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 (IDH1/2^mut) 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 IDH^mut 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.

Increasing evidence supports the interplay between oncogenic mutations and immune escape mechanisms. Strategies to counteract the immune escape mediated by oncogenic signaling could provide improved therapeutic options for patients with various malignancies. As mutant calreticulin (CALR) is a common driver of myeloproliferative neoplasms (MPN), we analyzed the impact of oncogenic CALR^del52 on the bone marrow (BM) microenvironment in MPN. Single-cell RNA sequencing revealed that CALR^del52 led to the expansion of TGFβ1-producing erythroid progenitor cells and promoted the expansion of FoxP3⁺ regulatory T cells (Treg) in a murine MPN model. Treatment with an anti-TGFβ antibody improved mouse survival and increased the glycolytic activity in CD4⁺ and CD8⁺ T cells in vivo, whereas T-cell depletion abrogated the protective effects conferred by neutralizing TGFβ. TGFβ1 reduced perforin and TNFα production by T cells in vitro. TGFβ1 production by CALR^del52 cells was dependent on JAK1/2, PI3K, and ERK activity, which activated the transcription factor Sp1 to induce TGFβ1 expression. In four independent patient cohorts, TGFβ1 expression was increased in the BM of patients with MPN compared with healthy individuals, and the BM of patients with MPN contained a higher frequency of Treg compared with healthy individuals. Together, this study identified an ERK/Sp1/TGFβ1 axis in CALR^del52 MPNs as a mechanism of immunosuppression that can be targeted to elicit T-cell-mediated cytotoxicity.

Human tumors are intricate ecosystems composed of diverse genetic clones and malignant cell states that evolve in a complex tumor micro-environment. Single-cell RNA-sequencing (scRNA-seq) provides a compelling strategy to dissect this intricate biology and has enabled a revolution in our ability to understand tumor biology over the last ten years. Here we reflect on this first decade of scRNA-seq in human tumors and highlight some of the powerful insights gleaned from these studies. We first focus on computational approaches for robustly defining cancer cell states and their diversity and highlight some of the most common patterns of gene expression intra-tumor heterogeneity (eITH) observed across cancer types. We then discuss ambiguities in the field in defining and naming such eITH programs. Finally, we highlight critical developments that will facilitate future research and the broader implementation of these technologies in clinical settings.

The mouse small intestine shows profound variability in gene expression along the cryptvillus axis^1,2. Whether similar spatial heterogeneity exists in the adult human gut remains unclear. Here we use spatial transcriptomics, spatial proteomics and single-molecule fluorescence in situ hybridization to reconstruct a comprehensive spatial expression atlas of the adult human proximal small intestine. We describe zonated expression and cell type representation for epithelial, mesenchymal and immune cell types. We find that migrating enterocytes switch from lipid droplet assembly and iron uptake at the villus bottom to chylomicron biosynthesis and iron release at the tip. Villus tip cells are pro-immunogenic, recruiting γδ T cells and macrophages to the tip, in contrast to their immunosuppressive roles in mouse. We also show that the human small intestine contains abundant serrated and branched villi that are enriched at the tops of circular folds. Our study presents a detailed resource for understanding the biology of the adult human small intestine.

A broad range of brain pathologies critically relies on the vasculature, and cerebrovascular disease is a leading cause of death worldwide. However, the cellular and molecular architecture of the human brain vasculature remains incompletely understood¹. Here we performed single-cell RNA sequencing analysis of 606,380 freshly isolated endothelial cells, perivascular cells and other tissue-derived cells from 117 samples, from 68 human fetuses and adult patients to construct a molecular atlas of the developing fetal, adult control and diseased human brain vasculature. We identify extensive molecular heterogeneity of the vasculature of healthy fetal and adult human brains and across five vascular-dependent central nervous system (CNS) pathologies, including brain tumours and brain vascular malformations. We identify alteration of arteriovenous differentiation and reactivated fetal as well as conserved dysregulated genes and pathways in the diseased vasculature. Pathological endothelial cells display a loss of CNS-specific properties and reveal an upregulation of MHC class II molecules, indicating atypical features of CNS endothelial cells. Cellcell interaction analyses predict substantial endothelial-to-perivascular cell ligandreceptor cross-talk, including immune-related and angiogenic pathways, thereby revealing a central role for the endothelium within brain neurovascular unit signalling networks. Our single-cell brain atlas provides insights into the molecular architecture and heterogeneity of the developing, adult/control and diseased human brain vasculature and serves as a powerful reference for future studies.

Background: Head and neck squamous cell carcinoma (HNSCC) is the 6^th leading cause of cancer-related mortality, with racial disparities amplifying the challenges in treatment. Although the relationship between hybrid epithelial/mesenchymal (E/M) states and tumor progression is of interest, no studies have characterized the clinical relevance of hybrid E/M states in head and neck cancer outcomes among self-reported racial cohorts. Methods: Given the overlap in gene expression between hybrid E/M malignant cells and cancer-associated fibroblasts, we utilized deconvolution of bulk RNA sequencing data from oral cavity and laryngeal squamous cell carcinoma tumors from The Cancer Genome Atlas. We utilized our previously collected single-cell profiles to generate inferred malignant profiles and then scored these for hybrid E/M. We then conducted a survival analysis on overall and disease-free survival among self-reported Black and White Americans. Findings: The hybrid E/M state was differentially associated with head and neck cancer survival by self-reported race and ethnicity, with a stronger association in non-Hispanic Black patients. Black patients with a high hybrid E/M score had a higher risk of death or recurrence (hazard ratio [HR]: 4.18 [95% confidence interval (CI): 2.06, 8.49]) than White patients with a high hybrid E/M score (HR: 1.58 [95% CI: 1.11, 2.26]). Conclusion: Our results suggest a complex interplay of social structure, racism, and genetic diversity. We implore researchers to consider the social and biological context contributing to disparities. Funding: A.L.M. received support from the National Institute of Minority Health and Health Disparities (K01MD013897 [principal investigator (PI), A.L.M.]). S.V.P. received support from the National Institute of Dental and Craniofacial Research (R01DE032865 [PI, S.V.P.] and R01DE032371 [PI, S.V.P.]).

Glioma contains malignant cells in diverse states. Here, we combine spatial transcriptomics, spatial proteomics, and computational approaches to define glioma cellular states and uncover their organization. We find three prominent modes of organization. First, gliomas are composed of small local environments, each typically enriched with one major cellular state. Second, specific pairs of states preferentially reside in proximity across multiple scales. This pairing of states is consistent across tumors. Third, these pairwise interactions collectively define a global architecture composed of five layers. Hypoxia appears to drive the layers, as it is associated with a long-range organization that includes all cancer cell states. Accordingly, tumor regions distant from any hypoxic/necrotic foci and tumors that lack hypoxia such as low-grade IDH-mutant glioma are less organized. In summary, we provide a conceptual framework for the organization of cellular states in glioma, highlighting hypoxia as a long-range tissue organizer.

A subset of patients with IDH-mutant glioma respond to inhibitors of mutant IDH (IDHi), yet the molecular underpinnings of such responses are not understood. Here, we profiled by single-cell or single-nucleus RNA-sequencing three IDH-mutant oligodendrogliomas from patients who derived clinical benefit from IDHi. Importantly, the tissues were sampled on-drug, four weeks from treatment initiation. We further integrate our findings with analysis of single-cell and bulk transcriptomes from independent cohorts and experimental models. We find that IDHi treatment induces a robust differentiation toward the astrocytic lineage, accompanied by a depletion of stem-like cells and a reduction of cell proliferation. Furthermore, mutations in NOTCH1 are associated with decreased astrocytic differentiation and may limit the response to IDHi. Our study highlights the differentiating potential of IDHi on the cellular hierarchies that drive oligodendrogliomas and suggests a genetic modifier that may improve patient stratification.

Immunotherapy failures can result from the highly suppressive tumour microenvironment that characterizes aggressive forms of cancer such as recurrent glioblastoma (rGBM) ^1,2. Here we report the results of a first-in-human phase I trial in 41 patients with rGBM who were injected with CAN-3110an oncolytic herpes virus (oHSV) ³. In contrast to other clinical oHSVs, CAN-3110 retains the viral neurovirulence ICP34.5 gene transcribed by a nestin promoter; nestin is overexpressed in GBM and other invasive tumours, but not in the adult brain or healthy differentiated tissue ⁴. These modifications confer CAN-3110 with preferential tumour replication. No dose-limiting toxicities were encountered. Positive HSV1 serology was significantly associated with both improved survival and clearance of CAN-3110 from injected tumours. Survival after treatment, particularly in individuals seropositive for HSV1, was significantly associated with (1) changes in tumour/PBMC T cell counts and clonal diversity, (2) peripheral expansion/contraction of specific T cell clonotypes; and (3) tumour transcriptomic signatures of immune activation. These results provide human validation that intralesional oHSV treatment enhances anticancer immune responses even in immunosuppressive tumour microenvironments, particularly in individuals with cognate serology to the injected virus. This provides a biological rationale for use of this oncolytic modality in cancers that are otherwise unresponsive to immunotherapy (ClinicalTrials.gov: NCT03152318 ).

The role of the nervous system in the regulation of cancer is increasingly appreciated. In gliomas, neuronal activity drives tumour progression through paracrine signalling factors such as neuroligin-3 and brain-derived neurotrophic factor¹³ (BDNF), and also through electrophysiologically functional neuron-to-glioma synapses mediated by AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptors^4,5. The consequent glioma cell membrane depolarization drives tumour proliferation^4,6. In the healthy brain, activity-regulated secretion of BDNF promotes adaptive plasticity of synaptic connectivity^7,8 and strength⁹¹⁵. Here we show that malignant synapses exhibit similar plasticity regulated by BDNF. Signalling through the receptor tropomyosin-related kinase B¹⁶ (TrkB) to CAMKII, BDNF promotes AMPA receptor trafficking to the glioma cell membrane, resulting in increased amplitude of glutamate-evoked currents in the malignant cells. Linking plasticity of glioma synaptic strength to tumour growth, graded optogenetic control of glioma membrane potential demonstrates that greater depolarizing current amplitude promotes increased glioma proliferation. This potentiation of malignant synaptic strength shares mechanistic features with synaptic plasticity¹⁷²² that contributes to memory and learning in the healthy brain²³²⁶. BDNFTrkB signalling also regulates the number of neuron-to-glioma synapses. Abrogation of activity-regulated BDNF secretion from the brain microenvironment or loss of glioma TrkB expression robustly inhibits tumour progression. Blocking TrkB genetically or pharmacologically abrogates these effects of BDNF on glioma synapses and substantially prolongs survival in xenograft models of paediatric glioblastoma and diffuse intrinsic pontine glioma. Together, these findings indicate that BDNFTrkB signalling promotes malignant synaptic plasticity and augments tumour progression.

Germline BRCAassociated pancreatic ductal adenocarcinoma (glBRCA PDAC) tumors are susceptible to platinum and PARP inhibition. The clinical outcomes of 125 patients with glBRCA PDAC were stratified based on the spectrum of response to platinum/PARP inhibition: (i) refractory [overall survival (OS) \lt;6 months], (ii) durable response followed by acquired resistance (OS \lt;36 months), and (iii) long-term responders (OS \gt;36 months). Patient-derived xenografts (PDX) were generated from 25 patients with glBRCA PDAC at different clinical time points. Response to platinum/PARP inhibition in vivo and ex vivo culture (EVOC) correlated with clinical response. We deciphered the mechanisms of resistance in glBRCA PDAC and identified homologous recombination (HR) proficiency and secondary mutations restoring partial functionality as the most dominant resistant mechanism. Yet, a subset of HR-deficient (HRD) patients demonstrated clinical resistance. Their tumors displayed basal-like molecular subtype and were more aneuploid. Tumor mutational burden was high in HRD PDAC and significantly higher in tumors with secondary mutations. AntiPD-1 attenuated tumor growth in a novel humanized glBRCA PDAC PDX model. This work demonstrates the utility of preclinical models, including EVOC, to predict the response of glBRCA PDAC to treatment, which has the potential to inform time-sensitive medical decisions.glBRCA PDAC has a favorable response to platinum/PARP inhibition. However, most patients develop resistance. Additional treatment options for this unique subpopulation are needed. We generated model systems in PDXs and an ex vivo system (EVOC) that faithfully recapitulate these specific clinical scenarios as a platform to investigate the mechanisms of resistance for further drug development.This article is highlighted in the In This Issue feature, p. 1749

Each tumour contains diverse cellular states that underlie intratumour heterogeneity (ITH), a central challenge of cancer therapeutics ¹. Dozens of recent studies have begun to describe ITH by single-cell RNA sequencing, but each study typically profiled only a small number of tumours and provided a narrow view of transcriptional ITH ². Here we curate, annotate and integrate the data from 77 different studies to reveal the patterns of transcriptional ITH across 1,163 tumour samples covering 24 tumour types. Among the malignant cells, we identify 41 consensus meta-programs, each consisting of dozens of genes that are coordinately upregulated in subpopulations of cells within many tumours. The meta-programs cover diverse cellular processes including both generic (for example, cell cycle and stress) and lineage-specific patterns that we map into 11 hallmarks of transcriptional ITH. Most meta-programs of carcinoma cells are similar to those identified in non-malignant epithelial cells, suggesting that a large fraction of malignant ITH programs are variable even before oncogenesis, reflecting the biology of their cell of origin. We further extended the meta-program analysis to six common non-malignant cell types and utilize these to map cellcell interactions within the tumour microenvironment. In summary, we have assembled a comprehensive pan-cancer single-cell RNA-sequencing dataset, which is available through the Curated Cancer Cell Atlas website, and leveraged this dataset to carry out a systematic characterization of transcriptional ITH.

Head and neck squamous cell carcinoma (HNSCC) includes a subset of cancers driven by human papillomavirus (HPV). Here we use single-cell RNA-seq to profile both HPV-positive and HPV-negative oropharyngeal tumors, uncovering a high level of cellular diversity within and between tumors. First, we detect diverse chromosomal aberrations within individual tumors, suggesting genomic instability and enabling the identification of malignant cells even at pathologically negative margins. Second, we uncover diversity with respect to HNSCC subtypes and other cellular states such as the cell cycle, senescence and epithelial-mesenchymal transitions. Third, we find heterogeneity in viral gene expression within HPV-positive tumors. HPV expression is lost or repressed in a subset of cells, which are associated with a decrease in HPV-associated cell cycle phenotypes, decreased response to treatment, increased invasion and poor prognosis. These findings suggest that HPV expression diversity must be considered during diagnosis and treatment of HPV-positive tumors, with important prognostic ramifications.

Background: Multiple glioblastoma studies have described a mesenchymal (MES) state, with each study defining the MES program by distinct sets of genes and highlighting distinct functional associations, including both immune activation and suppression. These variable descriptions complicate our understanding of the MES state and its implications. Here, we hypothesize that there is a range of glioma MES states, possibly reflecting distinct prior states in which a MES program can be induced, and/or distinct mechanisms that induce the MES states in those cells. Methods: We integrated multiple published single-cell and bulk RNA sequencing datasets and MES signatures to define a core MES program that recurs across studies, as well as multiple function-specific MES signatures that vary across MES cells. We then examined the co-occurrence of these signatures and their associations with genetic and microenvironmental features. Results: Based on co-occurrence of MES signatures, we found three main variants of MES states: hypoxia-related (MES-Hyp), astrocyte-related (MES-Ast), and an intermediate state. Notably, the MES states are differentially associated with genetic and microenvironmental features. MES-Hyp is preferentially associated with NF1 deletion, overall macrophage abundance, a high macrophage/microglia ratio, and M2-related macrophages, consistent with previous studies that associated MES with immune suppression. In contrast, MES-Ast is associated with T cell abundance and cytotoxicity, consistent with immune activation through expression of MHC-I/II. Conclusions: Diverse MES states occur in glioblastoma. These states share a subset of core genes but differ primarily in their association with hypoxia vs. astrocytic expression programs, and with immune suppression vs. activation, respectively.

There is a need for better classification and understanding of tumor-infiltrating lymphocytes (TILs). Here, we applied advanced functional genomics to interrogate 9,000 human tumors and multiple single-cell sequencing sets using benchmarked T cell states, comprehensive T cell differentiation trajectories, human and mouse vaccine responses, and other human TILs. Compared with other T cell states, enrichment of T memory/resident memory programs was observed across solid tumors. Trajectory analysis of single-cell melanoma CD8⁺ TILs also identified a high fraction of memory/resident memory-scoring TILs in anti-PD-1 responders, which expanded post therapy. In contrast, TILs scoring highly for early T cell activation, but not exhaustion, associated with non-response. Late/persistent, but not early activation signatures, prognosticate melanoma survival, and co-express with dendritic cell and IFN-γ response programs. These data identify an activation-like state associated to poor response and suggest successful memory conversion, above resuscitation of exhaustion, is an under-appreciated aspect of successful anti-tumoral immunity.

Epithelialmesenchymal transition (EMT) programs operate within carcinoma cells, where they generate phenotypes associated with malignant progression. In their various manifestations, EMT programs enable epithelial cells to enter into a series of intermediate states arrayed along the EM phenotypic spectrum. At present, we lack a coherent understanding of how carcinoma cells control their entrance into and continued residence in these various states, and which of these states favour the process of metastasis. Here we characterize a layer of EMT-regulating machinery that governs EM plasticity (EMP). This machinery consists of two chromatin-modifying complexes, PRC2 and KMT2D-COMPASS, which operate as critical regulators to maintain a stable epithelial state. Interestingly, loss of these two complexes unlocks two distinct EMT trajectories. Dysfunction of PRC2, but not KMT2D-COMPASS, yields a quasi-mesenchymal state that is associated with highly metastatic capabilities and poor survival of patients with breast cancer, suggesting that great caution should be applied when PRC2 inhibitors are evaluated clinically in certain patient cohorts. These observations identify epigenetic factors that regulate EMP, determine specific intermediate EMT states and, as a direct consequence, govern the metastatic ability of carcinoma cells.

Epithelial-to-mesenchymal transition (EMT) is the most commonly cited mechanism for cancer metastasis, but it is difficult to distinguish from profiles of normal stromal cells in the tumour microenvironment. In this study we use published single cell RNA-seq data to directly compare mesenchymal signatures from cancer and stromal cells. Informed by these comparisons, we developed a computational framework to decouple these two sources of mesenchymal expression profiles using bulk RNA-seq datasets. This deconvolution offers the opportunity to characterise EMT across hundreds of tumours and examine its association with metastasis and other clinical features. With this approach, we find three distinct patterns of EMT, associated with squamous, gynaecological and gastrointestinal cancer types. Surprisingly, in most cancer types, EMT patterns are not associated with increased chance of metastasis, suggesting that other steps in the metastatic cascade may represent the main bottleneck. This work provides a comprehensive evaluation of EMT profiles and their functional significance across hundreds of tumours while circumventing the confounding effect of stromal cells.

The mesenchymal subtype of glioblastoma is thought to be determined by both cancer cell-intrinsic alterations and extrinsic cellular interactions, but remains poorly understood. Here, we dissect glioblastoma-to-microenvironment interactions by single-cell RNA sequencing analysis of human tumors and model systems, combined with functional experiments. We demonstrate that macrophages induce a transition of glioblastoma cells into mesenchymal-like (MES-like) states. This effect is mediated, both in vitro and in vivo, by macrophage-derived oncostatin M (OSM) that interacts with its receptors (OSMR or LIFR) in complex with GP130 on glioblastoma cells and activates STAT3. We show that MES-like glioblastoma states are also associated with increased expression of a mesenchymal program in macrophages and with increased cytotoxicity of T cells, highlighting extensive alterations of the immune microenvironment with potential therapeutic implications.

Vascular anomalies, including local and peripheral thrombosis, are a hallmark of glioblastoma (GBM) and an aftermath of deregulation of the cancer cell genome and epigenome. Although the molecular effectors of these changes are poorly understood, the upregulation of podoplanin (PDPN) by cancer cells has recently been linked to an increased risk for venous thromboembolism (VTE) in GBM patients. Therefore, regulation of this platelet-activating protein by transforming events in cancer cells is of considerable interest. We used single-cell and bulk transcriptome data mining, as well as cellular and xenograft models in mice, to analyze the nature of cells expressing PDPN, as well as their impact on the activation of the coagulation system and platelets. We report that PDPN is expressed by distinct (mesenchymal) GBM cell subpopulations and downregulated by oncogenic mutations of EGFR and IDH1 genes, along with changes in chromatin modifications (enhancer of zeste homolog 2) and DNA methylation. Glioma cells exteriorize their PDPN and/or tissue factor (TF) as cargo of exosome-like extracellular vesicles (EVs) shed from cells in vitro and in vivo. Injection of glioma-derived podoplanin carrying extracelluar vesicles (PDPN-EVs) activates platelets, whereas tissue factor carrying extracellular vesicles (TF-EVs) activate the clotting cascade. Similarly, an increase in platelet activation (platelet factor 4) or coagulation (D-dimer) markers occurs in mice harboring the corresponding glioma xenografts expressing PDPN or TF, respectively. Coexpression of PDPN and TF by GBM cells cooperatively affects tumor microthrombosis. Thus, in GBM, distinct cellular subsets drive multiple facets of cancer-associated thrombosis and may represent targets for phenotype- and cell type-based diagnosis and antithrombotic intervention.

Complexities in celltype composition have rightfully led to skepticism and caution in the interpretation of bulk transcriptomic analyses. Recent studies have shown that deconvolution algorithms can be utilized to computationally estimate celltype proportions from the gene expression data of bulk blood samples, but their performance when applied to tumor tissues, including those from head and neck, remains poorly characterized. Here, we use singlecell data (~6000 single cells) collected from 21 head and neck squamous cell carcinoma (HNSCC) samples to generate celltype-specific gene expression signatures. We leverage bulk RNAseq data from >500 HNSCC samples profiled by The Cancer Genome Atlas (TCGA), and using singlecell data as a reference, apply two newly developed deconvolution algorithms (CIBERSORTx and MuSiC) to the bulk transcriptome data to quantitatively estimate celltype proportions for each tumor in TCGA. We show that these two algorithms produce similar estimates of constituent/major celltype proportions and that a high Tcell fraction correlates with improved survival. By further characterizing Tcell subpopulations, we identify that regulatory Tcells (Tregs) were the major contributor to this improved survival. Lastly, we assessed gene expression, specifically in the Treg population, and found that TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily Member 4) was differentially expressed in the core Treg subpopulation. Moreover, higher TNFRSF4 expression was associated with greater survival, suggesting that TNFRSF4 could play a key role in mechanisms underlying the contribution of Treg in HNSCC outcomes.

T cells are critical effectors of cancer immunotherapies, but little is known about their gene expression programs in diffuse gliomas. Here, we leverage single-cell RNA sequencing (RNA-seq) to chart the gene expression and clonal landscape of tumor-infiltrating T cells across 31 patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma and IDH mutant glioma. We identify potential effectors of anti-tumor immunity in subsets of T cells that co-express cytotoxic programs and several natural killer (NK) cell genes. Analysis of clonally expanded tumor-infiltrating T cells further identifies the NK gene KLRB1 (encoding CD161) as a candidate inhibitory receptor. Accordingly, genetic inactivation of KLRB1 or antibody-mediated CD161 blockade enhances T cell-mediated killing of glioma cells in vitro and their anti-tumor function in vivo. KLRB1 and its associated transcriptional program are also expressed by substantial T cell populations in other human cancers. Our work provides an atlas of T cells in gliomas and highlights CD161 and other NK cell receptors as immunotherapy targets. 

Head and neck squamous cell carcinoma (SCC) remains among the most aggressive human cancers. Tumour progression and aggressiveness in SCC are largely driven by tumour-propagating cells (TPCs). Aerobic glycolysis, also known as the Warburg effect, is a characteristic of many cancers; however, whether this adaptation is functionally important in SCC, and at which stage, remains poorly understood. Here, we show that the NAD⁺-dependent histone deacetylase sirtuin 6 is a robust tumour suppressor in SCC, acting as a modulator of glycolysis in these tumours. Remarkably, rather than a late adaptation, we find enhanced glycolysis specifically in TPCs. More importantly, using single-cell RNA sequencing of TPCs, we identify a subset of TPCs with higher glycolysis and enhanced pentose phosphate pathway and glutathione metabolism, characteristics that are strongly associated with a better antioxidant response. Together, our studies uncover enhanced glycolysis as a main driver in SCC, and, more importantly, identify a subset of TPCs as the cell of origin for the Warburg effect, defining metabolism as a key feature of intra-tumour heterogeneity.

Human tumors are composed of diverse malignant and nonmalignant cells, generating a complex ecosystem that governs tumor biology and response to treatments. Recent technological advances have enabled the characterization of tumors at single-cell resolution, providing a compelling strategy to dissect their intricate biology. Here we describe recent developments in single-cell expression profiling and the studies applying them in clinical settings. We highlight some of the powerful insights gleaned from these studies for tumor classification, stem cell programs, tumor microenvironment, metastasis, and response to targeted and immune therapies. Significance: Intratumor heterogeneity (ITH) has been a major barrier to our understanding of cancer. Single-cell genomics is leading a revolution in our ability to systematically dissect ITH. In this review, we focus on single-cell expression profiling and lessons learned in key aspects of human tumor biology.

Primary brain tumors remain among the deadliest of all cancers. Glioma grade IV (glioblastoma), the most common and malignant type of brain cancer, is associated with a 5-year survival rate of

Assays to study cancer cell responses to pharmacologic or genetic perturbations are typically restricted to using simple phenotypic readouts such as proliferation rate. Information-rich assays, such as gene-expression profiling, have generally not permitted efficient profiling of a given perturbation across multiple cellular contexts. Here, we develop MIX-Seq, a method for multiplexed transcriptional profiling of post-perturbation responses across a mixture of samples with single-cell resolution, using SNP-based computational demultiplexing of single-cell RNA-sequencing data. We show that MIX-Seq can be used to profile responses to chemical or genetic perturbations across pools of 100 or more cancer cell lines. We combine it with Cell Hashing to further multiplex additional experimental conditions, such as post-treatment time points or drug doses. Analyzing the high-content readout of scRNA-seq reveals both shared and context-specific transcriptional response components that can identify drug mechanism of action and enable prediction of long-term cell viability from short-term transcriptional responses to treatment.

Cultured cell lines are the workhorse of cancer research, but the extent to which they recapitulate the heterogeneity observed among malignant cells in tumors is unclear. Here we used multiplexed single-cell RNA-seq to profile 198 cancer cell lines from 22 cancer types. We identified 12 expression programs that are recurrently heterogeneous within multiple cancer cell lines. These programs are associated with diverse biological processes, including cell cycle, senescence, stress and interferon responses, epithelialmesenchymal transition and protein metabolism. Most of these programs recapitulate those recently identified as heterogeneous within human tumors. We prioritized specific cell lines as models of cellular heterogeneity and used them to study subpopulations of senescence-related cells, demonstrating their dynamics, regulation and unique drug sensitivities, which were predictive of clinical response. Our work describes the landscape of heterogeneity within diverse cancer cell lines and identifies recurrent patterns of heterogeneity that are shared between tumors and specific cell lines.

OBJECTIVES: To explore lymphocyte infiltration as a potential mechanism behind CXCL14-mediated tumor growth suppression in oral cavity squamous cell carcinoma (OSCC). METHODS: We analyzed single cell RNA-sequencing (scRNA-seq) data from OSCC to identify expression changes among malignant cells in lymph nodes (LN) versus primary tumors. CXCL14 expression in murine OSCC cell lines was quantified using qRT-PCR. Short hairpin RNA knockdown of CXCL14 was performed in mouse oral cavity (MOC)1 cells, and CXCL14 overexpression was performed in MOC2 cells. Cells in each condition were injected into C57BL/6 mice with and without T cell depletion, and tumor volume was measured. At 30 days, tumors were dissociated and analyzed by flow cytometry for CD45+CD3+ T cells. CXCL14 expression was correlated with gene expression signatures of tumor infiltrating lymphocytes (TIL) in scRNA-seq data, as well as TCGA tumors. RESULTS: scRNA-seq revealed CXCL14 as the most significantly downregulated gene among malignant cells in LNs relative to primary tumor, supporting a role in preventing invasion and/or metastasis. In a murine immunocompetent model, CXCL14 expression was higher in indolent MOC1 cells than in more aggressive MOC2 cells. Tumor growth in vivo was significantly increased by CXCL14 knockdown in MOC1 cells relative to control, with a corresponding decrease in TIL. In MOC2 cells, tumor growth was significantly reduced by CXCL14 overexpression relative to control and TIL were increased. Both effects were lost with T cell depletion. In a human tumor scRNA-seq cohort, we found that only malignant cell CXCL14, but not non-malignant cell or fibroblast CXCL14, was associated with TIL. Bulk CXCL14 from the TCGA cohort had no association with TIL. CONCLUSIONS: Higher CXCL14 expression by tumor cells is associated with reduced tumor growth and increased TIL, supporting immune-mediated suppression of tumor growth in OSCC. Given that CXCL14 is downregulated in LN metastases compared with primary tumors, our data raise the possibility that CXCL14-mediated immune infiltration may discourage invasion and metastasis. In human scRNA-seq data, only malignant cell-specific CXCL14 was associated with TIL, suggesting a critical context-dependent effect of CXCL14 expression.

Malignant abdominal fluid (ascites) frequently develops in women with advanced high-grade serous ovarian cancer (HGSOC) and is associated with drug resistance and a poor prognosis(1). To comprehensively characterize the HGSOC ascites ecosystem, we used single-cell RNA sequencing to profile similar to 11,000 cells from 22 ascites specimens from 11 patients with HGSOC. We found significant inter-patient variability in the composition and functional programs of ascites cells, including immunomodulatory fibroblast sub-populations and dichotomous macrophage populations. We found that the previously described immunoreactive and mesenchymal subtypes of HGSOC, which have prognostic implications, reflect the abundance of immune infiltrates and fibroblasts rather than distinct subsets of malignant cells(2). Malignant cell variability was partly explained by heterogeneous copy number alteration patterns or expression of a stemness program. Malignant cells shared expression of inflammatory programs that were largely recapitulated in single-cell RNA sequencing of similar to 35,000 cells from additionally collected samples, including three ascites, two primary HGSOC tumors and three patient ascites-derived xenograft models. Inhibition of the JAK/STAT pathway, which was expressed in both malignant cells and cancer-associated fibroblasts, had potent anti-tumor activity in primary short-term cultures and patient-derived xenograft models. Our work contributes to resolving the HSGOC landscape(3-5)and provides a resource for the development of novel therapeutic approaches.

Glioma stem cells (GSCs) are thought to underlie glioma initiation, evolution, and resistance to existing therapies. Although functional evidence for GSCs is abundant, tumor heterogeneity and intrinsic limitations in GSC assays have represented barriers for the field. In this perspective, we revisit the GSC model in light of recent single-cell expression profiling studies. We highlight how classes of glioma differ in their cellular architecture and relate the observed cellular states to established GSC markers. We additionally propose a set of single-cell informed definitions as a framework for our understanding of the cellular architecture of gliomas and a potential therapeutic outlook.

Glioblastoma is an incurable brain tumor notorious for its heterogeneity. Recent studies in Cell (Jacob et al., 2020) and Cell Stem Cell (Bhaduri et al., 2020) leverage novel glioblastoma organoid models and single-cell RNA-sequencing technologies to tackle glioblastoma's heterogeneous nature, providing new tools and insights into tumor biology.

Objectives: Quantify by immunohistochemistry (IHC) a partial epithelial-to-mesenchymal transition (p-EMT) population in oral cavity squamous cell carcinoma (OCSCC) and determine its predictive value for lymph node metastasis. Methods: Tissue microarrays (TMA) were created using 2 mm cores from 99 OCSCC patients (47 with low volume T2 disease, 52 with high volume T4 disease, and - 50% in each group with nodal metastasis). IHC staining was performed for three validated p-EMT markers (PDPN, LAMB3, LAMC2) and one marker of well-differentiated epithelial cells (SPRR1B). Staining was quantified in a blinded manner by two reviewers. Tumors were classified as malignant basal subtype based on staining for the four markers. In this subset, the p-EMT score was computed as the average of p-EMT markers.Results: 84 tumors were classified as malignant basal. There was 87% inter-rater consistency in marker quantification. There were associations of p-EMT scores with higher grade (2.15 vs. 1.92, p = 0.04), PNI (2.13 vs. 1.83, p = 0.003), and node positivity (2.09 vs. 1.87, p = 0.02), including occult node positivity (56% vs. 19%, p = 0.005). P-EMT was independently associated with nodal metastasis in a multivariate analysis (OR 3.12, p = 0.039). Overall and disease free survival showed trends towards being diminished in the p-EMT high group. Conclusions: IHC quantification of p-EMT in OCSCC primary tumors is reliably associated with nodal metastasis, PNI, and high grade. With prospective validation, p-EMT biomarkers may aid in decision-making over whether to perform a neck dissection in the NO neck and/or for adjuvant therapy planning.

Head and neck squamous cell carcinoma (HNSCC), like many tumors, is characterized by significant intra-tumoral heterogeneity, namely transcriptional, genetic, and epigenetic differences that define distinct cellular subpopulations. While it has been established that intra-tumoral heterogeneity may have prognostic significance in HNSCC, we are only beginning to describe and define such heterogeneity at a cellular resolution. Recent advances in single-cell sequencing technologies have been critical in this regard, opening new avenues in our understanding of more nuanced tumor biology by identifying distinct cellular subpopulations, dissecting signaling within the tumor microenvironment, and characterizing cellular genomic mutations and copy number aberrations. The combined effect of these insights is likely to be robust and meaningful changes in existing diagnostic and treatment algorithms through the application of novel biomarkers as well as targeted therapeutics. Here, we review single-cell technological and computational advances at the genomic, transcriptomic, and epigenomic levels, and discuss their applications in cancer research and clinical practice, with a specific focus on HNSCC.

Diverse genetic, epigenetic, and developmental programs drive glioblastoma, an incurable and poorly understood tumor, but their precise characterization remains challenging. Here, we use an integrative approach spanning single-cell RNA-sequencing of 28 tumors, bulk genetic and expression analysis of 401 specimens from the The Cancer Genome Atlas (TCGA), functional approaches, and single-cell lineage tracing to derive a unified model of cellular states and genetic diversity in glioblastoma. We find that malignant cells in glioblastoma exist in four main cellular states that recapitulate distinct neural cell types, are influenced by the tumor microenvironment, and exhibit plasticity. The relative frequency of cells in each state varies between glioblastoma samples and is influenced by copy number amplifications of the CDK4, EGFR, and PDGFRA loci and by mutations in the NF1 locus, which each favor a defined state. Our work provides a blueprint for glioblastoma, integrating the malignant cell programs, their plasticity, and their modulation by genetic drivers.

Bulk genomic analyses and expression profiling of clinical specimens have shaped much of our understanding of cancer in patients. However, human tumors are intricate ecosystems composed of diverse cells, including malignant, immune, and stromal subsets, whose precise characterization is masked by bulk genomic methods. Single-cell genomic techniques have emerged as powerful approaches to dissect human tumors at the resolution of individual cells, providing a compelling approach to deciphering cancer biology. Here, we discuss some of the common themes emerging from initial studies of single-cell RNA sequencing in cancer and then highlight challenges in cancer biology for which emerging single-cell genomics methods may provide a compelling approach.

Human tumors are complex ecosystems where diverse cancer and noncancer cells interact to determine tumor biology and response to therapies. Genomic and transcriptomic methods have traditionally profiled these intricate ecosystems as bulk samples, thereby masking individual cellular programs and the variability among them. Recent advances in single-cell profiling have paved the way for studying tumors at the resolution of individual cells, providing a compelling strategy to bridge gaps in our understanding of human tumors. Here, we review methodologies for single-cell expression profiling of tumors and the initial studies deploying them in clinical contexts. We highlight how these studies uncover new biology and provide insights into drug resistance, stem cell programs, metastasis, and tumor classifications. We also discuss areas of technology development in single-cell genomics that provide new tools to address key questions in cancer biology. These emerging studies and technologies have the potential to revolutionize our understanding and management of human malignancies.

Neoantigens, which are derived from tumour-specific protein-coding mutations, are exempt from central tolerance, can generate robust immune responses(1,2) and can function as bona fide antigens that facilitate tumour rejection(3). Here we demonstrate that a strategy that uses multi-epitope, personalized neoantigen vaccination, which has previously been tested in patients with high-risk melanoma(4-6), is feasible for tumours such as glioblastoma, which typically have a relatively low mutation load(1,7) and an immunologically 'cold' tumour microenvironment(8). We used personalized neoantigen-targeting vaccines to immunize patients newly diagnosed with glioblastoma following surgical resection and conventional radiotherapy in a phase I/Ib study. Patients who did not receive dexamethasone-a highly potent corticosteroid that is frequently prescribed to treat cerebral oedema in patients with glioblastoma-generated circulating polyfunctional neoantigen-specific CD4(+) and CD8(+) T cell responses that were enriched in a memory phenotype and showed an increase in the number of tumour-infiltrating T cells. Using single-cell T cell receptor analysis, we provide evidence that neoantigen-specific T cells from the peripheral blood can migrate into an intracranial glioblastoma tumour. Neoantigen-targeting vaccines thus have the potential to favourably alter the immune milieu of glioblastoma.

In the small intestine, a niche of accessory cell types supports the generation of mature epithelial cell types from intestinal stem cells (ISCs). It is unclear, however, if and how immune cells it the niche affect ISC fate or the balance between self-rei and differentiation. Here, we use single cell RNA sequencing (scRNA-seq) to identify MHC class II (MHCII) machinery enrichment in two subsets of Lgr(5+) ISCs. We show that MHCII+ Lgr(5+) ISCs are non-conventional antigen-presenting cells in co-cultures with CD4( +) T helper (Th) cells. Stimulation of intestinal organoids with key Th cytokines affects Lgr(5+) ISC renewal and differentiation in opposing ways: pro-inflammatory signals promote differentiation, while regulatory cells and cytokines reduce it. In vivo genetic perturbation of Th cells or MHCII expression on Lgr(5+) ISCs impacts epithelial cell differentiation and IEC fate during infection. These interactions between Th cells and Lgr(5+) ISCs, thus, orchestrate, tissue-wide responses to external signals.

The quest for tumor-associated antigens (TAA) and neoantigens is a major focus of cancer immunotherapy. Here, we combine a neoantigen prediction pipeline and human leukocyte antigen (HLA) peptidomics to identify TAAs and neoantigens in 16 tumors derived from seven patients with melanoma and characterize their interactions with their tumor-infiltrating lymphocytes (TIL). Our investigation of the antigenic and T-cell landscapes encompassing the TAA and neoantigen signatures, their immune reactivity, and their corresponding T-cell identities provides the first comprehensive analysis of cancer cell T-cell cosignatures, allowing us to discover remarkable antigenic and TIL similarities between metastases from the same patient. Furthermore, we reveal that two neoantigen-specific clonotypes killed 90% of autologous melanoma cells, both in vitro and in vivo, showing that a limited set of neoantigen-specific T cells may play a central role in melanoma tumor rejection. Our findings indicate that combining HLA peptidomics with neoantigen predictions allows robust identification of targetable neoantigens, which could successfully guide personalized cancer immunotherapies.SIGNIFICANCE: As neoantigen targeting is becoming more established as a powerful therapeutic approach, investigating these molecules has taken center stage. Here, we show that a limited set of neoantigen-specific T cells mediates tumor rejection, suggesting that identifying just a few antigens and their corresponding T-cell clones could guide personalized immunotherapy. (c) 2018 AACR.

Studies in single cell transcriptomics have significantly expanded our understanding of tumor biology, including recent analyses in head and neck squamous cell carcinoma. Here, we focus on the role of a partial epithelial-to-mesenchymal (EMT) program in these tumors, with discussion of its dynamics, regulation, and implications for diagnostic and therapeutic approaches.

Gliomas comprise heterogeneous malignant glial and stromal cells. While blood vessel co-option is a potential mechanismto escape anti-angiogenic therapy, the relevance of glial phenotype in this process is unclear. We show that Olig2(+) oligodendrocyte precursor-like glioma cells invade by single-cell vessel co-option and preserve the blood-brain barrier (BBB). Conversely, Olig2-negative glioma cells form dense perivascular collections and promote angiogenesis and BBB breakdown, leading to innate immune cell activation. Experimentally, Olig2 promotes Wnt7b expression, a finding that correlates in human glioma profiling. Targeted Wnt7a/7b deletion or pharmacologic Wnt inhibition blocks Olig2(+) glioma single-cell vessel co-option and enhances responses to temozolomide. Finally, Olig2 and Wnt7 become upregulated after anti-VEGF treatment in preclinical models and patients. Thus, glial-encoded pathways regulate distinct glioma-vascular micro-environmental interactions.

Gliomas with histone H3 lysine27-to-methionine mutations (H3K27M-glioma) arise primarily in the midline of the central nervous system of young children, suggesting a cooperation between genetics and cellular context in tumorigenesis. Although the genetics of H3K27M-glioma are well characterized, their cellular architecture remains uncharted. We performed single-cell RNA sequencing in 3321 cells from six primary H3K27M-glioma and matched models. We found that H3K27M-glioma primarily contain cells that resemble oligodendrocyte precursor cells (OPC-like), whereas more differentiated malignant cells are a minority. OPC-like cells exhibit greater proliferation and tumor-propagating potential than their more differentiated counterparts and are at least in part sustained by PDGFRA signaling. Our study characterizes oncogenic and developmental programs in H3K27M-glioma at single-cell resolution and across genetic subclones, suggesting potential therapeutic targets in this disease.

Diffuse gliomas are the most common human primary brain tumors and remain incurable. They are complex entities in which diverse genetic and nongenetic effects determine tumor biology and clinical course. Our current understanding of gliomas in patients is primarily based on genomic and transcriptomic methods that have profiled them as bulk, providing critical information yet masking the diversity of cells within each tumor. Recent advances in single-cell DNA and RNA profiling have paved the way to studying tumors at cellular resolution. Here, we review initial studies deploying single-cell analysis in clinical glioma samples, with a focus on RNA expression profiling. We highlight how these studies provide new insights into glioma biology, tumor heterogeneity, cancer cell lineages, cancer stem cell programs, the tumor microenvironment, and glioma classification.

The diverse malignant, stromal, and immune cells in tumors affect growth, metastasis, and response to therapy. We profiled transcriptomes of ∼6,000 single cells from 18 head and neck squamous cell carcinoma (HNSCC) patients, including five matched pairs of primary tumors and lymph node metastases. Stromal and immune cells had consistent expression programs across patients. Conversely, malignant cells varied within and between tumors in their expression of signatures related to cell cycle, stress, hypoxia, epithelial differentiation, and partial epithelial-to-mesenchymal transition (p-EMT). Cells expressing the p-EMT program spatially localized to the leading edge of primary tumors. By integrating single-cell transcriptomes with bulk expression profiles for hundreds of tumors, we refined HNSCC subtypes by their malignant and stromal composition and established p-EMT as an independent predictor of nodal metastasis, grade, and adverse pathologic features. Our results provide insight into the HNSCC ecosystem and define stromal interactions and a p-EMT program associated with metastasis. Single-cell transcriptomic analysis in patients with head and neck squamous cell carcinoma highlights the heterogeneous composition of malignant and non-malignant cells in the tumor microenvironment and associates a partial EMT program with metastasis.

Intestinal epithelial cells absorb nutrients, respond to microbes, function as a barrier and help to coordinate immune responses. Here we report profiling of 53,193 individual epithelial cells from the small intestine and organoids of mice, which enabled the identification and characterization of previously unknown subtypes of intestinal epithelial cell and their gene signatures. We found unexpected diversity in hormone-secreting enteroendocrine cells and constructed the taxonomy of newly identified subtypes, and distinguished between two subtypes of tuft cell, one of which expresses the epithelial cytokine Tslp and the pan-immune marker CD45, which was not previously associated with non-haematopoietic cells. We also characterized the ways in which cell-intrinsic states and the proportions of different cell types respond to bacterial and helminth infections: Salmonella infection caused an increase in the abundance of Paneth cells and enterocytes, and broad activation of an antimicrobial program; Heligmosomoides polygyrus caused an increase in the abundance of goblet and tuft cells. Our survey highlights previously unidentified markers and programs, associates sensory molecules with cell types, and uncovers principles of gut homeostasis and response to pathogens.

The application of RNA interference (RNAi) to mammalian cells has provided the means to perform phenotypic screens to determine the functions of genes. Although RNAi has revolutionized loss-of-function genetic experiments, it has been difficult to systematically assess the prevalence and consequences of off-target effects. The Connectivity Map (CMAP) represents an unprecedented resource to study the gene expression consequences of expressing short hairpin RNAs (shRNAs). Analysis of signatures for over 13,000 shRNAs applied in 9 cell lines revealed that microRNA (miRNA)-like off-target effects of RNAi are far stronger and more pervasive than generally appreciated. We show that mitigating off-target effects is feasible in these datasets via computational methodologies to produce a consensus gene signature (CGS). In addition, we compared RNAi technology to clustered regularly interspaced short palindromic repeat (CRISPR)-based knockout by analysis of 373 single guide RNAs (sgRNAs) in 6 cells lines and show that the on-target efficacies are comparable, but CRISPR technology is far less susceptible to systematic off-target effects. These results will help guide the proper use and analysis of loss-of-function reagents for the determination of gene function.

Homeostatic programs balance immune protection and self-tolerance. Such mechanisms likely impact autoimmunity and tumor formation, respectively. How homeostasis is maintained and impacts tumor surveillance is unknown. Here, we find that different immune mononuclear phagocytes share a conserved steady-state program during differentiation and entry into healthy tissue. IFNγ is necessary and sufficient to induce this program, revealing a key instructive role. Remarkably, homeostatic and IFNγ-dependent programs enrich across primary human tumors, including melanoma, and stratify survival. Single-cell RNA sequencing (RNA-seq) reveals enrichment of homeostatic modules in monocytes and DCs from human metastatic melanoma. Suppressor-of-cytokine-2 (SOCS2) protein, a conserved program transcript, is expressed by mononuclear phagocytes infiltrating primary melanoma and is induced by IFNγ. SOCS2 limits adaptive anti-tumoral immunity and DC-based priming of T cells in vivo, indicating a critical regulatory role. These findings link immune homeostasis to key determinants of anti-tumoral immunity and escape, revealing co-opting of tissue-specific immune development in the tumor microenvironment.

Single-cell analysis is a rapidly evolving approach to characterize genome-scale molecular information at the individual cell level. Development of single-cell technologies and computational methods has enabled systematic investigation of cellular heterogeneity in a wide range of tissues and cell populations, yielding fresh insights into the composition, dynamics, and regulatory mechanisms of cell states in development and disease. Despite substantial advances, significant challenges remain in the analysis, integration, and interpretation of single-cell omics data. Here, we discuss the state of the field and recent advances and look to future opportunities.

Tumor subclasses differ according to the genotypes and phenotypes of malignant cells as well as the composition of the tumor microenvironment (TME).We dissected these influences in isocitrate dehydrogenase (IDH)-mutant gliomas by combining 14,226 single-cell RNA sequencing (RNA-seq) profiles from 16 patient samples with bulk RNA-seq profiles from 165 patient samples. Differences in bulk profiles between IDH-mutant astrocytoma and oligodendroglioma can be primarily explained by distinct TME and signature genetic events, whereas both tumor types share similar developmental hierarchies and lineages of glial differentiation. As tumor grade increases, we find enhanced proliferation of malignant cells, larger pools of undifferentiated glioma cells, and an increase in macrophage over microglia expression programs in TME. Our work provides a unifying model for IDH-mutant gliomas and a general framework for dissecting the differences among human tumor subclasses.

Cells, the basic units of biological structure and function, vary broadly in type and state. Single-cell genomics can characterize cell identity and function, but limitations of ease and scale have prevented its broad application. Here we describe Drop-seq, a strategy for quickly profiling thousands of individual cells by separating them into nanoliter-sized aqueous droplets, associating a different barcode with each cell's RNAs, and sequencing them all together. Drop-seq analyzes mRNA transcripts from thousands of individual cells simultaneously while remembering transcripts' cell of origin. We analyzed transcriptomes from 44,808 mouse retinal cells and identified 39 transcriptionally distinct cell populations, creating a molecular atlas of gene expression for known retinal cell classes and novel candidate cell subtypes. Drop-seq will accelerate biological discovery by enabling routine transcriptional profiling at single-cell resolution.

Previous studies have described a transcriptional "memory effect," whereby transcript levels of many Abf1-regulated genes in the budding yeast Saccharomyces cerevisiae are undiminished even after Abf1 has dissociated from its regulatory sites. Here we provide additional support for this effect and investigate its molecular basis. We show that the effect is observed in a distinct abf1 ts mutant from that used in earlier studies, demonstrating that it is robust, and use chromatin immunoprecipitation to show that Abf1 association is decreased similarly from memory effect and transcriptionally responsive genes at the restrictive temperature. We also demonstrate that the association of TATA-binding protein and Pol II decreases after the loss of Abf1 binding for transcriptionally responsive genes but not for memory effect genes. Examination of genome-wide nucleosome occupancy data reveals that although transcriptionally responsive genes exhibit increased nucleosome occupancy in abf1 ts yeast, the promoter regions of memory effect targets show no change in abf1 ts mutants, maintaining an open chromatin conformation even after Abf1 eviction. This contrasting behavior reflects different inherent propensity for nucleosome formation between the two classes, driven by the presence of A/T-rich sequences upstream of the Abf1 site in memory effect gene promoters. These sequence-based differences show conservation in closely related fungi and also correlate with different gene expression noise, suggesting a physiological basis for greater access to "memory effect" promoter regions. Thus, our results establish a conserved mechanism underlying a transcriptional memory effect whereby sequences surrounding Abf1 binding sequences affect local nucleosome occupancy following loss of Abf1 binding. Furthermore, these findings demonstrate that sequence-based differences in the propensity for nucleosome occupancy can influence the transcriptional response of genes to an altered regulatory signal.

Genome-encoded microRNAs (miRNAs) provide a posttranscriptional regulatory layer that controls the differentiation and function of various cellular systems, including hematopoietic cells. miR-142 is one of the most prevalently expressed miRNAs within the hematopoietic lineage. To address the in vivo functions of miR-142 we utilized a novel reporter and loss-of-function mouse allele that we have recently generated. Here, we show that miR-142 is broadly expressed in the adult hematopoietic system. Our data further reveal that miR-142 is critical for megakaryopoiesis. Thus, genetic miR-142 ablation caused impaired megakaryocyte maturation, inhibition of polyploidization, abnormal proplatelet formation, and thrombocytopenia. Finally, we characterize a network of miR-142-3p targets which collectively controls actin filament homeostasis, thereby ensuring proper execution of actin-dependent proplatelet formation. Our study reveals a pivotal role for miR-142 activity in megakaryocyte maturation and function, and demonstrates a critical contribution of a single miRNA in orchestrating cytoskeletal dynamics and normal haemostasis.

Developmental fate decisions are dictated by master transcription factors (TFs) that interact with cis-regulatory elements to direct transcriptional programs. Certain malignant tumors may also depend on cellular hierarchies reminiscent of normal development but superimposed on underlying genetic aberrations. In glioblastoma (GBM), a subset of stem-like tumor-propagating cells (TPCs) appears to drive tumor progression and underlie therapeutic resistance yet remain poorly understood. Here, we identify a core set of neurodevelopmental TFs (POU3F2, SOX2, SALL2, and OLIG2) essential for GBM propagation. These TFs coordinately bind and activate TPC-specific regulatory elements and are sufficient to fully reprogram differentiated GBM cells to "induced" TPCs, recapitulating the epigenetic landscape and phenotype of native TPCs. We reconstruct a network model that highlights critical interactions and identifies candidate therapeutic targets for eliminating TPCs. Our study establishes the epigenetic basis of a developmental hierarchy in GBM, provides detailed insight into underlying gene regulatory programs, and suggests attendant therapeutic strategies. PaperClip

Human cancers are complex ecosystems composed of cells with distinct phenotypes, genotypes, and epigenetic states, but current models do not adequately reflect tumor composition in patients. We used single-cell RNA sequencing (RNA-seq) to profile 430 cells from five primary glioblastomas, which we found to be inherently variable in their expression of diverse transcriptional programs related to oncogenic signaling, proliferation, complement/immune response, and hypoxia. We also observed a continuum of stemness-related expression states that enabled us to identify putative regulators of stemness in vivo. Finally, we show that established glioblastoma subtype classifiers are variably expressed across individual cells within a tumor and demonstrate the potential prognostic implications of such intratumoral heterogeneity. Thus, we reveal previously unappreciated heterogeneity in diverse regulatory programs central to glioblastoma biology, prognosis, and therapy.

In this chapter, we focus on budding yeasts, a group of related species, with fully sequenced genomes. Haploids and diploids from these species can propagate asexually or mate to produce hybrids and polyploids. There are no zygotic barriers among budding yeasts. Thus, interspecific hybrids and polyploid yeasts are widespread in nature or in domesticated strains used for the making of wine, beer, cider, biofuel, and bread. This, together with all the advantages of being fast-growing unicellular organisms, makes yeasts ideally suited for contributing to the understanding of evolution in hybrids and polyploids. We describe the insights gained from the analysis of the ancient whole-genome duplication that occurred in yeast approximately 100 million years ago. Namely, we summarize lessons from the nonrandom retention of duplicated loci in the context of sub- and neofunctionalization of genes and of networks of genes and proteins. We discuss how experimental analysis of yeast evolution (a unique feature in the field of polyploidy research) has contributed to the debate on haploid versus diploid polyploid superiority, showing the complexity of the issue. We show how yeast hybrids have been used as tools to study the mechanisms of divergence between species with regard to gene expression, nucleosome occupancy, DNA replication, and RNA stability. Finally, we discuss the challenges and open questions in this field. This edition first published 2013

The bacterial community in the human gut has crucial health roles both in metabolic functions and in protection against pathogens. Phages, which are known to significantly affect microbial community composition in many ecological niches, have the potential to impact the gut microbiota, yet thorough characterization of this relationship remains elusive. We have reconstructed the content of the CRISPR bacterial immune system in the human gut microbiomes of 124 European individuals and used it to identify a catalog of 991 phages targeted by CRISPR across all individuals. Our results show that 78% of these phages are shared among two or more individuals. Moreover, a significant fraction of phages found in our study are shown to exist in fecal samples previously derived from American and Japanese individuals, identifying a common reservoir of phages frequently associated with the human gut microbiome. We further inferred the bacterial hosts for more than 130 such phages, enabling a detailed analysis of phage-bacteria interactions across the 124 individuals by correlating patterns of phage abundance with bacterial abundance and resistance. A subset of phages demonstrated preferred association with host genomes as lysogenized prophages, with highly increased abundance in specific individuals. Overall, our results imply that phage-bacterial attack-resistance interactions occur within the human gut microbiome, possibly affecting microbiota composition and human health. Our finding of global sharing of gut phages is surprising in light of the extreme genetic diversity of phages found in other ecological niches.

Gene expression shows a significant variation (noise) between genetically identical cells. Noise depends on the gene expression process regulated by the chromatin environment. We screened for chromatin factors that modulate noise in S. cerevisiae and analyzed the results using a theoretical model that infers regulatory mechanisms from the noise versus mean relationship. Distinct activities of the Rpd3(L) and Set3 histone deacetylase complexes were predicted. Both HDACs repressed expression. Yet, Rpd3(L)C decreased the frequency of transcriptional bursts, while Set3C decreased the burst size, as did H2B monoubiquitination (ubH2B). We mapped the acetylation of H3 lysine 9 (H3K9ac) upon deletion of multiple subunits of Set3C and Rpd3(L)C and of ubH2B effectors. ubH2B and Set3C appear to function in the same pathway to reduce the probability that an elongating PolII produces a functional transcript (PolII processivity), while Rpd3(L)C likely represses gene expression at a step preceding elongation.

Understanding why genes evolve at different rates is fundamental to evolutionary thinking. In species of the budding yeast, the rate at which genes diverge in expression correlates with the organization of their promoter nucleosomes: genes lacking a nucleosome-free region (denoted OPN for "Occupied Proximal Nucleosomes") vary widely between the species, while the expression of those containing NFR (denoted DPN for "Depleted Proximal Nucleosomes") remains largely conserved. To examine if early evolutionary dynamics contributes to this difference in divergence, we artificially selected for high expression of GFP-fused proteins. Surprisingly, selection was equally successful for OPN and DPN genes, with ~80% of genes in each group stably increasing in expression by a similar amount. Notably, the two groups adapted by distinct mechanisms: DPN-selected strains duplicated large genomic regions, while OPN-selected strains favored trans mutations not involving duplications. When selection was removed, DPN (but not OPN) genes reverted rapidly to wild-type expression levels, consistent with their lower diversity between species. Our results suggest that promoter organization constrains the early evolutionary dynamics and in this way biases the path of long-term evolution.

Background: GC-skews have previously been linked to transcription in some eukaryotes. They have been associated with transcription start sites, with the coding strand G-biased in mammals and C-biased in fungi and invertebrates.Results: We show a consistent and highly significant pattern of GC-skew within genes of almost all unicellular fungi. The pattern of GC-skew is asymmetrical: the coding strand of genes is typically C-biased at the 5' ends but G-biased at the 3' ends, with intermediate skews at the middle of genes. Thus, the initiation, elongation, and termination phases of transcription are associated with different skews. This pattern influences the encoded proteins by generating differential usage of amino acids at the 5' and 3' ends of genes. These biases also affect fourfold-degenerate positions and extend into promoters and 3' UTRs, indicating that skews cannot be accounted by selection for protein function or translation.Conclusions: We propose two explanations, the mutational pressure hypothesis, and the adaptive hypothesis. The mutational pressure hypothesis is that different co-factors bind to RNA pol II at different phases of transcription, producing different mutational regimes. The adaptive hypothesis is that cytidine triphosphate deficiency may lead to C-avoidance at the 3' ends of transcripts to control the flow of RNA pol II molecules and reduce their frequency of collisions.

To examine the role of nucleosome occupancy in the evolution of gene expression, we measured the genome-wide nucleosome profiles of four yeast species, three belonging to the Saccharomyces sensu stricto lineage and the more distantly related Candida glabrata. Nucleosomes and associated promoter elements at C. glabrata genes are typically shifted upstream by ~20 bp, compared to their orthologs from sensu stricto species. Nonetheless, all species display the same global organization features first described for Saccharomyces cerevisiae: a stereotypical nucleosome organization along genes and a division of promoters into those that contain or lack a pronounced nucleosome-depleted region (NDR), with the latter displaying a more dynamic pattern of gene expression. Despite this global similarity, however, nucleosome occupancy at specific genes diverged extensively between sensu stricto and C. glabrata orthologs (~50 million years). Orthologs with dynamic expression patterns tend to maintain their lack of NDR, but apart from that, sensu stricto and C. glabrata orthologs are nearly as similar in nucleosome occupancy patterns as nonorthologous genes. This extensive divergence in nucleosome occupancy contrasts with a conserved pattern of gene expression. Thus, while some evolutionary changes in nucleosome occupancy contribute to gene expression divergence, nucleosome occupancy often diverges extensively with apparently little impact on gene expression.

Genome-wide patterns of nucleosome occupancy and positioning have greatly impacted on studies of chromatin structure, yet these studies require extensive computational analysis which is crucial for the quality of the resulting datasets and inferred conclusions. This chapter describes the computational steps required in order to estimate genome-wide patterns of nucleosome occupancy and positioning from raw data obtained from high-throughput sequencing of mononucleosome DNA fragments. Potential pitfalls that may be encountered in such analysis and computational quality controls are further discussed in Subheading 3.

Closely related species show a high degree of differences in gene expression, but the functional significance of these differences remains unclear. Similarly, stress responses in yeast typically involve differential expression of numerous genes, and it is unclear how many of these are functionally significant. To address these issues, we compared the expression programs of four yeast species under different growth conditions, and found that the response of these species to stress has diverged extensively. On an individual gene basis, most transcriptional responses are not conserved in any pair of species, and there are very limited common responsesamong all four species. We present evidence that many evolutionary changes in stress responses are compensated either (i) by the response of related genes or (ii) by changes in the basal expression levels of the genes whose responses have diverged. Thus, stress-related genes are often induced upon stress in some species but maintain high levels even in the absence of stress at other species, indicating a transition between induced and constitutive activation. In addition, ∼15% of the stress responses are specific to only one of the four species, with no evidence for compensating effects or stress-related annotations, and these may reflect fortuitous regulation that is unimportant for the stress response (i.e., biological noise). Frequent compensatory changes and biological noise may explain how diverged expression responses support similar physiological responses.

mRNA levels are determined by the balance between transcription and mRNA degradation, and while transcription has been extensively studied, very little is known regarding the regulation of mRNA degradation and its coordination with transcription. Here we examine the evolution of mRNA degradation rates between two closely related yeast species. Surprisingly, we find that around half of the evolutionary changes in mRNA degradation were coupled to transcriptional changes that exert opposite effects on mRNA levels. Analysis of mRNA degradation rates in an interspecific hybrid further suggests that opposite evolutionary changes in transcription and in mRNA degradation are mechanistically coupled and were generated by the same individual mutations. Coupled changes are associated with divergence of two complexes that were previously implicated both in transcription and in mRNA degradation (Rpb4/7 and Ccr4-Not), as well as with sequence divergence of transcription factor binding motifs. These results suggest that an opposite coupling between the regulation of transcription and that of mRNA degradation has shaped the evolution of gene regulation in yeast.

Recent evidence suggests that post-transcriptional events that are executed in the cytoplasm can be predetermined during transcription. Here I speculate that this is a widespread mode of regulation and discuss the potential mechanisms, advantages and implications of such a regulatory strategy.

The number of sequenced species is increasing at a staggering rate, calling for new approaches for incorporating evolutionary information in the study of biological mechanisms. Evolutionary conservation is widely used for assigning a function to new proteins and for predicting functional coding or non-coding sequences. Here, we argue for a complementary approach that focuses on the divergence of regulatory programs. Regulatory mechanisms can be learned from patterns of evolutionary divergence in regulatory properties such as gene expression, transcription factor binding or nucleosome positioning. We review examples of this concept using yeast as a model system, and highlight a hybrid-based approach that is highly instrumental in this analysis.

Eukaryotic centromeres are maintained at specific chromosomal sites over many generations. In the budding yeast Saccharomyces cerevisiae, centromeres are genetic elements defined by a DNA sequence that is both necessary and sufficient for function; whereas, in most other eukaryotes, centromeres are maintained by poorly characterized epigenetic mechanisms in which DNA has a less definitive role. Here we use the pathogenic yeast Candida albicans as a model organism to study the DNA replication properties of centromeric DNA. By determining the genome-wide replication timing program of the C. albicans genome, we discovered that each centromere is associated with a replication origin that is the first to fire on its respective chromosome. Importantly, epigenetic formation of new ectopic centromeres (neocentromeres) was accompanied by shifts in replication timing, such that a neocentromere became the first to replicate and became associated with origin recognition complex (ORC) components. Furthermore, changing the level of the centromere-specific histone H3 isoform led to a concomitant change in levels of ORC association with centromere regions, further supporting the idea that centromere proteins determine origin activity. Finally, analysis of centromere-associated DNA revealed a replication-dependent sequence pattern characteristic of constitutively active replication origins. This strand-biased pattern is conserved, together with centromere position, among related strains and species, in a manner independent of primary DNA sequence. Thus, inheritance of centromere position is correlated with a constitutively active origin of replication that fires at a distinct early time. We suggest a model in which the distinct timing of DNA replication serves as an epigenetic mechanism for the inheritance of centromere position.

Background: The positions of nucleosomes along eukaryotic DNA are defined by the local DNA sequence and are further tuned by the activity of chromatin remodelers. While the genome-wide effect of most remodelers has not been described, recent studies in Saccharomyces cerevisiae have shown that Isw2 prevents ectopic expression of anti-sense and suppressed transcripts at gene ends.Results: We examined the genome-wide function of the Isw2 homologue, Isw1, by mapping nucleosome positioning in S. cerevisiae and Saccharomyces paradoxus strains deleted of ISW1. We found that Isw1 functions primarily within coding regions of genes, consistent with its putative role in transcription elongation. Upon deletion of ISW1, mid-coding nucleosomes were shifted upstream (towards the 5' ends) in about half of the genes. Isw1-dependent shifts were correlated with trimethylation of H3K79 and were enriched at genes with internal cryptic initiation sites.Conclusions: Our results suggest a division of labor between Isw1 and Isw2, whereby Isw2 maintains repressive chromatin structure at gene ends while Isw1 has a similar function at mid-coding regions. The differential specificity of the two remodelers may be specified through interactions with particular histone marks.

Gene expression varies widely between closely related species and strains, yet the genetic basis of most differences is still unknown. Several studies suggested that chromatin regulators have a key role in generating expression diversity, predicting a reduction in the interspecies differences on deletion of genes that influence chromatin structure or modifications. To examine this, we compared the genome-wide expression profiles of two closely related yeast species following the individual deletions of eight chromatin regulators and one transcription factor. In all cases, regulator deletions increased, rather than decreased, the expression differences between the species, revealing hidden genetic variability that was masked in the wild-type backgrounds. This effect was not observed for individual deletions of 11 enzymes involved in central metabolic pathways. The buffered variations were associated with trans differences, as revealed by allele-specific profiling of the interspecific hybrids. Our results support the idea that regulatory proteins serve as capacitors that buffer gene expression against hidden genetic variability.

Gene regulation differs greatly between related species, constituting a major source of phenotypic diversity. Recent studies characterized extensive differences in the gene expression programs of closely related species. In contrast, virtually nothing is known about the evolution of chromatin structure and how it influences the divergence of gene expression. Here, we compare the genome-wide nucleosome positioning of two closely related yeast species and, by profiling their inter-specific hybrid, trace the genetic basis of the observed differences into mutations affecting the local DNA sequences (cis effects) or the upstream regulators (trans effects). The majority (∼70%) of inter-species differences is due to cis effects, leaving a significant contribution (30%) for trans factors. We show that cis effects are well explained by mutations in nucleosome-disfavoring AT-rich sequences, but are not associated with divergence of nucleosome-favoring sequences. Differences in nucleosome positioning propagate to multiple adjacent nucleosomes, supporting the statistical positioning hypothesis, and we provide evidence that nucleosome-free regions, but not the 1 nucleosome, serve as stable border elements. Surprisingly, although we find that differential nucleosome positioning among cell types is strongly correlated with differential expression, this does not seem to be the case for evolutionary changes: divergence of nucleosome positioning is excluded from regulatory elements and is not correlated with gene expression divergence, suggesting a primarily neutral mode of evolution. Our results provide evolutionary insights to the genetic determinants and regulatory function of nucleosome positioning.

Evolutionary changes in gene expression are a main driver of phenotypic evolution. In yeast, genes that have rapidly diverged in expression are associated with particular promoter features, including the presence of a TATA box, a nucleosome-covered promoter and unstable tracts of tandem repeats. Here, we discuss how these promoter properties may confer an inherent capacity for flexibility of expression.

Histone monoubiquitylation is implicated in critical regulatory processes. We explored the roles of histone H2B ubiquitylation in human cells by reducing the expression of hBREl/RNF20, the major H2B-specific E3 ubiquitin ligase. While H2B ubiquitylation is broadly associated with transcribed genes, only a subset of genes was transcriptionally affected by RNF20 depletion and abrogation of H2B ubiquitylation. Gene expression dependent on RNF20 includes histones H2A and H2B and the p53 tumor suppressor. In contrast, RNF20 suppresses the expression of several proto-oncogenes, which reside preferentially in closed chromatin and are modestly transcribed despite bearing marks usually associated with high transcription rates. Remarkably, RNF20 depletion augmented the transcriptional effects of epidermal growth factor (EGF), increased cell migration, and elicited transformation and tumorigenesis. Furthermore, frequent RNF20 promoter hypermethylation was observed in tumors. RNF20 may thus be a putative tumor suppressor, acting through selective regulation of a distinct subset of genes.

Chromatin structure is central for the regulation of gene expression, but its genome-wide organization is only beginning to be understood. Here, we examine the connection between patterns of nucleosome occupancy and the capacity to modulate gene expression upon changing conditions, i.e., transcriptional plasticity. By analyzing genome-wide data of nucleosome positioning in yeast, we find that the presence of nucleosomes close to the transcription start site is associated with high transcriptional plasticity, while nucleosomes at more distant upstream positions are negatively correlated with transcriptional plasticity. Based on this, we identify two typical promoter structures associated with low or high plasticity, respectively. The first class is characterized by a relatively large nucleosome-free region close to the start site coupled with well-positioned nucleosomes further upstream, whereas the second class displays a more evenly distributed and dynamic nucleosome positioning, with high occupancy close to the start site. The two classes are further distinguished by multiple promoter features, including histone turnover, binding site locations, H2A.Z occupancy, expression noise, and expression diversity. Analysis of nucleosome positioning in human promoters reproduces the main observations. Our results suggest two distinct strategies for gene regulation by chromatin, which are selectively employed by different genes.

We show that, in yeast, the divergence rate of gene expression is not correlated with that of its associated coding sequence. Gene essentiality influences both modes of evolution, but other properties related to protein structure or promoter composition are only correlated with coding-sequence divergence or gene expression divergence, respectively. Based on these findings, we discuss the possibilities of neutral evolution of gene expression and of different modes of evolution in unicellular versus multicellular organisms.

Recent studies have characterized significant differences in the cis-regulatory sequences of related organisms, but the impact of these differences on gene expression remains largely unexplored. Here, we show that most previously identified differences in transcription factor (TF)-binding sequences of yeasts and mammals have no detectable effect on gene expression, suggesting that compensatory mechanisms allow promoters to rapidly evolve while maintaining a stabilized expression pattern. To examine the impact of changes in cis-regulatory elements in a more controlled setting, we compared the genes induced during mating of three yeast species. This response is governed by a single TF (STE12), and variations in its predicted binding sites can indeed account for about half of the observed expression differences. The remaining unexplained differences are correlated with the increased divergence of the sequences that flank the binding sites and an apparent modulation of chromatin structure. Our analysis emphasizes the flexibility of promoter structure, and highlights the interplay between specific binding sites and general chromatin structure in the control of gene expression.

Comparative analysis is a fundamental tool in biology. Conservation among species greatly assists the detection and characterization of functional elements, whereas inter-species differences are probably the best indicators of biological adaptation. Traditionally, comparative approaches were applied to the analysis of genomic sequences. With the growing availability of functional genomic data, comparative paradigms are now being extended also to the study of other functional attributes, most notably the gene expression. Here we review recent works applying comparative analysis to large-scale gene expression datasets and discuss the central principles and challenges of such approaches.

In Saccharomyces cerevisiae, transcription factor binding sites are found preferentially ∼100-200 bp upstream of the start codon. Here, we show that this region is associated with rigid DNA in promoters lacking a TATA box, but not in TATA-containing promoters. The association of rigid DNA with transcription factor binding sites is conserved in TATA-less promoters from 11 yeast species, whereas the position of the rigid DNA varies substantially among species. Rigid DNA could influence nucleosome positioning and assist in the assembly of the transcriptional machinery at TATA-less promoters.

Background: DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes. Results: In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures. Conclusions: Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data.

Background: Gene duplication provides raw material for the generation of new functions, but most duplicates are rapidly lost due to the initial redundancy in gene function. How gene function diversifies following duplication is largely unclear. Previous studies analyzed the diversification of duplicates by characterizing their coding sequence divergence. However, functional divergence can also be attributed to changes in regulatory properties, such as protein localization or expression, which require only minor changes in gene sequence. Results: We developed a novel method to compare expression profiles from different organisms and applied it to analyze the expression divergence of yeast duplicated genes. The expression profiles of Saccharomyces cerevisiae duplicate pairs were compared with those of their pre-duplication orthologs in Candida albicans. Duplicate pairs were classified into two classes, corresponding to symmetric versus asymmetric rates of expression divergence. The latter class includes 43 duplicate pairs in which only one copy has a significant expression similarity to the C. albicans ortholog. These may present cases of regulatory neofunctionalization, as supported also by their dispensability and variability. Conclusion: Duplicated genes may diversify through regulatory neofunctionalization. Notably, the asymmetry of gene sequence evolution and the asymmetry of gene expression evolution are only weakly correlated, underscoring the importance of expression analysis to elucidate the evolution of novel functions.

Phenotypic diversity is generated through changes in gene structure or gene regulation. The availability of full genomic sequences allows for the analysis of gene sequence evolution. In contrast, little is known about the principles driving the evolution of gene expression. Here we describe the differential transcriptional response of four closely related yeast species to a variety of environmental stresses. Genes containing a TATA box in their promoters show an increased interspecies variability in expression, independent of their functional association. Examining additional data sets, we find that this enhanced expression divergence of TATA-containing genes is consistent across all eukaryotes studied to date, including nematodes, fruit flies, plants and mammals. TATA-dependent regulation may enhance the sensitivity of gene expression to genetic perturbations, thus facilitating expression divergence at particular genetic loci.

Background: High-throughput methods identify an overwhelming number of protein-protein interactions. However, the limited accuracy of these methods results in the false identification of many spurious interactions. Accordingly, the resulting interactions are regarded as hypothetical and computational methods are needed to increase their confidence. Several methods have recently been suggested for this purpose including co-expression as a confidence measure for interacting proteins, but their performance is still quite poor. Results: We introduce a novel computational method for verification of protein-protein interactions based on the co-expression of orthologs of interacting partners. The performance of our method is analysed using known S. cerevisiae interactions, and is shown to overcome limitations of previous methods. We present specific examples of known and putative interactions that are detected by our method and not by previous methods, and suggest that they represent transient interactions that might have been conserved and stabilized in other species. Conclusion: Co-expression of orthologous protein-pairs can be used to increase the confidence of hypothetical protein-protein interactions in S. cerevisiae as well as in other species. This approach may be especially useful for species with no available expression profiles and for transient interactions.

For immune surveillance and function to be effective, T lymphocytes constantly recirculate via lymph and blood between lymphoid organs and body tissues. To enable efficient cell movement and migration, cell adhesion to components of the basement membrane and the extracellular matrix (ECM) must be a rapid and transitory process. Whether phosphorylation and dephosphorylation of cellular proteins are involved in this phenomena was explored by monitoring the adhesion of T cells to immobilized ECM proteins. A short exposure of ⁵¹Cr-labeled human CD4⁺ T cells to phorbol esters in vitro induced a rapid β 1-integrin-mediated adhesion to both fibronectin and laminin, as determined by inhibition with anti-integrin antibodies. Adhesion was reversible; detachment from the immobilized ECM ligands occurred between 20 and 120 min without further intervention. This T cell adhesion was regulated by the activation of protein kinase C because (a) staurosporine and H-7 inhibitors of protein kinase C suppressed T cell adhesion, and (b) PMA-induced down-regulation of intracellular levels of protein kinase C was associated with the abrogation of the T cell adhesiveness to fibronectin and laminin. Furthermore, inhibition of protein phosphatases activity by okadaic acid delayed the detachment of the T cells from fibronectin or laminin. Thus, we suggest that T cell-ECM interactions such as adhesion and detachment are regulated, respectively, by protein kinase C and protein phosphatases.