Single-cell Gene Expression Profiling Research Articles

Adult Human, but Not Rodent, Spermatogonial Stem Cells Retain States with a Foetal-like Signature.

Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling, it has been proposed that undifferentiated human spermatogonia can be subclassified into four heterogenous subtypes, termed states 0, 0A, 0B, and 1. To increase the resolution of the undifferentiated compartment and trace the origin of the spermatogenic trajectory, we re-analysed the single-cell (sc) RNA-sequencing libraries of 34 post-pubescent human testes to generate an integrated atlas of germ cell differentiation. We then used this atlas to perform comparative analyses of the putative SSC transcriptome both across human development (using 28 foetal and pre-pubertal scRNA-seq libraries) and across species (including data from sheep, pig, buffalo, rhesus and cynomolgus macaque, rat, and mouse). Alongside its detailed characterisation, we show that the transcriptional heterogeneity of the undifferentiated spermatogonial cell compartment varies not only between species but across development. Our findings associate 'state 0B' with a suppressive transcriptomic programme that, in adult humans, acts to functionally oppose proliferation and maintain cells in a ready-to-react state. Consistent with this conclusion, we show that human foetal germ cells-which are mitotically arrested-can be characterised solely as state 0B. While germ cells with a state 0B signature are also present in foetal mice (and are likely conserved at this stage throughout mammals), they are not maintained into adulthood. We conjecture that in rodents, the foetal-like state 0B differentiates at birth into the renewing SSC population, whereas in humans it is maintained as a reserve population, supporting testicular homeostasis over a longer reproductive lifespan while reducing mutagenic load. Together, these results suggest that SSCs adopt differing evolutionary strategies across species to ensure fertility and genome integrity over vastly differing life histories and reproductive timeframes.

Simultaneous single-cell three-dimensional genome and gene expression profiling uncovers dynamic enhancer connectivity underlying olfactory receptor choice

The simultaneous measurement of three-dimensional (3D) genome structure and gene expression of individual cells is critical for understanding a genome’s structure–function relationship, yet this is challenging for existing methods. Here we present ‘Linking mRNA to Chromatin Architecture (LiMCA)’, which jointly profiles the 3D genome and transcriptome with exceptional sensitivity and from low-input materials. Combining LiMCA and our high-resolution scATAC-seq assay, METATAC, we successfully characterized chromatin accessibility, as well as paired 3D genome structures and gene expression information, of individual developing olfactory sensory neurons. We expanded the repertoire of known olfactory receptor (OR) enhancers and discovered unexpected rules of their dynamics: OR genes and their enhancers are most accessible during early differentiation. Furthermore, we revealed the dynamic spatial relationship between ORs and enhancers behind stepwise OR expression. These findings offer valuable insights into how 3D connectivity of ORs and enhancers dynamically orchestrate the ‘one neuron–one receptor’ selection process.

Abstract 2278: Unraveling immune dynamics of CD4+ in non-small cell lung cancer through single-cell analysis and gene expression profiling

Abstract Non-small cell lung cancer (NSCLC) is a type of epithelial lung cancer other than small cell lung cancer and represents the majority of cases in lung cancer. The immune response against NSCLC relies significantly on the vital role by CD4+ T cells, contributing to the regulation of immune system and the suppression of tumor growth. Various CD4+ T cell subtypes, such as T conventional cells (Tconv cells) and T regulatory cells (Treg cells), perform distinct functions within the immune system. Tconv cells boost immune responses against specific pathogens, while Treg cells play a role in suppressing immune reactions. Investigating the correlation between Tconv cells and Treg cells in NSCLC could serve a valuable biomarker for evaluating the immune status of lung cancer patients. We examine the connection between particular CD4+ T cells in the lung and specific gene expressions associated with NSCLC. Through single-cell analysis, we classified the proportions of Treg cells and Tconv cells within CD4+ T cells in both the lungs and spleen of mice. Our discovery revealed that the proportion of Tconv cells in the lungs exceeded that in the spleen. From the differential gene expression (DEG) analysis using RNA-Seq data for Treg cells and Tconv cells in NSCLC, compared to the control group of Peripheral Blood Mononuclear Cells (PMBC), we identified 1823 genes uniquely expressed in NSCLC Treg cells and 711 genes in Tconv cells. Within these genes, we verified the expression of IL2RA and CTLA4, known to be expressed in NSCLC. Additionally, we identified high expression of genes TM4SF1 and KRT6A. By comparing the genes specific to Tconv and Treg cells in the lungs with those significantly expressed in NSCLC, we were able to identify 114 co-expressed genes in Treg cells and 71 in Tconv cells. We conducted GO and KEGG pathway analyses on these genes and examined the interaction networks among the associated genes. Furthermore, we found receptor interactions between Tconv cell subtypes (Th1, Th2, Th17, and Tfh) and Treg cells through cell-cell interaction analysis. We explored the mouse phenotypes associated with these genes. These discoveries unveiled connections within lung-specific gene networks of Treg and Tconv cells associated with NSCLC, highlighting candidate genes for targeted therapy in cancer. Citation Format: Hyunmin Woo, JiHye Yang, Siyoung Yang, Seong-il Eyun. Unraveling immune dynamics of CD4+ in non-small cell lung cancer through single-cell analysis and gene expression profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2278.

Abstract 5352: SOX9-dependent immune microenvironment remodeling drives KRAS-induced lung adenocarcinoma progression

Abstract Interactions between tumor intrinsic factors and tumor microenvironment play a vital role in disease progression and treatment response. SOX9, a transcription factor crucial for tissue development and homeostasis, has been linked to the advancement of tumor growth. However, its specific role as a driver in lung adenocarcinoma (LUAD) is not well-defined. Additionally, the impact of SOX9 on the tumor microenvironment has not been previously explored. We here identify SOX9 transcription factor to play a critical role in defining tumor immune microenvironment and driving disease progression. We employed CRISPR/Cas9 and Cre-LoxP gene knockout methods within the Kras G12D-induced mouse model of lung adenocarcinoma (LUAD). Our objective was to investigate the mechanisms through which SOX9 contributes to the development and advancement of lung adenocarcinoma. To substantiate our findings, we conducted immune profiling, gene expression analyses, RT-qPCR, and immunohistochemistry assessments in the Kras G12D-driven murine LUAD. These results were subsequently validated by examining bulk and single-cell gene expression profiles, as well as immunohistochemistry, in human lung adenocarcinoma. Our studies indicated that SOX9 played a very important role by enhancing lung tumor development, burden, and progression, leading to lower overall survival. SOX9. SOX9 consistently facilitated the growth of organoids in vitro. However, the promotion of tumor growth by SOX9 was notably reduced in immunocompromised mice compared to syngeneic mice. SOX9 demonstrated a suppressive effect on immune cell infiltration, particularly affecting the functionality of tumor-associated CD8+ T cells, natural killer cells, and dendritic cells. CD8+ T cells in the SOX9 overexpressing tumors showed upregulation of exhaustion markers. SOX9-mediated tumor growth advantage could not be observed in the CD8 knockout mice model, suggesting a CD8+ T cell-dependent role. In addition, SOX9 significantly upregulated collagen-related gene expression, leading to a substantial increase in collagen fibers possibly affecting the migration of immune cells into the tumor microenvironment. Together, our studies indicate that SOX9 plays a very critical role in modulating tumor microenvironment by controlling immune cell infiltration and CD8+ T cell exhaustion driving Kras G12D- driven lung tumor progression. Citation Format: Dinoop Ravindran Menon, Hua Zhong, Shridar Ganesan, Hatim Sabaawy, Sharon Pine. SOX9-dependent immune microenvironment remodeling drives KRAS-induced lung adenocarcinoma progression [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5352.

Abstract 3952: Multiomic single-cell tumor evolution models of minimal residual disease in pediatric B-cell acute lymphoblastic leukemia

Abstract Detection of minimal residual disease (MRD) after initial diagnosis (IDX) and therapy is a strong prognostic marker for relapse in pediatric B-cell acute lymphoblastic leukemia (B-ALL). Previous studies have explored clonal genetic and gene expression changes between initial diagnosis and relapse. However, studying tumor cells present at MRD is challenging due to their low abundance. Examining the genomic profiles of leukemia cells that resist induction chemotherapy and understanding their evolutionary relationship to cells present at diagnosis may lead to a better understanding of the cells that eventually seed relapse. We analyzed somatic point mutations, indels, and copy number variants from 41 pediatric B-ALL patients with high-risk B-ALL. We specifically focused on patients from the following four common high-risk subtypes: KMT2A-rearranged, Ph+, Ph-like, and iAMP21, who had detectable disease at the end of induction. Leukemic burden at end-induction (day 29) ranged from 0.03% to 66.00%. Data were generated in partnership with the National Cancer Institute’s Human Tumor Atlas Network and the Children’s Oncology Group. Our data set of 41 patients includes 39 with paired initial diagnostic and end-induction samples that we used to create tumor evolution models based on single cells across disease stages. We produced single-cell multiome gene expression (scRNA) and chromatin accessibility (scATAC) profiles (10x Genomics) with a median of 7428 leukemic blast cells at IDX (range: 2490-14219) and 1907 at MRD (range: 240-10167) after filtering. We called somatic mutations from scRNA and scATAC using SComatic and Monopogen, and we detected copy number changes using Numbat and EpiAneufinder. We also designed a targeted DNA sequencing panel including 335 variants based on B-ALL literature and database searches to produce scDNA (Mission Bio) for 24 patients (16 IDX-MRD pairs) with a median of 2346 cells profiled at IDX (range: 340-8849) and 1828 at MRD (range: 596-5133). We built tumor phylogenies based on somatic SNVs and CNVs with COMPASS. Using multiple tools and complementary single-cell omics data types to detect somatic changes improved our confidence in the events used for tumor evolution tree construction. Our approach allowed us to define recurrent genomic events and patterns across pediatric B-ALL subtypes and to describe the clonal evolution of cells measured at initial diagnostic and end-induction disease stages. We were also able to link cell-specific mutation events to their transcriptional and epigenomic signatures, including mapping mutation events along the B-cell development trajectory and within differentially expressed gene pathways. Some cases showed dramatic shifts in subclonal structure between IDX and MRD that may be related to therapy-induced clonal selection, such as a loss of NRAS hotspot mutation. Citation Format: Steven M. Foltz, Avi Loren, Changya Chen, Rushabh Mehta, Elizabeth Li, Jason Xu, Fatemeh Alikarami, Kathrin M. Bernt, Kai Tan. Multiomic single-cell tumor evolution models of minimal residual disease in pediatric B-cell acute lymphoblastic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3952.

Data-driven detection of age-related arbitrary monotonic changes in single-cell gene expression distributions.

Identification of genes whose expression increases or decreases with age is central to understanding the mechanisms behind aging. Recent scRNA-seq studies have shown that changes in single-cell expression profiles with aging are complex and diverse. In this study, we introduce a novel workflow to detect changes in the distribution of arbitrary monotonic age-related changes in single-cell expression profiles. Since single-cell gene expression profiles can be analyzed as probability distributions, our approach uses information theory to quantify the differences between distributions and employs distance matrices for association analysis. We tested this technique on simulated data and confirmed that potential parameter changes could be detected in a set of probability distributions. Application of the technique to a public scRNA-seq dataset demonstrated its potential utility as a straightforward screening method for identifying aging-related cellular features.

Generating single-cell gene expression profiles for high-resolution spatial transcriptomics based on cell boundary images.

The source code of STCellbin is available at https://github.com/STOmics/STCellbin.

A Novel, Probe-Based and Instrument-Free Method for Improved Ultrahigh-Throughput Single-Cell Gene Expression Analysis of Peripheral Blood Mononuclear Cells

Single-cell gene expression assays are critical tools for identifying functional subtypes of immune cells, as well as changes within cells resulting from pathology or treatment. However, most current methods are expensive, low in sample throughput, rely on reverse transcription and lack the sensitivity to consistently measure low expressed genes from single cells - preventing measurements of many key immune biomarkers and molecular pathways. Another problem with existing single-cell sequencing methods is that many of the cell-associated reads either fail to map to transcripts or map to uninformative ribosomal and mitochondrial genes. Some methods also require the use of live cells, which means the single-cell assay has to be carried out at the specific time of treatment or when culture is terminated. The aforementioned limitations have contributed to most single-cell sequencing studies being restricted to small numbers of samples and have prevented their wider scale adoption in biopharma, clinical, translational and applied applications. Here we report on the development and performance of a novel combinatorial split-pool-based workflow, TempO-LINC™, that adds cell-identifying molecular barcodes onto high-sensitivity gene expression probes within fixed cells. Cells can be fixed at the end of a treatment, or when obtained from a patient and stably stored for months until they are ready to be processed with other samples through the TempO-LINC assay. All probes within the same fixed cell receive an identical barcode, enabling the reconstruction of single-cell gene expression profiles across as few as several hundred cells and up to 100,000 cells per run. TempO-LINC simultaneously processes up to 96 fixed cell samples per run, has a simple workflow that is amenable to automation and as we will show, has a higher gene detection rate than existing single-cell platforms. We will also show that TempO-LINC has an observed doublet rate of less than 0.5% for 12,500 cells analyzed. Critically, TempO-LINC reduces sample sequencing costs and although we show the assay accurately profiles the whole transcriptome (23,000 transcripts), it can also be targeted to measure only genes/pathways of interest - dramatically reducing sequencing costs yet further. We applied TempO-LINC to assay PBMCs and a human hepatocyte model for toxicology and demonstrated the ability to correctly identify unique cell states and molecular pathways from these populations. We will also present time course and dose response data from compound treatment of cells. All of these features position TempO-LINC as a potential disruptive technology that hematology researchers, clinicians and drug developers can use for new large-scale applications/studies using single-cell sequencing across thousands of samples while obtaining improved data quality.

A PERK-Specific Inhibitor Blocks Metastatic Progression by Limiting Integrated Stress Response-Dependent Survival of Quiescent Cancer Cells.

The integrated stress response (ISR) kinase PERK serves as a survival factor for both proliferative and dormant cancer cells. We aim to validate PERK inhibition as a new strategy to specifically eliminate solitary disseminated cancer cells (DCC) in secondary sites that eventually reawake and originate metastasis. A novel clinical-grade PERK inhibitor (HC4) was tested in mouse syngeneic and PDX models that present quiescent/dormant DCCs or growth-arrested cancer cells in micro-metastatic lesions that upregulate ISR. HC4 significantly blocks metastasis, by killing quiescent/slow-cycling ISRhigh, but not proliferative ISRlow DCCs. HC4 blocked expansion of established micro-metastasis that contained ISRhigh slow-cycling cells. Single-cell gene expression profiling and imaging revealed that a significant proportion of solitary DCCs in lungs were indeed dormant and displayed an unresolved ER stress as revealed by high expression of a PERK-regulated signature. In human breast cancer metastasis biopsies, GADD34 expression (PERK-regulated gene) and quiescence were positively correlated. HC4 effectively eradicated dormant bone marrow DCCs, which usually persist after rounds of therapies. Importantly, treatment with CDK4/6 inhibitors (to force a quiescent state) followed by HC4 further reduced metastatic burden. In HNSCC and HER2+ cancers HC4 caused cell death in dormant DCCs. In HER2+ tumors, PERK inhibition caused killing by reducing HER2 activity because of sub-optimal HER2 trafficking and phosphorylation in response to EGF. Our data identify PERK as a unique vulnerability in quiescent or slow-cycling ISRhigh DCCs. The use of PERK inhibitors may allow targeting of pre-existing or therapy-induced growth arrested "persister" cells that escape anti-proliferative therapies.

Construction of EMT related prognostic signature for kidney renal clear cell carcinoma, through integrating bulk and single-cell gene expression profiles.

Introduction: Kidney renal clear cell carcinoma (KIRC), as a main type of malignant kidney cancers, has a poor prognosis. Epithelial-mesenchymal transformation (EMT) exerts indispensable role in tumor progression and metastasis, including in KIRC. This study aimed to mine more EMT related details and build prognostic signature for KIRC. Methods: The KIRC scRNA-seq data and bulk data were downloaded from GEO and TCGA databases, respectively. The cell composition in KIRC was calculated using CIBERSORT. Univariate Cox regression analysis and LASSO Cox regression analysis were combined to determine the prognostic genes. Gene set variation analysis and cell-cell communication analysis were conducted to obtain more functional information. Additionally, functional analyses were conducted to determine the biological roles of si-LGALS1 in vitro. Results: We totally identified 2,249 significant differentially expressed genes (DEGs) in KIRC samples, meanwhile a significant distinct expression pattern was found in KIRC, involving Epithelial Mesenchymal Transition pathway. Among all cell types, significantly higher proportion of epithelial cells were observed in KIRC, and 289 DEGs were identified in epithelial cells. After cross analysis of all DEGs and 970 EMT related genes, SPARC, TMSB10, LGALS1, and VEGFA were optimal to build prognostic model. Our EMT related showed good predictive performance in KIRC. Remarkably, si-LGALS1 could inhibit migration and invasion ability of KIRC cells, which might be involved in suppressing EMT process. Conclusion: A novel powerful EMT related prognostic signature was built for KIRC patients, based on SPARC, TMSB10, LGALS1, and VEGFA. Of which, si-LGALS1 could inhibit migration and invasion ability of KIRC cells, which might be involved in suppressing EMT process.

Single Cell Correlation Analysis: A Novel Method to Analyze Single Cell RNA Sequencing Data Identifies a Self-Renewing Subpopulation of Human Acute Myeloid Leukemia Stem Cells

Introduction Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy. Despite early response to standard chemotherapy, 60-70% of patients relapse with treatment resistant disease and die of relapsed disease. Leukemia stem cells (LSCs), the subpopulation of leukemia cells with self-renewal capacity, can recapitulate leukemia to cause relapse. Ongoing work to define therapeutic targets that can block self-renewal would prevent relapse and disease progression in AML. Prior work has established that LSCs express a distinct gene expression profile. We sought to define the gene expression profile of self-renewal at the single-cell level because a precise understanding of the transcriptional basis for self-renewal could provide more effective therapeutic targets. Our group previously demonstrated that activated NRAS (NRAS G12V) mediates self-renewal in the LSC-enriched subpopulation of AML in the Mll-AF9/NRAS G12V mouse model of AML (Sachs 2014). Single cell RNA-sequencing (scRNA-seq) of the LSC-enriched subpopulation identified three distinct transcriptional profiles. Two genes that encode cell surface markers, Cd36 and Cd69, delineate these distinct profiles. Using in vivo leukemia engraftment assays, we found that only the CD36 -CD69 + LSC subgroup repopulates leukemia while the CD36 +CD69 - LSC subgroup does not, demonstrating that self-renewal capacity is limited to the CD36 -CD69 + subset of the LSC-enriched compartment (Sachs 2020). In contrast, the CD36 +CD69 - LSCs were highly proliferative while the CD36 -CD69 + LSCs were poorly proliferative. These experiments show that self-renewal and rapid proliferation are mutually exclusive features of LSCs, as has previously been shown in normal hematopoietic stem cells (Li 2013). Methods and Results We investigated whether primary human AML stem cells express the murine-derived single-cell self-renewal and proliferation gene expression profiles at the single-cell level. Current computational methods to compare single-cell gene expression profiles use arbitrary similarity scores and do not assess the statistical significance of their findings. Therefore, we developed a new computational method called Single cell Correlation Analysis (SCA). SCA is designed to quantitate the expression of a predefined profile in single-cell RNA sequencing data. The quantification of the expression profiles is assessed on a per-cell basis in an unsupervised manner, meaning that SCA does not rely on any pre-sorting or classification of the query cells. The significance of the quantitative metric (i.e. level of expression) is determined by permutation-based false discovery rate testing. SCA can therefore identify cells that express a profile of interest within a single-cell RNA sequencing dataset and incorporates a measure of statistical significance to that assignment. We used SCA to analyze scRNA-seq data from primary human AML samples. We used data from two samples sequenced by our group and previously published data from 16 samples (van Galen 2019). SCA identified cells that express the murine single-cell self-renewal profile in every sample (0.32-11.5%; FDR < 0.25). We sorted two primary human AML samples to isolate LSCs (CD34 +CD38 -) prior to single-cell capture and sequencing. SCA identified cells that express murine LSC self-renewal profile in both of these samples as well (8.9-11.3%; FDR < 0.25). Furthermore, with these analyses, we found that the single-cell profiles of self-renewal and proliferation were mutually exclusive in human LSCs, as they are in murine LSCs and normal HSCs. We performed gene set enrichment analysis (GSEA) and confirmed that the human cells that express the murine single cell self-renewal profile are enriched in previously reported LSC self-renewal gene expression profiles. Conclusion We present SCA, a novel computational method designed to quantitatively assess single-cell transcriptional datasets and evaluate the statistical significance of its results. Using this method, we demonstrate that primary human AML samples express the single-cell profiles of self-renewal that we previously validated experimentally. SCA-based identification of human self-renewing cells will allow us to interrogate novel transcriptional features of these cells in future studies.

B-Cell Receptor Function and Gene Expression Profiling at Single-Cell Level across the Spectrum from Normal to Neoplastic CD5-Positive B-Cell Compartments in Humans

Antigen-independent, autonomous signalling of the B-cell receptor (BCR) is an oncogenic driver common to all cases and subtypes of chronic lymphocytic leukemia (CLL). We have recently shown that the dominant clonal population of low-count (<500 cells/µL) monoclonal B lymphocytosis (MBL) with CD5 +CD20 lowCD79B low CLL phenotype identified prospectively in healthy siblings of CLL patients also exhibit autonomous BCR signalling, albeit with lower signalling strength than CLL BCR (Quinten et al., Haematologica 2023). To gain further insight into the mechanisms of clonal expansion within the CD5 + B-cell compartment as the possible origin of CLL, we performed single-cell gene expression profiling and exemplary analyses of BCR function in normal CD5 + B cells (CD20 hiCD79B hi) and in CLL-phenotype B cells (CD5 +CD20 lowCD79B low) of healthy siblings of CLL patients in comparison to CLL and high-count MBL cells. Screening of blood samples of 16 sibling stem cell donors of CLL patients by flow cytometry revealed the presence of CD5 +CD20 lowCD79B low B cells at low counts in 5 donors. These cells and normal CD5 +CD20 hiCD79B hi B cells were sorted in parallel, pooled at equal ratios, and analyzed together with CLL B cells from their sibling stem cell recipients and 2 unrelated high-count MBL B cells on two 10X Genomics chips for single-cell 5‘ gene expression and BCR sequencing. Data deconvolution per individual was performed based on expressed SNPs and on the individuals’ HLA types. In a combined 2-dimensional t-SNE plot based on the 2000 most variably expressed genes, the normal CD5 +CD20 hiCD79B hi B cells from all 5 donors clustered distinctly from CLL-phenotype cells from all sources (dotted lines, Figure) and indeed showed significantly higher expression of CD20 and CD79B. Gene set enrichment analysis revealed significant upregulation of the hallmark oxidative phosphorylation gene set in all CLL samples compared to non-CLL B-cell populations. BCR analysis demonstrated clonal dominance of >99% for both Ig heavy and light chains in the 5 CLL samples. In accordance with the indication for allogeneic stem cell transplantation, these CLL BCR were unmutated. In marked contrast, normal CD5 +CD20 hiCD79B hi B cells from the healthy SC donors were also unmutated but completely polyclonal, i.e. no identical BCR was detected in any two cells of this compartment. In 4/5 donors, the CLL-phenotype CD5 +CD20 lowCD79B low compartment contained multiple clonal expansions of various degrees. In one high-count MBL, 17 other B-cell clones with various degrees of low-level expansion coexisted with the >90% dominant MBL clone. BCR from the most dominant and one or more of the less expanded CD5 +CD20 lowCD79B low clones of the healthy donors were tested for autonomous signaling as quantified by BCR-induced calcium flux without experimental cross-linking in murine TKO pre-B cells and compared to BCR from nonexpanded CD5 +CD20 hiCD79B hi cells and from their CLL siblings. Autonomous BCR signaling strength was calculated from the fraction of cells with spontaneous calcium flux above test background and calibrated against calcium flux after BCR crosslinking. CLL and high-count MBL BCR had robust median autonomous BCR signaling of 0.326. Expanded CD5 +CD20 lowCD79B low clones of the healthy donors showed significantly weaker BCR signalling strength of 0.163 (p<0.01; Scatter Plot). BCR signalling in nonexpanded CD5 + B cells appeared weaker than in expanded clones but was clearly above the background of BCR from mature B cells isolated from lymph node biopsies expressing a mutated IgG. In conclusion, the low-count CD5 +CD20 lowCD79B low CLL-phenotype B-cell compartment in healthy adults is composed of multiple, predominantly mutated B-cell clones. Therefore, the term “monoclonal B lymphocytosis” is highly misleading for these B-cell populations and should be avoided. Normal CD5 +CD20 hiCD79B hi B cells are exclusively unexpanded and express unmutated BCR, indicating a naïve status. Unexpectedly, these nonexpanded CD5 + B cells express BCR with relatively weak but quantifiable autonomous signalling. Globally, autonomous BCR signalling strength across the CD5 + B-cell compartment appears to be correlated to the degree of clonal expansion. Fully malignant CLL cells overexpress genes of the oxidative phosphorylation pathway, presumably to meet increased energy demand from alternative sources.

Identifying genes associated with resistance to KRAS G12C inhibitors via machine learning methods

BackgroundTargeted therapy has revolutionized cancer treatment, greatly improving patient outcomes and quality of life. Lung cancer, specifically non-small cell lung cancer, is frequently driven by the G12C mutation at the KRAS locus. The development of KRAS inhibitors has been a breakthrough in the field of cancer research, given the crucial role of KRAS mutations in driving tumor growth and progression. However, over half of patients with cancer bypass inhibition show limited response to treatment. The mechanisms underlying tumor cell resistance to this treatment remain poorly understood. MethodsTo address above gap in knowledge, we conducted a study aimed to elucidate the differences between tumor cells that respond positively to KRAS (G12C) inhibitor therapy and those that do not. Specifically, we analyzed single-cell gene expression profiles from KRAS G12C-mutant tumor cell models (H358, H2122, and SW1573) treated with KRAS G12C (ARS-1620) inhibitor, which contained 4297 cells that continued to proliferate under treatment and 3315 cells that became quiescent. Each cell was represented by the expression levels on 8687 genes. We then designed an innovative machine learning based framework, incorporating seven feature ranking algorithms and four classification algorithms to identify essential genes and establish quantitative rules. ResultsOur analysis identified some top-ranked genes, including H2AFZ, CKS1B, TUBA1B, RRM2, and BIRC5, that are known to be associated with the progression of multiple cancers. ConclusionAbove genes were relevant to tumor cell resistance to targeted therapy. This study provides important insights into the molecular mechanisms underlying tumor cell resistance to KRAS inhibitor treatment.

POT1a deficiency in mesenchymal niches perturbs B-lymphopoiesis

Protection of telomeres 1a (POT1a) is a telomere binding protein. A decrease of POT1a is related to myeloid-skewed haematopoiesis with ageing, suggesting that protection of telomeres is essential to sustain multi-potency. Since mesenchymal stem cells (MSCs) are a constituent of the hematopoietic niche in bone marrow, their dysfunction is associated with haematopoietic failure. However, the importance of telomere protection in MSCs has yet to be elucidated. Here, we show that genetic deletion of POT1a in MSCs leads to intracellular accumulation of fatty acids and excessive ROS and DNA damage, resulting in impaired osteogenic-differentiation. Furthermore, MSC-specific POT1a deficient mice exhibited skeletal retardation due to reduction of IL-7 producing bone lining osteoblasts. Single-cell gene expression profiling of bone marrow from POT1a deficient mice revealed that B-lymphopoiesis was selectively impaired. These results demonstrate that bone marrow microenvironments composed of POT1a deficient MSCs fail to support B-lymphopoiesis, which may underpin age-related myeloid-bias in haematopoiesis.

Projecting RNA measurements onto single cell atlases to extract cell type-specific expression profiles using scProjection

Multi-modal single cell RNA assays capture RNA content as well as other data modalities, such as spatial cell position or the electrophysiological properties of cells. Compared to dedicated scRNA-seq assays however, they may unintentionally capture RNA from multiple adjacent cells, exhibit lower RNA sequencing depth compared to scRNA-seq, or lack genome-wide RNA measurements. We present scProjection, a method for mapping individual multi-modal RNA measurements to deeply sequenced scRNA-seq atlases to extract cell type-specific, single cell gene expression profiles. We demonstrate several use cases of scProjection, including identifying spatial motifs from spatial transcriptome assays, distinguishing RNA contributions from neighboring cells in both spatial and multi-modal single cell assays, and imputing expression measurements of un-measured genes from gene markers. scProjection therefore combines the advantages of both multi-modal and scRNA-seq assays to yield precise multi-modal measurements of single cells.

Single-cell transcriptome reveals cell division-regulated hub genes in the unicellular eukaryote Paramecium

The transition from growth to division during the cell cycle encompasses numerous conserved processes such as large-scale DNA replication and protein synthesis. In ciliate cells, asexual cell division is accompanied by additional cellular changes including amitotic nuclear division, extensive ciliogenesis, and trichocyst replication. However, the molecular mechanisms underlying these processes remain elusive. In this study, we present single-cell gene expression profiles of Paramecium cf. multimicronucleatum cells undergoing cell division. Our results reveal that the most up-regulated genes in dividing cells compared to growing cells are associated with 1) cell cycle signaling pathways including transcription, DNA replication, chromosome segregation and protein degradation; 2) microtubule proteins and tubulin glycylases which are essential for ciliogenesis, nuclei separation and structural differentiation signaling; and 3) trichocyst matrix proteins involved in trichocyst synthesis and reproduction. Furthermore, weighted gene co-expression network analysis identified hub genes that may play crucial roles during cell division. Our findings provide insights into cell cycle regulators, microtubules and trichocyst matrix proteins that may exert influence on this process in ciliates.

Abstract 2472: Interdisciplinary method to elucidate the interaction between brain microenvironment and cancer cells

Abstract Cancer cells may escape from host immunity to form distant metastases. We have made an original imaging model of brain metastasis (IBrM) to show a heterogeneous interaction between microglia, the tissue macrophages in the brain, and cancer cells in the brain niche. Here we report that enhanced microglial elimination of cancer cells is a new potential treatment for metastatic brain tumors by inhibiting their engraftment. First, to explore factors that favor survival of cancer cells in the brain microenvironment, mouse lung cancer cells (CMT167) were injected through the internal carotid artery, and after 4, 7, 10, and 13 days, surviving cancer cells in the mouse brain were collected and RNAseq was performed. In particular, we focused on CD24/CD7/PD-L1, a known factor that escapes phagocytosis by macrophages. The expression of CD24/CD47 in cancer cells gradually increased, while that of PD-L1 decreased. Next, we injected adenocarcinoma lung cancer cells (LUCs, CMT167) or breast cancer cells (BCCs, E0711) expressing mCherry via the internal carotid artery of the CX3CR1-EGFP mice, whose microglia had been specifically labeled with EGFP. The microglia and LUCs/BCCs were visualized in vivo simultaneously by two-photon microscopy for 14 days. The tumor fate and microglial response against cancer cells were evaluated at single cell resolution in the IBrM. Microglial phagocytosis was significantly increased by single deletion of CD47 or CD24 compared with WT cells. Combined deletion of CD47 and CD24 also synergically increased microglial phagocytosis, resulting in reduced IBrM and prolonged mouse survival. By contrast, deletion of PD-L1 did not enhance microglial phagocytosis or prolong survival. The pharmacological (PLX3397) or genetic conditional (Siglechdtr het/CX3CR1GFP het) conditional depletion of microglia canceled both the increased phagocytosis and the extended survival time, suggesting that the effect of “don't eat me” signals was microglia dependent. The extended survival time was also observed in IBrM using BALB-c nu/nu, that suggest the effect is not dependent on matured T-lymphocytes.These results indicate that novel function of microglia against cancer cells, and suppression of both CD24 and CD47 in cancer cells and enhances microglial phagocytic activity and suppresses the metastatic formation. We are further developing a method for isolating LUCs fluorescently labeled in vivo using holographic 2-photon microscopy for evaluating single cell gene expression profiles. Using the novel techniques, the spatio-temporal information can be integrated across the molecular, cellular and tissue levels that allow us to further investigate the dynamic behavior of not only tumors, but also microglia and neurons. Citation Format: Takahiro Tsuji, Hiroaki Wake, Mariko Shindo, Rahadian Y. Hartantio, Misuzu Horikoshi, Daisuke Kato, Hiroaki Ozasa, Toyohiro Hirai. Interdisciplinary method to elucidate the interaction between brain microenvironment and cancer cells [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 2472.

Single-cell RNA sequencing reveals maturation trajectory in human pluripotent stem cell-derived cardiomyocytes in engineered tissues.

Cardiac invitro models have become increasingly obtainable and affordable with the optimization of human pluripotent stem cell-derived cardiomyocyte (hPSC-CM) differentiation. However, these CMs are immature compared to their invivo counterparts. Here we study the cellular phenotype of hPSC-CMs by comparing their single-cell gene expression and functional profiles in three engineered cardiac tissue configurations: human ventricular (hv) cardiac anisotropic sheet, cardiac tissue strip, and cardiac organoid chamber (hvCOC), with spontaneously aggregated 3D cardiac spheroids (CS) as control. The CM maturity was found to increase with increasing levels of complexity of the engineered tissues from CS to hvCOC. The contractile components are the first function to mature, followed by electrophysiology and oxidative metabolism. Notably, the 2D tissue constructs show a higher cellular organization whereas metabolic maturity preferentially increases in the 3D constructs. We conclude that the tissue engineering models resembling configurations of native tissues may be reliable for drug screening or disease modeling.

Integrative analysis of bulk and single-cell gene expression profiles to identify tumor-associated macrophage-derived CCL18 as a therapeutic target of esophageal squamous cell carcinoma

BackgroundEsophageal squamous cell carcinoma (ESCC) is a common gastrointestinal malignancy with poor patient prognosis. Current treatment for ESCC, including immunotherapy, is only beneficial for a small subset of patients. Better characterization of the tumor microenvironment (TME) and the development of novel therapeutic targets are urgently needed.MethodsIn the present study, we hypothesized that integration of single-cell transcriptomic sequencing and large microarray sequencing of ESCC biopsies would reveal the key cell subtypes and therapeutic targets that determine the prognostic and tumorigenesis of ESCC. We characterized the gene expression profiles, gene sets enrichment, and the TME landscape of a microarray cohort including 84 ESCC tumors and their paired peritumor samples. We integrated single-cell transcriptomic sequencing and bulk microarray sequencing of ESCC to reveal key cell subtypes and druggable targets that determine the prognostic and tumorigenesis of ESCC. We then designed and screened a blocking peptide targeting Chemokine C–C motif ligand 18 (CCL18) derived from tumor associated macrophages and validated its potency by MTT assay. The antitumor activity of CCL18 blocking peptide was validated in vivo by using 4-nitroquinoline-1-oxide (4-NQO) induced spontaneous ESCC mouse model.ResultsComparative gene expression and cell–cell interaction analyses revealed dysregulated chemokine and cytokine pathways during ESCC carcinogenesis. TME deconvolution and cell interaction analyses allow us to identify the chemokine CCL18 secreted by tumor associated macrophages could promote tumor cell proliferation via JAK2/STAT3 signaling pathway and lead to poor prognosis of ESCC. The peptide Pep3 could inhibit the proliferation of EC-109 cells promoted by CCL18 and significantly restrain the tumor progression in 4-NQO-induced spontaneous ESCC mouse model.ConclusionsFor the first time, we discovered and validated that CCL18 blockade could significantly prevent ESCC progression. Our study revealed the comprehensive cell–cell interaction network in the TME of ESCC and provided novel therapeutic targets and strategies to ESCC treatment.

Integrative in situ mapping of single-cell transcriptional states and tissue histopathology in a mouse model of Alzheimer's disease.

Complex diseases are characterized by spatiotemporal cellular and molecular changes that may be difficult to comprehensively capture. However, understanding the spatiotemporal dynamics underlying pathology can shed light on disease mechanisms and progression. Here we introduce STARmap PLUS, a method that combines high-resolution spatial transcriptomics with protein detection in the same tissue section. As proof of principle, we analyze brain tissues of a mouse model of Alzheimer's disease at 8 and 13 months of age. Our approach provides a comprehensive cellular map of disease progression. It reveals a core-shell structure where disease-associated microglia (DAM) closely contact amyloid-β plaques, whereas disease-associated astrocyte-like (DAA-like) cells and oligodendrocyte precursor cells (OPCs) are enriched in the outer shells surrounding the plaque-DAM complex. Hyperphosphorylated tau emerges mainly in excitatory neurons in the CA1 region and correlates with the local enrichment of oligodendrocyte subtypes. The STARmap PLUS method bridges single-cell gene expression profiles with tissue histopathology at subcellular resolution, providing a tool to pinpoint the molecular and cellular changes underlying pathology.