创新链/学科链/研发链/产业链

新药研发前沿动态 / 医药领域趋势进展

代谢组学技术在鉴别免疫治疗疗效生物标志物中的应用进展

Advances in the Application of Metabolomics in Identification of Biomarkers for Immunotherapy Efficacy

  • 摘要: 免疫治疗作为新兴的肿瘤干预方法,通过调节患者自身的免疫系统,取得了显著的治疗效果,对癌症治疗具有重要意义。然而,并非所有患者都能从免疫治疗中获益。有些患者可能会出现不良反应,从而导致病情加重。因此,发现能够预测或监测免疫治疗效果的生物标志物显得尤为重要。代谢组学专注于研究生物体内的低分子量代谢产物;通过分析代谢产物在不同生理和病理条件下的变化规律,可以揭示代谢产物与疾病及其临床治疗之间的关联,因此其在寻找预测免疫治疗效果的小分子生物标志物方面显示出广阔的应用前景。当前,代谢组学被广泛应用于癌症研究领域,并已有多项研究发现了与免疫治疗效果相关的代谢产物。综述总结了近年来发现的糖类、脂类和氨基酸类等生物标志物对免疫治疗效果产生的影响,进一步证明了代谢组学在寻找预测免疫治疗效果小分子生物标志物方面的巨大潜力。

     

    Abstract: Immunotherapy, as an emerging oncological intervention method, has achieved significant therapeutic effects by modulating the patient's own immune system, thereby holding substantial promise for cancer treatment. However, not all patients derive significant benefits from immunotherapy. Some may experience adverse reactions, which potentially exacerbate their cancer condition. Hence, identifying biomarkers capable of predicting or monitoring immunotherapy efficacy is crucial. Metabolomics focuses on studying lowmolecular-weight metabolites within organisms. By analyzing metabolite changes under various physiological and pathological conditions, metabolomics may reveal the associations between metabolites, diseases, and their clinical treatments, thus with broad prospect of application in identifying small-molecule biomarkers for predicting immunotherapeutic efficacy. Currently, metabolomics is widely applied in cancer research, with several studies identifying metabolites associated with immunotherapy efficacy. This review summarizes recent findings in the impact of biomolecules such as sugars, lipids, and amino acids on immunotherapy efficacy, further validating the immense potential of metabolomics in identifying predictive small-molecule biomarkers for immunotherapy efficacy.

     

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