Rare Cell Populations Research Articles

Abstract 2086: ISCVAM, an Interactive Single Cell Visual Analytics for Multiomics, accelerates the identification of novel rare cell populations

Abstract BACKGROUND Emergent single cell technologies have accelerated the discovery of rare cell populations and characterization of complex tumor microenvironment (TME). We developed an Interactive Single Cell Visual Analytics for Multiomics, ISCVAM, a bioinformatics infrastructure to integrate and visualize high-dimensional sparse multiome single cell data. METHODS We built an interactive tool, ISCVAM with react.js for the web frontend, and node.js in the backend, with a data bridge to portable HDF5 storage. Commonly used R packages including Seurat, Signac, SingleR, and scType, were used offline for data processing and analyses. We investigated cell populations using two Multiome datasets for proof of principle:1) ~22K cells from the matched pairs of sorted CD8+Tissue resident memory (TRM) and recirculating (ReCir) T cells from 4 ovarian cancer patients in (Anadon, Yu et al. 2022) and 2) ~11K cells from a PBMC sample (from 10X Genomics). RESULTS ISCVAM enables users to investigate both user-defined markers in multiple modalities (RNA and ATAC) individually and jointly (through weighted nearest neighbor), in different dimension reduction projections and on multiple panels. It also allows discovery of novel signatures of unidentified cell populations using unsupervised clustering algorithms in multiple resolutions. Using the paired TRM and ReCir samples from a single patient as the discovery set, ISCVAM identified a small cluster of mucosal-associated invariant T (MAIT) cells with unique gene and open chromatin peak profiles in both samples (2.18% of the ReCir T cells and 1.50% of the TRM T cells), which was not reported in the original study. Using the identified signature (with SLC4A10, TLE1 and their linked peaks), the MAIT cells were observed in remaining 6 ovarian samples (5.39 ±4.05% cells in 3 ReCir samples and 1.05 ± 1.02% cells in 3 TRM samples) from the same study. The markers are robust and also validated in an independent PBMC 10X Genomics dataset. CONCLUSION The tool ISCVAM enables the discovery of rare immune cell populations by integrating transcriptional and epigenic profiles simultaneously at multiple resolutions. This information rich tool with multiple panels and modalities with high interactivity enables rapid identification of rare cell populations. This will accelerate the understanding of complex TME in cancer research. Citation Format: Thanh N. M. Nguyen. ISCVAM, an Interactive Single Cell Visual Analytics for Multiomics, accelerates the identification of novel rare cell populations [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2086.

Abstract 3459: Drug persistence pathways in ovarian cancer identified by single-cell analysis of patient samples and cell line models

Abstract Drug resistance and disease recurrence represent a major obstacle in the treatment of high-grade serous ovarian cancer (HGSOC). Here, we performed a comprehensive characterization, at the single-cell level, of residual (persister) cancer cells that survive neoadjuvant treatment in HGSOC and can give rise to future recurrences. We aim to understand the adaptive responses that enable persistence and the key pathways that underlie them to find new targets for combination therapy with the ultimate goal of eradicating all tumor cells. We collected 27 tumor samples (16 pre-treatment and 11 post-neoadjuvant carboplatin/taxol samples, with multi-site sampling per patient) for single-cell RNA sequencing (scRNA-Seq). To complement the patient-derived dataset and model the time course of drug persistence, we performed scRNA-Seq of 13 distinct ovarian cancer cell lines treated with chemotherapy in vitro for a series of time points up to 28 days. We performed single-cell gene expression and copy number analyses of patient samples, annotated detailed cell types, and detected multiple immune cell populations, the majority of which maintained a highly immunosuppressive program both in untreated and treated samples. Remarkably, we detected a rare population of cancer cells that differed dramatically in their transcriptional program. These cells exhibited high expression of components of motile cilia and the transcription factor FOXJ1, a master regulator of ciliogenesis. We validated the presence of FOXJ1+ cells in patient samples by immunohistochemistry and immunofluorescence. Ciliated cells were enriched in the post-treatment vs. pre-treatment samples, suggesting a possible role in drug persistence. We are now experimentally testing the role of the FOXJ1-driven transcriptional program in mediating drug resistance. To systematically identify transcriptional programs activated in persister cells, we performed differential expression analysis on pre- vs. post-treatment samples. We identified previously implicated mechanisms of drug resistance, such as the Epithelial-Mesenchymal Transition and the antiapoptotic response driven by MCL1. We additionally detected upregulation of the metallothionein family of genes, which may represent a mechanism of resistance to platinum-based compounds. We detected potentially novel mechanisms representing a stress response signature driven by JUND, an interferon gamma signature, and a pro-stem cell signature characterized by LGR5 expression. Independently, our analysis of the ovarian cancer cell lines treated with taxol in vitro confirmed the JUND transcriptional program as potentially driving ovarian cancer persistence. Our study will help reveal pathways enabling ovarian cancer cells to persist through treatment and, ultimately, could lead to novel approaches for targeting persistence and achieving deeper therapeutic responses. Citation Format: Elizaveta Leshchiner, Richard Panayiotou, Anay Gupta, Thomas Zhang, Kayli Neil, Nomeda Girnius, Aylin Henstridge, Brian P. Danysh, Ignaty Leshchiner, Sarah J. Hill, Laxmi Parida, Ursula A. Matulonis, Joan S. Brugge, Gad Getz. Drug persistence pathways in ovarian cancer identified by single-cell analysis of patient samples and cell line models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3459.

Abstract 2292: Novel method for the detection and evaluation of disease biomarkers on white blood cells from liquid biopsies

Abstract Purpose: Blood based liquid biopsies of circulating tumor cells (CTCs) are a non-invasive tool with proven effectiveness in the prognosis, treatment selection, and stratification of cancer patients. In this study we demonstrate a novel application of the RareCyte platform, which was developed to find and analyze rare CTCs from blood samples, in evaluating white blood cell (WBC) sub-populations for disease biomarkers. Experimental Procedures: Using AccuCyte®, an unbiased density-based method for collecting nucleated cells from whole blood, we transferred the nucleated cells to slides and stained for CD14, CD66b, and CK/EpCAM to identify monocytes (CD14+/CD66b-), granulocytes (CD14-/CD66b+), and CTCs (CK/EpCAM+), as well as a drug-target biomarker to evaluate its expression across all cells. These slides were then imaged with CyteFinder®, an automated multiparameter immunofluorescent (IF) microscopy system that applies machine learning algorithms for cell identification. Each slide contains millions of cells, so we developed novel scanning and analysis algorithms to quantify WBC sub-populations in addition to rare CTCs. Results: In addition to detection and enumeration of CTCs, the RareCyte system was able to detect individual white blood cells and quantify monocyte and granulocyte subpopulations. Our results correlated very well with standard CBC (Complete Blood Count) readings from multiple donors. Additionally, the monocyte and granulocyte populations were evaluated for expression of a drug-target biomarker. While expression was observed on both granulocytes and monocytes, monocytes had a significantly higher expression of the drug-target biomarker, a critical finding for future implementation of this drug. Conclusions: Our results show that through modifications to the RareCyte platform we can identify rare and non-rare cell populations simultaneously and evaluate expression of biomarkers and drug-targets across multiple cells of interest. This new application combines the benefits of high throughput data analysis of flow cytometry with the specificity and sensitivity of rare cell detection. Additionally, high-resolution multiplexed immunofluorescent imaging provides cell morphology and biomarker localization information. Our ability to add multiple biomarkers in conjunction with CTC and other rare cell detection provides multiple avenues for future research. One possible application is characterizing white blood cells that cluster with CTCs, which are known to portend a worse prognosis for patients. Our modified workflow could be implemented to precisely characterize these WBCs that contribute to the metastatic process. Utilization of the RareCyte platform for both rare and non-rare cell analysis presents an exciting opportunity for a deeper evaluation of patients and their prognosis through liquid biopsies. Citation Format: Erin Bayer, Jon Ladd, Joshua Nordberg, Arturo B. Ramirez, Jessica A. Baker, Thomas Daly. Novel method for the detection and evaluation of disease biomarkers on white blood cells from liquid biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2292.

Abstract 3517: Multi-modal single-cell and spatial genomics reveals genomic, adaptive and microenvironmental features of human non-small cell lung cancer brain metastasis

Abstract Non-small cell lung cancer (NSCLC) accounts for nearly half of all newly diagnosed patients with brain metastasis (BM), followed by melanoma and breast carcinomas. The presence of BM is associated with reduced response to several modern cancer therapies and a poor prognosis, but the underlying molecular underpinnings remain poorly understood. Here, we performed multi-modal single-nucleus RNA, T cell receptor, single-cell spatial, and whole-genome sequencing (WGS) of 44 primary NSCLC tumors (PTs) and BMs. Through combination of WGS with inferred copy-number alterations (CNAs) and gene expression snRNA-seq, we robustly identify malignant cells despite the presence of healthy cell mosaicism. We find a strong association of chromosomal instability (CIN) and brain-metastatic organotropism. Through integration with clinical information and thousands of publicly available whole-exome sequencing (WES) profiles obtained from patients with NSCLC, we validate this observation and show that CIN progressively increases from PTs to extracranial metastases (ECMs) and is the highest in BMs. Using non-negative matrix factorization, we identify recurrent transcriptional hallmarks cancer metastasis, and additionally find that cancer cells from BMs strongly enrich for a neuronal-like cell state. At single-cell resolution, we indeed identify a rare cancer cell population genomically define by very high CIN, and transcriptionally characterized by a program of epithelial-to-mesenchymal transition (EMT), neuronal-like differentiation, and loss of lineage attribution. We show in our data and external scRNA-seq data that this cell state does not ecist in healthy lungs, progressively enriches from PTs to ECMs, and is most abundant in BMs, suggesting that these cells may indeed give rise to BMs. Furthermore, through integration of snRNA/TCR-seq and spatial transcriptomics, we find distinct tumor-microenvironments across disease sites, including, nearly exclusive expansion of tissue-resident myeloid cells in PTs, while BMs are largely dominated by dense infiltration with monocyte-derived macrophages and granulocytes, impaired T cell infiltration, activation and clonal expansion. Lastly, spatial transcriptomics also recurrent, cell-type specific patterns of geographic variability in key pathways, including antigen presentation, EMT, oxidative phosphorylation, and inflammatory response and associated cellular micro-niches. Together, this work identifies cellular, genomic, and transcriptional features of NSCLC BMs and has important therapeutic implications for novel therapies, in particular immunomodulatory approaches targeting cell types/states unique to disease sites. Citation Format: Somnath Tagore, Lindsay Caprio, Amit Dipak Amin, Irving Barrera, Johannes Melms, Karan Luthria, Yiping Wang, Yohanna Georgis, Abhi Jaiswal, Galina G. Lagos, Zachary Walsh, Parin Shah, Jana Biermann, Neha Sheikh, Priyanka Ramaradj, Niroshana Anandasabapathy, Hanina Hibshoosh, Gary Schwartz, Brian Henick, Alison Taylor, Fei Chen, Benjamin Izar. Multi-modal single-cell and spatial genomics reveals genomic, adaptive and microenvironmental features of human non-small cell lung cancer brain metastasis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3517.

PD46-02 BLOOD-BASED LIQUID BIOPSY FOR DIAGNOSIS AND SURVEILLANCE OF PRIMARY UPPER TRACT UROTHELIAL CARCINOMA: ROAD TO EMERGING NOVEL BIOMARKER

You have accessJournal of UrologyCME1 Apr 2023PD46-02 BLOOD-BASED LIQUID BIOPSY FOR DIAGNOSIS AND SURVEILLANCE OF PRIMARY UPPER TRACT UROTHELIAL CARCINOMA: ROAD TO EMERGING NOVEL BIOMARKER Alireza Ghoreifi, Stephanie Shishido, George Courcoubetis, Salmaan Sayeed, Amy Huang, Andrew Hung, Anne Schuckman, Monish Aron, Mihir Desai, Siamak Daneshmand, Inderbir Gill, Peter Kuhn, Jeremy Mason, and Hooman Djaladat Alireza GhoreifiAlireza Ghoreifi More articles by this author , Stephanie ShishidoStephanie Shishido More articles by this author , George CourcoubetisGeorge Courcoubetis More articles by this author , Salmaan SayeedSalmaan Sayeed More articles by this author , Amy HuangAmy Huang More articles by this author , Andrew HungAndrew Hung More articles by this author , Anne SchuckmanAnne Schuckman More articles by this author , Monish AronMonish Aron More articles by this author , Mihir DesaiMihir Desai More articles by this author , Siamak DaneshmandSiamak Daneshmand More articles by this author , Inderbir GillInderbir Gill More articles by this author , Peter KuhnPeter Kuhn More articles by this author , Jeremy MasonJeremy Mason More articles by this author , and Hooman DjaladatHooman Djaladat More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003359.02AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Blood-based liquid biopsy has emerged as a novel diagnostic and prognostic biomarker in cancer patients, yet the efficacy of this test in patients with upper tract urothelial carcinoma (UTUC) is unknown. The aim of this study is to explore the feasibility of a liquid biopsy in the diagnosis and surveillance of primary UTUC. METHODS: In this prospective pilot study, under an IRB-approved protocol (#HS-19-00886), blood samples were collected between May 2021 and September 2022 from primary UTUC patients before surgical intervention with curative intent as well as follow-up visits. The samples were analyzed using the third generation comprehensive high-definition single cell assay (HDSCA3.0) to detect rare cells (e.g., circulating tumor cells [CTCs]) and other rare events (e.g., large extracellular vesicles [LEVs]) (Figure 1-A). The findings of pre-surgery liquid biopsies were compared to the blood samples of normal donors (NDs) who had no known pathology. Follow-up samples were compared to the baseline findings. RESULTS: A total of 22 UTUC patients and 50 NDs were included in the analysis. Pathologic staging of UTUC patients revealed 13 non-muscle invasive (<T2) and 9 muscle-invasive (≥T2) tumors. Most cases (17/22) were high-grade. Eight patients received neoadjuvant chemotherapy as well. HDSCA3.0 analysis indicated that rare cells were detectable in the peripheral blood collected from UTUC patients with a high heterogeneity. Total rare events and total rare cells detected in UTUC samples before surgery were significantly higher than that from the NDs. Similar trend was seen in other CTC and rare cell populations, including D|V, D|CK|V|CD, D|V|CD, D, D|CK, and total CK+cells as well as total LEVs and CK+only LEVs (Figure 1-B). Additionally, 11 follow-up samples, collected within a median 8 months following surgery, were available for the analysis that showed significant decrease in the incidence of total LEVs, CK LEVs, and CK|CD LEVs (Figure 1-C). Among these patients, there were 4 bladder recurrences but no distant metastasis. CONCLUSIONS: This study demonstrates promising evidence for the possible clinical utility of the liquid biopsy in UTUC. Rare cells and LEVs may be used in the diagnosis and surveillance of patients with UTUC. Source of Funding: USC Urology Research Council © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e1169 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Alireza Ghoreifi More articles by this author Stephanie Shishido More articles by this author George Courcoubetis More articles by this author Salmaan Sayeed More articles by this author Amy Huang More articles by this author Andrew Hung More articles by this author Anne Schuckman More articles by this author Monish Aron More articles by this author Mihir Desai More articles by this author Siamak Daneshmand More articles by this author Inderbir Gill More articles by this author Peter Kuhn More articles by this author Jeremy Mason More articles by this author Hooman Djaladat More articles by this author Expand All Advertisement PDF downloadLoading ...

Ganglioglioma deep transcriptomics reveals primitive neuroectoderm neural precursor-like population

Gangliogliomas are brain tumors composed of neuron-like and macroglia-like components that occur in children and young adults. Gangliogliomas are often characterized by a rare population of immature astrocyte-appearing cells expressing CD34, a marker expressed in the neuroectoderm (neural precursor cells) during embryogenesis. New insights are needed to refine tumor classification and to identify therapeutic approaches. We evaluated five gangliogliomas with single nucleus RNA-seq, cellular indexing of transcriptomes and epitopes by sequencing, and/or spatially-resolved RNA-seq. We uncovered a population of CD34+ neoplastic cells with mixed neuroectodermal, immature astrocyte, and neuronal markers. Gene regulatory network interrogation in these neuroectoderm-like cells revealed control of transcriptional programming by TCF7L2/MEIS1-PAX6 and SOX2, similar to that found during neuroectodermal/neural development. Developmental trajectory analyses place neuroectoderm-like tumor cells as precursor cells that give rise to neuron-like and macroglia-like neoplastic cells. Spatially-resolved transcriptomics revealed a neuroectoderm-like tumor cell niche with relative lack of vascular and immune cells. We used these high resolution results to deconvolute clinically-annotated transcriptomic data, confirming that CD34+ cell-associated gene programs associate with gangliogliomas compared to other glial brain tumors. Together, these deep transcriptomic approaches characterized a ganglioglioma cellular hierarchy—confirming CD34+ neuroectoderm-like tumor precursor cells, controlling transcription programs, cell signaling, and associated immune cell states. These findings may guide tumor classification, diagnosis, prognostication, and therapeutic investigations.

Single Cell Type Prediction from Gene Profiles - An Overview of Different Computational Methods

Proven to be useful in quantitative analysis of mRNA, scRNA-seq measures the individual gene expression profile and helps with rare cell population identification. Successful scRNA-seq analysis would be useful to boost knowledge of cancer cells and tumorigenesis, thus improving the ability to identify biomarkers and detect individuals disease susceptibility. This work conducted dimensionality reduction using naive principal component analysis. Then, several classification algorithms, including support vector machine, random forest, boosting, and neural networks, were examined with best hyperparameters determined by grid search. With the comparison of data dimensionality N=83 and N=127, each method generated the prediction accuracy of the dataset, with the support vector machine achieving the highest testing accuracy of 53.52%. The relatively high prediction accuracy enables better characterization of single gene expression profiles due to support vector machines ability to regularize high-dimensional data. Deeper architectures and usage of Bayesian optimization may further encourage efficient analysis of larger datasets with better classification accuracy.

Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.

The evolution of omics and computational competency has accelerated discoveries of the underlying biological processes in an unprecedented way. High throughput methodologies, such as flow cytometry, can reveal deeper insights into cell processes, thereby allowing opportunities for scientific discoveries related to health and diseases. However, working with cytometry data often imposes complex computational challenges due to high-dimensionality, large size, and nonlinearity of the data structure. In addition, cytometry data frequently exhibit diverse patterns across biomarkers and suffer from substantial class imbalances which can further complicate the problem. The existing methods of cytometry data analysis either predict cell population or perform feature selection. Through this study, we propose a "wisdom of the crowd" approach to simultaneously predict rare cell populations and perform feature selection by integrating a pool of modern machine learning (ML) algorithms. Given that our approach integrates superior performing ML models across different normalization techniques based on entropy and rank, our method can detect diverse patterns existing across the model features. Furthermore, the method identifies a dynamic biomarker structure that divides the features into persistently selected, unselected, and fluctuating assemblies indicating the role of each biomarker in rare cell prediction, which can subsequently aid in studies of disease progression.

Current understanding of cancer stem cells: Immune evasion and targeted immunotherapy in gastrointestinal malignancies.

As a relatively rare population of cancer cells existing in the tumor microenvironment, cancer stem cells (CSCs) possess properties of immune privilege to evade the attack of immune system, regulated by the microenvironment of CSCs, the so-called CSCs niche. The bidirectional interaction of CSCs with tumor microenvironment (TME) components favors an immunosuppressive shelter for CSCs' survival and maintenance. Gastrointestinal cancer stem cells (GCSCs) are broadly regarded to be intimately involved in tumor initiation, progression, metastasis and recurrence, with elevated tumor resistance to conventional therapies, which pose a major hindrance to the clinical efficacy for treated patients with gastrointestinal malignancies. Thus, a multitude of efforts have been made to combat and eradicate GCSCs within the tumor mass. Among diverse methods of targeting CSCs in gastrointestinal malignancies, immunotherapy represents a promising strategy. And the better understanding of GCSCs immunomodulation and immunoresistance mechanisms is beneficial to guide and design novel GCSCs-specific immunotherapies with enhanced immune response and clinical efficacy. In this review, we have gathered available and updated information to present an overview of the immunoevasion features harbored by cancer stem cells, and we focus on the description of immune escape strategies utilized by CSCs and microenvironmental regulations underlying CSCs immuno-suppression in the context of gastrointestinal malignancies. Importantly, this review offers deep insights into recent advances of CSC-targeting immunotherapeutic approaches in gastrointestinal cancers.

LC-MS-Based Targeted Metabolomics for FACS-Purified Rare Cells.

Metabolism plays a fundamental role in regulating cellular functions and fate decisions. Liquid chromatography-mass spectrometry (LC-MS)-based targeted metabolomic approaches provide high-resolution insights into the metabolic state of a cell. However, the typical sample size is in the order of 105-107 cells and thus not compatible with rare cell populations, especially in the case of a prior flow cytometry-based purification step. Here, we present a comprehensively optimized protocol for targeted metabolomics on rare cell types, such as hematopoietic stem cells and mast cells. Only 5000 cells per sample are required to detect up to 80 metabolites above background. The use of regular-flow liquid chromatography allows for robust data acquisition, and the omission of drying or chemical derivatization avoids potential sources of error. Cell-type-specific differences are preserved while the addition of internal standards, generation of relevant background control samples, and targeted metabolite with quantifiers and qualifiers ensure high data quality. This protocol could help numerous studies to gain thorough insights into cellular metabolic profiles and simultaneously reduce the number of laboratory animals and the time-consuming and costly experiments associated with rare cell-type purification.

Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution

Long-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.

Abstract A011: Detection of disseminated tumor cells in advanced clear cell renal cell carcinoma through research autopsy

Abstract Background: The vast majority of cancer deaths can be attributed to tumor metastases. Disseminated tumor cells (DTCs) are thought to act as a reservoir of tumor clones which can lie dormant before causing overt metastases. Their presence has been shown to be a poor prognostic indicator in several tumor types. Despite their importance, the timing and source of DTCs is unclear across most solid cancers and even less is known about them in late-stage disease. The Posthumous Evaluation of the Advanced Cancer Environment (PEACE) post-mortem study enables extensive sampling of malignant lesions but also normal tissues, thereby allowing study of DTCs in patients with advanced cancer. Methods: We performed research autopsy sampling of macroscopically normal bone, lung and liver in 3 patients with advanced clear cell renal cell carcinoma (RCC). In addition, we performed bone marrow aspiration at autopsy from vertebral bodies and the ilium using an anterior approach. Mechanical disaggregation followed by collagenase digestion was used to generate single cell suspensions. Detection of tumor cells was carried out using antibodies against known tumor or epithelial markers carbonic anhydrase IX (CAIX). Epithelial cell adhesion molecule (EpCAM) was also used for bone marrow samples as native bone marrow cells do not express this marker. These sub-populations were then isolated using fluorescence activated cell sorting and DNA was extracted and amplified from single cells. Results: We performed and optimised collagenase-based digestion on all solid tissues collected. The percentage of viable cells generated varied significantly between subjects and tissues with bone marrow samples more viable than lung and liver. Rare and distinct populations of CAIX+ and EpCAM+ cells were detected in normal tissues between 0.5-2%. DNA amplification was successful on single cells isolated from normal lung and liver but not from bone tissue. Pilot shallow coverage whole genome sequencing revealed genomically aberrant cells ranging from single chromosome arm losses to widespread copy number aberrations. Conclusion: We demonstrate feasibility of sequencing single cells from autopsy study subjects. Rare populations of single cells with markers of clear cell RCC were detected and isolated both in normal tissues of patients with advanced disease. Genomic analyses of these cells will lead to insights into their relationship to the primary tumor and overt metastatic lesions. Citation Format: Haixi Yan, Cristina Cotobal Martin, Christie English, Annelien Verfaillie, Jonas Demeulemeester, Andrew Rowan, Annika Fendler, Anne-Laure Cattin, Sucheta Mahapatra, Lewis Au, Scott Shepherd, Ben Shum, Charlotte Spencer, Zayd Tippu, Ula Mahadeva, Anna Green, Eleanor Carlyle, Cristina Naceur-Lombardelli, PEACE consortium, Mariam Jamal-Hanjani, Charles Swanton, Samra Turajlic, Peter Van Loo. Detection of disseminated tumor cells in advanced clear cell renal cell carcinoma through research autopsy [abstract]. In: Proceedings of the AACR Special Conference: Cancer Metastasis; 2022 Nov 14-17; Portland, OR. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_2):Abstract nr A011.

Recent advances in ex vivo expansion of human hematopoietic stem cells.

Hematopoietic stem cells (HSCs) are a rare cell population present in the bone marrow. They possess self-renewal and multipotent differentiation capacities and play a crucial role in lifelong hematopoiesis and reconstitution of the hematopoietic system after hematopoietic stem cell transplantation (HSCT). HSCT remains the only curative treatment for refractory hematologic disorders. Umbilical cord blood (CB) has several advantages as an alternative donor for HSCT, including HLA flexibility and lack of donor burden. However, CB has limitations in terms of cell dose, restricted donor options, and prolonged time to engraftment. Development of techniques for expanding HSCs ex vivo, especially those contained in CB, has become a goal in the field of hematology. Attempts have been made to use various combinations of cytokines for this purpose, but these protocols showed limited expansion rates and did not progress to clinical applications. Recent advances that include the addition of small molecules to cytokines have enabled long-term and stable ex vivo expansion of human HSCs. Clinical trials have been conducted with HSCs expanded in CB using these techniques, confirming their efficacy and safety. Furthermore, we recently developed a recombinant cytokine-free, albumin-free culture system for long-term expansion of human HSCs. This approach has the potential to selectively expand human HSCs more effectively than the previous protocols. We herein present an overview of ex vivo culture protocols for expanding human HSCs together with the results of clinical trials that utilized these techniques.

Guidelines for DC preparation and flow cytometry analysis of mouse nonlymphoid tissues.

This article is part of the Dendritic Cell Guidelines article series, which provides a collection of state-of-the-art protocols for the preparation, phenotype analysis by flow cytometry, generation, fluorescence microscopy and functional characterization of mouse and human dendritic cells (DC) from lymphoid organs and various nonlymphoid tissues. DC are sentinels of the immune system present in almost every mammalian organ. Since they represent a rare cell population, DC need to be extracted from organs with protocols that are specifically developed for each tissue. This article provides detailed protocols for the preparation of single-cell suspensions from various mouse nonlymphoid tissues, including skin, intestine, lung, kidney, mammary glands, oral mucosa and transplantable tumors. Furthermore, our guidelines include comprehensive protocols for multiplex flow cytometry analysis of DC subsets and feature top tricks for their proper discrimination from other myeloid cells. With this collection, we provide guidelines for in-depth analysis of DC subsets that will advance our understanding of their respective roles in healthy and diseased tissues. While all protocols were written by experienced scientists who routinely use them in their work, this article was also peer-reviewed by leading experts and approved by all coauthors, making it an essential resource for basic and clinical DC immunologists.

Integration of scATAC-Seq with scRNA-Seq Data.

Single-cell studies are enabling our understanding of the molecular processes of normal cell development and the onset of several pathologies. For instance, single-cell RNA sequencing (scRNA-Seq) measures the transcriptome-wide gene expression at a single-cell resolution, allowing for studying the heterogeneity among the cells of the same population and revealing complex and rare cell populations. On the other hand, single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-Seq) can be used to define transcriptional and epigenetic changes by analyzing the chromatin accessibility at the single-cell level. However, the integration of multi-omics data still remains one of the most difficult tasks in bioinformatics. In this chapter, we focus on the combination of scRNA-Seq and scATACSeq data to perform an integrative analysis of the single-cell transcriptome and chromatin accessibility of human fetal progenitors.

A machine learning framework for scRNA-seq UMI threshold optimization and accurate classification of cell types.

Recent advances in single cell RNA sequencing (scRNA-seq) technologies have been invaluable in the study of the diversity of cancer cells and the tumor microenvironment. While scRNA-seq platforms allow processing of a high number of cells, uneven read quality and technical artifacts hinder the ability to identify and classify biologically relevant cells into correct subtypes. This obstructs the analysis of cancer and normal cell diversity, while rare and low expression cell populations may be lost by setting arbitrary high cutoffs for UMIs when filtering out low quality cells. To address these issues, we have developed a novel machine-learning framework that: 1. Trains cell lineage and subtype classifier using a gold standard dataset validated using marker genes 2. Systematically assess the lowest UMI threshold that can be used in a given dataset to accurately classify cells 3. Assign accurate cell lineage and subtype labels to the lower read depth cells recovered by setting the optimal threshold. We demonstrate the application of this framework in a well-curated scRNA-seq dataset of breast cancer patients and two external datasets. We show that the minimum UMI threshold for the breast cancer dataset could be lowered from the original 1500 to 450, thereby increasing the total number of recovered cells by 49%, while achieving a classification accuracy of >0.9. Our framework provides a roadmap for future scRNA-seq studies to determine optimal UMI threshold and accurately classify cells for downstream analyses.

Characterization of Dynamic Niche Signaling Modules during Embryonic Hematopoietic Development Using Spatial Transcriptomics

Directed differentiation of pluripotent stem cells (PSCs) into functional hematopoietic stem cells (HSCs) remains elusive. A better understanding of HSC development, both intrinsically and extrinsically, will provide insights to guide PSC-HSC differentiation. During mouse embryogenesis, a subpopulation of endothelial cells in the aorta-gonad-mesonephros (AGM) region are specified at embryonic day (E) 9.5 to hemogenic endothelial cells (HECs). HECs then undergo an endothelial to hematopoietic transition (EHT) between E9.5 and E10.5. Among these hematopoietic cells, only a few are nascent HSCs (pre-HSCs) that migrate to the fetal liver for maturation and expansion. Recent advances in single cell RNA sequencing (scRNA-seq) substantially improved our understanding of intrinsic cellular programs of human and mouse HSC development; however, much less is known about the hematopoietic niche cells and niche-emanated signals in the AGM region and fetal liver. To characterize the niche components and related signaling of HSC development, we conducted a spatial transcriptomics analysis using Slide-seq (with 10 µm resolution) on mouse E10.5, E11.5 and E12.5 trunk tissues covering both the AGM region and fetal liver. We also performed scRNA-seq on seven samples collected from trunk tissues, including E10.5, E11.5 and E12.5 AGM regions; E10.5, E11.5 and E12.5 trunks; and E12.5 fetal liver. We developed an algorithm to integrate the Slide-seq and scRNA-seq data that takes advantage of their spatial and in-depth transcriptional sequencing capacity, respectively. Using E11.5 Slide-seq data as an example, we successfully identified most, if not all, of the tissue structures at a near single cell level in trunk tissue (see Figure). Furthermore, we could determine the expression of thousands of genes on individual beads, providing an invaluable tool for investigating spatial-characterized niche cells and signals. Compared to the dorsal aorta, which was dominated by one cell cluster expressing Nfgr, a complex and multilayered cellular architecture was revealed in the ventral part of aorta where EHT occurs, including pre-HSCs, endothelial cells, neural crest derived cells, mesonephric cells, and macrophages. We found a rare population of mesenchymal stromal cells (MSCs) that co-express Cdh2 (encodes N-cadherin or N-cad) and Pdgfra. Of note, these N-cad+ MSCs exclusively localize to the ventral part of the aorta as a single cell layer and are sandwiched between an inner layer of aortic endothelial cells and an outer layer of mesonephric cells. Secondly, we identified multiple genes enriched in the ventral aorta compared to the dorsal aorta, including Dlk1, Wnt4, Igf1, and Ptn. Gene Ontology analysis and KEGG signaling pathway analysis were also performed to investigate the biological processes and signaling pathways enriched in individual cell clusters. Potential signaling modules representing ligand-receptor interactions between niche cells and HECs/pre-HSCs were analyzed by CellphoneDB; the identified spatial location of niche cells relative to pre-HSCs allows us to exclude predicted interactions in which niche cells were located too far from pre-HSCs to be relevant. As a result, we generated a list of known and potentially novel signals critical for EHT, including DLK1, JAG1 and TGFβ emanating from N-cad+ MSCs, endothelial cell-derived JAG2 and DLL1/4, mesonephric cell-secreted WNT2b, GREM1 (a BMP antagonist) and R-spondin1, gonad cell-derived SPP1, and macrophage-produced TNFα. A thorough analysis on both AGM and fetal liver at different developmental stages is ongoing. In summary, we dissected dynamic and near single cell-resolved spatial characteristics of the niche components and signals for HSC development in the AGM region and fetal liver. These findings will deepen our knowledge of embryonic hematopoiesis and guide the in vitro induction of human PSCs to functional HSCs. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

CBFB-MYH11 Is Required for the Maintenance of Inv(16) AML

Acute myeloid leukemia (AML) is a heterogenous disease arising from the immature blood cells in the bone marrow. One of the most common chromosomal aberrations, inversion of chromosome 16 [inv(16)], generates the fusion gene Cbfb-MYH11 (CM) which is known to initiate leukemogenesis. Because the fusion protein is invariably found in patients at relapse, it is assumed that CM is also required after leukemic transformation. However, knockdown of CM in the inv(16) immortalized cell line ME-1, caused relatively subtle effects on differentiation but did not affect viability. This raises the possibility that CM may be dispensable after leukemic transformation. To address this possibility in primary leukemia cells, we generated a new knock-in mouse model with the CM fusion gene flanked by loxP sites (CbfbflMYH11). This allows for the fusion gene to be deleted by Cre Recombinase (Cre) after leukemia development. To test the effect of loss of CM in vitro, we transduced Cbfb+/flMYH11 leukemia cells from three independent CbfbflMYH11 mice with a lentivirus expressing Cre. We confirmed the deletion of CM by qPCR and western blot. In Cbfb+/flMYH11, Cre+ cells, we observed a statistically significant increase in Annexin V staining and a decrease in colony forming ability as compared to control Cbfb+/flMYH11 cells. To determine if the colonies that did grow from Cre-infected cells had successfully deleted CM, individual colonies were picked. We found that majority of the colonies retained the unexcised CM allele, but 5-20% of colonies had successfully deleted CM, indicating that a rare population of leukemia cells can survive without CMin vitro. To test the requirement for CM in vivo, we used an inducible shRNA against CM rather than Cre+CbfbflMYH11 leukemia cells, as the inducible knockdown model will allow us to avoid potential defects in engraftment. We transduced CM expressing leukemic cells with a lentiviral construct with a doxycycline (Dox) inducible shRNA against MYH11 (shMYH11) that also expresses GFP. To test the feasibility of this approach in vitro, the sorted shCM+ leukemia cells were incubated with Dox for 48 hours. We found that Cbfb-MYH11 mRNA and protein were decreased in Dox treated leukemia cells, as compared to control cells. In addition, Dox treated shCM+ cells showed increased apoptosis and decreased colony forming ability, similar to Cbfb+/flMYH11Cre+ cells. To test the effect of CM knockdown in vivo, shCM transduced leukemia cells were transplanted into sub-lethally irradiated mice and monitored for leukemic engraftment. Once significant leukemic burden in the peripheral blood was detected, mice were given Dox or vehicle in their drinking water. Starting on day 7, we observed a statistically significant decrease in leukemia burden in Dox treated mice in the peripheral blood and spleen, with the percent of leukemia cells below 5% starting on day 14. In the bone marrow, there was a statistically significant decrease in leukemic burden starting on day 14, but the leukemia cells remained at 30-40% through day 28. Our initial tests indicate that the remaining GFP+ leukemia cells in the bone marrow express reduced levels of CM, implying that these cells may not strictly require the fusion protein or may be able to survive with only low levels of Cbfb-MYH11 activity. In a separate, small cohort of shCM+ transplanted mice, we treated the mice with Dox or control water and monitored for leukemia development. All the control treated mice developed fatal leukemia by day 21, whereas the majority of the Dox treated mice survived until day 42 of treatment. Interestingly, among the 6 Dox treated mice, 2 showed re-emergence of GFP+ leukemia cells in the peripheral blood on day 21 and 28, respectively. We are currently testing whether these relapsed leukemia cells re-express CM. Taken together, our results indicate that Cbfb-MYH11 is largely required for leukemia maintenance, although a subset of cells may be able to survive without the fusion gene. These results imply that drugs targeting the Cbfb-MYH11 have the potential to be effective treatments for inv(16) AML, although substantial inhibition of the fusion protein will likely be needed for effective treatment of the disease.

LepR+ Niche Cell-Derived AREG Compromises Hematopoietic Stem Cell Maintenance Under Conditions of DNA Repair Deficiency and Aging

The maintenance of the rare hematopoietic stem cell (HSC) population in the bone marrow (BM) and preservation of their functional properties is supported by a highly specialized microenvironment inside the BM, the HSC niche. However, the crosstalk between extrinsic niche-derived and intrinsic HSC factors controlling hematopoiesis remain elusive. Using three niche-specific conditional knockout mouse models, here we demonstrate that epidermal growth factor (EGF)-like molecule, amphiregulin (AREG) from bone marrow (BM) leptin receptor (LepR+) stromal cells is an important factor that mediates the crosstalk between BM niche and HSCs in stem cell maintenance. Mice deficient for the DNA repair gene Brca2 specifically in LepR+ cells (LepR-Cre;Brca2fl/fl) exhibit increased frequencies of total and myeloid-biased HSCs. Furthermore, HSCs from LepR-Cre;Brca2fl/flmice show compromised repopulation, increased expansion of donor-derived myeloid-biased HSCs and myeloid output in the transplanted recipients. Brca2-deficient BM LepR+ cells exhibit persistent DNA damage-inducible overproduction of stromal AREG. Ex vivo treatment of WT HSCs or systemic treatment of C57BL/6 mice with recombinant AREG impairs repopulation, leading to HSC exhaustion. Conversely, inhibition of AREG by anti-AREG neutralizing antibody or deletion of the Areg gene in LepR-Cre;Brca2fl/flmice rescues the HSC defects caused by AREG. Mechanistically, AREG activates the PI3K/AKT/mTOR pathway, promotes HSC cycling and compromises HSC quiescence. Finally, we demonstrate that BM LepR+ niche cells from other DNA repair-deficient and aged mice also show persistent DNA damage-associated overexpression of AREG, which exerts similar negative effects on HSC maintenance. We have therefore identified an important niche factor negatively regulating HSCs function under conditions of DNA repair deficiency and aging, and underscored the therapeutic potential of AREG intervention in improving HSC function.

Meis1 Establishes the Pre-Hemogenic Endothelial State Prior to Runx1 Expression

Hematopoietic Stem Cells (HSCs) are the most primitive cells of the hematopoietic system, defined by their ability to sustain lifelong hematopoiesis and differentiate to all mature hematopoietic lineages. HSC transplant (HSCT) is the first-line treatment for many patients diagnosed with a serious hematological disease, however HSCs are an exceedingly rare cell population that are challenging to expand ex vivo. Generating functional HSCs ex vivo from reprogrammed somatic cells or pluripotent stem cells (PSC) is a promising alternative. However, a gap remains in the knowledge of the developmental pathways regulating HSC ontogenesis, making it challenging to reproducibly engineer bona fide HSCs. Hematopoietic stem and progenitor cells (HSPCs) originate from an endothelial-to-hematopoietic transition (EHT) during embryogenesis. EHT is a step-wise process initiating when a specialized subset of endothelial cells (EC), termed hemogenic endothelial cells (HEC) undergo dyshesion from the endothelial bed and form intra-aortic hematopoietic clusters within the major arteries of the embryo. The processes driving the specification of these HEC rather than a vascular fate is not well understood, despite representing a critical need to replicate EHT in vitro. To define factors in the endothelium that prime EC towards a hemogenic phenotype, we performed Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) on CD31+ FACS-isolated cells from the aorta-gonad-mesonephros (AGM) of E10.5 wildtype mouse embryos (Figure 1). CITE-seq can simultaneously label cells based on surface protein markers and profile single-cell transcriptomes, therefore bypassing the need for isolation of rare cells by FACS. Unsupervised clustering based on single cell transcriptomes showed distinct populations of EC (composed of venous and arterial subpopulations), cells undergoing EHT that expressed both endothelial and hematopoietic genes, and mature hematopoietic cells. In addition to EC and EHT clusters, the CITE-seq data revealed a small population of pre-hemogenic endothelial cells (pre-HE) that was distinct from HE cells, which clustered with "EHT" cells (Figure 1). Pre-HE cells expressed high levels endothelial markers and Cd44, a marker recently associated with hemogenic potential, but lacked expression of the prototypic HE markers Runx1 and Gfi1(Figure 1). To look for drivers of hematopoietic cell fate we identified 12 transcription factors (TFs) that were upregulated between the arterial endothelial cells (aEC) and pre-HE clusters identified by CITE-Seq, and that persisted through EHT. Within this list, Meis1 ranked as being the most significantly enriched, with its binding partner Pbx1 ranked fourth, therefore we hypothesized that Meis1 may be required to drive early hemogenic specification. We generated embryos with endothelial-specific deletion of Meis1 to investigate the functional requirement for Meis1 in EC. Endothelial-specific deletion of Meis1 impaired the formation of functional Runx1-expressing HE which significantly impeded the emergence of pre-HSPC via EHT. In summary, we used a combination of CITE-seq and bulk RNA-seq to identify Meis1 as a candidate early functional marker of hemogenic specification. We show that Meis1 primes arterial endothelial cells towards the hemogenic trajectory, and that it is required in the mouse embryo for the formation of early pre-hemogenic cells prior to the emergence of functional HE and pre-HSPCs. Our findings implicate Meis1 in a critical fate-determining step for establishing EHT potential in endothelial cells. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal