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Introduction: Well-known adverse events of antipsychotics are movement disorders, or extrapyramidal symptoms, such as drug-induced parkinsonism and tardive dyskinesia. Objective: With new evidence suggesting a link between low high-density lipoprotein cholesterol (HDL-C) and risk of Parkinson's disease, this study sought to investigate if that link also translated to patients taking antipsychotics with low HDL-C and an increased risk for developing a movement disorder. Design: Adult patients (n=89) at an inpatient state psychiatric facility taking at least one antipsychotic with at least one HDL-C level were assessed for signs of a movement disorder through their history and physical, progress notes, and Abnormal Involuntary Movement Scale (AIMS) score. Results: There was no statistical significance when comparing a patient's movement disorder, AIMS scores, and HDL-C levels to suggest that the HDL-C level influenced a patient's movement disorder. Conclusion: This study did not show a correlation between HDL-C levels and a patient's risk of developing a movement disorder while taking an antipsychotic.
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The growing scale and dimensionality of multiplexed imaging require reproducible and comprehensive yet user-friendly computational pipelines. TRACERx-PHLEX performs deep learning-based cell segmentation (deep-imcyto), automated cell-type annotation (TYPEx) and interpretable spatial analysis (Spatial-PHLEX) as three independent but interoperable modules. PHLEX generates single-cell identities, cell densities within tissue compartments, marker positivity calls and spatial metrics such as cellular barrier scores, along with summary graphs and spatial visualisations. PHLEX was developed using imaging mass cytometry (IMC) in the TRACERx study, validated using published Co-detection by indexing (CODEX), IMC and orthogonal data and benchmarked against state-of-the-art approaches. We evaluated its use on different tissue types, tissue fixation conditions, image sizes and antibody panels. As PHLEX is an automated and containerised Nextflow pipeline, manual assessment, programming skills or pathology expertise are not essential. PHLEX offers an end-to-end solution in a growing field of highly multiplexed data and provides clinically relevant insights.
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Aprendizaje Profundo , Humanos , Procesamiento de Imagen Asistido por Computador/métodos , Animales , Programas Informáticos , Análisis Espacial , Análisis de la Célula Individual/métodos , Fenotipo , Ratones , Citometría de Imagen/métodosRESUMEN
Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis. SIGNIFICANCE: This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.