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Prognostic and predictive value of a pathomics signature in gastric cancer.

Dexin ChenMeiting FuLiangjie ChiLiyan LinJiaxin ChengWeisong XueChenyan LongWei JiangXiaoyu DongJian SuiDajia LinJianping LuShuangmu ZhuoSide LiuGuoxin LiGang ChenJun Yan
Published in: Nature communications (2022)
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.
Keyphrases
  • gas chromatography
  • lymph node
  • decision making
  • mass spectrometry
  • pet ct
  • healthcare
  • squamous cell carcinoma
  • radiation therapy
  • tandem mass spectrometry
  • locally advanced
  • solid phase extraction