澳大利亚研究人员将肺癌细胞中高血糖摄入量与免疫疗法抗药性联系起来,利用机器学习确定可使治疗个性化的新陈代谢模式。 Australian researchers link high glucose uptake in lung cancer cells to immunotherapy resistance, using machine learning to identify metabolic patterns that could personalize treatment.

澳大利亚科学家发现,肺癌细胞的葡萄糖新陈代谢可以预测免疫疗法的反应,而更高的葡萄糖摄入量与治疗耐药性有关。 Australian scientists have found that lung cancer cells' glucose metabolism can predict immunotherapy response, with higher glucose uptake linked to treatment resistance. 昆士兰大学的研究人员利用机器学习,分析了非小细胞肺癌肿瘤,并确定了影响结果的代谢“邻居”。 Using machine learning, researchers at the University of Queensland analyzed non-small cell lung carcinoma tumors and identified metabolic "neighborhoods" influencing outcomes. 这种发现可能有助于使治疗个性化,提高免疫疗法的效力,并指导今后的治疗方法,同时计划扩大治疗其他癌症的方法。 The discovery may help personalize treatment, improve immunotherapy effectiveness, and guide future therapies, with plans to expand the approach to other cancers.