血代谢体的特征可以预测乳腺癌中对新辅助化疗的反应
Alex Ap Rosini Silva1, Marcella R Cardoso2,3, Danilo Cardoso de Oliveira1
1MS4Life Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Av. São Francisco de Assis, 218, Sala 211, Prédio 5, Bragança Paulista 12916900, São Paulo, Brazil.
Cancers
|July 13, 2024
概括
这项研究开发了一种代谢模型,以预测乳腺癌患者对新辅助化疗 (NACT) 的反应. 该模型准确地识别了可能响应的患者,从而实现了个性化的治疗策略.
科学领域:
- 生物化学和分子生物学
- 在瘤学瘤学.
- 翻译医学是一种翻译医学.
背景情况:
- 新辅助化疗 (NACT) 是一种乳腺癌 (BC) 治疗方法,但反应因亚型而异,且不可预测.
- 代谢学为识别生物标志物和预测化疗反应提供了潜力.
- 在NACT之前的BC血代谢变化需要对临床相关性进行调查.
研究的目的:
- 开发和验证使用血代谢学研究的乳腺癌患者NACT反应的预测模型.
- 确定与化疗反应和耐药性相关的特定代谢物和代谢途径.
- 在乳腺癌治疗中建立精准医学策略的基础.
主要方法:
- 在NACT之前,从75名BC患者的血样本使用液态染色体质谱法 (LC-MS) 进行了分析.
- 一个支持矢量机 (SVM) 分类模型被构建并使用75%/25%的数据分割进行验证.
- 为了构建预测面板,进行了数据过和代谢物识别.
主要成果:
- 一个19代谢物模型准确地预测了高灵敏度 (95.4%) 和特异性 (91.6%) 的NACT反应.
- 该模型在训练和验证组中都取得了高准确率 (94.6%),正确分类了95%的耐药和94%的敏感病例.
- 鉴定到的代谢物主要是脂质和氨基酸,这表明与化学抵抗相关的改变途径.
结论:
- 成功开发了一种可靠的模型,用于预测患者对乳腺癌中NACT的反应.
- 鉴定的代谢物板通过使瘤分层成为可能,为精准医学提供临床实用性.
- 这种方法支持为改善乳腺癌结果制定量身定制的治疗策略.
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