Single-cell Sequencing Studies Research Articles

A natural language processing system for the efficient extraction of cell markers

Single-cell RNA sequencing (scRNA-seq) has emerged as a pivotal tool for exploring cellular landscapes across diverse species and tissues. Precise annotation of cell types is essential for understanding these landscapes, relying heavily on empirical knowledge and curated cell marker databases. In this study, we introduce MarkerGeneBERT, a natural language processing (NLP) system designed to extract critical information from the literature regarding species, tissues, cell types, and cell marker genes in the context of single-cell sequencing studies. Leveraging MarkerGeneBERT, we systematically parsed full-text articles from 3702 single-cell sequencing-related studies, yielding a comprehensive collection of 7901 cell markers representing 1606 cell types across 425 human tissues/subtissues, and 8223 cell markers representing 1674 cell types across 482 mouse tissues/subtissues. Comparative analysis against manually curated databases demonstrated that our approach achieved 76% completeness and 75% accuracy, while also unveiling 89 cell types and 183 marker genes absent from existing databases. Furthermore, we successfully applied the compiled brain tissue marker gene list from MarkerGeneBERT to annotate scRNA-seq data, yielding results consistent with original studies. Conclusions: Our findings underscore the efficacy of NLP-based methods in expediting and augmenting the annotation and interpretation of scRNA-seq data, providing a systematic demonstration of the transformative potential of this approach. The 27323 manual reviewed sentences for training MarkerGeneBERT and the source code are hosted at https://github.com/chengpeng1116/MarkerGeneBERT.

Deciphering the impact of aggregated autophagy-related genes TUBA1B and HSP90AA1 on colorectal cancer evolution: a single-cell sequencing study of the tumor microenvironment

BackgroundColorectal cancer (CRC) is the third most prevalent cancer worldwide, with the tumor microenvironment (TME) playing a crucial role in its progression. Aggregated autophagy (AA) has been recognized as a factor that exacerbates CRC progression. This study aims to study the relationship between aggregated autophagy and CRC using single-cell sequencing techniques. Our goal is to explain the heterogeneity of the TME and to explore the potential for targeted personalized therapies.ObjectiveTo study the role of AA in CRC, we employed single-cell sequencing to discern distinct subpopulations within the TME. These subpopulations were characterized by their autophagy levels and further analyzed to identify specific biological processes and marker genes.ResultsOur study revealed significant correlations between immune factors and both clinical and biological characteristics of the tumor microenvironment (TME), particularly in cells expressing TUBA1B and HSP90AA1. These immune factors were associated with T cell depletion, a reduction in protective factors, diminished efficacy of immune checkpoint blockade (ICB), and enhanced migration of cancer-associated fibroblasts (CAFs), resulting in pronounced inflammation. In vitro experiments showd that silencing TUBA1B and HSP90AA1 using siRNA (Si-TUBA1B and Si-HSP90AA1) significantly reduced the expression of IL-6, IL-7, CXCL1, and CXCL2 and inhibition of tumor cell growth in Caco-2 and Colo-205 cell lines. This reduction led to a substantial alleviation of chronic inflammation and highlighted the heterogeneous nature of the TME.ConclusionThis study marks an initial foray into understanding how AA-associated processes may potentiate the TME and weaken immune function. Our findings provide insights into the complex dynamics of the TME and highlight potential targets for therapeutic intervention, suggesting a key role for AA in the advancement of colorectal cancer.

Light and dopamine impact two circadian neurons to promote morning wakefulness

In both mammals and flies, circadian brain neurons orchestrate physiological oscillations and behaviors like wake and sleep-these neurons can be subdivided by morphology and by gene expression patterns. Recent single-cell sequencing studies identified 17 Drosophila circadian neuron groups. One of these includes only two lateral neurons (LNs), which are marked by the expression of the neuropeptide ion transport peptide (ITP). Although these two ITP+ LNs have long been grouped with five other circadian evening activity cells, inhibiting the two neurons alone strongly reduces morning activity, indicating that they also have a prominent morning function. As dopamine signaling promotes activity in Drosophila, like in mammals, we considered that dopamine might influence this morning activity function. Moreover, the ITP+ LNs express higher mRNA levels than other LNs of the type 1-like dopamine receptor Dop1R1. Consistent with the importance of Dop1R1, cell-specific CRISPR-Cas9 mutagenesis of this receptor in the two ITP+ LNs renders flies significantly less active in the morning, and exvivo live imaging shows Dop1R1-dependent cyclic AMP (cAMP) responses to dopamine in these two neurons. Notably, the response is more robust in the morning, reflecting higher morning Dop1R1 mRNA levels in the two neurons. As mRNA levels are not elevated in constant darkness, this suggests light-dependent upregulation of morning Dop1R1 transcript levels. Taken together with the enhanced morning cAMP response to dopamine, the data indicate how light and dopamine promote morning wakefulness in flies, mimicking the important effect of light on morning wakefulness in humans.

Abstract PO4-13-09: Paclitaxel affects the efficacy of PD-1 blockade by interfering with lipid metabolism reprogramming in patients with breast cancer

Abstract Background: The question of how chemotherapeutic drugs affect the efficacy of PD-1/PD-L1 antibodies in patients with breast cancer is still pending. In a previously single-cell sequencing study, we have demonstrated that paclitaxel reduces the level of CXCL13+ T cells and other immune cells critical for atezolizumab to work, leading to inferior efficacy of atezolizumab in triple negative breast cancer (TNBC). How paclitaxel affects these important immune cells remains obscure. Recently, plasma metabolomic and proteomics analysis have shown that patients’ systemic metabolic signatures is correlated with the response of PD-1/PD-L1 antibody. As such, understanding the differential metabolic influences of the diverse chemotherapeutic drugs that comprise an immune response to TNBC offers an opportunity to appropriately select chemotherapeutic backbones for ICIs. Methods: We collected pre- and post-treatment plasma samples from breast cancer patients for metabolomic and proteomic analysis, including four patient cohorts: two independent cohorts (discovery cohort and validation cohort) in which patients were treated with ICIs, one cohort in which patients were treated with paclitaxel, and one cohort of patients treated with nab-paclitaxel. Patients were divided into responder group (R, tumor shrinkage) or non-responder group (NR, tumor increase) according to the change in tumor size after treatment relative to baseline. This was followed by integrating metabolomics and proteomics with single-cell transcriptome, along with in vitro experiments, to shed light on the mechanisms of action leading to ICIs resistance in breast cancer patients. Results: In the discovery cohort, the metabolites that mostly differed between the R and NR groups at baseline were lysoglycerophospholipids. These results were further validated in the validation cohort of patients. The dynamic changes of lysoglycerophospholipids were still significantly different between the R and the NR groups after ICIs treatment in the discovery cohort. It’s worth noting that the level of lysophosphatidylcholines (LPCs), the most prominent lysoglycerophospholipids, increased significantly in the R group, while no significant changes among LPCs were found in the NR group after ICIs treatment. In the validation cohort, the median PFS of LPClow patients was 1.8 months versus 6.8 months in the LPChigh group (P = 0.0068). After one cycle of paclitaxel treatment, the metabolic status of patients changed dramatically, especially the levels of lipids. It is notable that most LPCs were significantly downregulated after paclitaxel treatment. However, in patients who received nab-paclitaxel, few significantly changed lipids were detected after one cycle nab-paclitaxel treatment compared with their baseline conditions. Interestingly, the levels of LPCs were upregulated after one cycle nab-paclitaxel treatment, but decreased after paclitaxel treatment. Single-cell omics results showed that in patients' PBMCs, CXCR4+ NK cells were the most closely related to plasma LPC levels, while FGFBP2+ NK cells were in the tumor microenvironment. We isolated and expanded NK cells from PBMCs for in vitro experiments, and found that LPC stimulation can significantly upregulate the expression of CXCR4+ in NK cells, and further increase the chemotaxis and cytotoxicity of NK cells. Conclusions: In breast cancer patients receiving ICIs, the systemic lipid metabolism status, especially lysoglycerophospholipids, is closely related to the efficacy of immunotherapy. The key molecule LPC, the most prominent lysoglycerophospholipids, may promote the efficacy of immunotherapy by activating NK cells in breast cancer patients. Paclitaxel may impair the efficacy of immunotherapy by affecting the systemic lipid metabolism status, especially by reducing plasma LPC levels, so it is not a suitable partner for ICIs. Citation Format: Hongnan Mo, Jiashu Han, Jingtong Zhai, Xiaoying Sun, Xiuwen Guan, Haili Qian, Fei Ma. Paclitaxel affects the efficacy of PD-1 blockade by interfering with lipid metabolism reprogramming in patients with breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-13-09.

Cancer-associated fibroblasts: protagonists of the tumor microenvironment in gastric cancer.

Enhanced knowledge of the interaction of cancer cells with their environment elucidated the critical role of tumor microenvironment in tumor progression and chemoresistance. Cancer-associated fibroblasts act as the protagonists of the tumor microenvironment, fostering the metastasis, stemness, and chemoresistance of cancer cells and attenuating the anti-cancer immune responses. Gastric cancer is one of the most aggressive cancers in the clinic, refractory to anti-cancer therapies. Growing evidence indicates that cancer-associated fibroblasts are the most prominent risk factors for a poor tumor immune microenvironment and dismal prognosis in gastric cancer. Therefore, targeting cancer-associated fibroblasts may be central to surpassing resistance to conventional chemotherapeutics, molecular-targeted agents, and immunotherapies, improving survival in gastric cancer. However, the heterogeneity in cancer-associated fibroblasts may complicate the development of cancer-associated fibroblast targeting approaches. Although single-cell sequencing studies started dissecting the heterogeneity of cancer-associated fibroblasts, the research community should still answer these questions: "What makes a cancer-associated fibroblast protumorigenic?"; "How do the intracellular signaling and the secretome of different cancer-associated fibroblast subpopulations differ from each other?"; and "Which cancer-associated fibroblast subtypes predominate specific cancer types?". Unveiling these questions can pave the way for discovering efficient cancer-associated fibroblast targeting strategies. Here, we review current knowledge and perspectives on these questions, focusing on how CAFs induce aggressiveness and therapy resistance in gastric cancer. We also review potential therapeutic approaches to prevent the development and activation of cancer-associated fibroblasts via inhibition of CAF inducers and CAF markers in cancer.

Abstract B001: Glioblastoma evolution and resistance is mediated by a shift in cell state and tumor microenvironmental interactions

Abstract Glioblastoma (GBM) is a lethal disease characterized by inevitable recurrence. Recently, single cell sequencing studies of primary GBM have defined various tumor cell states, specifically the neural progenitor-like (NPC-like), oligodendrocyte progenitor (OPC-like), astrocyte-like(AC-like), and mesenchymal(MES-like) states. Yet, the role these cell states play in treatment resistance and recurrence is not well defined. Furthermore, the spatial tumor microenvironmental (TME) context of tumor cells clearly plays a role in treatment response. Here we utilize in vivo recurrence models, and single cell and spatial transcriptomic (ST) analyses of primary and recurrent GBM to determine the pathways and spatial TME interactions mediating recurrence. Experimental Design: To define the evolution of the tumor landscape from primary to recurrence, we performed single cell RNA sequencing from stereotactically resected primary GBM (178K cells from 26 patients) and at recurrence (170K cells from 12 patients). ST analyses were also completed, as well as in vitro and in vivo mechanistic studies. Results: We identified a notable shift in the proportion of cell states in response to treatment from primary to recurrence with a significant decrease in AC-like cells (72% vs 55%, p<2e-16) and increase in MES-like cells (15% vs 34%, p<2e-16). This suggests that AC-like cells may be more treatment sensitive compared to other cell states, especially MES-like cells. We then worked to define potential TME interactions of these cell states to define drivers of recurrence. ST analyses revealed NPC-like cells in the infiltrative edge, AC-like cells in the tumor core, and MES-like cells in the hypoxic zones. We performed pseudotime trajectory analysis which identified that NPC-like cells divided into 2 daughter lineages: 1) AC-like cells which form the bulk of primary tumors and 2) MES-like cells that make up a large proportion of the recurrence. We then found that THY1, a cell surface receptor, was highly expressed in NPC-like cells in the primary tumors. While at recurrence, there was a remarkable increase in THY1 expression coincident with a switch to a predominantly MES-like state. Furthermore, ST analyses revealed upregulation of stem-like pathways in THY1 regions, as well as co-localization of MES-like THY1 cells with monocytes in hypoxic zones(p<0.001), suggesting an important role for TME interactions in mediating recurrence. To assess the biological implications of THY1, subsequent in vitro and in vivo studies revealed that THY1 knockout significantly decreased cell proliferation and tumor volume, and improved treatment response suggesting an important role for THY1 in driving treatment resistance and inevitable recurrence. Conclusions: Utilizing mechanistic and bioinformatic analyses, we show that a small population of NPC and MES-like THY1+ cells in primary GBM is likely to survive chemoradiation and mediate recurrence. Defining the interactions of these cell states in their TME and the mechanistic underpinnings of THY1 interactions may be critical to identifying new treatments. Citation Format: Sunita Shankar, Visweswaran Ravikumar, Arushi Tripathy, Sunjong Ji, Jackson Loper, Zainab Hassan, Ziad Fehmi, Yacoub Haydin, Dah-Luen Huang, Sagnik Bhadury, Reva Kulkarni, Jeffrey Regier, Daniel Wahl, Arvind Rao, Alnawaz Rehemtulla, Wajd N. Al-Holou. Glioblastoma evolution and resistance is mediated by a shift in cell state and tumor microenvironmental interactions [abstract]. In: Proceedings of the AACR Special Conference on Brain Cancer; 2023 Oct 19-22; Minneapolis, Minnesota. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_1):Abstract nr B001.

Abstract B058: Deconvoluting the intra-tumour heterogeneity and subclonal evolution of CDK4/6 inhibitor resistance in ER+ breast cancer

Abstract Subclonal heterogeneity and evolution are characteristics of breast cancer (BC), that play a key role in tumour development, progression, and resistance to current therapies. Preliminary single-cell sequencing studies suggest that subclonal heterogeneity drives therapy response in aggressive BC. Here, we sought to identify whether pre-existing transcriptomically defined cell subpopulations underpin resistance to CDK4/6 inhibitors (CDK4/6i) in ER+ BC, and to identify the distinct or shared resistance mechanisms between different CDK4/6i currently used in the clinic. ER+ BC cell lines, MCF7 and T47D, were infected with a lentiviral barcode library and were long-term exposed to DMSO or CDK4/6i (Abemaciclib or Palbociclib) until drug resistance was achieved. CDK4/6i resistant or DMSO cell lines were then subjected to DNA sequencing for the detection of barcodes coupled with single-cell transcriptomic and barcode sequencing, whole exome sequencing and G1/S cell cycle checkpoint analysis at a protein level. Single-cell lineage tracing identified that resistance to both CDK4/6i in MCF7 cells was stochastic, while in T47D cells, resistance to both CDK4/6i was conserved across all biological replicates. In all cell models, abemaciclib exerted a stronger selective pressure than palbociclib. Detection of barcodes from dead cells highlighted differential selective pressures of the drugs during resistance generation and upon resistance emergence. Single-cell transcriptomic sequencing identified shared and differential mechanisms of resistance between cell lines and specific CDK4/6i, suggestive of different subclonal, non-genetic mechanisms driving resistance. Some of these subclones were pre-defined (i.e. shared transcriptomic features with parental cells), whereas other resistant subclones were demarked by acquisition of pathway up-regulation. For instance, RB1 expression was abolished in the entire palbociclib-resistant T47D population, with copy number loss, indicating RB1 as a genetic driver of resistance. No evidence of RB1 loss was observed in MCF7 palbociclib-resistant clonal population, however a subclonal cluster was identified with loss of RB1 expression. Interestingly, abemaciclib-resistant MCF7 cells had lost RB1 protein expression, suggesting differential non-genetic mechanisms of resistance to CDK4/6i in MCF7 cells. Through single-cell lineage tracing, we have identified that resistance to CDK4/6i can be stochastic or conserved according to the cell model. Additionally, single-cell transcriptomic sequencing identified that in some cell models, cells that have the ability to become resistant are pre-existing, suggesting transcriptomic and epigenomic mechanisms of resistance, where cells exhibit drug-tolerant or drug-induced persistent properties. Citation Format: Ioanna Mavrommati, Fatemeh Ahmadi Moughari, Shefali Thakur, Yu Zhang, Lesley-Ann Martin, Syed Haider, Rachael Natrajan. Deconvoluting the intra-tumour heterogeneity and subclonal evolution of CDK4/6 inhibitor resistance in ER+ breast cancer [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr B058.

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.

BRAF-Mutated Acute Myeloid Leukemia (AML) Represents a Distinct, Prognostically Poor Subgroup Enriched in Myelodysplasia-Related (MR-)AML

Background RAS signaling pathway mutations, mainly NRAS, KRAS, and/or PTPN11 variants, are common somatic events in de novo and MR-AML. BRAF mutations occur with lower frequency in AML and are reported to be associated with poor treatment outcome. However, no comprehensive analysis exists that firmly delineates clinical and molecular characteristics of BRAF-mutated AML, including insights into clonal architecture and co-occurring mutations. Methods We identified 42 patients (pts) with BRAF-mutated AML among pts with molecularly profiled disease in the setting of large comprehensive cancer centers [enriched for relapsed/refractory (R/R) and secondary AML] and cooperative group frontline trials (Cancer and Leukemia Group B/Alliance for Clinical Trials in Oncology, enriched for de novo AML). All pts had NGS-based targeted sequencing data, cytogenetic information, and detailed clinical annotations available. To fully evaluate the molecular landscape, 6 pts underwent integrated genomic profiling including paired tumor/normal whole exome sequencing and total transcriptome sequencing. We also analyzed pt samples using simultaneous single-cell molecular profiling and cell surface protein expression (DNA+Protein) sequencing to assess cell states and clonal make-up at single-cell resolution in a subset of pts (n=8). Results The 42 pts with BRAF-mutated AML had a median age of 67 years (range, 19-84); 57% were male. BRAF mutations were most common in cases of MR-AML (as defined by WHO 5th edition), accounting for 32 (76%) pts. BRAF mutations were found in newly diagnosed (n=19, 45%), R/R (n=8, 19%) and secondary AML (n=15, 36%) pts. As detected by bulk NGS sequencing, BRAF mutations were found both as dominant clonal and subclonal events, present at variant allele fractions (VAF) of 1-83% ( Figure 1, BRAF VAF indicated via color scale). Most (n=30, 71%) pts had non-V600 BRAF mutations (including G469, n=12; D594, n=7 and other, n=12). The most frequent co-occurring mutations were in the TET2 (36%), ASXL1 (33%), NRAS (29%), KRAS (26%), RUNX1 (19%), DNMT3A, FLT3-ITD/TKD, NPM1 and SRSF2 (all 17%) genes. By whole exome sequencing, BRAF-mutated AML samples carried a median mutational burden of 15 non-synonymous coding variants (range, 9-30), including 6 RAS-pathway and 3 MR-AML mutations. In 2 pts with paired relapse material available, the BRAF mutation was either stable at relapse or lost and the pt instead acquired a IQGAP3 mutation, supporting the RAS-pathway “addiction” of this leukemia. Single-cell multi-omic sequencing studies uncovering unique genotype-immunophenotype relationships and confirming clonal hierarchies are ongoing and will be presented at the meeting. Clinically, the BRAF-mutated pts had extremely poor survival, regardless of therapy. Pts were treated with low intensity [LI, n=10 (29%); LI+venetoclax (VEN, n=10 (29%)], high-intensity [HI, n=12 (34%) or HI+VEN, n=3 (9%)] regimens. The overall composite remission (CR+CRi) rate was 39%. Median overall survival (OS) for the entire cohort was 7 months, with 31 (89%) of pts deceased at the time of last follow-up. There were no significant differences in OS based on treatment regimens ( Figure 2). Importantly, there was no impact of BRAF variant allele burden on OS, with pts wiith dominant clonal and those with subclonal mutations having similar outcomes. Given the enrichment of BRAF mutations in MR-AML, we assessed whether RAS pathway mutations generally represented poor outcome prognosticators in this subgroup. A comparison of a control cohort of MR-AML pts with (n=129) and without (n=403) RAS pathway mutations treated on cytarabine/daunorubicin-based frontline protocols, revealed no survival difference between RAS-mutated and wild-type pts, suggesting a negative survival impact specific to BRAF-carrying leukemic clones. Conclusions BRAF mutations are rare, but recurrent molecular alterations in AML that are enriched in MR-AML. They associate with distinctly poor prognosis regardless of their clonal burden, without significant therapeutic advantage of currently available treatment regimens. This suggests the need to assess the utility of BRAF inhibitors and/or RAS pathway-targeting regimens such as MEK inhibitors in pts with AML carrying BRAF mutations. Support: U10CA180821, U10CA180882, U24CA196171; Clinicaltrials.gov: NCT00048958 (CALGB 8461), NCT00899223 (CALGB 9665), NCT00900224 (CALGB 20202)

Multimodal Atlas of Paired Diagnosis and Relapse AML Samples Enables Novel Therapeutic Targeting of Surface Antigens

Note: A.H. and M.U. share co-first authorship. AML is an aggressive clonal malignancy characterized by combinations of chromosomal abnormalities, gene mutations, and cell surface antigen (Ag) expression profiles. This heterogeneity contributes to refractory or relapsed disease that presents a major challenge when treating AML. Previous single cell sequencing studies of primary AML samples have provided remarkable insight into the clonal architecture of AML cell populations and how their mutational, transcriptomic, and surface Ag profiles vary between patients. However, information addressing clonal shifts during progression from diagnosis to relapse in large cohorts is lacking. Here, we adapted single cell RNA sequencing with surface Ag feature barcoding to analyze more than 450,000 cells from 28 paired AML patient bone marrow mononuclear cell samples collected at diagnosis and relapse (56 samples). To our knowledge, it is the largest and most comprehensive single cell AML atlas to date. This atlas contains rich clinical metadata including cytogenetics, mutation status of canonical AML genes, treatment history, and survival information. We leveraged these data to identify potential correlations with clonal heterogeneity during progression to relapse and to propose novel strategies for targeting the surface of AML cells. The feature barcoding panel consists of a comprehensive list of 81 surface Ags reported in clinicaltrials.gov or mined from literature, including large proteomics mass spectrometry datasets of AML patient bone marrow samples (deBoer et. al. Cancer Cell 2018; Jayavelu et al, Cancer Cell 2022). Feature barcoding produces antibody derived tag (ADT) counts which are interpreted as relative values but alone does not indicate absolute number of Ags per cell. We addressed this limitation by measuring absolute Ag density of AML Ags, CD33, CLL1, CD123, and EMR2 in patient samples using the flow cytometric QuantiBRITE assay. Focusing on these four Ags, we modeled the relationship between ADT expression and antibodies per cell (ABC) Ag density from QuantiBRITE. The model was applied to impute absolute Ag density for the remaining 77 Ags in all samples. UMAP visualization after sample transcriptome integration revealed distinct clustering of CD45-dim myeloblasts, T cells, B cells, and erythroid cells. Longitudinal analysis identified 28 surface Ags that were differentially expressed (absolute log 2FC > 1, p < 0.01) between relapse and diagnosis myeloblasts across multiple patients (Fig. 1A). An additional 19 Ags were differentially expressed in no more than one patient while the other 19 had no significant change in any patient, highlighting the inter-and intra- heterogeneity of AML at diagnosis and relapse in these patients. Targeting multiple antigens simultaneously may help address the issue of antigen heterogeneity of tumor cells and help avoid potential antigen escape. Because multi-targeting therapies are a potential solution to this, weleveraged the single-cell resolution of our atlas to systematically identify Ags that in combination provide maximum coverage and are significantly co-expressed in myeloblasts. From this analysis, we found 48 and 52 co-expressed Ag pairs in diagnosis and relapse blasts, respectively (r > 0.4, p < 0.01; Fig. 1B). Of note, CD44 and EMR2 were co-expressed at both diagnosis (r = 0.49 p < 0.01) and relapse (r = 0.3, p < 0.01) with >90% of their blasts expressing CD44, EMR2, or both at targetable antigen levels of >1000 Ags/cell. Furthermore, 10 samples had >40% of their blasts co-expressing both Ags simultaneously at >1000 Ags/cell at diagnosis or relapse. 6 of these patients had a >10% increase in co-expression at relapse, 3 had >10% decrease at relapse, and one patient had no co-expression change. Our comprehensive profiling of AML has provided high resolution insight on cell surface at diagnosis and during disease progression and produced novel hypotheses about targetable combinations of surface Ags based on their expression changes between timepoints, co-expression, and surface densities. Furthermore, our reference atlas can be further dissected to characterize the transcriptome and mutational profiles of myeloblasts at diagnosis and relapse thereby prodding an important resource to create surface antigen protein - transcript correlations within AML blasts and to trace molecular signatures during disease progression.

Utility of Immunohistochemistry With Antibodies to SS18-SSX Chimeric Proteins and C-Terminus of SSX Protein for Synovial Sarcoma Differential Diagnosis.

Synovial sarcoma is a relatively common soft tissue tumor characterized by highly specific t(X;18)(p11;q11) translocation resulting in the fusion of SS18 with members of SSX gene family. Typically, detection of SS18 locus rearrangement by fluorescence in situ hybridization or SS18 :: SSX fusion transcripts confirms the diagnosis. More recently, immunohistochemistry (IHC) for SS18-SSX chimeric protein (E9X9V) and C-terminus of SSX (E5A2C) showed high specificity and sensitivity for synovial sarcoma. This study screened a cohort of >1000 soft tissue and melanocytic tumors using IHC and E9X9V and E5A2C antibodies. Three percent (6/212) of synovial sarcomas were either negative for SS18-SSX or had scattered positive tumor cells (n=1). In these cases, targeted RNA next-generation sequencing detected variants of SS18 :: SSX chimeric transcripts. DNA methylation profiles of 2 such tumors matched with synovial sarcoma. A few nonsynovial sarcoma tumors (n=6) revealed either focal SS18-SSX positivity (n=1) or scattered positive tumor cells. However, targeted RNA next-generation sequencing failed to detect SS18 :: SSX transcripts in these cases. The nature of this immunopositivity remains elusive and may require single cell sequencing studies. All synovial sarcomas showed positive SSX IHC. However, a mosaic staining pattern or focal loss of expression was noticed in a few cases. Strong and diffuse SSX immunoreactivity was also seen in epithelioid sclerosing osteosarcoma harboring EWSR1 :: SSX1 fusion, while several sarcomas and melanocytic tumors including cellular blue nevus (5/7, 71%) revealed focal to diffuse, mostly weak to intermediate SSX staining. The SS18-SSX and SSX IHC is a useful tool for synovial sarcoma differential diagnosis, but unusual immunophenotype should trigger molecular genetic testing.

Abnormal lactate metabolism is linked to albuminuria and kidney injury in diabetic nephropathy

Diabetic nephropathy (DN) is characterized by abnormal kidney energy metabolism, but its causes and contributions to DN pathogenesis are not clear. To examine this issue, we carried out targeted metabolomics profiling in a mouse model of DN that develops kidney disease resembling the human disorder. We found a distinct profile of increased lactate levels and impaired energy metabolism in kidneys of mice with DN, and treatment with an angiotensin-receptor blocker (ARB) reduced albuminuria, attenuated kidney pathology and corrected many metabolic abnormalities, restoring levels of lactate toward normal while increasing kidney ATP content. We also found enhanced expression of lactate dehydrogenase isoforms in DN. Expression of both the LdhA and LdhB isoforms were significantly increased in kidneys of mice, and treatment with ARB significantly reduced their expression. Single-cell sequencing studies showed specific up-regulation of LdhA in the proximal tubule, along with enhanced expression of oxidative stress pathways. There was a significant correlation between albuminuria and lactate in mice, and also in a Southeast Asian patient cohort consisting of individuals with type 2 diabetes and impaired kidney function. In the individuals with diabetes, this association was independent of ARB and angiotensin-converting enzyme inhibitor use. Furthermore, urinary lactate levels predicted the clinical outcomes of doubling of serum creatinine or development of kidney failure, and there was a significant correlation between urinary lactate levels and biomarkers of tubular injury and epithelial stress. Thus, we suggest that kidney metabolic disruptions leading to enhanced generation of lactate contribute to the pathogenesis of DN and increased urinary lactate levels may be a potential biomarker for risk of kidney disease progression.

CCIDB: a manually curated cell-cell interaction database with cell context information.

Cell-cell interaction (CCI) is a crucial event in the development and function of multicellular organisms. The development of CCI databases is beneficial for researchers who want to analyze single-cell sequencing data or study CCI through molecular experiments. CCIs are known to act differently according to cellular and biological contexts such as cell types, gene mutations or disease status; however, previous CCI databases do not completely provide this contextual information pertaining to CCIs. We constructed a cell-cell interaction database (CCIDB) containing the biological and clinical contexts involved in each interaction. To build a database of cellular and tissue contexts, we collected 38 types of context features, which were categorized into seven categories, including 'interaction', 'cell type', 'cofactor', 'effector', 'phenotype', 'pathology' and 'reference'. CCIs were manually retrieved from 272 studies published recently (less than 6 years ago). In the current version of CCIDB, 520 CCIs and their 38 context features have been manually collected and curated by biodata engineers. We suggest that CCIDB is a manually curated CCI resource that is highly useful, especially for analyzing context-dependent alterations in CCIs. Database URL https://ccidb.sysmed.kr/.

Dysregulation of Immune Cell Subpopulations in Atypical Hemolytic Uremic Syndrome.

Atypical hemolytic uremic syndrome (aHUS) is a rare, life-threatening thrombotic microangiopathy. Definitive biomarkers for disease diagnosis and activity remain elusive, making the exploration of molecular markers paramount. We conducted single-cell sequencing on peripheral blood mononuclear cells from 13 aHUS patients, 3 unaffected family members of aHUS patients, and 4 healthy controls. We identified 32 distinct subpopulations encompassing 5 B-cell types, 16 T- and natural killer (NK) cell types, 7 monocyte types, and 4 other cell types. Notably, we observed a significant increase in intermediate monocytes in unstable aHUS patients. Subclustering analysis revealed seven elevated expression genes, including NEAT1, MT-ATP6, MT-CYB, VIM, ACTG1, RPL13, and KLRB1, in unstable aHUS patients, and four heightened expression genes, including RPS27, RPS4X, RPL23, and GZMH genes, in stable aHUS patients. Additionally, an increase in the expression of mitochondria-related genes suggested a potential influence of cell metabolism on the clinical progression of the disease. Pseudotime trajectory analysis revealed a unique immune cell differentiation pattern, while cell-cell interaction profiling highlighted distinctive signaling pathways among patients, family members, and controls. This single-cell sequencing study is the first to confirm immune cell dysregulation in aHUS pathogenesis, offering valuable insights into molecular mechanisms and potential new diagnostic and disease activity markers.

Role of Gltp in Maturation of Oligodendrocytes Under the Regulation of Nkx2.2.

Myelin, a lipid-enriched multi-layer membrane structure, allows for rapid long-distance saltatory conduction of neuronal impulses. Although glycolipids are the predominant types of lipids in the myelin bilayer, the role of glycolipid transfer protein (GLTP), which selectively mediates the transfer of various glycolipids between phospholipid bilayer, in myelin development and maintenance remains unknown at present. In this study, we identified Gltp as the key lipid metabolism gene in myelin-forming oligodendrocytes (OLs) through integrated omics analysis across independent transcriptomic and single-cell sequencing studies. Gene expression analysis revealed that Gltp is selectively expressed in the differentiated OLs. Functional study demonstrated that its expression is essential for the differentiation of OLs, and promotes the outgrowth of OL membrane. Moreover, we found that the expression of Gltp is regulated by OL-lineage transcriptional factors, such as NKX2.2, OLIG2, SOX10, and MYRF. These findings provide important insights into the unrecognized functions of Gltp in OL differentiation and maturation.

Abstract 5288: Single-cell multiomics reveal divergent transcriptional and epigenetic cell states in breast cancer

Abstract Over the recent years, single-cell sequencing studies have been used to better describe the highly heterogeneous nature of breast cancers on transcriptional and genetic levels. It is also known that breast cancers are highly driven by estrogen receptor alpha (ER), a transcription factor that’s important for mammary tissue homeostasis. However, little is known about how estrogen signaling heterogeneity affects cancer progression and response to anti-estrogen therapy at a single-cell level. Leveraging single-omic and multi-omic single-cell sequencing technologies, we tracked estrogen response in breast cancer cell and organoid models. We developed TITAN, a topic-modeling based analysis tool to reveal signaling gradients in single-cell RNA-seq data. With this approach we showed that distinct cells prioritize distinct gene groups in response to estrogen. We defined two of these gene networks to be driven by either ER or FOXM1. These same networks exist not only in all the models used in the study but also in breast cancer patient datasets. FOXM1 is activated in estrogen treated cells and the FOXM1 driven gene signature correlates with more aggressive types of disease. Our combined scRNA and scATAC-seq experiments also highlighted distinct chromatin accessibility states associated with either cell group. Using scNMT-seq in patient samples we were able to describe DNA methylation and chromatin accessibility influence on hormone signaling patterns at the single-cell level. Together, our results provide insights into defining transcriptional and epigenetic cell states in ER positive breast cancer. Citation Format: Aysegul Ors, Hisham Mohammed, Aaron R. Doe, Syber Haverlack, Mithila Handu, Ryan Mulqueen. Single-cell multiomics reveal divergent transcriptional and epigenetic cell states in breast cancer. [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 5288.

Bibliometric analysis of single-cell sequencing researches on immune cells and their application of DNA damage repair in cancer immunotherapy.

In recent decades, single-cell sequencing technology has developed rapidly and used widely in various fields of life sciences, especially for the detection of immune cells. A bibliometric analysis of single-cell sequencing research work on immune cells published during the 2011-2021 period should provide new insight on the use of single-cell sequencing. We screened 1,460 publications on single-cell sequencing on immune cells according to the publication date, article type, language, and country. The United States published the first and largest number of articles, while China's research started relatively late, but ranked second in the number of publications. T cells were the most commonly studied immune cells by single-cell sequencing, followed by mononuclear macrophages. Cancer biology was the most common field of immune cell research by single-cell sequencing. Single-cell sequencing studies using γδ T cells were mainly in the fields of cancer biology and cell development, and focused over time from cell surface receptor to cell function. Through in-depth analysis of the articles on single-cell sequencing of T cells in the oncology field, our analysis found that immunotherapy and tumor microenvironment were the most popular research directions in recent years. The combination of DNA damage repair and immunotherapy seems to provide a new strategy for cancer therapy.

RIIβ-PKA in GABAergic Neurons of Dorsal Median Hypothalamus Governs White Adipose Browning.

The RIIβ subunit of cAMP-dependent protein kinase A (PKA) is expressed in the brain and adipose tissue. RIIβ-knockout mice show leanness and increased UCP1 in brown adipose tissue. The authors have previously reported that RIIβ reexpression in hypothalamic GABAergic neurons rescues the leanness. However, whether white adipose tissue (WAT) browning contributes to the leanness and whether RIIβ-PKA in these neurons governs WAT browning are unknown. Here, this work reports that RIIβ-KO mice exhibit a robust WAT browning. RIIβ reexpression in dorsal median hypothalamic GABAergic neurons (DMH GABAergic neurons) abrogates WAT browning. Single-cell sequencing, transcriptome sequencing, and electrophysiological studies show increased GABAergic activity in DMH GABAergic neurons of RIIβ-KO mice. Activation of DMH GABAergic neurons or inhibition of PKA in these neurons elicits WAT browning and thus lowers body weight. These findings reveal that RIIβ-PKA in DMH GABAergic neurons regulates WAT browning. Targeting RIIβ-PKA in DMH GABAergic neurons may offer a clinically useful way to promote WAT browning for treating obesity and other metabolic disorders.

Systems genomics in age-related macular degeneration.

Genomic studies in age-related macular degeneration (AMD) have identified genetic variants that account for the majority of AMD risk. An important next step is to understand the functional consequences and downstream effects of the identified AMD-associated genetic variants. Instrumental for this next step are 'omics' technologies, which enable high-throughput characterization and quantification of biological molecules, and subsequent integration of genomics with these omics datasets, a field referred to as systems genomics. Single cell sequencing studies of the retina and choroid demonstrated that the majority of candidate AMD genes identified through genomic studies are expressed in non-neuronal cells, such as the retinal pigment epithelium (RPE), glia, myeloid and choroidal cells, highlighting that many different retinal and choroidal cell types contribute to the pathogenesis of AMD. Expression quantitative trait locus (eQTL) studies in retinal tissue have identified putative causal genes by demonstrating a genetic overlap between gene regulation and AMD risk. Linking genetic data to complement measurements in the systemic circulation has aided in understanding the effect of AMD-associated genetic variants in the complement system, and supports that protein QTL (pQTL) studies in plasma or serum samples may aid in understanding the effect of genetic variants and pinpointing causal genes in AMD. A recent epigenomic study fine-mapped AMD causal variants by determing regulatory regions in RPE cells differentiated from induced pluripotent stem cells (iPSC-RPE). Another approach that is being employed to pinpoint causal AMD genes is to produce synthetic DNA assemblons representing risk and protective haplotypes, which are then delivered to cellular or animal model systems. Pinpointing causal genes and understanding disease mechanisms is crucial for the next step towards clinical translation. Clinical trials targeting proteins encoded by the AMD-associated genomic loci C3, CFB, CFI, CFH, and ARMS2/HTRA1 are currently ongoing, and a phase III clinical trial for C3 inhibition recently showed a modest reduction of lesion growth in geographic atrophy. The EYERISK consortium recently developed a genetic test for AMD that allows genotyping of common and rare variants in AMD-associated genes. Polygenic risk scores (PRS) were applied to quantify AMD genetic risk, and may aid in predicting AMD progression. In conclusion, genomic studies represent a turning point in our exploration of AMD. The results of those studies now serve as a driving force for several clinical trials. Expanding to omics and systems genomics will further decipher function and causality from the associations that have been reported, and will enable the development of therapies that will lessen the burden of AMD.

DDDR-27. A PATIENT-DERIVED DRUG SCREENING PLATFORM PREDICTS RESPONSE TO TEMOZOLOMIDE AND IDENTIFIES POTENTIAL NEW TREATMENTS FOR GLIOBLASTOMA

Abstract BACKGROUND Major obstacles that have impeded the development of effective new therapies for GBM include inter- and intratumoral heterogeneity, the blood-brain-barrier and use of sub-optimal cell line-based preclinical models. Taking these hurdles into account, we have set up a patient-derived GBM drug-screening platform. We optimized protocols to improve cell culture success rate and retrospectively assessed the predictive power of our assay for patient response to TMZ. A large panel of GBM cells was screened for sensitivity to available oncological agents. Drugs of interest were selected based on favorable physicochemical properties for BBB crossing and potent activity in (a subset of) GBM cultures. Finally, we determined the success rate of performing a small-scale screen with 20 selected agents within 4 weeks of receiving tumor tissue. RESULTS By combining both CUSA and tissue piece-derived dissociation protocols, culture success increased to 95%, ensuring representation of the near-complete spectrum of GBM subtypes. Single-cell sequencing studies confirmed heterogeneity in our low-passage cell cultures. In vitro screening of TMZ on a large cohort (n = 55) identified 3 response categories (responders/intermediates/non-responders) for which Cox regression analysis revealed significantly different overall survival curves of corresponding patients. Screening of 107 FDA-approved anticancer agents on 45 GBM cultures underscored the tremendous intertumoral heterogeneity in drug sensitivities. We identified 20 potent agents each effective at clinically-achievable concentrations in (a subset of) GBM cultures and having favorable BBB penetration properties (CNS-MPO score). Screening of these agents on a per patient basis within 4 weeks of receiving tissue was successful in 18 out of 24 (75%) tested tumors. In the remaining cases the tumor cells grew very slowly and longer culture times were required. CONCLUSION Our drug screening platform offers a tool to predict TMZ response and assess sensitivity to candidate treatments, either for GBM subsets or on a per patient basis.