Prognostic and predictive value of a pathomics signature in gastric cancer

作者：Dexin Chen, Meiting Fu, Liangjie Chi, Liyan Lin, Jiaxin Cheng, Weisong Xue, Chenyan Long, Wei Jiang, Xiaoyu Dong, Jian Sui, Dajia Lin, Jianping Lu, Shuangmu Zhuo, Side Liu, Guoxin Li, Gang Chen, Jun Yan · 发表于：Nature Communications · 年份：2022 · DOI：10.1038/s41467-022-34703-w · 被引用次数：162 · 研究领域：Gastric Cancer Management and Outcomes、Radiomics and Machine Learning in Medical Imaging、Lung Cancer Diagnosis and Treatment

Abstract The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer (GC). Pathomics, which is based on the development of digital pathology, is an emerging field that might improve clinical management. Herein, we propose a pathomics signature (PS GC ) that is derived from multiple pathomics features of haematoxylin and eosin-stained slides. We find that the PS GC is an independent predictor of prognosis. A nomogram incorporating the PS GC and TNM staging system shows significantly improved accuracy in predicting the prognosis compared to the TNM staging system alone. Moreover, in stage II and III GC patients with a low PS GC (but not in those with a high PS GC ), satisfactory chemotherapy benefits are observed. Therefore, the PS GC could serve as a prognostic predictor in patients with GC and might be a potential predictive indicator for decision-making regarding adjuvant chemotherapy.