Cytometry By Time-of-flight Research Articles

TMIC-80. HIGH-DIMENSIONAL HISTOPATHOLOGIC EVALUATION OF THE HYPOXIC TUMOR MICROENVIRONMENT IN GLIOBLASTOMA

Abstract Gliobastoma (GBM) is a highly aggressive solid tumor of the brain, characterized by a hypoxic tumor microevironment (TME) leading to histopathological features of necrosis, microvascular proliferation and deregulated hypervascularization. The heterogeneous nature of GBM results in a gradient of intra-tumoral hypoxia that causes molecular changes to specific cell populations within the bulk of the tumor. Our study is the first clinical study to utilize the exogenous oxygen-independent marker pimonidazole (PIMO) to identify the hypoxic TME using high-dimensional spatial and single-cell proteomics of specific cell populations within GBM. A cohort of 35 patients with primary GBM, recurrent GBM or IDH-mutant glioma were administered PIMO prior to surgical resection of tumor tissue for downstream bulk proteomic analysis of bulk tissue by serial immunohistochemistry and imaging mass cytometry (IMC) and single-cell analysis of dissociated tissue by Cytometry by time-of-flight (CyTOF). We utilized high-resolution imaging analyses to validate PIMO as a sensitive and stable marker for hypoxia against a panel of transiently expressed HIF-target genes and examine the inter- and intra-tumoral heterogeneity of hypoxia within each tumor subtype. A custom CyTOF marker panel was developed for further single-cell analyses of T-cell subsets and their functional states, myeloid cell subpopulations, natural killer cells, glial cells, and tumor cells in the hypoxic TME. We demonstrate the utility of PIMO to effectively study the hypoxic TME through spatial and single cell methods and further elucidate mechanisms of hypoxia-driven treatment resistance.

ACE2 Enhances Sensitivity to PD-L1 Blockade by Inhibiting Macrophage-Induced Immunosuppression and Angiogenesis.

Anti-PD-L1-based combination immunotherapy has become the first-line treatment for unresectable hepatocellular carcinoma (HCC). However, the objective response rate is lower than 40%, highlighting the need to identify mechanisms of tolerance to immune checkpoint inhibitors and accurate biomarkers of response. Here, we employed next-generation sequencing to analyze HCC samples from 10 patients receiving anti-PD-L1 therapy. Activation of the renin-angiotensin system was elevated in nonresponders compared with responders, and ACE2 expression was significantly downregulated in nonresponders. ACE2 deficiency promoted HCC development and anti-PD-L1 resistance, whereas ACE2 overexpression inhibited HCC progression in immune competent mice. Mass cytometry by time of flight (CyTOF) revealed that ACE2 deficient murine orthotopic tumor tissues featured elevated M2-like tumor-associated macrophages (TAMs), displayed a CCR5+PD-L1+ immunosuppressive phenotype, and exhibited high VEGFα expression. ACE2 downregulated tumor intrinsic CCL5 expression by suppressing NF-κB signaling through the ACE2/angiotensin-(1-7)/Mas receptor axis. The lower CCL5 levels led to reduced activation of the JAK-STAT3 pathway and suppressed PD-L1 and VEGFα expression in macrophages, blocking macrophage infiltration and M2-like polarization. Pharmacological targeting of CCR5 using maraviroc enhanced the tumor suppressive effect of anti-PD-L1 therapy. Together, these findings suggest that activation of the ACE2 axis overcomes the immunosuppressive microenvironment of HCC and may serve as an immunotherapeutic target and predictive biomarker of response to PD-L1 blockade.

Myeloid derived suppressor cells mediate hepatocyte proliferation and immune suppression during liver regeneration following resection.

Liver regeneration following resection is a complex process relying on coordinated pathways and cell types in the remnant organ. Myeloid-Derived Suppressor Cells (MDSCs) have a role in liver regeneration-related angiogenesis but other roles they may play in this process remain to be elucidated. In this study, we sought to examine the effect of G-MDSCs on hepatocytes proliferation and immune modulation during liver regeneration. Global gene expression profiling of regenerating hepatocytes in mice with CD11b+Ly6G+ MDSCs (G-MDSCs) depletion revealed disrupted transcriptional progression from day one to day two after major liver resection. Key genes and pathways related to hepatocyte proliferation and immune response were differentially expressed upon MDSC depletion. Hepatocytes cellularity increased when co-cultured with G-MDSCs, or treated with amphiregulin, which G-MDSCs upregulate during regeneration. Cytometry by time-of-flight (CyTOF) analysis of the intra-liver immune milieu upon MDSC depletion during regeneration demonstrated increased natural killer cell proportions, alongside changes in other immune cell populations. Taken together, these results provide evidence that MDSCs contribute to early liver regeneration by promoting hepatocyte proliferation and modulating the intra-liver immune response, and illuminate the multifaceted role of MDSCs in liver regeneration.

ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.

Mass cytometry is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level, advancing clinical research in immune monitoring. Nevertheless, the vast data generated by cytometry by time-of-flight (CyTOF) poses a significant analytical challenge. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel toolkit for CyTOF data analysis. This framework incorporates BinaryClust, an in-house developed semi-supervised clustering tool that automatically identifies main cell types. BinaryClust outperforms existing clustering tools in accuracy and speed, as shown in benchmarks with two datasets of approximately 4 million cells, matching the precision of manual gating by human experts. Furthermore, ImmCellTyper offers various visualisation and analytical tools, spanning from quality control to differential analysis, tailored to users' specific needs for a comprehensive CyTOF data analysis solution. The workflow includes five key steps: (1) batch effect evaluation and correction, (2) data quality control and pre-processing, (3) main cell lineage characterisation and quantification, (4) in-depth investigation of specific cell types; and (5) differential analysis of cell abundance and functional marker expression across study groups. Overall, ImmCellTyper combines expert biological knowledge in a semi-supervised approach to accurately deconvolute well-defined main cell lineages, while maintaining the potential of unsupervised methods to discover novel cell subsets, thus facilitating high-dimensional immune profiling.

Voluntary exercise sensitizes cancer immunotherapy via the collagen inhibition-orchestrated inflammatory tumor immune microenvironment

Physical activity reduces cancer-associated mortality through multiple mechanisms, including tumor immune microenvironment (TIME) reprogramming. However, whether and how physiological interventions promote anti-tumor immunity remain elusive. Here, we report that clinically relevant voluntary exercise promotes muscle-derived extracellular vesicle (EV)-associated miR-29a-3p for tumor extracellular matrix (ECM) inhibition in patients and mouse models, thereby permitting immune cell infiltration and immunotherapy. Mechanistically, an unbiased screening identifies EV-associated miR-29a-3p in response to leisure-time physical activity or voluntary exercise. MiR-29a-3p-containing EVs accumulate in tumors and downregulate collagen composition by targeting COL1A1. Gain- and loss-of-function experiments and cytometry by time of flight (CyTOF) demonstrate that myocyte-secreted miR-29a-3p promotes anti-tumor immunity. Combining immunotherapy with voluntary exercise or miR-29a-3p further enhances anti-tumor efficacy. Clinically, miR-29a-3p correlates with reduced ECM, increased Tcell infiltration, and response to immunotherapy. Our work reveals the predictive value of miR-29a-3p for immunotherapy, provides mechanistic insights into exercise-induced anti-cancer immunity, and highlights the potential of voluntary exercise in sensitizing immunotherapy.

Immune-related events in individuals with solid tumors on immunotherapy associate with Th17 and Th2 signatures.

BACKGROUNDImmune-related adverse events (irAEs) and their associated morbidity/mortality are a key concern for patients receiving immune checkpoint inhibitors (ICIs). Prospective evaluation of the drivers of irAEs in a diverse pan-tumor cohort is needed to identify patients at greatest risk and to develop rational treatment and interception strategies.METHODSIn an observational study, we prospectively collected blood samples and performed regular clinical evaluations for irAEs in patients receiving ICI therapy as standard of care for solid tumors. We performed in-parallel analysis of cytokines by Luminex immunoassay and circulating immune cells by cytometry by time-of-flight (CyTOF) at baseline and on treatment to investigate mechanisms of irAEs.RESULTSWe enrolled 111 patients, of whom 40.5% developed a symptomatic irAE (grade ≥ 2). Development of a grade ≥ 2 irAE was positively associated with the use of combination ICI and a history of an autoimmune disorder. Early changes in T helper 17 (Th17) (IL-6, IL-17f), type 2 (IL-5, IL-13, IL-25), and type 1 (TNF-α) cytokine signatures and congruent on-treatment expansions of Th17 and Th2 effector memory (Th2EM) T cell populations in peripheral blood were positively associated with the development of grade ≥2 irAEs. IL-6 levels were also associated with inferior cancer-specific survival and overall survival.CONCLUSIONSIn a diverse, prospective pan-tumor cohort, Th17 and Th2 skewing during early ICI treatment was associated with the development of clinically relevant irAEs but not antitumor responses, providing possible targets for monitoring and therapeutic interventions.FUNDINGJohns Hopkins Bloomberg-Kimmel Institute for Cancer Immunotherapy, the NCI SPORE in Gastrointestinal Cancers (P50 CA062924), NCI grant (R50CA243627 to LD), the NIH Center Core Grant (P30 CA006973), Swim Across America (to MY), NIAMS (K23AR075872 to LC), and imCORE-Genentech grant 137515 (to Johns Hopkins Medicine on behalf of MY).

Comprehensive Characterization of Islet Remodeling in Development and in Diabetes Using Mass Cytometry.

The pancreatic islet is the functional and structural unit of the pancreatic endocrine portion. Islet remodeling occurs in both normal development and pathogenesis of type 1 (T1D) and type 2 diabetes (T2D). However, accurately quantifying changes in islet cellular makeup and hormone expressions poses significant challenges due to large intra- and inter-donor heterogeneity and the limited scalability of traditional methods such as immunostaining. The cytometry by time-of-flight (CyTOF) technology enables simultaneous quantification of more than 30 protein markers at single-cell resolution in a high-throughput fashion. Moreover, with distinct DNA and viability markers, single live cells can be explicitly selected in CyTOF. Here, leveraging the CyTOF data generated by the Human Pancreas Analysis Program, we characterized more than 12 million islet cells from 71 donors. Our data revealed continued age-related changes in islet endocrine cell compositions, but the maturity of endocrine cells is reached by 3 years of age. We also observed significant changes in beta cell numbers and key protein expressions, along with a significant increase in bihormonal cells in T1D donors. In contrast, T2D donors exhibited minimal islet remodeling events. Our data shine a light on the islet dynamics during development and diabetes pathogenesis and suggest divergent pathogenesis processes of T1D and T2D. Our comprehensive approach not only elucidates islet plasticity but also establishes a foundation for integrated CyTOF analysis in islet biology and beyond.

T-cell responses in colorectal peritoneal metastases are recapitulated in a humanized immune system mouse model.

The occurrence of peritoneal metastasis (PM) in patients with colorectal cancer (CRC) has a dismal prognosis. There is often limited response to systemic- and immunotherapy, even in microsatellite unstable (MSI) CRC. To overcome therapy resistance, it is critical to understand local immune environment in the peritoneal cavity, and to develop models to study anti-tumor immune responses. Here, we defined the peritoneal immune system (PerIS) in PM-CRC patients and evaluate the pre-clinical potential of a humanized immune system (HIS) mouse model for PM-CRC. We studied the human PerIS in PM-CRC patients (n=20; MSS 19/20; 95%) and in healthy controls (n=3). HIS mice (NODscid gamma background; n=18) were generated, followed by intraperitoneal injection of either saline (HIS control; n=3) or human MSS/MSI CRC cell lines HUTU80, MDST8 and HCT116 (HIS-PM, n=15). Immune cells in peritoneal fluid and peritoneal tumors were analyzed using cytometry by time of flight (CyTOF). The human and HIS mouse homeostatic PerIS was equally populated by NK cells and CD4+- and CD8+ T cells, however differences were observed in macrophage and B cell abundance. In HIS mice, successful peritoneal engraftment of both MSI and MSS tumors was observed (15/15; 100%). Both in human PM-CRC and in the HIS mouse PM-CRC model, we observed that MSS PM-CRC triggered a CD4+ Treg response in the PerIS, while MSI PM-CRC drives CD8+ TEMs responses. In conclusion, T cell responses in PM-CRC in HIS mice mirror those in human PM-CRC, making this model suitable to study antitumor T cell responses in PM-CRC.

High-dimensional mapping of human CEACAM1 expression on immune cells and association with melanoma drug resistance

BackgroundHuman carcinoembryonic antigen cell adhesion molecule 1 (CEACAM1) is an inhibitory cell surface protein that functions through homophilic and heterophilic ligand binding. Its expression on immune cells in human tumors is poorly understood.MethodsAn antibody that distinguishes human CEACAM1 from other highly related CEACAM family members was labeled with 159Tb and inserted into a panel of antibodies that included specificity for programmed cell death protein 1 (PD1) and PD-L1, which are targets of immunotherapy, to gain a data-driven immune cell atlas using cytometry by time-of-flight (CyTOF). A detailed inventory of CEACAM1, PD1, and PD-L1 expression on immune cells in metastatic lesions to lymph node or soft tissues and peripheral blood samples from patients with treatment-naive and -resistant melanoma as well as peripheral blood samples from healthy controls was performed.ResultsCEACAM1 is absent or at low levels on healthy circulating immune cells but is increased on immune cells in peripheral blood and tumors of melanoma patients. The majority of circulating PD1-positive NK cells, innate T cells, B cells, monocytic cells, dendritic cells, and CD4+ T cells in the peripheral circulation of treatment-resistant disease co-express CEACAM1 and are demonstrable as discrete populations. CEACAM1 is present on distinct types of cells that are unique to the tumor microenvironment and exhibit expression levels that are highest in treatment resistance; this includes tumor-infiltrating CD8+ T cells.ConclusionsTo the best of our knowledge, this work represents the first comprehensive atlas of CEACAM1 expression on immune cells in a human tumor and reveals an important correlation with treatment-resistant disease. These studies suggest that agents targeting CEACAM1 may represent appropriate partners for PD1-related pathway therapies.

IGATE analysis improves the interpretability of single-cell immune landscape of influenza infection.

Influenza poses a persistent health burden worldwide. To design equitable vaccines effective across all demographics, it is essential to better understand how host factors such as genetic background and aging affect the single-cell immune landscape of influenza infection. Cytometry by time-of-flight (CyTOF) represents a promising technique in this pursuit, but interpreting its large, high-dimensional data remains difficult. We have developed a new analytical approach, in silico gating annotating training elucidating (iGATE), based on probabilistic support vector machine classification. By rapidly and accurately "gating" tens of millions of cells in silico into user-defined types, iGATE enabled us to track 25 canonical immune cell types in mouse lung over the course of influenza infection. Applying iGATE to study effects of host genetic background, we show that the lower survival of C57BL/6 mice compared with BALB/c was associated with a more rapid accumulation of inflammatory cell types and decreased IL-10 expression. Furthermore, we demonstrate that the most prominent effect of aging is a defective T cell response, reducing survival of aged mice. Finally, iGATE reveals that the 25 canonical immune cell types exhibited differential influenza infection susceptibility and replication permissiveness in vivo, but neither property varied with host genotype or aging. The software is available at https://github.com/UmichWenLab/iGATE.

Abstract PO1-13-03: Tumour infiltrating double negative (CD20+CD27- IgD-) B cells in high-risk early breast cancers. Friend or Foe??

Abstract Background: B cells exhibit diverse phenotypes and function and the complex interplay between different B cell subsets in the context of chemotherapy treated breast cancers remains unclear. Here, we investigate the dynamic changes in the B cell immune landscape before and after NACT treatment across different breast cancer subtypes. Methods: Treatment naïve, mid-treatment and post-NACT breast tumour, matched lymph node, blood and serum samples were profiled for B cell subsets and cytokines by flow cytometry, cytometry by time-of-flight (CyTOF) and Luminex technologies. Ex vivo autologous tumour organoid and immune cells cocultures to functionally assess the B-cell interactions across breast cancer subtypes were performed. Multiplex spatial analysis method was used to explore the dynamics of double negative B cell cellular crosstalk within the tumour and axillary lymph nodes. The results are being associated with treatment outcomes. Expression and activity of purinergic ectoenzymes within B cell subsets were also assessed by flow cytometry and high-performance liquid chromatography. Current work focusses on how these findings may relate to immunotherapy response, a new paradigm shift in the treatment of triple negative breast cancer patients. Results: We observed a significant expansion in the CD20+CD27−IgD− cells, also termed as double-negative (DN) B cells, within the TME of treatment naïve and post-neoadjuvant residual tumours compared to the periphery. Specifically, DN1 (CD20+ CD27−IgD− CD21+CXCR5+) cells represented the majority of DN B cells within the treatment naïve TME and in circulation. However, NACT promotes an expansion of the DN2 (CD20+CD27−IgD−CD21-CXCR5-) subset as well as a relatively uncharacterised DN3 (CD19+IgD−CD27−CXCR5−CD11c−) cell population. Preliminary analyses on how these changes (especially the enrichment of DN2 cells) relate to treatment response show significant expansion of DN2 cells in the periphery of poor responders to NACT, coupled with significantly reduced infiltration of DN2 into resistant residual tumours. Among circulating B, T and NK cells, B cells showed the highest CD73 and CD39 surface expression at baseline, but their expression significantly drops following NACT especially within the DN2 B cell subset. These ecto-5’-nucleotidases are known to play a critical role in B and T cell interactions. Spatial analyses between these cell types is ongoing. Conclusion: We report for the first time an enrichment of DN cells in breast cancer tumour tissue, specifically the expansion of DN2 cells following neoadjuvant chemotherapy. Functional analyses of tumour-infiltrated B-cells suggest that mechanistically, these B-cell subgroups may contribute to immunosurveillance and point to an important role of purinergic signalling in early breast cancers. Our study highlights the requirement for further investigation into the role of DN B cells in the context of chemo/immunotherapy resistance in breast cancers. Citation Format: Esme Carpenter, Paul Buckley, Thanussuyah Alaguthurai, Rosalind Graham, Helen Kakkassery, Gheed Alhity, Farhana Hossain, Sadiyah Mukhtar, Sheeba Irshad. Tumour infiltrating double negative (CD20+CD27- IgD-) B cells in high-risk early breast cancers. Friend or Foe?? [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 PO1-13-03.

Impact on in-depth immunophenotyping of delay to peripheral blood processing.

Peripheral blood mononuclear cell (PBMC) immunophenotyping is crucial in tracking activation, disease state, and response to therapy in human subjects. Many studies require the shipping of blood from clinical sites to a laboratory for processing to PBMC, which can lead to delays that impact sample quality. We used an extensive cytometry by time-of-flight (CyTOF) immunophenotyping panel to analyze the impacts of delays to processing and distinct storage conditions on cell composition and quality of PBMC from seven adults across a range of ages, including two with rheumatoid arthritis. Two or more days of delay to processing resulted in extensive red blood cell contamination and increased variability of cell counts. While total memory and naïve B- and T-cell populations were maintained, 4-day delays reduced the frequencies of monocytes. Variation across all immune subsets increased with delays of up to 7 days in processing. Unbiased clustering analysis to define more granular subsets confirmed changes in PBMC composition, including decreases of classical and non-classical monocytes, basophils, plasmacytoid dendritic cells, and follicular helper T cells, with each subset impacted at a distinct time of delay. Expression of activation markers and chemokine receptors changed by Day 2, with differential impacts across subsets and markers. Our data support existing recommendations to process PBMC within 36 h of collection but provide guidance on appropriate immunophenotyping experiments with longer delays.

An Alternative Immune Cell Labeling System Based on the New Two-Dimensional Nanomaterials MXenes

Abstract Deepening our understanding of immune cell behavior is vital for creating safe, effective treatments, particularly as immune cell therapy, also known as cellular immunotherapy or cell-based immunotherapy, represents a groundbreaking approach in the treatment of various diseases, including cancer. Transition metal carbides and nitrides (MXenes), a novel family of 2D nanomaterials, show promise as advanced trackers for immune cells—key for precise diagnostics and therapies. Traditional cell labeling methods have stagnated due to limited chemical options, impeding progress in applied medicine. Moreover, these methods are incompatible with single-cell mass cytometry by time-of-flight (CyTOF), a globally adopted technology that improves classical flow cytometry. We propose an innovative solution utilizing MXenes to overcome these challenges. Our method, Label-free sINgle-cell tracKing of 2D matErials by mass cytometry (LINKED), leverages a novel, biocompatible, multiplexed, label-free detection approach via CyTOF and Mass Ion Beam Imaging by Time-of-Flight (MIBI-TOF). This technique overcomes chemical limitations and integrates seamlessly with CyTOF, allowing for nanomaterial detection and simultaneous measurement of diverse immune cell and tissue features. Our work promises to advance immunological research significantly, offering refined cell labeling and tracking techniques crucial for the advancement of translational medicine.

Abstract 3075: Effect Of Inhaled Benzene Exposure On Atherogenesis

Background: Benzene is a ubiquitous environmental pollutant generated by a variety of natural and anthropological sources. It is a known carcinogen and hematopoietic toxin; however, little is known about benzene's potential atherogenicity. Hypothesis: Inhaled benzene induces atherogenesis by increasing vascular inflammation in LDL receptor Knockout (LDLR-KO) mice. Methods: Male LDLR-KO mice were exposed to HEPA-filtered air or benzene (1 ppm, 6h/day, 5days/week) for 24 weeks. For the last 12 weeks of exposure, the mice were maintained on a western diet. The single nuclei RNA sequencing (snRNAseq) of aortae was performed at Novogene. In an independent experiment, male ApoE-KO mice were maintained on a western diet for 12 weeks and then exposed to benzene for 2 weeks. Cytometry by time of flight (CyTOF) analysis was used for the plaque immunophenotyping. For in vitro experiments, splenic naïve T cells were exposed to 1 μM of hydroquinone (HQ) for 24 hours, and intracellular ROR-gamma levels were measured by flow cytometry. Results: Benzene inhalation increased the aortic valve lesion area by more than 25% (P<0.05) in LDLR-KO mice. Using snRNAseq, eleven major cell types were detected, including T cells and vascular smooth muscle cells (VSMC). Benzene increased the number of T cells by 2.5-fold, proliferating T-cells by 5.8-fold, and VSMC by 1.6-fold, suggesting increased cellularity and reduced plaque stability. In addition, benzene upregulated Th17 polarization marker Rorc and negative regulators of apoptosis Rag1 and Bcl11b while significantly attenuating the expression of proliferation inhibitor Ms4a4b in T cells. In VSMC, benzene downregulated extracellular matrix organization genes and upregulated platelet degranulation pathways. CyTOF analysis of the plaques of ApoE-KO mice showed that even short-term benzene exposure increased T-cell abundance in pre-existing lesions. Polarization of T cells into Th17 was confirmed by HQ-dependent upregulation of ROR-gamma in vitro . Conclusion: Our data suggest that inhaled benzene exposure compromises plaque cellularity and stability by facilitating T-cell proliferation and polarization, which coincides with the degradation of smooth muscle extracellular matrix and platelet activation.

Adaptive immune changes associate with clinical progression of Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is the most frequent cause of dementia. Recent evidence suggests the involvement of peripheral immune cells in the disease, but the underlying mechanisms remain unclear.MethodsWe comprehensively mapped peripheral immune changes in AD patients with mild cognitive impairment (MCI) or dementia compared to controls, using cytometry by time-of-flight (CyTOF).ResultsWe found an adaptive immune signature in AD, and specifically highlight the accumulation of PD1+ CD57+ CD8+ T effector memory cells re-expressing CD45RA in the MCI stage of AD. In addition, several innate and adaptive immune cell subsets correlated to cerebrospinal fluid (CSF) biomarkers of AD neuropathology and measures for cognitive decline. Intriguingly, subsets of memory T and B cells were negatively associated with CSF biomarkers for tau pathology, neurodegeneration and neuroinflammation in AD patients. Lastly, we established the influence of the APOE ε4 allele on peripheral immunity.ConclusionsOur findings illustrate significant peripheral immune alterations associated with both early and late clinical stages of AD, emphasizing the necessity for further investigation into how these changes influence underlying brain pathology.

High dimensional proteomic mapping of bone marrow immune characteristics in immune thrombocytopenia.

To investigate the role of co-stimulatory and co-inhibitory molecules on immune tolerance in immune thrombocytopenia (ITP), this study mapped the immune cell heterogeneity in the bone marrow of ITP at the single-cell level using Cytometry by Time of Flight (CyTOF). Thirty-six patients with ITP and nine healthy volunteers were enrolled in the study. As soluble immunomodulatory molecules, more sCD25 and sGalectin-9 were detected in ITP patients. On the cell surface, co-stimulatory molecules like ICOS and HVEM were observed to be upregulated in mainly central memory and effector T cells. In contrast, co-inhibitory molecules such as CTLA-4 were significantly reduced in Th1 and Th17 cell subsets. Taking a platelet count of 30×109 L-1 as the cutoff value, ITP patients with high and low platelet counts showed different T cell immune profiles. Antigen-presenting cells such as monocytes and B cells may regulate the activation of T cells through CTLA-4/CD86 and HVEM/BTLA interactions, respectively, and participate in the pathogenesis of ITP. In conclusion, the proteomic and soluble molecular profiles brought insight into the interaction and modulation of immune cells in the bone marrow of ITP. They may offer novel targets to develop personalized immunotherapies.

Identification of clinically relevant subsets CD39+PD-1+CD8+ T cells and CD39+ regulatory T cells in intrahepatic cholangiocarcinoma using single-cell CyTOF

Intrahepatic cholangiocarcinoma (iCCA) is an aggressive liver malignancy with limited treatment options and a dismal prognosis. The tumor immune microenvironment (TIME) is crucial for iCCA progression, yet its comprehensive characterization remains incomplete. This study utilized mass cytometry by time of flight (CyTOF) to comprehensively analyze immune cell populations in fresh iCCA tumor samples and adjacent peritumor liver tissues. Notably, NK cell percentages significantly decreased in iCCA lesions compared to peritumor liver tissues. Conversely, an enrichment of immunosuppressive CD39+Foxp3+CD4+ regulatory T cells (CD39+T-regs) and exhausted-like CD8+T cells (with pronounced CD39 and PD-1 expression) within TIME was identified and confirmed by multiplex immunofluorescence staining in an independent patient cohort (n = 140). Crucially, tumor-infiltrating CD39+T-regs and CD39+PD-1+CD8+T cells emerged as independent prognostic indicators associated with an unfavorable prognosis in iCCA. These findings unveil the intricate immune landscape within iCCA, offering valuable insights for disease management and novel cancer immunotherapies.

Abstract CT016: Immunomodulation of the tumor microenvironment of pancreatic ductal adenocarcinoma with histone deacetylase inhibition: Results of a phase 2 clinical trial of entinostat in combination with nivolumab

Abstract Background The tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDA) is characterized by a paucity of cytotoxic tumor-infiltrating lymphocytes, an abundance of immune-suppressive cell populations, and a general resistance to immune checkpoint inhibitor (ICI) therapy. In preclinical models of PDA, the HDAC inhibitor entinostat modulated the transcriptional programming of myeloid cells, reducing their capacity for immunosuppression and sensitizing tumors to ICI therapy. Methods We conducted a single-center, open-label, Simon two-stage, phase II study of entinostat in combination with the PD1 inhibitor nivolumab in patients with advanced PDA. Patients received oral entinostat 5 mg once a week. After a 14-day lead-in with entinostat monotherapy, patients concurrently receive entinostat 5 mg orally once a week plus nivolumab 240 mg intravenously every 2 weeks. After 4 months, therapy was continued with entinostat 5 mg weekly plus nivolumab at a dose of 480 mg fixed dose every 4 weeks until the time of progression or unacceptable toxicities. The primary endpoint was the objective response rate by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Peripheral immune profiles at baseline and on treatment were assessed by high-dimensional mass cytometry by time of flight (CyTOF) and by Luminex of chemokines in the plasma, and changes in the TME were performed on paired baseline and on treatment biopsies by multiplexed immunohistochemistry (mIHC), image cytometry-based quantification, and bulk RNA-seq analysis. Results From November 2017 to November 2020, 27 evaluable patients were enrolled. Three patients had a partial response (PR) by RECIST v1.1 criteria (objective response rate (ORR)) of 11%, 95% CI, 0.024-0.292), with a median duration of response of 10.2 months. Grade ≥3 treatment-related adverse events (TRAEs) were observed in 19 (63%) patients. The most common grade ≥3 TRAEs were decreased lymphocyte count, anemia hypoalbuminemia, and hyponatremia. Dendritic cell (DC) activation, maturation, migration, antigen processing, and presentation were increased in the periphery after entinostat treatment, consistent with HDAC inhibitor mediated myeloid reprogramming. Gene expression analysis of paired baseline and on treatment tumors demonstrated an enrichment in inflammatory response signaling pathways with combination treatment. Conclusions Entinostat and nivolumab demonstrated durable radiological responses in a subset of patients with PDA. Paired tissue and peripheral analysis showed immunomodulation of myeloid cell populations, consistent with the preclinical hypothesis supporting the trial. This study creates a roadmap for this strategy with future combinatorial therapeutic approaches to enhance the clinical benefit in PDA patients further. Citation Format: Marina Baretti, Ludmila Danilova, Jennifer N. Durham, Courtney B. Betts, Leslie Cope, Dimitrios N. Sidiropoulos, Joseph A. Tandurella, Soren Charmsaz, Nicole Gross, Alexei Hernandez, Won J. HO, Chris Thoburn, Rosalind Walker, James Leatherman Leatherman, Sarah Mitchell, Brian Christmas, Daria A. Gaykalova, Srinivasan Yegnasubramanian, Elana J. Fertig, Lisa M. Coussens, Mark Yarchoan, Elizabeth Jaffee, Nilofer S. Azad. Immunomodulation of the tumor microenvironment of pancreatic ductal adenocarcinoma with histone deacetylase inhibition: Results of a phase 2 clinical trial of entinostat in combination with nivolumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT016.

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning.

The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians. Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity. Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively. Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Abstract 4961: Large-scale CyTOF data modeling of leukemia patient cohorts

Abstract Introduction: Cytometry by Time-of-Flight (CyTOF) is a single-cell proteomic assay that uses antibody-lanthanide metal conjugates to tag surface or intracellular proteins, quantified via mass spectrometry. Compared to flow cytometry, CyTOF significantly reduces overlapping signals and increases the maximum protein features from 8 to 50. CyTOF data is commonly analyzed with the ‘gating’ workflow, which is the iterative process of plotting cells by two protein features to select discrete cell populations. While CyTOF can comprehensively profile nuanced cell types, gating does not scale well in the number of features. Biases in gating often arise from the forced discretization of cell populations, subjectivity of gate boundaries, and intrinsic sample-sample variation. Contemporary challenges in CyTOF data analysis can be attributed to data volume and gating bias, which can lead to oversight of disease-related cell populations while hindering reproducibility. Methods: We developed a computational platform that enables the processing and analysis of large-scale CyTOF data. Our workflow includes modular components for data harmonization, normalization, transformation, batch correction, quality control, subsampling, and dimensionality reduction via UMAP of input sample files in Flow Cytometry Standard (FCS) format. Further, additional analytical modules are currently being integrated to deploy large-scale machine learning models for cell type identification. We use the results of these models as input for multi-scale analysis, where we aim to link single-cell CyTOF data with clinical outcomes. We test our workflow on previously published datasets and apply it to new leukemia patient cohorts of blood and bone marrow samples and a variety of marker panels. Results: We tested our workflow on previously published datasets of 4.7 M peripheral blood mononuclear cells from healthy donors (N= 20) and T cells (N = 8). We observed that samples mixed well upon integration and separated into major cell types like monocytes, CD4+/CD8+ T-cells, naïve/mature B-cells, and natural killer T-cells. We then applied it to a bone marrow cohort of healthy donors (N = 10), where we observe good mixing of samples but less clear separation of cell types. Finally, we applied our workflow to 9.3 M cells from 51 chronic lymphocytic leukemia (CLL) patients and 4 healthy donors, using a lymphocytic marker panel. Here, we observed a clear resolution of a major clonal B-cell population and immune T-cells. We are in the process of applying it to Acute Myeloid Leukemia (AML) patient data with myeloid and immune marker panels. Conclusions: We developed a computational platform that facilitates the simultaneous analysis of large-scale CyTOF data, both in the number of samples and cells per sample, a variety of marker panels, while minimizing gating biases common in traditional gating analysis. Citation Format: Garth Kong, Tania Vu, Evan Lind, Olga H. Nikolova. Large-scale CyTOF data modeling of leukemia patient cohorts [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 4961.