Unravelling NK cell subset dynamics and specific gene signatures post-ibrutinib therapy in chronic lymphocytic leukaemia via single-cell transcriptomics

通过单细胞转录组学揭示慢性淋巴细胞白血病患者接受伊布替尼治疗后NK细胞亚群动态变化及特定基因特征

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Abstract

BACKGROUND: As part of the innate immune system, NK cells contribute to optimizing cancer immunotherapy strategies and are becoming a focal point in cancer research. However, limited research has been conducted to further investigate changes in NK cell subsets and their critical genes following ibrutinib treatment in CLL patients. METHODS: Peripheral blood samples from patients clinically and pathologically diagnosed with monoclonal B-cell lymphocytosis (MBL), newly diagnosed with CLL (ND-CLL), postibrutinib-treated patients who achieved a complete response (CR) or partial response (PR), and those with Richter's syndrome (RS) were collected. Single-cell transcriptome sequencing was performed, followed by pseudotemporal analysis and functional enrichment to characterize the NK cell subsets. Mendelian randomization analysis and colocalization analysis were employed to identify key genes. Multiple algorithms were used for immune infiltration analysis, and drug sensitivity analysis was conducted to pinpoint potential therapeutic agents. RESULTS: Three distinct NK cell subsets were identified: CD56bright_NK cells, CD56dim_NK cells, and a highly cytotoxic CLL_NK subset. The core genes of the CLL_NK subset were elucidated through Mendelian randomization and colocalization analyses. A cell subset-specific novel index (CNI) was constructed based on these core genes and was shown to be capable of predicting responses to immunotherapy. Oncopredictive algorithms and molecular docking screenings further identified semaxanib and ulixertinib as potential therapeutic candidates for CLL. CONCLUSION: The CLL_NK subset plays a crucial role in the development and progression of CLL. The CNI, derived from its key genes, holds promise as a predictor of immune therapeutic responses, highlighting the significance of CLL_NK subset dynamics and their genetic underpinnings in CLL management.

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