Academic Journal
Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data
| العنوان: | Predicting gastric cancer response to anti-HER2 therapy or anti-HER2 combined immunotherapy based on multi-modal data |
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| المؤلفون: | Zifan Chen, Yang Chen, Yu Sun, Lei Tang, Li Zhang, Yajie Hu, Meng He, Zhiwei Li, Siyuan Cheng, Jiajia Yuan, Zhenghang Wang, Yakun Wang, Jie Zhao, Jifang Gong, Liying Zhao, Baoshan Cao, Guoxin Li, Xiaotian Zhang, Bin Dong, Lin Shen |
| المصدر: | Signal Transduction and Targeted Therapy, Vol 9, Iss 1, Pp 1-12 (2024) |
| بيانات النشر: | Nature Publishing Group, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Medicine LCC:Biology (General) |
| مصطلحات موضوعية: | Medicine, Biology (General), QH301-705.5 |
| الوصف: | Abstract The sole use of single modality data often fails to capture the complex heterogeneity among patients, including the variability in resistance to anti-HER2 therapy and outcomes of combined treatment regimens, for the treatment of HER2-positive gastric cancer (GC). This modality deficit has not been fully considered in many studies. Furthermore, the application of artificial intelligence in predicting the treatment response, particularly in complex diseases such as GC, is still in its infancy. Therefore, this study aimed to use a comprehensive analytic approach to accurately predict treatment responses to anti-HER2 therapy or anti-HER2 combined immunotherapy in patients with HER2-positive GC. We collected multi-modal data, comprising radiology, pathology, and clinical information from a cohort of 429 patients: 310 treated with anti-HER2 therapy and 119 treated with a combination of anti-HER2 and anti-PD-1/PD-L1 inhibitors immunotherapy. We introduced a deep learning model, called the Multi-Modal model (MuMo), that integrates these data to make precise treatment response predictions. MuMo achieved an area under the curve score of 0.821 for anti-HER2 therapy and 0.914 for combined immunotherapy. Moreover, patients classified as low-risk by MuMo exhibited significantly prolonged progression-free survival and overall survival (log-rank test, P |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2059-3635 |
| Relation: | https://doaj.org/toc/2059-3635 |
| DOI: | 10.1038/s41392-024-01932-y |
| URL الوصول: | https://doaj.org/article/062220a2398042a6b940e9ea3599d1a0 |
| رقم الانضمام: | edsdoj.062220a2398042a6b940e9ea3599d1a0 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20593635 |
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| DOI: | 10.1038/s41392-024-01932-y |