Santacroce Elena, D'Angerio Miriam, Ciobanu Alin Liviu, Masini Linda, Lo Tartaro Domenico, Coloretti Irene, Busani Stefano, Rubio Ignacio, Meschiari Marianna, Franceschini Erica, Mussini Cristina, Girardis Massimo, Gibellini Lara, Cossarizza Andrea, De Biasi Sara
Department of Medical and Surgical Sciences for Children & Adults, University of Modena and Reggio Emilia, 41125 Modena, Italy.
Department of Surgery, Medicine, Dentistry and Morphological Sciences, University of Modena and Reggio Emilia, 41121 Modena, Italy.
Cells. 2024 Mar 2;13(5):439. doi: 10.3390/cells13050439.
Sepsis, a critical condition marked by systemic inflammation, profoundly impacts both innate and adaptive immunity, often resulting in lymphopenia. This immune alteration can spare regulatory T cells (Tregs) but significantly affects other lymphocyte subsets, leading to diminished effector functions, altered cytokine profiles, and metabolic changes. The complexity of sepsis stems not only from its pathophysiology but also from the heterogeneity of patient responses, posing significant challenges in developing universally effective therapies. This review emphasizes the importance of phenotyping in sepsis to enhance patient-specific diagnostic and therapeutic strategies. Phenotyping immune cells, which categorizes patients based on clinical and immunological characteristics, is pivotal for tailoring treatment approaches. Flow cytometry emerges as a crucial tool in this endeavor, offering rapid, low cost and detailed analysis of immune cell populations and their functional states. Indeed, this technology facilitates the understanding of immune dysfunctions in sepsis and contributes to the identification of novel biomarkers. Our review underscores the potential of integrating flow cytometry with omics data, machine learning and clinical observations to refine sepsis management, highlighting the shift towards personalized medicine in critical care. This approach could lead to more precise interventions, improving outcomes in this heterogeneously affected patient population.
脓毒症是一种以全身炎症为特征的危急病症,对固有免疫和适应性免疫均产生深远影响,常导致淋巴细胞减少。这种免疫改变可使调节性T细胞(Tregs)不受影响,但会显著影响其他淋巴细胞亚群,导致效应功能减弱、细胞因子谱改变和代谢变化。脓毒症的复杂性不仅源于其病理生理学,还源于患者反应的异质性,这给开发普遍有效的治疗方法带来了重大挑战。本综述强调了脓毒症表型分析对于增强针对患者个体的诊断和治疗策略的重要性。基于临床和免疫学特征对患者进行分类的免疫细胞表型分析对于定制治疗方法至关重要。流式细胞术成为这一努力中的关键工具,可对免疫细胞群体及其功能状态进行快速、低成本且详细的分析。事实上,这项技术有助于理解脓毒症中的免疫功能障碍,并有助于识别新型生物标志物。我们的综述强调了将流式细胞术与组学数据、机器学习和临床观察相结合以优化脓毒症管理的潜力,突出了重症监护中向个性化医疗的转变。这种方法可能会带来更精确的干预措施,改善这一受异质性影响的患者群体的治疗结果。