通过二维气色谱-质谱分析的汗液样本进行乳腺癌查:一项初步研究
Michelle Leemans1, Vincent Cuzuel2, Pierre Bauër3
1Clinical Epidemiology and Ageing Unit, Institut Mondor de Recherche Biomédicale, Paris-Est University, 94010 Créteil, France.
Cancers
|June 10, 2023
概括
研究人员在患者的汗水中确定了乳腺癌特异性挥发性有机化合物 (VOC). 这些在汗水样本中检测到的新型生物标志物可能会导致非侵入性乳腺癌 (BC) 查方法.
科学领域:
- 生物化学 生物化学
- 分析化学 分析化学
- 在瘤学瘤学.
背景情况:
- 乳腺癌 (BC) 是女性癌症的主要原因.
- 对BC的非侵入性查方法非常受欢迎.
- 癌细胞产生的挥发性有机化合物 (VOC) 作为生物标志物具有前景.
研究的目的:
- 在人类汗水中识别乳腺癌特定的VOC.
- 探索汗液VOCs作为非侵入性BC生物标志物的潜力.
- 用VOC分析在BC患者中区分手术前和手术后的状态.
主要方法:
- 收集了BC患者 (n=21) 瘤切除前后的乳房和手部的汗液样本.
- 分析了使用热溶解加上2D气色谱-质谱的VOC.
- 应用机器学习 (逻辑回归) 和统计方法 (PCA,SHAP) 用于VOC识别和分析.
主要成果:
- 在BC患者的汗水样本中检测到至少77个VOC.
- 主要成分分析表明,在手术前和手术后的状态之间,有明显的VOC概况.
- 后勤回归模型在分辨手术前和手术后的VOC中实现了高灵敏度 (接近1) .
- 确定了特定于乳房和手部区域的关键VOC,使手术状态有所不同.
结论:
- 汗液VOC可以在乳腺癌患者的手术前和手术后状态之间进行区分.
- 这项研究提出了一个新的管道,用于识别汗水中的潜在内源性BC生物标志物.
- 需要进一步的大规模多中心研究来验证这些发现的临床应用.
关键词:
乳腺癌 乳腺癌 乳腺癌染色体学 染色体学 染色体学机器学习是机器学习.质谱测量质谱测量质谱测量质量测量质谱测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量质量测量查检查 查检查 查检查 查检查汗水,汗水,汗水,这是一个很好的方法.更多相关视频
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