Single-cell Proteomic Analysis Research Articles

Single-cell transcriptomic and proteomic analysis of Parkinson's disease brains.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder, and recent evidence suggests that pathogenesis may be in part mediated by inflammatory processes, the molecular and cellular architectures of which are largely unknown. To identify and characterize selectively vulnerable brain cell populations in PD, we performed single-nucleus transcriptomics and unbiased proteomics to profile the prefrontal cortex from postmortem human brains of six individuals with late-stage PD and six age-matched controls. Analysis of nearly 80,000 nuclei led to the identification of eight major brain cell types, including elevated brain-resident T cells in PD, each with distinct transcriptional changes in agreement with the known genetics of PD. By analyzing Lewy body pathology in the same postmortem brain tissues, we found that α-synuclein pathology was inversely correlated with chaperone expression in excitatory neurons. Examining cell-cell interactions, we found a selective abatement of neuron-astrocyte interactions and enhanced neuroinflammation. Proteomic analyses of the same brains identified synaptic proteins in the prefrontal cortex that were preferentially down-regulated in PD. By comparing this single-cell PD dataset with a published analysis of similar brain regions in Alzheimer's disease (AD), we found no common differentially expressed genes in neurons but identified many shared differentially expressed genes in glial cells, suggesting that the disease etiologies, especially in the context of neuronal vulnerability, in PD and AD are likely distinct.

SLB-msSIM: a spectral library-based multiplex segmented SIM platform for single-cell proteomic analysis.

Mass spectrometry (MS)-based single-cell proteomics, while highly challenging, offers unique potential for a wide range of applications to interrogate cellular heterogeneity, trajectories, and phenotypes at a functional level. We report here the development of the spectral library-based multiplex segmented selected ion monitoring (SLB-msSIM) method, a conceptually unique approach with significantly enhanced sensitivity and robustness for single-cell analysis. The single-cell MS data is acquired by msSIM technique, which sequentially applies multiple isolation cycles with the quadrupole using a wide isolation window in each cycle to accumulate and store precursor ions in the C-trap for a single scan in the Orbitrap. Proteomic identification is achieved through spectral matching using a well-defined spectral library. We applied the SLB-msSIM method to interrogate cellular heterogeneity among multiple cell lines and to analyze cellular trajectories during epithelial-mesenchymal transition. Our results demonstrate that SLB-msSIM is a highly sensitive and robust platform applicable to a wide range of single-cell proteomic studies.

Circulating RAC1 contributed to steroid-sensitive nephrotic syndrome: Mendelian randomization, single-cell RNA-sequencing, proteomic, and experimental evidence

Objectives The small GTPase Rac1 (RAC1) has been linked to podocyte disorders and steroid-sensitive nephrotic syndrome (SSNS). The aim of this study was to explore and validate the potential causal association between circulating RAC1 and SSNS. Methods The association between circulating RAC1 and SSNS at both gene expression and proteomic levels was investigated using Mendelian randomization analysis, and further validated by single-cell RNA-sequencing, proteomic analysis, and experimental studies. The genetic instruments comprised cis-expression quantitative trait loci (cis-eQTLs) associated with RAC1 gene expression and protein QTLs correlated with plasma RAC1 protein levels. Causal associations were estimated utilizing the inverse variance weighted and MR-PRESSO methods. Validation of RAC1 expression was conducted through single-cell RNA-sequencing of peripheral blood mononuclear cells from patients with SSNS and healthy controls. Proteomic analysis was performed among patients with minimal change nephrotic syndrome. Experimental validation was conducted using a puromycin aminonucleoside (PAN)-induced nephrosis model. Results Increased expression of RAC1 was associated with a higher risk of SSNS (gene expression level: odds ratio [OR], 1.53; 95% confidence interval [CI], 1.02–2.28; protein level: OR, 1.82; 95% CI, 1.05–3.17). The results of MR-PRESSO were consistent (gene expression level: OR, 1.49; 95% CI, 1.17–1.92; protein level: OR, 1.81; 95% CI, 1.16–2.85). Single-cell RNA sequencing and proteomic analysis confirmed elevated RAC1 expression in patients with SSNS compared to healthy controls. Experimental data further supported increased RAC1 expression in PAN-induced nephropathy. Conclusions Increased expression of RAC1 might be causally associated with SSNS, suggesting that targeting RAC1 might represent a potential therapeutic strategy for SSNS.

Alpha-2-macroglobulin mitigates glucocorticoid-induced osteonecrosis via Keap1/Nrf2 pathway activation

Glucocorticoids (GCs) are widely prescribed for various medical conditions, but prolonged use can result in osteonecrosis of the femoral head (ONFH), a serious condition characterized by bone tissue death due to reduced blood flow. Alpha-2-macroglobulin (A2M) is known to regulate oxidative stress and has been implicated in numerous biological processes. However, its role in GCs-induced ONFH has not been fully elucidated. This study investigates the involvement of A2M in ONFH by examining its activation of the Keap1/Nrf2 signaling pathway. Transcriptomic and proteomic analyses of patient samples with GCs-induced ONFH revealed a significant downregulation of A2M. A rat model of GCs-induced ONFH was then used to overexpress A2M, with subsequent evaluation through histopathological staining. Single-cell RNA sequencing and proteomic analysis indicated that A2M overexpression promotes the proliferation of anti-inflammatory macrophage clusters. Both in vivo and in vitro experiments demonstrated that A2M overexpression significantly alleviated ONFH symptoms by modulating oxidative stress and apoptosis via the Keap1/Nrf2 pathway. These findings underscore the critical role of A2M in mitigating GCs-induced ONFH, providing new therapeutic strategies and targets for future research.

A novel study on CXXC5: unraveling its regulatory mechanisms in hematopoietic stem cell biology through proteomics and gene editing.

This study investigates the role of CXXC5 in the self-renewal and differentiation of hematopoietic stem cells (HSCs) within the bone marrow microenvironment, utilizing advanced methodologies such as single-cell RNA sequencing (scRNA-seq), CRISPR-Cas9, and proteomic analysis. We employed flow cytometry to isolate HSCs from bone marrow samples, followed by scRNA-seq analysis using the 10x Genomics platform to examine cell clustering and CXXC5 expression patterns. CRISPR-Cas9 and lentiviral vectors facilitated the knockout and overexpression of CXXC5 in HSCs. The impact on HSCs was assessed through qRT-PCR, Western blot, CCK-8, CFU, and LTC-IC assays, alongside flow cytometry to measure apoptosis and cell proportions. A mouse model was also used to evaluate the effects of CXXC5 manipulation on HSC engraftment and survival rates. Our findings highlight the diversity of cell clustering and the significant role of CXXC5 in HSC regulation. Knockout experiments showed reduced proliferation and accelerated differentiation, whereas overexpression led to enhanced proliferation and delayed differentiation. Proteomic analysis identified key biological processes influenced by CXXC5, including cell proliferation, differentiation, and apoptosis. In vivo results demonstrated that CXXC5 silencing impaired HSC engraftment in a bone marrow transplantation model. CXXC5 is crucial for the regulation of HSC self-renewal and differentiation in the bone marrow microenvironment. Its manipulation presents a novel approach for enhancing HSC function and provides a potential therapeutic target for hematological diseases.

Falcon Probe: A High-Pressure and Robust Sampling Interface for Coupling Lossless Liquid Chromatography Injection with In Situ Nanoliter-Scale Sample Pretreatment.

With the increasing demand for trace sample analysis, injecting trace samples into liquid chromatography-mass spectrometry (LC-MS) systems with minimal loss has become a major challenge. Herein, we describe an in situ LC-MS analytical probe, the Falcon probe, which integrates multiple functions of high-pressure sample injection without sample loss, high-efficiency LC separation, and electrospray. The main body of the Falcon probe is made of stainless steel and fabricated by the computer numerical control (CNC) technique, which has ultrahigh mechanical strength. By coupling a nanoliter-scale droplet reactor made of polyether ether ketone (PEEK) material, the Falcon probe-based LC-MS system was capable of operating at mobile-phase pressures up to 800 bar, which is comparable to those of conventional ultraperformance liquid chromatography (UPLC) systems. Using the probe pressing microamount in situ (PPMI) injection approach, the Falcon probe-based LC-MS system showed high separation efficiency and good repeatability with relative standard deviations (RSDs) of retention time and peak area of 1.8% and 9.9%, respectively, in peptide mixture analysis (n = 6). We applied this system to the analysis of a trace amount of 200 pg of HeLa protein digest and successfully identified an average of 766 protein groups (n = 5). By combining in situ sample pretreatment at the nanoliter range, we further applied the present system in single-cell proteomic analysis, and 241 protein groups were identified in single 293 cells, which preliminarily demonstrated its potential in the analysis of trace amounts of samples with complex compositions.

Insufficient PD-1 expression during active autoimmune responses: a deep single-cell proteomics analysis in inflammatory arthritis.

Programmed cell death protein-1 (PD-1) maintains peripheral immune tolerance by preventing T cell continuous activation. Aiming to understand the extent of PD-1 expression in inflammatory arthritis beyond its involvement with T cells, we assess its presence on various circulating single cells. Mass cytometry analysis of patients with active seropositive/seronegative rheumatoid (RA; n=9/8) and psoriatic (PsA; n=9) arthritis versus healthy controls (HC; n=13), re-evaluating patients after 3 months of anti-rheumatic treatment. PD-1 was expressed in all leukocyte subpopulations, with the highest PD-1+ cell frequencies in eosinophils (59-73%) and T cells (50-60%), and the lowest in natural-killer cells (1-3%). PD-1+ cell frequencies and PD-1 median expression were comparable between patient subgroups and HC, in the majority of cell subsets. Exceptions included increases in certain T cell/B cell subsets of seropositive RA and specific monocyte subsets and dendritic cells of PsA; an expanded PD-1+CD4+CD45RA+CD27+CD28+ T subset, denoting exhausted T cells, was common across patient subgroups. Strikingly, significant inverse correlations between individual biomarkers of systemic inflammation (ESR and/or serum CRP) and PD-1+ cell frequencies and/or median expression were evident in several innate and adaptive immunity cell subsets of RA and PsA patients. Furthermore, all inverse correlations noted in individuals with active arthritis were no longer discernible in those who attained remission/low disease activity post-treatment. PD-1 expression may be insufficient, relative to the magnitude of the concomitant systemic inflammatory response on distinct leukocyte subsets, varying between RA and PsA. Our results point to the potential therapeutic benefits of pharmacological PD-1 activation, to rebalance the autoimmune response and reduce inflammation.

Single-cell proteomic analysis of peripheral blood mononuclear cells in patients with pulmonary long COVID

Abstract An estimated 15% of patients are expected to continue to exhibit respiratory symptoms after their SARS-CoV-2 infection. The mechanisms behind these symptoms remain unknown. We recruited twenty-three patients (65% female) who were on average 406 ± 251 days post-COVID-19. The cohort consists of primarily mild (non-hospitalized) patients (87%), with an average age of 43 ± 15 years. Nine of these patients had self-reported dyspnea, which we defined as pulmonary long COVID (PLC). The remaining 14 patients recovered without persistent dyspnea. We performed a 38-panel cytometry by time-of-flight on the peripheral blood mononuclear cells of this cohort. Quality control was performed using FloJo. Further analysis, was done using the CyCombine, CATALYST, and FlowSom packages in R. Our final annotation uncovered 17 different cell clusters. In PLC patients, double-positive T-cells (DPTs) were significantly increased (Wilcoxon p<0.05), indicating that T-cell development or differentiation may be altered in these patients. Though DPTs are known to be increased in females, there was no significant difference in the proportion of DPTs between males and females in our cohort. PLC stem cells had increased expression of CD304 and CD200R (Wilcoxon p<0.05). CD304 is as a co-receptor for SARS-CoV-2, while CD200R is a limiter of pro-inflammatory activity. These findings indicate that the immune landscape in PLC patients is altered, compared to those who recover without residual pulmonary symptoms.

The role of proliferating stem-like plasma cells in relapsed or refractory multiple myeloma: Insights from single-cell RNA sequencing and proteomic analysis.

The management and comprehension of relapsed or refractory multiple myeloma (RRMM) continues to pose a significant challenge. By integrating single-cell RNA sequencing (scRNA-seq) data of 15 patients with plasma cell disorders (PCDs) and proteomic data obtained from mass spectrometry-based analysis of CD138+ plasma cells (PCs) from 144 PCDs patients, we identified a state of malignant PCs characterized by high stemness score and increased proliferation originating from RRMM. This state has been designated as proliferating stem-like plasma cells (PSPCs). NUCKS1 was identified as the gene marker representing the stemness of PSPCs. Comparison of differentially expressed genes among various PC states revealed a significant elevation in LGALS1 expression in PSPCs. Survival analysis on the MMRF CoMMpass dataset and GSE24080 dataset established LGALS1 as a gene associated with unfavourable prognostic implications for multiple myeloma. Ultimately, we discovered three specific ligand-receptor pairs within the midkine (MDK) signalling pathway network that play distinct roles in facilitating efficient cellular communication between PSPCs and the surrounding microenvironment cells. These insights have the potential to contribute to the understanding of molecular mechanism and the development of therapeutic strategies involving the application of stem-like cells in RRMM treatment.

Ultrasensitive and Multiplexed Protein Imaging with Clickable and Cleavable Fluorophores.

Single-cell spatial proteomic analysis holds great promise to advance our understanding of the composition, organization, interaction, and function of the various cell types in complex biological systems. However, the current multiplexed protein imaging technologies suffer from low detection sensitivity, limited multiplexing capacity, or are technically demanding. To tackle these issues, here, we report the development of a highly sensitive and multiplexed in situ protein profiling method using off-the-shelf antibodies. In this approach, the protein targets are stained with horseradish peroxidase (HRP) conjugated antibodies and cleavable fluorophores via click chemistry. Through repeated cycles of target staining, fluorescence imaging, and fluorophore cleavage, many proteins can be profiled in single cells in situ. Applying this approach, we successfully quantified 28 different proteins in human formalin-fixed paraffin-embedded (FFPE) tonsil tissue, which represents the highest multiplexing capacity among the tyramide signal amplification (TSA) methods. Based on their unique protein expression patterns and their microenvironment, ∼820,000 cells in the tissue are classified into distinct cell clusters. We also explored the cell-cell interactions between these varied cell clusters and observed that different subregions of the tissue are composed of cells from specific clusters.

Quantification Quality Control Emerges as a Crucial Factor to Enhance Single-Cell Proteomics Data Analysis

Mass spectrometry (MS)-based single-cell proteomics (SCP) provides us the opportunity to unbiasedly explore biological variability within cells without the limitation of antibody availability. This field is rapidly developed with the main focuses on instrument advancement, sample preparation refinement, and signal boosting methods; however, the optimal data processing and analysis are rarely investigated which holds an arduous challenge because of the high proportion of missing values and batch effect. Here, we introduced a quantification quality control to intensify the identification of differentially expressed proteins (DEPs) by considering both within and across SCP data. Combining quantification quality control with isobaric matching between runs (IMBR) and PSM-level normalization, an additional 12% and 19% of proteins and peptides, with more than 90% of proteins/peptides containing valid values, were quantified. Clearly, quantification quality control was able to reduce quantification variations and q-values with the more apparent cell type separations. In addition, we found that PSM-level normalization performed similar to other protein-level normalizations but kept the original data profiles without the additional requirement of data manipulation. In proof of concept of our refined pipeline, six uniquely identified DEPs exhibiting varied fold-changes and playing critical roles for melanoma and monocyte functionalities were selected for validation using immunoblotting. Five out of six validated DEPs showed an identical trend with the SCP dataset, emphasizing the feasibility of combining the IMBR, cell quality control, and PSM-level normalization in SCP analysis, which is beneficial for future SCP studies.

FOXO1 reshapes neutrophils to aggravate acute brain damage and promote late depression after traumatic brain injury

BackgroundNeutrophils are traditionally viewed as first responders but have a short onset of action in response to traumatic brain injury (TBI). However, the heterogeneity, multifunctionality, and time-dependent modulation of brain damage and outcome mediated by neutrophils after TBI remain poorly understood.MethodsUsing the combined single-cell transcriptomics, metabolomics, and proteomics analysis from TBI patients and the TBI mouse model, we investigate a novel neutrophil phenotype and its associated effects on TBI outcome by neurological deficit scoring and behavioral tests. We also characterized the underlying mechanisms both in vitro and in vivo through molecular simulations, signaling detections, gene expression regulation assessments [including dual-luciferase reporter and chromatin immunoprecipitation (ChIP) assays], primary cultures or co-cultures of neutrophils and oligodendrocytes, intracellular iron, and lipid hydroperoxide concentration measurements, as well as forkhead box protein O1 (FOXO1) conditional knockout mice.ResultsWe identified that high expression of the FOXO1 protein was induced in neutrophils after TBI both in TBI patients and the TBI mouse model. Infiltration of these FOXO1high neutrophils in the brain was detected not only in the acute phase but also in the chronic phase post-TBI, aggravating acute brain inflammatory damage and promoting late TBI-induced depression. In the acute stage, FOXO1 upregulated cytoplasmic Versican (VCAN) to interact with the apoptosis regulator B-cell lymphoma-2 (BCL-2)-associated X protein (BAX), suppressing the mitochondrial translocation of BAX, which mediated the antiapoptotic effect companied with enhancing interleukin-6 (IL-6) production of FOXO1high neutrophils. In the chronic stage, the “FOXO1-transferrin receptor (TFRC)” mechanism contributes to FOXO1high neutrophil ferroptosis, disturbing the iron homeostasis of oligodendrocytes and inducing a reduction in myelin basic protein, which contributes to the progression of late depression after TBI.ConclusionsFOXO1high neutrophils represent a novel neutrophil phenotype that emerges in response to acute and chronic TBI, which provides insight into the heterogeneity, reprogramming activity, and versatility of neutrophils in TBI.

AM-DMF-SCP: Integrated Single-Cell Proteomics Analysis on an Active Matrix Digital Microfluidic Chip.

Single-cell proteomics offers unparalleled insights into cellular diversity and molecular mechanisms, enabling a deeper understanding of complex biological processes at the individual cell level. Here, we develop an integrated sample processing on an active-matrix digital microfluidic chip for single-cell proteomics (AM-DMF-SCP). Employing the AM-DMF-SCP approach and data-independent acquisition (DIA), we identify an average of 2258 protein groups in single HeLa cells within 15 min of the liquid chromatography gradient. We performed comparative analyses of three tumor cell lines: HeLa, A549, and HepG2, and machine learning was utilized to identify the unique features of these cell lines. Applying the AM-DMF-SCP to characterize the proteomes of a third-generation EGFR inhibitor, ASK120067-resistant cells (67R) and their parental NCI-H1975 cells, we observed a potential correlation between elevated VIM expression and 67R resistance, which is consistent with the findings from bulk sample analyses. These results suggest that AM-DMF-SCP is an automated, robust, and sensitive platform for single-cell proteomics and demonstrate the potential for providing valuable insights into cellular mechanisms.

Abstract 176: Stearic acid induces pro-inflammatory macrophage response important for lung cancer development

Abstract Background Survival is improved with early detection and treatment initiation in patients with lung cancer (LC) emphasizing the importance of tumor initiation and biomarker development in individuals at high risk for developing LC and those with early-stage LC. Recent studies suggest that immunologic and metabolic changes within the microenvironment are pivotal for tumor formation. We recently demonstrated that in patients with resectable, early-stage LC, elevated levels of stearic acid (SA), a long chain fatty acid, and macrophage inflammatory protein 1β (MIP-1β/CCL4) were predictive of tumor affected lung lobes. Therefore, we hypothesize that SA promotes LC initiation through the activation of macrophages (MΦ) and production of proinflammatory cytokines like CCL4. Methods and Results: We performed untargeted metabolomics utilizing LC-MS from the plasma of patients with various stages of LC and found elevated levels of SA in patients with early-stage LC. To further study the mechanistic role of SA in tumorigenesis, cell lines including immortalized lung epithelial, LC cells, and immune (MΦ and T) cells were treated with SA. We found that physiological concentrations of SA did not affect cellular viability. However, in MΦ, SA induced expression of inflammatory (IL6, iNOS), and immunomodulatory (Arg1, CD206) genes suggesting a role for SA in promoting a pro-tumorigenic immunologic state. Additionally, analysis of the secretome from SA stimulated MΦ using single cell proteomic analysis (Isolight, Bruker Cellular Analysis, Inc), indicated a significant enrichment of polyfunctional MΦs with enhanced secretion of enriched effector and stimulatory cytokines. Furthermore, conditioned media derived from SA stimulated MΦ led to increased proliferation, as well as anchorage independent growth, of BEAS2B immortalized lung epithelial cells. Conclusion: Our data demonstrates plasma levels of SA are increased in early-stage compared to late-stage patients with LC. This observation corresponds to our prior data demonstrating enrichment of SA in the tumor affected lobes of patients with early-stage LC. Recent studies demonstrating the induction of inflammatory responses through MΦ activation in obese patients by circulating SA in blood corroborates our observations as well. Our data suggests that the SA effect on MΦ, is critical in LC initiation not only increasing proliferation but also induction of neoplastic transformation of immortalized lung epithelial cells. Furthermore, our data indicates that blood plasma levels of SA, a fatty acid understudied in tumor biology, could also be exploited as a potential biomarker for LC development in individuals at high-risk for LC development as well as those patients with early-stage disease. Citation Format: Amrita Roy, Martin Davis, Samuel Weinberg, Apurva Mallisetty, Alicia Hulbert, Frank D. Weinberg. Stearic acid induces pro-inflammatory macrophage response important for lung cancer development [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 176.

Abstract 5462: Single-cell spatial proteomic analysis to explore the spatial heterogeneity of desmoplastic small round cell tumors

Abstract Desmoplastic small round cell tumor (DSRCT) is a rare and usually incurable aggressive sarcoma subtype. All malignant cells harbor a pathognomonic EWSR1::WT1 fusion protein (FP). However, FP-targeted agents are nonexistent; less than 20% of patients survive beyond five years. The spatial organization of DSRCT, consisting of tumor nests surrounded by desmoplastic stroma, is a hallmark of this disease. Given this context, we seek to understand the spatial heterogeneity within DSRCT and the tumor-stroma interactions to reveal potential therapeutic vulnerabilities. We generated a 20-panel marker developed to interrogate the cellular constituents of the tumor microenvironment (TME) and to characterize the multilineage expression DSRCT, including androgen receptor (AR) and neuroendocrine signatures (NE). The following markers were used: DSRCT (ST6GALNAC, pan-Cytokeratin), Fibroblasts (Collagen, α-smooth muscle actin), Endothelial Cells (CD31, α-smooth muscle actin), T-cells (CD45, CD4, CD8), Macrophages (CD45, CD68, CD163, CD11c), AR/NE markers (AR, neural-specific enolase, synaptophysin). We explored the expression of these markers in a nine-patient cohort from 9 x 9 mm2 tissue sections imaged by the Lunaphore COMET. We used a deep learning model in Visiopharm to extract high-quality areas and segment cells based on their nucleus. The spatial image data was converted into matrix data, which could be further analyzed in R. We confirmed that the tumor nests are surrounded by dense desmoplasia by collagen expression. We identified tumor cells, fibroblasts, immune cells, and endothelial cells by thresholding for classical cell markers. ST6GALNAC, a sialyltransferase that was found to be highly expressed in DSRCT based on RNA-seq data, marked the tumor nests. Previous data from single-nucleus RNA-sequencing (snRNA-seq) showed that DSRCT exhibited three possible subtypes: AR+/NE-, AR-/NE+, and Hybrid AR+/NE+. We found concordance between the prior transcriptomic signatures and the proteomic markers. In tumor nests that were positive for AR, we found AR localized to the nucleus, suggesting downstream activation of this pathway. High AR expression was also correlated with positive expression of pan-cytokeratin in the tumor nests. Future work will focus on quantifying spatial relationships and patterns. This includes characterizing the spatial distribution of all cell types found in DSRCT, including fibroblasts, endothelial cells, and immune cells. We will also address whether tumor nest characteristics are associated with cell phenotype or DSRCT subtype. Citation Format: Danh Truong, Sandhya Krishnan, Clement Agyemang, Davis Ingram, Rossana Lascano, Akshay Basi, Javier Gomez, Jared Burks, Alexander Lazar, Joseph Ludwig. Single-cell spatial proteomic analysis to explore the spatial heterogeneity of desmoplastic small round cell tumors [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 5462.

Abstract 5557: Stem-like T cells maintain latent anticancer activity and underly therapy resistance

Abstract Pre-cancerous cells are normally recognized and eliminated by immune cells. Cancer progresses only when this immunosurveillance system fails. Although immunotherapy has driven the most significant and exciting advances in cancer treatment in modern times, current approaches are running into barriers. An emerging area of interest includes evidence for rare but highly potent stem cell-like T cells. Stem-like T cells combine long-term persistence and high potency with immunological memory. Our recent findings reveal insights into the nature and regulation of stem-like T cells and their potential anticancer activity. Minimal residual disease (MRD) underlies therapeutic resistance, dictates treatment escalation, and predicts patient outcomes. We have shown that the Wnt and PI3K pathways promote the transformation of hematopoietic stem cells (HSCs) into chemoresistant leukemia stem cells (LSCs), which form the root of leukemia initiation and post-treatment recurrence. High-throughput screening revealed that LSCs could be targeted by low dose anthracycline treatment. Mechanistically, low dose, but not high dose anthracyclines indirectly target LSCs by inhibiting their unique properties of immune escape, allowing for their elimination by CD8+ T cells. We employed single-cell genomic and proteomic analysis to investigate immunological changes during development of HSCs, LSCs, and their progeny in response to low dose anthracycline treatment. While leukemia progression results in exhaustion of differentiated CD8+ T cells, stem-like T cells accumulate. However, low dose anthracycline treatment reverses this imbalance. Comparing MRD+ and MRD- patient samples, we found that differential proportions of stem-like T cells persist in the bone marrow of leukemia patients. While T cells of MRD- patients recover following chemotherapy induction, T cell recovery is severely attenuated in MRD+ patients. Furthermore, failure of immunological recovery is driven at least partially by a lack of stem-like T cells in MRD+ leukemia patients. Overall, our studies have revealed that low dose anthracyclines, in contrast to high dose, induce opposing, dichotomous effects on LSCs vs. HSCs and stem-like vs. differentiated T cells. Citation Format: Fang Tao, Sara McElroy, Jacqelyn Nemechek, Irina Pushel, John Szarejko, Santosh Khanal, Todd Bradley, Doug Myers, John M. Perry. Stem-like T cells maintain latent anticancer activity and underly therapy resistance [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 5557.

Fine needle aspiration of human lymph nodes reveals cell populations and soluble interactors pivotal to immunological priming.

Lymph node (LN) fine needle aspiration (LN FNA) represents a powerful technique for minimally invasive sampling of human LNs in vivo and has been used effectively to directly study aspects of the human germinal center response. However, systematic deep phenotyping of the cellular populations and cell-free proteins recovered by LN FNA has not been performed. Thus, we studied human cervical LN FNAs as a proof-of-concept and used single-cell RNA-sequencing and proteomic analysis to benchmark this compartment, define the purity of LN FNA material, and facilitate future studies in this immunologically pivotal environment. Our data provide evidence that LN FNAs contain bone-fide LN-resident innate immune populations, with minimal contamination of blood material. Examination of these populations reveals unique biology not predictable from equivalent blood-derived populations. LN FNA supernatants represent a specific source of lymph- and lymph node-derived proteins, and can, aided by transcriptomics, identify likely receptor-ligand interactions. This represents the first description of the types and abundance of immune cell populations and cell-free proteins that can be efficiently studied by LN FNA. These findings are of broad utility for understanding LN physiology in health and disease, including infectious or autoimmune perturbations, and in the case of cervical nodes, neuroscience.

Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell

The shotgun proteomic analysis is currently the most promising single-cell protein sequencing technology, however its identification level of ~1000 proteins per cell is still insufficient for practical applications. Here, we develop a pick-up single-cell proteomic analysis (PiSPA) workflow to achieve a deep identification capable of quantifying up to 3000 protein groups in a mammalian cell using the label-free quantitative method. The PiSPA workflow is specially established for single-cell samples mainly based on a nanoliter-scale microfluidic liquid handling robot, capable of achieving single-cell capture, pretreatment and injection under the pick-up operation strategy. Using this customized workflow with remarkable improvement in protein identification, 2449–3500, 2278–3257 and 1621–2904 protein groups are quantified in single A549 cells (n = 37), HeLa cells (n = 44) and U2OS cells (n = 27) under the DIA (MBR) mode, respectively. Benefiting from the flexible cell picking-up ability, we study HeLa cell migration at the single cell proteome level, demonstrating the potential in practical biological research from single-cell insight.

Single cell proteomics analysis of drug response shows its potential as a drug discovery platform.

Single-cell analysis has clearly established itself in biology and biomedical fields as an invaluable tool that allows one to comprehensively understand the relationship between cells, including their types, states, transitions, trajectories, and spatial position. Scientific methods such as fluorescence labeling, nanoscale super-resolution microscopy, advances in single cell RNAseq and proteomics technologies, provide more detailed information about biological processes which were not evident with the analysis of bulk material. This new era of single-cell biology provides a better understanding of such complex biological systems as cancer, inflammation, immunity mechanism and aging processes, and opens the door into the field of drug response heterogeneity. The latest discoveries of cellular heterogeneity gives us a unique understanding of complex biological processes, such as disease mechanism, and will lead to new strategies for better and personalized treatment strategies. Recently, single-cell proteomics techniques that allow quantification of thousands of proteins from single mammalian cells have been introduced. Here we present an improved single-cell mass spectrometry-based proteomics platform called SCREEN (Single Cell pRotEomE aNalysis) for deep and high-throughput single-cell proteome coverage with high efficiency, less turnaround time and with an improved ability for protein quantitation across more cells than previously achieved. We applied this new platform to analyze the single-cell proteomic landscape under different drug treatment over time to uncover heterogeneity in cancer cell response, which for the first time, to our knowledge, has been achieved by mass spectrometry based analytical methods. We discuss challenges in single-cell proteomics, future improvements and general trends with the goal to encourage forthcoming technical developments.

Single-Cell Proteomics Analysis with Tecan Uno and SCREEN Workflow.

With advances in sample preparation, small-volume liquid dispensing technologies, high-resolution MS/MS instrumentation, and data acquisition methodologies, it has become increasingly possible to confidently investigate the heterogeneous proteome found within individual cells. In this chapter, we present an automated high-throughput sample preparation workflow based on the Tecan Uno instrument for quantitative single-cell mass spectrometry-based proteomics. Cells are analyzed by the Single-Cell Proteome Analysis platform (SCREEN), which was introduced earlier and provides deeper proteome coverage across single cells.