Machine learning models-based on integration of next-generation sequencing testing and tumor cell sizes improve subtype classification of mature B-cell neoplasms.

Background: Next-generation sequencing (NGS) panels for mature B-cell neoplasms (MBNs) are widely applied clinically but have yet to be routinely used in a manner that is suitable for subtype differential diagnosis. This study retrospectively investigated newly diagnosed cases of MBNs from our laboratory to investigate mutation landscapes in Chinese patients with MBNs and to combine mutational information and machine learning (ML) into clinical applications for MBNs, especially for subtype classification. Methods: Samples from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database were collected for ML model construction and cases from our laboratory were used for ML model validation. Five repeats of 10-fold cross-validation Random Forest algorithm was used for ML model construction. Mutation detection was performed by NGS and tumor cell size was confirmed by cell morphology and/or flow cytometry in our laboratory. Results: Totally 849 newly diagnosed MBN cases from our laboratory were retrospectively identified and included in mutational landscape analyses. Patterns of gene mutations in a variety of MBN subtypes were found, important to investigate tumorigenesis in MBNs. A long list of novel mutations was revealed, valuable to both functional studies and clinical applications. By combining gene mutation information revealed by NGS and ML, we established ML models that provide valuable information for MBN subtype classification. In total, 8895 cases of 8 subtypes of MBNs in the COSMIC database were collected and utilized for ML model construction, and the models were validated on the 849 MBN cases from our laboratory. A series of ML models was constructed in this study, and the most efficient model, with an accuracy of 0.87, was based on integration of NGS testing and tumor cell sizes. Conclusions: The ML models were of great significance in the differential diagnosis of all cases and different MBN subtypes. Additionally, using NGS results to assist in subtype classification of MBNs by method of ML has positive clinical potential.

Identification of "antigen-specific" neutrophils in atherosclerosis patients that compromise vascular endothelial barrier function.

The vascular endothelial barrier dysfunction is associated with the pathogenesis of many cardiovascular diseases, such as atherosclerosis (AS). This study aims to identify specific antigen (Ag, in short)-specific polymorphonuclear neutrophils (PMN) in AS patients and to investigate the role of "Ag-specific" PMN activation in causing vascular endothelial barrier dysfunction. In this study, PMNs were isolated from blood samples collected from patients with AS and analyzed with immunological approaches. Human umbilical vein endothelial cells (HUVEC) monolayers were used as a vascular endothelial barrier model. The results showed that "Ag-specific" PMNs were identified in the blood of 50 AS patients. This subset of PMN was featured as the FcγRI and specific IgG (sIgG) complexes on the cell surface; exposure to specific Ags triggered the "Ag-specific" PMNs to release proinflammatory cytokines. PMN-derived cytokine levels in the serum were positively correlated with the serum levels of sIgG in AS patients. Exposure of naive PMNs to sIgG formed FcγRI and sIgG complexes on the surface; this conferred PMNs the property to be recognized and activated by specific Ag. Stimulation of "Ag-specific" PMN activated the mitogen-activated protein kinase and the activities of nuclear factor activated T cells and promoted the gene transcription of tumor necrosis factor-α. Coculture of "Ag-specific" PMNs and HUVEC monolayers in the presence of specific Ag resulted in the HUVEC monolayer barrier dysfunction. In conclusion, "Ag-specific" PMNs were identified in AS patients. Activation of the PMNs compromised vascular endothelial barrier function. Therefore, to regulate the "Ag-specific" PMN's activities may have translational potential in the treatment of AS.

Cold stress promotes IL-33 expression in intestinal epithelial cells to facilitate food allergy development.

BACKGROUND: The causative factors and pathogenesis of food allergy (FA) is not fully understood yet. Cold stress (CS) occurs frequently in human life that influences physiological activities in the body. In this study, we aimed to investigate the chronic CS (CS) effects on promoting the expression of IL-33 in intestinal epithelial cells. METHODS: CS was carried out by placing mice at 4 °C for 1 h daily for 7 consecutive days. We developed a mouse model used to test the effects of CS on the FA development. RESULTS: We found that, similar to conventional FA mouse model, CS induced the core body temperature to drop markedly in mice, increased intestinal epithelial barrier permeability and facilitated FA development. CS promoted interleukin (IL)-33 expression in intestinal epithelial cells through the adrenocorticotropic hormone (ACTH)/cortisol axis and via inducing the Il33 promoter methylation. CS facilitated the FA development in mice, that could be blocked by depletion of IL-33 expression in intestinal epithelial cells. CONCLUSIONS: CS induces IL-33 expression in intestinal epithelial cells to promote Th2 polarization in the intestinal tissues and facilitates FA development.