Yingwei Xue
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MCAT-mediated mitochondrial fatty acid metabolism regulates Lauren subtype divergence and suppresses gastric cancer progression through ROS/P53-dependent mitophagy and ferroptosis
Abstract Gastric cancer (GC) displays marked heterogeneity under the Lauren classification, yet the metabolic determinants of subtype divergence remain unclear. Here, we identify Malonyl-CoA:ACP transacylase (MCAT), a Lauren subtype-associated gene encoding a key mitochondrial fatty acid synthesis (mtFAS) enzyme, as a subtype-specific tumor suppressor in GC. Integrative multi-omics profiling revealed that MCAT expression is enriched in intestinal-type GC and correlates with favorable prognosis.
Deep learning-based pathomics signature predicts prognosis and treatment response in gastric cancer: a multicenter retrospective study
Abstract The existing TNM staging system provides insufficient prognostic information in gastric cancer (GC) patients. This study aims to establish a pathomics signature of GC (PSGC) that uses deep learning (DL) to directly analyze H&E slides for predicting GC outcomes. We propose a multi-scale graph neural network with gated attention mechanism for multi-instance learning (MS-GMIL) for the construction of PSGC.
Prognostic value of inflammatory indices in papillary gastric carcinom
Back to Journals » Journal of Inflammation Research » Volume 18 Authors Wang Y , Zhu M, Xue Y Received 4 April 2025 Accepted for publication 27 June 2025 Published 15 July 2025 Volume 2025:18 Pages 9243—9259 DOI https://doi.org/10.2147/JIR.S532396 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 2 Editor who approved publication: Dr Nadia Andrea Andreani Yufei Wang,1,* Meng Zhu,2,* Yingwei Xue1 1Department of Gastroenterological Surgery, Harbin...
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