Objective To develop a prognostic prediction model for early-stage triple-negative breast cancer(TNBC)using H&E-stained pathological images and to investigate its underlying biological interpretability.Methods A d...Objective To develop a prognostic prediction model for early-stage triple-negative breast cancer(TNBC)using H&E-stained pathological images and to investigate its underlying biological interpretability.Methods A deep learning model was trained on 340 WSIs and externally validated using 81 TCGA cases.Image-derived features extracted through convolutional neural networks were integrated with clinicopathological variables.Model performance was assessed using ROC curve analysis,and interpretability was evaluated by correlating image features with mRNA-seq data and characteristics of the immune microenvironment.Results The model achieved AUCs of 0.86 and 0.75 in the training and validation cohorts,respectively.Analysis using HoVer-Net indicated that lymphocyte abundance was associated with recurrence risk.Texture-related features showed significant correlations with immune cell infiltration and prognostic gene expression profiles.Conclusion This study demonstrates that deep learning can enable accurate prognostic prediction in early-stage TNBC,with interpretable image features that reflect the tumor immune microenvironment and gene expression profiles.展开更多
Clinical studies on trastuzumab deruxtecan for human epidermal growth factor receptor 2-positive brain metastases Several previous clinical studies have suggested significant intracranial activity of trastuzumab derux...Clinical studies on trastuzumab deruxtecan for human epidermal growth factor receptor 2-positive brain metastases Several previous clinical studies have suggested significant intracranial activity of trastuzumab deruxtecan(T-DXd)in brain metastases(BMs)of human epidermal growth factor receptor 2(HER2)-positive(HER2-positive)metastatic breast cancer(mBC).Pooled analyses from DESTINY-Breast(DB)01,02,and 03 showed that T-DXd outperformed controls in terms of intracranial overall response rate(ORR)and median progression-free survival(mPFS).展开更多
基金Supported by Capital’s Funds for Health Improvement and Research(CFH2024-1-4021)。
文摘Objective To develop a prognostic prediction model for early-stage triple-negative breast cancer(TNBC)using H&E-stained pathological images and to investigate its underlying biological interpretability.Methods A deep learning model was trained on 340 WSIs and externally validated using 81 TCGA cases.Image-derived features extracted through convolutional neural networks were integrated with clinicopathological variables.Model performance was assessed using ROC curve analysis,and interpretability was evaluated by correlating image features with mRNA-seq data and characteristics of the immune microenvironment.Results The model achieved AUCs of 0.86 and 0.75 in the training and validation cohorts,respectively.Analysis using HoVer-Net indicated that lymphocyte abundance was associated with recurrence risk.Texture-related features showed significant correlations with immune cell infiltration and prognostic gene expression profiles.Conclusion This study demonstrates that deep learning can enable accurate prognostic prediction in early-stage TNBC,with interpretable image features that reflect the tumor immune microenvironment and gene expression profiles.
基金supported by the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences(No.2023-JKCS-23)the Special Research Fund for Central Universities,Peking Union Medical College(No.2022-I2M-C&T-A-014).
文摘Clinical studies on trastuzumab deruxtecan for human epidermal growth factor receptor 2-positive brain metastases Several previous clinical studies have suggested significant intracranial activity of trastuzumab deruxtecan(T-DXd)in brain metastases(BMs)of human epidermal growth factor receptor 2(HER2)-positive(HER2-positive)metastatic breast cancer(mBC).Pooled analyses from DESTINY-Breast(DB)01,02,and 03 showed that T-DXd outperformed controls in terms of intracranial overall response rate(ORR)and median progression-free survival(mPFS).
