相关实验视频

Updated: Jun 28, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

基于循环瘤DNA的机器学习模型的开发和验证,用于预测非小细胞肺癌的免疫治疗反应

Ji Xia^1,2,3, Tianchu He⁴, Yong Hu⁵

¹Department of Oncology, The Second Affiliated Hospital, Guizhou Medical University, Kaili, China.

Translational cancer research

|January 9, 2026

概括

使用循环瘤DNA (ctDNA) 的新机器学习模型准确预测免疫检查点抑制剂 (ICI) 在非小细胞肺癌 (NSCLC) 中的益处. 这种液体活检方法改善了患者分层,并简化了免疫治疗决策.

科学领域:

在瘤学瘤学.
基因组学就是基因组学.
免疫治疗是一种免疫疗法.

背景情况:

目前的生物标志物如PD-L1和TMB对非小细胞肺癌 (NSCLC) 免疫检查点抑制剂 (ICI) 反应的预测能力有限.
循环瘤DNA (ctDNA) 的机器学习分析为通过液体活检基因组签名增强患者分层提供了一个有前途的途径.

研究的目的:

开发和验证一个支持向量机 (SVM) 模型,利用基线ctDNA来预测ICI对晚期NSCLC患者的临床益处.
评估模型在预测持久临床益处 (DCB) 和生存结果方面的准确性.

主要方法:

在OAK试验 (n=303) 的预处理ctDNA全外体序列 (WES) 数据上训练了一种SVM模型,以预测DCB (响应或稳定疾病≥6个月).
最小绝对收缩和选择操作员 (LASSO) 回归确定了41种预测性体质突变.
模型性能在独立的POPLAR (n=97) 和区域多中心 (n=41) 队列中使用ROC曲线分析和Kaplan-Meier方法得到验证.

主要成果:

基于ctDNA的SVM模型显示出高预测准确度,AUC为0.87 (OAK),0.92 (POPLAR) 和0.83 (本地队列).
与SVM高的患者相比,被归类为SVM低的患者表现出明显更长的中位数无进展生存期 (mPFS) 和总生存期 (mOS).
功能丰富分析涉及VEGF,JAK-STAT和Ras信号通路在ICI电阻中.

结论:

开发的基于ctDNA的SVM模型准确地预测了ICI治疗的NSCLC患者的持久临床益处和生存结果.
这种非侵入性,单基线液体活检方法有可能简化免疫治疗决策,减少重复组织活检的需要.
该模型的研究结果突出了ICI耐药性的关键途径,为未来的治疗策略提供了洞察力.

关键词:

循环瘤DNA (ctDNA) 是一种循环瘤DNA.免疫检查点抑制剂 (ICI)机器学习是机器学习.非小细胞肺癌 (NSCLC) 是一种非小细胞肺癌.预测性的生物标志物

更多相关视频

Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence

Semi-automatic PD-L1 Characterization and Enumeration of Circulating Tumor Cells from Non-small Cell Lung Cancer Patients by Immunofluorescence

Published on: August 14, 2019

Predictive Immune Modeling of Solid Tumors

Predictive Immune Modeling of Solid Tumors

Published on: February 25, 2020

相关概念视频

Adaptive Mechanisms in Cancer Cells

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...

Adaptive Mechanisms in Cancer Cells

Adaptive Mechanisms in Cancer Cells

Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
Some of the advantages that cancer cells have on normal cells include - enhanced ability to divide without terminally differentiating, induce new blood vessel formation,...

Tumor Immunotherapy

Tumor Immunotherapy

Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.