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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.

Although advances in immune checkpoint inhibitor (ICI) research have provided a new treatment approach for lung adenocarcinoma (LUAD) patients, their survival is still unsatisfactory, and there are issues in the era of response prediction to immunotherapy. Using bioinformatics methods, a prognostic signature was constructed, and its predictive ability was validated both in the internal and external datasets (GSE68465). We also explored the tumor-infiltrating immune cells, mutation profiles, and immunophenoscore (IPS) in the low-and high-risk groups. As far as we are aware, this is the first study which introduces a novel prognostic signature model using BIRC5, CBLC, S100P, SHC3, ANOS1, VIPR1, LGR4, PGC, and IGKV4.1. According to multivariate analysis, the 9-immune-related genes (IRGs) signature provided an independent prognostic factor for the overall survival (OS). The low-risk group had better OS, and the tumor mutation burden (TMB) was significantly lower in this group. Moreover, the risk scores were negatively associated with the tumor-infiltrating immune cells, like CD8.sup.+ T cells, macrophages, dendritic cells, and NK cells. In addition, the IPS were significantly higher in the low-risk group as they had higher gene expression of immune checkpoints, suggesting that ICIs could be a promising treatment option for low-risk LUAD patients. The combination of these 9-IRGs not only could efficiently predict overall survival of LUAD patients but also show a powerful association with the expression of immune checkpoints and response to ICIs based on IPS; hoping this model paves the way for better stratification and management of patients in clinical practice.

Background Vaccination has played a pivotal role in reducing the burden of COVID-19. Despite numerous studies highlighting its benefits in reducing the risk of severe disease and death, we still lack a quantitative understanding of how varying vaccination roll-out rates influence COVID-19 mortality. Methods We developed a framework for estimating the number of avertable COVID-19 deaths (ACDs) by vaccination in Iran. To achieve this, we compared Iran’s vaccination roll-out rates with those of eight model countries that predominantly used inactivated virus vaccines. We calculated net differences in the number of fully vaccinated individuals under counterfactual scenarios where Iran’s per-capita roll-out rate was replaced with that of the model countries. This, in turn, enabled us to determine age specific ACDs for the Iranian population under counterfactual scenarios where number of COVID-19 deaths are estimated using all-cause mortality data. These estimates covered the period from the start of 2020 to 20 April 2022. Results We found that while Iran would have had an approximately similar number of fully vaccinated individuals under counterfactual roll-out rates based on Bangladesh, Nepal, Sri Lanka, and Turkey (~ 65–70%), adopting Turkey’s roll-out rates could have averted 50,000 (95% confidence interval: 38,100–53,500) additional deaths, while following Bangladesh’s rates may have resulted in 52,800 (17,400–189,500) more fatalities in Iran. Surprisingly, mimicking Argentina’s slower roll-out led to only 12,600 (10,400–13,300) fewer deaths, despite a higher counterfactual percentage of fully vaccinated individuals (~ 79%). Emulating Montenegro or Bolivia, with faster per capita roll-out rates and approximately 50% counterfactual full vaccination, could have prevented more deaths in older age groups, especially during the early waves. Finally, replicating Bahrain’s model as an upper-bound benchmark, Iran could have averted 75,300 (56,000–83,000) deaths, primarily in the > 50 age groups. Conclusions Our analysis revealed that faster roll-outs were consistently associated with higher numbers of averted deaths, even in scenarios with lower overall coverage. This study offers valuable insights into future decision-making regarding infectious disease epidemic management through vaccination strategies. It accomplishes this by comparing various countries’ relative performance in terms of timing, pace, and vaccination coverage, ultimately contributing to the prevention of COVID-19-related deaths.

High-dimensional cytometry is an innovative tool for immune monitoring in health and disease, and it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here, we describe ImmunoCluster ( https://github.com/kordastilab/ImmunoCluster ), an R package for immune profiling cellular heterogeneity in high-dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a nonspecialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users’ needs. The protocol consists of three core computational stages: (1) data import and quality control; (2) dimensionality reduction and unsupervised clustering; and (3) annotation and differential testing, all contained within an R-based open-source framework.

Severe immune aplastic anemia is a fatal disease due to the destruction of marrow hematopoietic cells by cytotoxic lymphocytes, serving as a paradigm for marrow failure syndromes and autoimmune diseases. To better understand its pathophysiology, we apply advanced single cell methodologies, including mass cytometry, single-cell RNA, and TCR/BCR sequencing, to patient samples from a clinical trial of immunosuppression and growth factor stimulation. We observe opposing changes in the abundance of myeloid cells and T cells, with T cell clonal expansion dominated by effector memory cells. Therapy reduces and suppresses cytotoxic T cells, but new T cell clones emerge hindering robust hematopoietic recovery. Enhanced cell-cell interactions including between hematopoietic cells and immune cells, in particular evolving IFNG and IFNGR, are noted in patients and are suppressed post-therapy. Hematologic recovery occurs with increases in the progenitor rather than stem cells. Genetic predispositions linked to immune activation genes enhances cytotoxic T cell activity and crosstalk with target cells. The transcriptional phenotype of immune cells associated with severe aplastic anaemia (SAA) may change post immunotherapy. Here the authors analyse single cell transcriptomics of hematopoietic and immune cells from SAA patients and assess how these phenotypes change after treatment showing alterations in myeloid cells and TCR clonal abundance correlate with robustness of hematopoietic response.

Advanced head and neck squamous cell carcinoma (HNSCC) is associated with a poor prognosis, and biomarkers that predict response to treatment are highly desirable. The primary aim was to predict progression-free survival (PFS) with a multivariate risk prediction model. Experimental covariates were derived from blood samples of 56 HNSCC patients which were prospectively obtained within a Phase 2 clinical trial (NCT02633800) at baseline and after the first treatment cycle of combined platinum-based chemotherapy with cetuximab treatment. Clinical and experimental covariates were selected by Bayesian multivariate regression to form risk scores to predict PFS. A 'baseline' and a 'combined' risk prediction model were generated, each of which featuring clinical and experimental covariates. The baseline risk signature has three covariates and was strongly driven by baseline percentage of CD33 CD14 HLADR monocytes. The combined signature has six covariates, also featuring baseline CD33 CD14 HLADR monocytes but is strongly driven by on-treatment relative change of CD8 central memory T cells percentages. The combined model has a higher predictive power than the baseline model and was successfully validated to predict therapeutic response in an independent cohort of nine patients from an additional Phase 2 trial (NCT03494322) assessing the addition of avelumab to cetuximab treatment in HNSCC. We identified tissue counterparts for the immune cells driving the models, using imaging mass cytometry, that specifically colocalized at the tissue level and correlated with outcome. This immune-based combined multimodality signature, obtained through longitudinal peripheral blood monitoring and validated in an independent cohort, presents a novel means of predicting response early on during the treatment course. Daiichi Sankyo Inc, Cancer Research UK, EU IMI2 IMMUCAN, UK Medical Research Council, European Research Council (335326), Merck Serono. Cancer Research Institute, National Institute for Health Research, Guy's and St Thomas' NHS Foundation Trust and The Institute of Cancer Research. NCT02633800.

Sarcoidosis, a multi-organ system disease, often presents insidiously. Thrombocytopenia in sarcoidosis is frequent because of hypersplenism, granulomas infiltrating the bone marrow, or immune thrombocytopenia (ITP). The diagnosis of ITP relies on exclusionary criteria, given the absence of a definitive laboratory diagnostic feature. In the era prior to modern ITP management, sarcoidosis-associated ITP was known to manifest severely, often showing resistance to treatment and an increased risk of mortality. In this case, we present a young male who was admitted to a district hospital’s emergency room, displaying symptoms of hematuria, gingival bleeding, and a petechial rash. Blood tests revealed severe thrombocytopenia with a platelet count of 0, while all other metabolic and serological exams returned normal results. Infectious and autoimmune causes were ruled out, and a bone marrow examination excluded any hematological disorder. Initial management, including platelet transfusion and presumptive treatment for ITP with dexamethasone and Human Immunoglobulin IV (IVIG), failed to improve the patient’s platelet count or alleviate the hemorrhagic diathesis. Second-line therapy with Rituximab and Methylprednisolone was initiated with no benefit. Considering the hemorrhagic signs and the delayed response of Rituximab, we shifted to third-line therapy with Romiplostim at the maximal dose and continued Methylprednisolone. The platelet count recovered completely after the second Romiplostim administration (over 350 × 109 platelets/L) and Methylprednisolone was rapidly tapered. To further study the causes of thrombocytopenia a total body CT scan was performed and it identified non-homogeneously hypodense tissue in the bilateral hilar area extending medially to the subcarinal area, suggesting possible lymphatic origin and raising suspicion of sarcoidosis. Further investigations, including Angiotensin Converting Enzyme (ACE) titration, bronchoscopy, bronchoalveolar lavage, and EndoBronchial UltraSound-guided TransBronchial Needle Aspiration (EBUS-TBNA), confirmed the diagnosis of sarcoidosis. Despite a mild restrictive insufficiency noted in spirometry, the patient remained asymptomatic with only a mild respiratory insufficiency, and hence, was enlisted for follow-up. As for the ITP, the platelet count remained normal over a year. Notably, while sarcoidosis onset often predates ITP onset by an average of 48 months, in our case the onset of the two diseases was simultaneously. Our case adds valuable information to the limited body of knowledge regarding the treatment of sarcoidosis-associated ITP.