-mutant glioma using CAR-T cell therapy will enable effective control of these tumors. To design CAR constructs that target this population, we performed in silico screening of scRNAseq data from IDH-mutant glioma patient samples to identify highly expressed genes associated with the stem-like surfaceome. Candidate targets with publicly available single-chain variable fragments (scFvs) were engineered into tool 2nd generation CARs and screened for antitumor activity against patient-derived IDH-mutant glioma models. Coculture assays demonstrated in vitro cytokine production and antitumor cytotoxicity against these patient-derived models. Additionally, we demonstrate the ability of these CAR-T cells to clear an aggressive patient-derived orthotopic IDH-mutant glioma xenograft model and significantly extend survival. In summary, our findings validate the potential of a cell state-directed strategy to identify CAR-T cell targets in IDH-mutant gliomas that may inform future translational efforts.
Neuroendocrine tumors (NETs) occur primarily in the small intestine, lung, and pancreas. Due to their rarity compared to other malignancies in these organs, their complex biology remains poorly understood, including their oncogenesis, tumor composition, and the intriguing phenomena of mixed neuroendocrine non-neuroendocrine neoplasms (MiNEN). Here, we profiled ten low-grade small intestine NET (SiNET) samples as well as one mixed lung tumor by single-cell or single-nuclei RNA-seq. We find that SiNETs are largely separated into two distinct subtypes, in which the neuroendocrine cells upregulate epithelial or neuronal markers, respectively. Surprisingly, in both subtypes, the neuroendocrine cells are largely non-proliferative while higher proliferation is observed in multiple non-malignant cell types. Specifically, B and plasma cells are highly proliferative in the epithelial-like SiNET subtype, potentially reflecting the outcome of high Migration Inhibitory Factor (MIF) expression in those tumors, which may constitute a relevant target. Finally, our analysis of a mixed lung neuroendocrine tumor identifies a population of putative progenitor cells that may give rise to both neuroendocrine and non-neuroendocrine (squamous) cells, potentially explaining the origin of the mixed histology. Taken together, our results provide important insights and hypotheses regarding the biology of neuroendocrine neoplasms.
Immuno-oncology is increasingly becoming the standard of care for cancers, with the identification of biomarkers that reliably classify immune checkpoint inhibitor response, resistance, and toxicity becoming the next frontier toward improvements in immunomodulatory treatment regimens. Recent advances in multiparametric, multiomics, and computational data platforms generating an unprecedented depth of data may assist in the discovery of increasingly robust biomarkers for enhanced patient selection and more personalized or longitudinal treatment approaches. Which emerging technologies to implement in future research and clinical settings, used alone or in combination, relies on weighing the pros and cons that aid in maximizing data outputs while minimizing patient sampling, with high reproducibility and representativeness, and minimal turnaround time and data fragmentation toward later private and public dataset harmonization strategies. The Society for Immunotherapy of Cancer Biomarkers Committee convened to identify important advances in biomarker technologies and highlight advances in biomarker discovery using liquid biopsy and in vivo imaging technologies. We address advances in liquid biopsy technologies monitoring cells, proteins, nucleic acids, antibodies, and drugs or analytes and radiomics technologies monitoring whole hostlevel imaging methods, including immuno-PET and MRI technologies, which are able to couple biomarkers with physical location. We include a summary of key metrics obtained by these technologies and their ease of interpretation, limitations and dependencies, technical improvements, and outward comparisons. By highlighting some of the most interesting recent examples contributed by these technologies and providing examples of improved outputs, we hope to guide correlative research directions and assist in their becoming clinically useful in immuno-oncology.
We built a repository of 124 tumor single-cell RNA-sequencing datasets and used it to systematically characterize the expression heterogeneity within tumors. These data and analyses together constitute the Curated Cancer Cell Atlas and are freely available for exploration and download via an enhanced online portal.
The evolution of isocitrate dehydrogenase (IDH)-wildtype glioblastoma (GBM) after standard-of-care therapy remains poorly understood. Here we analyzed matched primary and recurrent GBMs from 59 patients using single-nucleus RNA sequencing and bulk DNA sequencing, assessing the longitudinal evolution of the GBM ecosystem across layers of cellular and molecular heterogeneity. The most consistent change was a lower malignant cell fraction at recurrence and a reciprocal increase in glial and neuronal cell types in the tumor microenvironment (TME). The predominant malignant cell state differed between most matched pairs, but no states were exclusive or highly enriched in either time point, nor was there a consistent longitudinal trajectory across the cohort. Nevertheless, specific trajectories were enriched in subsets of patients. Changes in malignant state abundances mirrored changes in TME composition and baseline profiles, reflecting the co-evolution of the GBM ecosystem. Our study provides a blueprint of GBMs diverse longitudinal trajectories and highlights the treatment and TME modifiers that shape them.
In isocitrate dehydrogenase wildtype glioblastoma (GBM), cellular heterogeneity across and within tumors may drive therapeutic resistance. Here we analyzed 121 primary and recurrent GBM samples from 59 patients using single-nucleus RNA sequencing and bulk tumor DNA sequencing to characterize GBM transcriptional heterogeneity. First, GBMs can be classified by their broad cellular composition, encompassing malignant and nonmalignant cell types. Second, in each cell type we describe the diversity of cellular states and their pathway activation, particularly an expanded set of malignant cell states, including glial progenitor cell-like, neuronal-like and cilia-like. Third, the remaining variation between GBMs highlights three baseline gene expression programs. These three layers of heterogeneity are interrelated and partially associated with specific genetic aberrations, thereby defining three stereotypic GBM ecosystems. This work provides an unparalleled view of the multilayered transcriptional architecture of GBM. How this architecture evolves during disease progression is addressed in the companion manuscript by Spitzer et al.
(Cancer Cell 39, 779792.e1e11; June 14, 2021) We, the authors of the paper, reported that macrophages and microglia induce the transition of glioblastoma cells into a mesenchymal-like cellular state through oncostatin M signaling. Upon review of the published article, we noticed that the same heatmap of gene expression was inadvertently used for both macrophages and microglia in the top panels of Figure S5C. This error occurred during figure preparation and does not affect the conclusions of the paper. We have now provided the corrected Figure S5 and apologize for any confusion this error may have caused.[Figure
Recent years have seen a rapid proliferation of single-cell cancer studies, yet most of these studies profiled few tumors, limiting their statistical power. Combining data and results across studies holds great promise but also involves various challenges. We recently began to address these challenges by curating a large collection of cancer single-cell RNA-sequencing datasets, leveraging it for systematic analyses of tumor heterogeneity. Here we greatly extend this repository to 124 datasets for over 40 cancer types, together comprising 2,836 samples, with improved data annotations, visualizations and exploration. Using this vast cohort, we generate an updated map of recurrent expression programs in malignant cells and systematically quantify context-dependent gene expression and cell-cycle patterns across cell types and cancer types. These data, annotations and analysis results are all freely available for exploration and download through the Curated Cancer Cell Atlas, a central community resource that opens new avenues in cancer research.
With immuno-oncology becoming the standard of care for a variety of cancers, identifying biomarkers that reliably classify patient response, resistance, or toxicity becomes the next critical barrier toward improving care. Multiparametric, multi-omics, and computational platforms generating an unprecedented depth of data are poised to usher in the discovery of increasingly robust biomarkers for enhanced patient selection and personalized treatment approaches. Deciding which developing technologies to implement in clinical settings ultimately, applied either alone or in combination, relies on weighing pros and cons, from minimizing patient sampling to maximizing data outputs, and assessing the reproducibility and representativeness of findings, while lessening data fragmentation toward harmonization. These factors are all assessed while taking into consideration the shortest turnaround time. The Society for Immunotherapy of Cancer Biomarkers Committee convened to identify important advances in biomarker technologies and to address advances in biomarker discovery using multiplexed IHC and immunofluorescence, their coupling to single-cell transcriptomics, along with mass spectrometrybased quantitative and spatially resolved proteomics imaging technologies. We summarize key metrics obtained, ease of interpretation, limitations and dependencies, technical improvements, and outward comparisons of these technologies. By highlighting the most interesting recent data contributed by these technologies and by providing ways to improve their outputs, we hope to guide correlative research directions and assist in their evolution toward becoming clinically useful in immuno-oncology.
Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of complex tissues both in health and in disease. Over the past decade, scRNA-seq has been applied to tumour samples obtained from patients with cancer in hundreds of studies, thereby advancing the view that each tumour is a complex ecosystem and uncovering the diverse states of both cancer cells and the tumour microenvironment. Such studies have primarily investigated and provided insights into the basic biology of cancer, although considerable research interest exists in leveraging these findings towards clinical applications. In this Review, we summarize the available data from scRNA-seq studies investigating samples from patients with cancer with a particular focus on findings that are of potential clinical relevance. We highlight four main research objectives of scRNA-seq studies and describe some of the most relevant findings towards such goals. We also describe the limitations of scRNA-seq, as well as future approaches in this field that are anticipated to further advance clinical applicability.
Glioblastoma (GBM) is characterized by heterogeneous malignant cells that are functionally integrated within the neuroglial microenvironment. In this study, we model this ecosystem by growing GBM into long-term cultured human cortical organoids that contain the major neuroglial cell types found in the cerebral cortex. Single-cell RNA sequencing analysis suggests that, compared with matched gliomasphere models, GBM cortical organoids more faithfully recapitulate the diversity and expression programs of malignant cell states found in patient tumors. Additionally, we observe widespread transfer of GBM transcripts and GFP to nonmalignant cells in the organoids. Mechanistically, this transfer involves extracellular vesicles and is biased toward defined GBM cell states and astroglia cell types. These results extend previous GBM organoid modeling efforts and suggest widespread intercellular transfer in the GBM neuroglial microenvironment. Significance: Models that recapitulate intercellular communications in GBM are limited. In this study, we leverage GBM cortical organoids to characterize widespread mRNA and GFP transfer from malignant to nonmalignant cells in the GBM neuroglial microenvironment. This transfer involves extracellular vesicles, may contribute to reprogramming the microenvironment, and may extend to other cancer types. See related commentary by Shakya et al., p. 261.
Malignant gliomas are heterogeneous tumors, mostly incurable, arising in the central nervous system (CNS) driven by genetic, epigenetic, and metabolic aberrations. Mutations in isocitrate dehydrogenase (IDH1/2mut) enzymes are predominantly found in low-grade gliomas and secondary high-grade gliomas, with IDH1 mutations being more prevalent. Mutant-IDH1/2 confers a gain-of-function activity that favors the conversion of a-ketoglutarate (α-KG) to the oncometabolite 2-hydroxyglutarate (2-HG), resulting in an aberrant hypermethylation phenotype. Yet, the complete depiction of the epigenetic alterations in IDHmut cells has not been thoroughly explored. Here, we applied an unbiased approach, leveraging epigenetic-focused cytometry by time-of-flight (CyTOF) analysis, to systematically profile the effect of mutant-IDH1 expression on a broad panel of histone modifications at single-cell resolution. This analysis revealed extensive remodeling of chromatin patterns by mutant-IDH1, with the most prominent being deregulation of histone acetylation marks. The loss of histone acetylation occurs rapidly following mutant-IDH1 induction and affects acetylation patterns over enhancers and intergenic regions. Notably, the changes in acetylation are not predominantly driven by 2-HG, can be rescued by pharmacological inhibition of mutant-IDH1, and reversed by acetate supplementations. Furthermore, cells expressing mutant-IDH1 show higher epigenetic and transcriptional heterogeneity and upregulation of oncogenes such as KRAS and MYC, highlighting its tumorigenic potential. Our study underscores the tight interaction between chromatin and metabolism dysregulation in glioma and highlights epigenetic and oncogenic pathways affected by mutant-IDH1-driven metabolic rewiring.