Mapping human tissues with highly multiplexed RNA in situ hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. There has been a surge of multiplexed RNA in situ mapping techniques but their application to human tissues has been limited due to their large size, general lower tissue quality and high autofluorescence. Here we report DART-FISH, a padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections. We introduce an omni-cell type cytoplasmic stain that substantially improves the segmentation of cell bodies. Our enzyme-free isothermal decoding procedure allows us to image 121 genes in large sections from the human neocortex in <10 h. We successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

Single-cell analyses of metastatic bone marrow in human neuroblastoma reveals microenvironmental remodeling and metastatic signature

Neuroblastoma is an aggressive pediatric cancer with a high rate of metastasis to the BM. Despite intensive treatments including high-dose chemotherapy, the overall survival rate for children with metastatic neuroblastoma remains dismal. Understanding the cellular and molecular mechanisms of the metastatic tumor microenvironment is crucial for developing new therapies and improving clinical outcomes. Here, we used single-cell RNA-Seq to characterize immune and tumor cell alterations in neuroblastoma BM metastases by comparative analysis with patients without metastases. Our results reveal remodeling of the immune cell populations and reprogramming of gene expression profiles in the metastatic niche. In particular, within the BM metastatic niche, we observed the enrichment of immune cells, including tumor-associated neutrophils, macrophages, and exhausted T cells, as well as an increased number of Tregs and a decreased number of B cells. Furthermore, we highlighted cell communication between tumor cells and immune cell populations, and we identified prognostic markers in malignant cells that are associated with worse clinical outcomes in 3 independent neuroblastoma cohorts. Our results provide insight into the cellular, compositional, and transcriptional shifts underlying neuroblastoma BM metastases that contribute to the development of new therapeutic strategies.

Single-cell analysis of immune and stroma cell remodeling in clear cell renal cell carcinoma primary tumors and bone metastatic lesions

BACKGROUND

Despite therapeutic advances, once a cancer has metastasized to the bone, it represents a highly morbid and lethal disease. One third of patients with advanced clear cell renal cell carcinoma (ccRCC) present with bone metastasis at the time of diagnosis. However, the bone metastatic niche in humans, including the immune and stromal microenvironments, has not been well-defined, hindering progress towards identification of therapeutic targets.

METHODS

We collected fresh patient samples and performed single-cell transcriptomic profiling of solid metastatic tissue (Bone Met), liquid bone marrow at the vertebral level of spinal cord compression (Involved), and liquid bone marrow from a different vertebral body distant from the tumor site but within the surgical field (Distal), as well as bone marrow from patients undergoing hip replacement surgery (Benign). In addition, we incorporated single-cell data from primary ccRCC tumors (ccRCC Primary) for comparative analysis.

RESULTS

The bone marrow of metastatic patients is immune-suppressive, featuring increased, exhausted CD8 + cytotoxic T cells, T regulatory cells, and tumor-associated macrophages (TAM) with distinct transcriptional states in metastatic lesions. Bone marrow stroma from tumor samples demonstrated a tumor-associated mesenchymal stromal cell population (TA-MSC) that appears to be supportive of epithelial-to mesenchymal transition (EMT), bone remodeling, and a cancer-associated fibroblast (CAFs) phenotype. This stromal subset is associated with poor progression-free and overall survival and also markedly upregulates bone remodeling through the dysregulation of RANK/RANKL/OPG signaling activity in bone cells, ultimately leading to bone resorption.

CONCLUSIONS

These results provide a comprehensive analysis of the bone marrow niche in the setting of human metastatic cancer and highlight potential therapeutic targets for both cell populations and communication channels.

Gene panel selection for targeted spatial transcriptomics

Targeted spatial transcriptomics hold particular promise in analyzing complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is their reliance on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method performing gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

A pan-tissue survey of mosaic chromosomal alterations in 948 individuals

Genetic mutations accumulate in an organism's body throughout its lifetime. While somatic single-nucleotide variants have been well characterized in the human body, the patterns and consequences of large chromosomal alterations in normal tissues remain largely unknown. Here, we present a pan-tissue survey of mosaic chromosomal alterations (mCAs) in 948 healthy individuals from the Genotype-Tissue Expression project, augmenting RNA-based allelic imbalance estimation with haplotype phasing. We found that approximately a quarter of the individuals carry a clonally-expanded mCA in at least one tissue, with incidence strongly correlated with age. The prevalence and genome-wide patterns of mCAs vary considerably across tissue types, suggesting tissue-specific mutagenic exposure and selection pressures. The mCA landscapes in normal adrenal and pituitary glands resemble those in tumors arising from these tissues, whereas the same is not true for the esophagus and skin. Together, our findings show a widespread age-dependent emergence of mCAs across normal human tissues with intricate connections to tumorigenesis.

Mapping Human Tissues with Highly Multiplexed RNA in situ Hybridization

In situ transcriptomic techniques promise a holistic view of tissue organization and cell-cell interactions. Recently there has been a surge of multiplexed RNA in situ techniques but their application to human tissues and clinical biopsies has been limited due to their large size, general lower tissue quality and high background autofluorescence. Here we report DART-FISH, a versatile padlock probe-based technology capable of profiling hundreds to thousands of genes in centimeter-sized human tissue sections at cellular resolution. We introduced an omni-cell type cytoplasmic stain, dubbed RiboSoma that substantially improves the segmentation of cell bodies. We developed a computational decoding-by-deconvolution workflow to extract gene spots even in the presence of optical crowding. Our enzyme-free isothermal decoding procedure allowed us to image 121 genes in a large section from the human neocortex in less than 10 hours, where we successfully recapitulated the cytoarchitecture of 20 neuronal and non-neuronal subclasses. Additionally, we demonstrated the detection of transcripts as short as 461 nucleotides, including neuropeptides and discovered new cortical layer markers. We further performed in situ mapping of 300 genes on a diseased human kidney, profiled >20 healthy and pathological cell states, and identified diseased niches enriched in transcriptionally altered epithelial cells and myofibroblasts.

An atlas of healthy and injured cell states and niches in the human kidney

Understanding kidney disease relies on defining the complexity of cell types and states, their associated molecular profiles and interactions within tissue neighbourhoods1. Here we applied multiple single-cell and single-nucleus assays (>400,000 nuclei or cells) and spatial imaging technologies to a broad spectrum of healthy reference kidneys (45 donors) and diseased kidneys (48 patients). This has provided a high-resolution cellular atlas of 51 main cell types, which include rare and previously undescribed cell populations. The multi-omic approach provides detailed transcriptomic profiles, regulatory factors and spatial localizations spanning the entire kidney. We also define 28 cellular states across nephron segments and interstitium that were altered in kidney injury, encompassing cycling, adaptive (successful or maladaptive repair), transitioning and degenerative states. Molecular signatures permitted the localization of these states within injury neighbourhoods using spatial transcriptomics, while large-scale 3D imaging analysis (around 1.2 million neighbourhoods) provided corresponding linkages to active immune responses. These analyses defined biological pathways that are relevant to injury time-course and niches, including signatures underlying epithelial repair that predicted maladaptive states associated with a decline in kidney function. This integrated multimodal spatial cell atlas of healthy and diseased human kidneys represents a comprehensive benchmark of cellular states, neighbourhoods, outcome-associated signatures and publicly available interactive visualizations.

Gene panel selection for targeted spatial transcriptomics

Targeted spatial transcriptomics hold particular promise in analysis of complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is that they rely on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method to perform gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

Dissection of gastric homeostasis in vivo facilitates permanent capture of isthmus-like stem cells in vitro

The glandular stomach is composed of two regenerative compartments termed corpus and antrum, and our understanding of the transcriptional networks that maintain these tissues is incomplete. Here we show that cell types with equivalent functional roles in the corpus and antrum share similar transcriptional states including the poorly characterized stem cells of the isthmus region. To further study the isthmus, we developed a monolayer two-dimensional (2D) culture system that is continually maintained by Wnt-responsive isthmus-like cells capable of differentiating into several gastric cell types. Importantly, 2D cultures can be converted into conventional three-dimensional organoids, modelling the plasticity of gastric epithelial cells in vivo. Finally, we utilized the 2D culture system to show that Sox2 is both necessary and sufficient to generate enterochromaffin cells. Together, our data provide important insights into gastric homeostasis, establish a tractable culture system to capture isthmus cells and uncover a role for Sox2 in enterochromaffin cells.

Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes

Genome instability and aberrant alterations of transcriptional programs both play important roles in cancer. Single-cell RNA sequencing (scRNA-seq) has the potential to investigate both genetic and nongenetic sources of tumor heterogeneity in a single assay. Here we present a computational method, Numbat, that integrates haplotype information obtained from population-based phasing with allele and expression signals to enhance detection of copy number variations from scRNA-seq. Numbat exploits the evolutionary relationships between subclones to iteratively infer single-cell copy number profiles and tumor clonal phylogeny. Analysis of 22 tumor samples, including multiple myeloma, gastric, breast and thyroid cancers, shows that Numbat can reconstruct the tumor copy number profile and precisely identify malignant cells in the tumor microenvironment. We identify genetic subpopulations with transcriptional signatures relevant to tumor progression and therapy resistance. Numbat requires neither sample-matched DNA data nor a priori genotyping, and is applicable to a wide range of experimental settings and cancer types.

Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses

The treatment of low-risk primary prostate cancer entails active surveillance only, while high-risk disease requires multimodal treatment including surgery, radiation therapy, and hormonal therapy. Recurrence and development of metastatic disease remains a clinical problem, without a clear understanding of what drives immune escape and tumor progression. Here, we comprehensively describe the tumor microenvironment of localized prostate cancer in comparison with adjacent normal samples and healthy controls. Single-cell RNA sequencing and high-resolution spatial transcriptomic analyses reveal tumor context dependent changes in gene expression. Our data indicate that an immune suppressive tumor microenvironment associates with suppressive myeloid populations and exhausted T-cells, in addition to high stromal angiogenic activity. We infer cell-to-cell relationships from high throughput ligand-receptor interaction measurements within undissociated tissue sections. Our work thus provides a highly detailed and comprehensive resource of the prostate tumor microenvironment as well as tumor-stromal cell interactions.

scFates: a scalable python package for advanced pseudotime and bifurcation analysis from single-cell data

SUMMARY

scFates provides an extensive toolset for the analysis of dynamic trajectories comprising tree learning, feature association testing, branch differential expression and with a focus on cell biasing and fate splits at the level of bifurcations. It is meant to be fully integrated into the scanpy ecosystem for seamless analysis of trajectories from single-cell data of various modalities (e.g. RNA and ATAC).

AVAILABILITY AND IMPLEMENTATION

scFates is released as open-source software under the BSD 3-Clause 'New' License and is available from the Python Package Index at https://pypi.org/project/scFates/. The source code is available on GitHub at https://github.com/LouisFaure/scFates/. Code reproduction and tutorials on published datasets are available on GitHub at https://github.com/LouisFaure/scFates_notebooks.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging

Tissue function depends on cellular organization. While the properties of individual cells are increasingly being deciphered using powerful single-cell sequencing technologies, understanding their spatial organization and temporal evolution remains a major challenge. Here, we present Image-seq, a technology that provides single-cell transcriptional data on cells that are isolated from specific spatial locations under image guidance, thus preserving the spatial information of the target cells. It is compatible with in situ and in vivo imaging and can document the temporal and dynamic history of the cells being analyzed. Cell samples are isolated from intact tissue and processed with state-of-the-art library preparation protocols. The technique therefore combines spatial information with highly sensitive RNA sequencing readouts from individual, intact cells. We have used both high-throughput, droplet-based sequencing as well as SMARTseq-v4 library preparation to demonstrate its application to bone marrow and leukemia biology. We discovered that DPP4 is a highly upregulated gene during early progression of acute myeloid leukemia and that it marks a more proliferative subpopulation that is confined to specific bone marrow microenvironments. Furthermore, the ability of Image-seq to isolate viable, intact cells should make it compatible with a range of downstream single-cell analysis tools including multi-omics protocols.

Upper cortical layer-driven network impairment in schizophrenia

Schizophrenia is one of the most widespread and complex mental disorders. To characterize the impact of schizophrenia, we performed single-nucleus RNA sequencing (snRNA-seq) of >220,000 neurons from the dorsolateral prefrontal cortex of patients with schizophrenia and matched controls. In addition, >115,000 neurons were analyzed topographically by immunohistochemistry. Compositional analysis of snRNA-seq data revealed a reduction in abundance of GABAergic neurons and a concomitant increase in principal neurons, most pronounced for upper cortical layer subtypes, which was substantiated by histological analysis. Many neuronal subtypes showed extensive transcriptomic changes, the most marked in upper-layer GABAergic neurons, including down-regulation in energy metabolism and up-regulation in neurotransmission. Transcription factor network analysis demonstrated a developmental origin of transcriptomic changes. Last, Visium spatial transcriptomics further corroborated upper-layer neuron vulnerability in schizophrenia. Overall, our results point toward general network impairment within upper cortical layers as a core substrate associated with schizophrenia symptomatology.

A transcriptional metastatic signature predicts survival in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer in adults. When ccRCC is localized to the kidney, surgical resection or ablation of the tumor is often curative. However, in the metastatic setting, ccRCC remains a highly lethal disease. Here we use fresh patient samples that include treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. Single-cell transcriptomic analysis of tumor cells from the primary tumors reveals a distinct transcriptional signature that is predictive of metastatic potential and patient survival. Analysis of supporting stromal cells within the tumor environment demonstrates vascular remodeling within the endothelial cells. An in silico cell-to-cell interaction analysis highlights the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets. Our findings provide biological insights into the interplay between tumor cells and the ccRCC microenvironment.

Metastatic clear cell renal cell carcinoma has a poor prognosis. Here, the authors use single cell RNA-seq to show a distinct gene expression signature in the primary tumour of metastatic patients, and highlights immune cell receptor interactions as potential therapeutic targets.

The immune cell atlas of human neuroblastoma

Understanding the complete immune cell composition of human neuroblastoma (NB) is crucial for the development of immunotherapeutics. Here, we perform single-cell RNA sequencing (scRNA-seq) on 19 human NB samples coupled with multiplex immunohistochemistry, survival analysis, and comparison with normal fetal adrenal gland data. We provide a comprehensive immune cell landscape and characterize cell-state changes from normal tissue to NB. Our analysis reveals 27 immune cell subtypes, including distinct subpopulations of myeloid, NK, B, and T cells. Several different cell types demonstrate a survival benefit. In contrast to adult cancers and previous NB studies, we show an increase in inflammatory monocyte cell state when contrasting normal and tumor tissue, while no differences in cytotoxicity and exhaustion score for T cells, nor in Treg activity, are observed. Our receptor-ligand interaction analysis reveals a highly complex interactive network of the NB microenvironment from which we highlight several interactions that we suggest for future therapeutic studies.

•

27 different immune subtypes form a complex neuroblastoma microenvironment

•

Inflammatory monocytes correlate with neuroblastoma disease progression

•

Active NK cells correlate with improved survival in human neuroblastoma

•

T cell exhaustion and Treg activity demonstrate no difference between risk groups

Abstract 982: A new transcriptional metastatic signature predicts survival in clear cell renal cell carcinoma

Introduction: Renal cell carcinoma, particularly the clear cell histological subtype (ccRCC), is the most common kidney cancer in adults, accounting for 75-85% of all cases. When it is localized to the kidney, it is often cured with surgical resection or thermal ablation. One quarter of the patients have evidence of metastatic disease at the time of diagnosis, and in this setting ccRCC still is a highly lethal disease with few effective treatment options. In this study we used single-cell RNA-sequencing to characterize tumor cell clonality, metastatic signatures and the tumor microenvironment in ccRCC at the single-cell level.

Methodological approach: Here we took advantage of fresh patient samples that included treatment-naive primary tumor tissue, matched adjacent normal kidney tissue, as well as tumor samples collected from patients with bone metastases. We used single cell RNA sequencing (10X Genomics, Chromium 3’ v2 kit, 10x Genomics), that was analyzed with PAGODA and CONOS.

Summary of new unpublished data: Our analysis revealed a distinct transcriptional signature that predicts metastatic potential and patient survival was disclosed through the single-cell analysis. In-depth exploration of the supporting stromal cells displayed a phenotype of vascular remodeling within the endothelial cells. The fibroblasts showed a proliferative signature that was associated with poor survival. An in silico cell-to-cell interaction analysis highlighted the CXCL9/CXCL10-CXCR3 axis and the CD70-CD27 axis as potential therapeutic targets.

Conclusions: Our discoveries in ccRCC provide complementary biological insights, specifically in the interplay between tumor cells and their microenvironment in ccRCC. We demonstrate important biological insights into ccRCC biology including: (1) identification of a distinct metastatic signature that predicts survival outcome, (2) discovery of a proximal tubule cell population that may represent the ccRCC cell of origin, and (3) a detailed exploration in the immunosuppressive environment and the stromal alterations in treatment-naïve patients. In addition, we stress potential therapeutic targets for further evaluation in preclinical models.

Citation Format: Adele Mirna Alchahin, Shenglin Mei, Ioanna Tsea, Taghreed Hirz, Youmna Kfoury, Douglas Dahl, Chin-Lee Wu, Alexander O. Subtelny, Shulin WU, David T. Scadden, John H. Shin, Philip J. Saylor, David B. Sykes, Peter V. Kharchenko, Ninib Baryawno. A new transcriptional metastatic signature predicts survival in clear cell renal cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 982.

Abstract 2510: An atlas of single-cell and spatial transcriptomics reveals alterations that correlate with human prostate cancer progression

Most systemic therapies for prostate cancer target androgen receptor signaling. Given the ongoing disease burden and mortality from advanced prostate cancer that persist despite available therapies, novel therapeutic targets are clearly needed.

To this end, we conducted a high-resolution analysis of primary prostate cancer samples across a spectrum of tumor stage using 10x Chromium scRNAseq. Within each patient, we compared the prostate tumor to its adjacent normal tissue. These samples were also compared to healthy prostate samples collected from patients whose prostates were removed in the setting of bladder cancer surgery.

Joint analysis revealed a rich repertoire of immune and non-immune stroma cells. Significant alterations were apparent in the prostate tumor microenvironment compared to adjacent normal and healthy samples. One striking difference was an expansion of T-cell cluster characterized by decreased cytotoxic and an increased exhaustion gene signatures. Another difference was the significantly higher regulatory T cell (Treg) activity.

There was a substantial population shift within the myeloid compartment. Specifically, tumor tissue showed a selective enrichment in M2-like macrophages which was validated by multiplex immunohistochemistry. In addition, tumor tissue showed a significant increase in the myeloid-derived suppressor cell scoring in tumor inflammatory monocytes that strongly correlated with Treg activity. The changes in both myeloid and T cell gene expression suggest an immune suppressive environment within the tumor.

In addition, we performed Slide-seqV2 to generate high spatial resolution maps of cellular organization of prostate tissues. The highly detailed spatial configuration of the healthy prostate tissue showed well-organized prostate epithelial glands surrounded by immune and non-immune stromal cells. This tissue architecture was severely disrupted within the cancerous prostate. Endothelial and fibroblast populations were disorganized and dispersed throughout the invading tumor. Context-dependent differential expression gene analysis on endothelial cells showed significant upregulation of sprouting angiogenesis and vascular endothelial growth factor pathways in the tumor context. In addition, we developed an approach to characterize the coordination between tumor cells and stromal compartment via spatial ligand-receptor (L/R) interaction. Data revealed 405 significant potential communication channels with many of these interactions known to have a role in prostate tumor angiogenesis and progression.

These data provide a high resolution landscape of localized prostate cancer via 10x and Slide-seq. Data showed an immunosuppressive milieu in addition to highly active endothelial angiogenic program. L/R interaction analysis revealed interactions that may serve as potential therapeutic targets.

Citation Format: Taghreed Hirz, Shenglin Mei, Hirak Sarkar, Youmna Kfoury, Shulin Wu, Chin-Lee Wu, Fei Chen, Evan Z. Macosko, Douglas M. Dahl, Ninib Baryawno, David T. Scadden, Philip J. Saylor, Peter V. Kharchenko, David B. Sykes. An atlas of single-cell and spatial transcriptomics reveals alterations that correlate with human prostate cancer progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2510.

Abstract 6215: The immune cell atlas of human neuroblastoma

Our current knowledge of the different immune cells in neuroblastoma is based on in vitro and in vivo studies mainly focusing on a single cell type. Different studies have conveyed conflicting results and despite the use of anti-GD2 immunotherapy in the clinic, a comprehensive immune cell overview at the single-cell level is still missing and understanding the complete composition of immune cells neuroblastoma will be crucial for the development of novel immunotherapeutics against the disease. In this study, we performed single-cell RNA-sequencing on human neuroblastoma coupled with multiplex immunohistochemistry and survival analysis to provide a complete cellular and molecular immune cell landscape of human neuroblastoma. Further, we contrasted the neuroblastoma data with single-cell RNA-sequencing data from normal fetal adrenal gland to characterize cell-state changes from normal tissue to neuroblastoma. Our analysis revealed 27 immune cell subtypes including distinct subpopulations of myeloid, NK, B and T cells that were associated with a survival benefit. Multiple subtypes of B and NK cells, not seen in neuroblastoma before, were identified. We propose the presence of tertiary lymphoid structures and showed that Active NK cells correlated with improved survival. In contrast to adult cancers, we detected no difference in cytotoxicity and exhaustion score for cytotoxic T cells, nor Treg activity. However, we demonstrated an increase in inflammatory monocyte signature score from normal to tumor derived myeloid cells. Finally, we performed receptor-ligand interaction analysis between tumor, stroma and immune cells, where we highlight several interactions that we suggest for future studies of how to exploit immune cells as a therapeutic option in neuroblastoma. Our findings significantly broaden the understanding of the immune composition in neuroblastoma and provides a resource for the development of novel immunotherapeutics.

Citation Format: Bronte Manouk Verhoeven, Shenglin Mei, Thale K. Olsen, Karin K. Gustafsson, Anders Valind, Axel Lindström, David G. Nord, Shahrzad S. Fard, Catharina Hagerling, Peter V. Kharchenko, Per Kogner, John I. Johnsen, Ninib Baryawno. The immune cell atlas of human neuroblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6215.

Liver stromal cells restrict macrophage maturation and stromal IL-6 limits the differentiation of cirrhosis-linked macrophages

BACKGROUND & AIMS

Myeloid cells are key regulators of cirrhosis, a major cause of mortality worldwide. Because stromal cells can modulate the functionality of myeloid cells in vitro, targeting stromal-myeloid interactions has become an attractive potential therapeutic strategy. We aimed to investigate how human liver stromal cells impact myeloid cell properties and to understand the utility of a stromal-myeloid coculture system to study these interactions in the context of cirrhosis.

METHODS

Single-cell RNA-sequencing analyses of non-cirrhotic (n = 7) and cirrhotic (n = 5) human liver tissue were correlated to the bulk RNA-sequencing results of in vitro cocultured human CD14⁺ and primary liver stromal cells. Complimentary mechanistic experiments and flow cytometric analysis were performed on human liver stromal-myeloid coculture systems.

RESULTS

We found that stromal-myeloid coculture reduces the frequency CD14⁺ cell subsets transcriptionally similar to liver macrophages, showing that stromal cells inhibit the maturation of monocytes into macrophages. Stromal cells also influenced in vitro macrophage differentiation by skewing away from cirrhosis-linked CD9⁺ scar-associated macrophage-like cells and towards CD163⁺ Kupffer cell-like macrophages. We identify IL-6 production as a mechanism by which stromal cells limit CD9⁺ macrophage differentiation and find that local IL-6 levels are decreased in early-stage human liver disease compared to healthy liver tissue, suggesting a protective role for local IL-6 in the healthy liver.

CONCLUSIONS

Our work reveals an unanticipated role for liver stromal cells in impeding the maturation and altering the differentiation of macrophages and should prompt investigations into the role of local IL-6 production in the pathogenesis of liver disease. These studies provide a framework for investigating macrophage-stromal interactions during cirrhosis.

LAY SUMMARY

The impact of human liver stromal cells on myeloid cell maturation and differentiation in liver disease is incompletely understood. In this study, we present a mechanistic analysis using a primary in vitro human liver stromal-myeloid coculture system that is translated to liver disease using single-cell RNA sequencing analysis of cirrhotic and non-cirrhotic human liver tissue. Our work supports a role for stromal cell contact in restricting macrophage maturation and for stromal-derived IL-6 in limiting the differentiation of a cirrhotic macrophage subset.

Human prostate cancer bone metastases have an actionable immunosuppressive microenvironment

Bone metastases are devastating complications of cancer. They are particularly common in prostate cancer (PCa), represent incurable disease, and are refractory to immunotherapy. We seek to define distinct features of the bone marrow (BM) microenvironment by analyzing single cells from bone metastatic prostate tumors, involved BM, uninvolved BM, and BM from cancer-free, orthopedic patients, and healthy individuals. Metastatic PCa is associated with multifaceted immune distortion, specifically exhaustion of distinct T cell subsets, appearance of macrophages with states specific to PCa bone metastases. The chemokine CCL20 is notably overexpressed by myeloid cells, as is its cognate CCR6 receptor on T cells. Disruption of the CCL20-CCR6 axis in mice with syngeneic PCa bone metastases restores T cell reactivity and significantly prolongs animal survival. Comparative high-resolution analysis of PCa bone metastases shows a targeted approach for relieving local immunosuppression for therapeutic effect.

Cell type ontologies of the Human Cell Atlas

Massive single-cell profiling efforts have accelerated our discovery of the cellular composition of the human body while at the same time raising the need to formalize this new knowledge. Here, we discuss current efforts to harmonize and integrate different sources of annotations of cell types and states into a reference cell ontology. We illustrate with examples how a unified ontology can consolidate and advance our understanding of cell types across scientific communities and biological domains.

Rewiring of human neurodevelopmental gene regulatory programs by human accelerated regions

Human accelerated regions (HARs) are the fastest-evolving regions of the human genome, and many are hypothesized to function as regulatory elements that drive human-specific gene regulatory programs. We interrogate the in vitro enhancer activity and in vivo epigenetic landscape of more than 3,100 HARs during human neurodevelopment, demonstrating that many HARs appear to act as neurodevelopmental enhancers and that sequence divergence at HARs has largely augmented their neuronal enhancer activity. Furthermore, we demonstrate PPP1R17 to be a putative HAR-regulated gene that has undergone remarkable rewiring of its cell type and developmental expression patterns between non-primates and primates and between non-human primates and humans. Finally, we show that PPP1R17 slows neural progenitor cell cycle progression, paralleling the cell cycle length increase seen predominantly in primate and especially human neurodevelopment. Our findings establish HARs as key components in rewiring human-specific neurodevelopmental gene regulatory programs and provide an integrated resource to study enhancer activity of specific HARs.

Cell segmentation in imaging-based spatial transcriptomics

Single-molecule spatial transcriptomics protocols based on in situ sequencing or multiplexed RNA fluorescent hybridization can reveal detailed tissue organization. However, distinguishing the boundaries of individual cells in such data is challenging and can hamper downstream analysis. Current methods generally approximate cells positions using nuclei stains. We describe a segmentation method, Baysor, that optimizes two-dimensional (2D) or three-dimensional (3D) cell boundaries considering joint likelihood of transcriptional composition and cell morphology. While Baysor can take into account segmentation based on co-stains, it can also perform segmentation based on the detected transcripts alone. To evaluate performance, we extend multiplexed error-robust fluorescence in situ hybridization (MERFISH) to incorporate immunostaining of cell boundaries. Using this and other benchmarks, we show that Baysor segmentation can, in some cases, nearly double the number of cells compared to existing tools while reducing segmentation artifacts. We demonstrate that Baysor performs well on data acquired using five different protocols, making it a useful general tool for analysis of imaging-based spatial transcriptomics.

Comparative cellular analysis of motor cortex in human, marmoset and mouse

The primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch-seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

Single-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1-3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas-containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities-is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

A multimodal cell census and atlas of the mammalian primary motor cortex

Here we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Our results advance the collective knowledge and understanding of brain cell-type organization1-5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

Diversity of developing peripheral glia revealed by single-cell RNA sequencing

The peripheral nervous system responds to a wide variety of sensory stimuli, a process that requires great neuronal diversity. These diverse neurons are closely associated with glial cells originating from the neural crest. However, the molecular nature and diversity among peripheral glia are not understood. Here, we used single-cell RNA sequencing to profile developing and mature glia from somatosensory dorsal root ganglia and auditory spiral ganglia. We found that glial precursors (GPs) in these two systems differ in their transcriptional profiles. Despite their unique features, somatosensory and auditory GPs undergo convergent differentiation to generate molecularly uniform myelinating and non-myelinating Schwann cells. By contrast, somatosensory and auditory satellite glial cells retain system-specific features. Lastly, we identified a glial signature gene set, providing new insights into commonalities among glia across the nervous system. This survey of gene expression in peripheral glia constitutes a resource for understanding functions of glia across different sensory modalities.

Population sequencing data reveal a compendium of mutational processes in the human germ line

Biological mechanisms underlying human germline mutations remain largely unknown. We statistically decompose variation in the rate and spectra of mutations along the genome using volume-regularized nonnegative matrix factorization. The analysis of a sequencing dataset (TOPMed) reveals nine processes that explain the variation in mutation properties between loci. We provide a biological interpretation for seven of these processes. We associate one process with bulky DNA lesions that are resolved asymmetrically with respect to transcription and replication. Two processes track direction of replication fork and replication timing, respectively. We identify a mutagenic effect of active demethylation primarily acting in regulatory regions and a mutagenic effect of long interspersed nuclear elements. We localize a mutagenic process specific to oocytes from population sequencing data. This process appears transcriptionally asymmetric.

RNA velocity-current challenges and future perspectives

RNA velocity has enabled the recovery of directed dynamic information from single-cell transcriptomics by connecting measurements to the underlying kinetics of gene expression. This approach has opened up new ways of studying cellular dynamics. Here, we review the current state of RNA velocity modeling approaches, discuss various examples illustrating limitations and potential pitfalls, and provide guidance on how the ensuing challenges may be addressed. We then outline future directions on how to generalize the concept of RNA velocity to a wider variety of biological systems and modalities.

The triumphs and limitations of computational methods for scRNA-seq

The rapid progress of protocols for sequencing single-cell transcriptomes over the past decade has been accompanied by equally impressive advances in the computational methods for analysis of such data. As capacity and accuracy of the experimental techniques grew, the emerging algorithm developments revealed increasingly complex facets of the underlying biology, from cell type composition to gene regulation to developmental dynamics. At the same time, rapid growth has forced continuous reevaluation of the underlying statistical models, experimental aims, and sheer volumes of data processing that are handled by these computational tools. Here, I review key computational steps of single-cell RNA sequencing (scRNA-seq) analysis, examine assumptions made by different approaches, and highlight successes, remaining ambiguities, and limitations that are important to keep in mind as scRNA-seq becomes a mainstream technique for studying biology.

Distinct evolutionary paths in chronic lymphocytic leukemia during resistance to the graft-versus-leukemia effect

Leukemic relapse remains a major barrier to successful allogeneic hematopoietic stem cell transplantation (allo-HSCT) for aggressive hematologic malignancies. The basis for relapse of advanced lymphoid malignancies remains incompletely understood and may involve escape from the graft-versus-leukemia (GvL) effect. We hypothesized that for patients with chronic lymphocytic leukemia (CLL) treated with allo-HSCT, leukemic cell-intrinsic features influence transplant outcomes by directing the evolutionary trajectories of CLL cells. Integrated genetic, transcriptomic, and epigenetic analyses of CLL cells from 10 patients revealed that the clinical kinetics of post-HSCT relapse are shaped by distinct molecular dynamics. Early relapses after allo-HSCT exhibited notable genetic stability; single CLL cell transcriptional analysis demonstrated a cellular heterogeneity that was static over time. In contrast, CLL cells relapsing late after allo-HSCT displayed notable genetic evolution and evidence of neoantigen depletion, consistent with marked single-cell transcriptional shifts that were unique to each patient. We observed a greater rate of epigenetic change for late relapses not seen in early relapses or relapses after chemotherapy alone, suggesting that the selection pressures of the GvL bottleneck are unlike those imposed by chemotherapy. No selective advantage for human leukocyte antigen (HLA) loss was observed, even when present in pretransplant subpopulations. Gain of stem cell modules was a common signature associated with leukemia relapse regardless of posttransplant relapse kinetics. These data elucidate the biological pathways that underlie GvL resistance and posttransplant relapse.

Single-cell transcriptomics of human embryos identifies multiple sympathoblast lineages with potential implications for neuroblastoma origin

Characterization of the progression of cellular states during human embryogenesis can provide insights into the origin of pediatric diseases. We examined the transcriptional states of neural crest- and mesoderm-derived lineages differentiating into adrenal glands, kidneys, endothelium and hematopoietic tissue between post-conception weeks 6 and 14 of human development. Our results reveal transitions connecting the intermediate mesoderm and progenitors of organ primordia, the hematopoietic system and endothelial subtypes. Unexpectedly, by using a combination of single-cell transcriptomics and lineage tracing, we found that intra-adrenal sympathoblasts at that stage are directly derived from nerve-associated Schwann cell precursors, similarly to local chromaffin cells, whereas the majority of extra-adrenal sympathoblasts arise from the migratory neural crest. In humans, this process persists during several weeks of development within the large intra-adrenal ganglia-like structures, which may also serve as reservoirs of originating cells in neuroblastoma.

Abstract IA23: Impact of metastatic prostate cancer on human bone marrow

Cancer-related mortality due to solid tumor malignancies is overwhelmingly due to the development and progression of metastases. In advanced prostate cancer, metastases most often involve the bone and generally represent incurable disease. It remains unclear what aspects of the bone marrow microenvironment make it hospitable to metastatic dissemination. Similarly, the impact of the metastatic tumor on hematopoiesis and the marrow immune response is poorly understood. We took advantage of rare spinal cord decompression surgeries to profile marrow and metastatic tumors from men with advanced prostate cancer at single-cell resolution. Our analysis contrasts the cellular composition and transcriptional states in matched samples of tumor and liquid bone marrow collected at adjacent vertebral body levels, as well as bone marrow of orthopedic patients without malignancy. Metastatic prostate cancer was associated with hematopoietic suppression and multifaceted immune distortion. There was exhaustion of specific T cell subsets, appearance of inflammatory monocytes and macrophages, and alteration of cytokine profiles. Computational analysis showed association between the presence of specific myeloid subsets and the level of T lymphocyte dysfunction in the tumor fraction. We screened for potential signaling axes that may underlie this interaction. Among them was chemokine CCL20, notably overexpressed by myeloid cells, as was its cognate CCR6 receptor, expressed on T cells. We developed a syngeneic mouse model of bone-metastatic prostate cancer to explore this observation, and demonstrated that disruption of the CCL20-CCR6 axis from either side resulted in significant prolongation of survival. Our results further indicated that this dual overexpression was associated with repressed immune responses. Overall, comparative high-resolution analysis of bone marrow reveals distinct alterations associated with prostate cancer bone metastases that may be amenable to therapeutic targeting with the goal of altering cancer progression.

Citation Format: Ninib Baryawno, Youmna Kfoury, Nicolas Severe, Shenglin Mei, Karin Gustafsson, Taghreed Hirz, Thomas Brouse, Elizabeth W. Scadden, Anna A. Igolkina, Bryan D. Choi, Nikolas Barkas, John H. Shin, Philip J. Saylor, David T. Scadden, David B. Sykes, Peter V. Kharchenko, as part of the Boston Bone Metastasis Consortium. Impact of metastatic prostate cancer on human bone marrow [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr IA23.

Identification of epilepsy-associated neuronal subtypes and gene expression underlying epileptogenesis

Epilepsy is one of the most common neurological disorders, yet its pathophysiology is poorly understood due to the high complexity of affected neuronal circuits. To identify dysfunctional neuronal subtypes underlying seizure activity in the human brain, we have performed single-nucleus transcriptomics analysis of >110,000 neuronal transcriptomes derived from temporal cortex samples of multiple temporal lobe epilepsy and non-epileptic subjects. We found that the largest transcriptomic changes occur in distinct neuronal subtypes from several families of principal neurons (L5-6_Fezf2 and L2-3_Cux2) and GABAergic interneurons (Sst and Pvalb), whereas other subtypes in the same families were less affected. Furthermore, the subtypes with the largest epilepsy-related transcriptomic changes may belong to the same circuit, since we observed coordinated transcriptomic shifts across these subtypes. Glutamate signaling exhibited one of the strongest dysregulations in epilepsy, highlighted by layer-wise transcriptional changes in multiple glutamate receptor genes and strong upregulation of genes coding for AMPA receptor auxiliary subunits. Overall, our data reveal a neuronal subtype-specific molecular phenotype of epilepsy.

The pathophysiology of epilepsy is unclear. Here, the authors present single-nuclei transcriptomic profiling of human temporal lobe epilepsy from patients. They identified epilepsy-associated neuronal subtypes, and a panel of dysregulated genes, predicting neuronal circuits contributing to epilepsy.

Dental cell type atlas reveals stem and differentiated cell types in mouse and human teeth

Understanding cell types and mechanisms of dental growth is essential for reconstruction and engineering of teeth. Therefore, we investigated cellular composition of growing and non-growing mouse and human teeth. As a result, we report an unappreciated cellular complexity of the continuously-growing mouse incisor, which suggests a coherent model of cell dynamics enabling unarrested growth. This model relies on spatially-restricted stem, progenitor and differentiated populations in the epithelial and mesenchymal compartments underlying the coordinated expansion of two major branches of pulpal cells and diverse epithelial subtypes. Further comparisons of human and mouse teeth yield both parallelisms and differences in tissue heterogeneity and highlight the specifics behind growing and non-growing modes. Despite being similar at a coarse level, mouse and human teeth reveal molecular differences and species-specific cell subtypes suggesting possible evolutionary divergence. Overall, here we provide an atlas of human and mouse teeth with a focus on growth and differentiation.

Joint analysis of heterogeneous single-cell RNA-seq dataset collections

Single-cell RNA sequencing is often applied in study designs that include multiple individuals, conditions or tissues. To identify recurrent cell subpopulations in such heterogeneous collections, we developed Conos, an approach that relies on multiple plausible inter-sample mappings to construct a global graph connecting all measured cells. The graph enables identification of recurrent cell clusters and propagation of information between datasets in multi-sample or atlas-scale collections.

Spatiotemporal structure of cell fate decisions in murine neural crest

Neural crest cells are embryonic progenitors that generate numerous cell types in vertebrates. With single-cell analysis, we show that mouse trunk neural crest cells become biased toward neuronal lineages when they delaminate from the neural tube, whereas cranial neural crest cells acquire ectomesenchyme potential dependent on activation of the transcription factor Twist1. The choices that neural crest cells make to become sensory, glial, autonomic, or mesenchymal cells can be formalized as a series of sequential binary decisions. Each branch of the decision tree involves initial coactivation of bipotential properties followed by gradual shifts toward commitment. Competing fate programs are coactivated before cells acquire fate-specific phenotypic traits. Determination of a specific fate is achieved by increased synchronization of relevant programs and concurrent repression of competing fate programs.

RNA velocity of single cells

RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity-the time derivative of the gene expression state-can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

dropEst: pipeline for accurate estimation of molecular counts in droplet-based single-cell RNA-seq experiments

Recent single-cell RNA-seq protocols based on droplet microfluidics use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data creates challenges for subsequent computational processing and troubleshooting of these experiments, with few software options currently available. Here, we describe a flexible pipeline for processing droplet-based transcriptome data that implements barcode corrections, classification of cell quality, and diagnostic information about the droplet libraries. We introduce advanced methods for correcting composition bias and sequencing errors affecting cellular and molecular barcodes to provide more accurate estimates of molecular counts in individual cells.

Multipotent peripheral glial cells generate neuroendocrine cells of the adrenal medulla

Adrenaline is a fundamental circulating hormone for bodily responses to internal and external stressors. Chromaffin cells of the adrenal medulla (AM) represent the main neuroendocrine adrenergic component and are believed to differentiate from neural crest cells. We demonstrate that large numbers of chromaffin cells arise from peripheral glial stem cells, termed Schwann cell precursors (SCPs). SCPs migrate along the visceral motor nerve to the vicinity of the forming adrenal gland, where they detach from the nerve and form postsynaptic neuroendocrine chromaffin cells. An intricate molecular logic drives two sequential phases of gene expression, one unique for a distinct transient cellular state and another for cell type specification. Subsequently, these programs down-regulate SCP-gene and up-regulate chromaffin cell-gene networks. The AM forms through limited cell expansion and requires the recruitment of numerous SCPs. Thus, peripheral nerves serve as a stem cell niche for neuroendocrine system development.

Abstract 27: Integrated analysis of targeted single-cell genetic and transcriptional heterogeneity suggests novel drivers of chronic lymphocytic leukemia

Intratumoral genetic heterogeneity has been characterized across cancers, including chronic lymphocytic leukemia (CLL), and presents challenges to therapy as presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. While insights have been previously gained from bulk analysis, further characterization on the single-cell level is needed to more accurately dissect the pathway and regulatory features associated with distinct genetic subclones. In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples.

To precisely establish the subclonal architecture of the five CLL samples, we first applied targeted single-cell DNA sequencing for detection of mutation and copy number variation using CLL samples previously characterized by bulk whole exome sequencing (WES). Our results identified multiple genetically distinct subclones in four out of five CLL samples. Next, to understand the subclonal architecture and their associated gene expression pattern, we performed single-cell whole transcriptome sequencing (scRNA-seq) and pathway and geneset overdispersion analysis. Although scRNA-seq identified clear transcriptional heterogeneity, these data could neither be used to confidently resolve the genetic subclone structure nor assess the correspondence of genetic structure with the observed transcriptional heterogeneity due to sparseness of coverage at mutation sites of interest. Thus, we developed a targeted RNA approach to assess transcript expression profiles and mutational status in the same single cells. Our approach reliably detects subclonal mutations and enables recapitulation of single-cell DNA information, including phylogenetic structure. Integrative analysis to correlate genotype and phenotype reveals phenotypic convergence between distinct subclones and prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Specifically, by clearly resolving phylogenic relationships and simultaneously assessing DNA and RNA-level information from the same single cells, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways.

Overall, we demonstrate the ability to robustly integrate DNA- and RNA-level information in order to dissect the impact of somatic mutations on cellular phenotype. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells leading to an increased understanding of driving events in malignancy.

Citation Format: Jean Fan, Lili Wang, Joshua M. Francis, George Georghiou, Sarah Hergert, Shuqiang Li, Rutendo Gambe, Chensheng W. Zhou, Chunxiao Yang, Sheng Xiao, Paola Dal Chin, Michaela Bowden, Dylan Kotliar, Sachet A. Shukla, Jennifer R. Brown, Donna Neuberg, Dario R. Alessi, Cheng-Zhong Zhang, Peter V. Kharchenko, Kenneth J. Livak, Catherine J. Wu. Integrated analysis of targeted single-cell genetic and transcriptional heterogeneity suggests novel drivers of chronic lymphocytic leukemia [abstract]. In: Proceedings of the Second AACR Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; May 6-9, 2017; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(24_Suppl):Abstract nr 27.

Rapid Mobilization Reveals a Highly Engraftable Hematopoietic Stem Cell

Hematopoietic stem cell transplantation is a potential curative therapy for malignant and nonmalignant diseases. Improving the efficiency of stem cell collection and the quality of the cells acquired can broaden the donor pool and improve patient outcomes. We developed a rapid stem cell mobilization regimen utilizing a unique CXCR2 agonist, GROβ, and the CXCR4 antagonist AMD3100. A single injection of both agents resulted in stem cell mobilization peaking within 15 min that was equivalent in magnitude to a standard multi-day regimen of granulocyte colony-stimulating factor (G-CSF). Mechanistic studies determined that rapid mobilization results from synergistic signaling on neutrophils, resulting in enhanced MMP-9 release, and unexpectedly revealed genetic polymorphisms in MMP-9 that alter activity. This mobilization regimen results in preferential trafficking of stem cells that demonstrate a higher engraftment efficiency than those mobilized by G-CSF. Our studies suggest a potential new strategy for the rapid collection of an improved hematopoietic graft.

Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia

Intra-tumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells, leading to increased understanding of driving events in malignancy.

Transcriptomic Characterization of SF3B1 Mutation Reveals Its Pleiotropic Effects in Chronic Lymphocytic Leukemia

Mutations in SF3B1, which encodes a spliceosome component, are associated with poor outcome in chronic lymphocytic leukemia (CLL), but how these contribute to CLL progression remains poorly understood. We undertook a transcriptomic characterization of primary human CLL cells to identify transcripts and pathways affected by SF3B1 mutation. Splicing alterations, identified in the analysis of bulk cells, were confirmed in single SF3B1-mutated CLL cells and also found in cell lines ectopically expressing mutant SF3B1. SF3B1 mutation was found to dysregulate multiple cellular functions including DNA damage response, telomere maintenance, and Notch signaling (mediated through KLF8 upregulation, increased TERC and TERT expression, or altered splicing of DVL2 transcript, respectively). SF3B1 mutation leads to diverse changes in CLL-related pathways.

Proximity-Based Differential Single-Cell Analysis of the Niche to Identify Stem/Progenitor Cell Regulators

Physiological stem cell function is regulated by secreted factors produced by niche cells. In this study, we describe an unbiased approach based on the differential single-cell gene expression analysis of mesenchymal osteolineage cells close to, and further removed from, hematopoietic stem/progenitor cells (HSPCs) to identify candidate niche factors. Mesenchymal cells displayed distinct molecular profiles based on their relative location. We functionally examined, among the genes that were preferentially expressed in proximal cells, three secreted or cell-surface molecules not previously connected to HSPC biology-the secreted RNase angiogenin, the cytokine IL18, and the adhesion molecule Embigin-and discovered that all of these factors are HSPC quiescence regulators. Therefore, our proximity-based differential single-cell approach reveals molecular heterogeneity within niche cells and can be used to identify novel extrinsic stem/progenitor cell regulators. Similar approaches could also be applied to other stem cell/niche pairs to advance the understanding of microenvironmental regulation of stem cell function.