{"title":"代谢指纹能够快速,无标记的组织病理学胃癌诊断和预后预测。","authors":"Fei Teng, Juxiang Zhang, Yida Huang, Wei Xu, Wanshan Liu, Liming Sun, Meng Yan, Jiao Wu, Ruimin Wang, Shouzhi Yang, Lin Huang, Zhengying Gu, Haiyang Su, Xiaoyu Xu, Dingyitai Liang, Ning Ren, Chunmeng Ding, Yanyan Li, Qiongzhu Dong, Lingchuan Guo, Shaoqun Liu, Xuefei Wang, Kun Qian","doi":"10.1016/j.xcrm.2025.102238","DOIUrl":null,"url":null,"abstract":"<p><p>Histopathological evaluation is a cornerstone of cancer identification but often involves time-consuming labeling processes (∼days per sample) and experience-dependent interpretation. Herein, we introduce a rapid (∼40 min per sample) and label-free histopathological method based on metabolic fingerprinting of tissue using nanoparticle-enhanced laser desorption/ionization mass spectrometry. Applied to gastric cancer (GC, n = 284 paired tissue), this approach distinguishes malignant from benign tissues (area under the curve [AUC] of 0.979), identifies tumor subtypes (AUC of 0.963), and assesses prognosis (p < 0.05) without specialized pathologists. External validation on 238 samples from an independent cohort confirmed its robustness. This method advances histopathological analysis, offering potential for scalable clinical use.</p>","PeriodicalId":9822,"journal":{"name":"Cell Reports Medicine","volume":"6 7","pages":"102238"},"PeriodicalIF":11.7000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metabolic fingerprinting enables rapid, label-free histopathology in gastric cancer diagnosis and prognostic prediction.\",\"authors\":\"Fei Teng, Juxiang Zhang, Yida Huang, Wei Xu, Wanshan Liu, Liming Sun, Meng Yan, Jiao Wu, Ruimin Wang, Shouzhi Yang, Lin Huang, Zhengying Gu, Haiyang Su, Xiaoyu Xu, Dingyitai Liang, Ning Ren, Chunmeng Ding, Yanyan Li, Qiongzhu Dong, Lingchuan Guo, Shaoqun Liu, Xuefei Wang, Kun Qian\",\"doi\":\"10.1016/j.xcrm.2025.102238\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Histopathological evaluation is a cornerstone of cancer identification but often involves time-consuming labeling processes (∼days per sample) and experience-dependent interpretation. Herein, we introduce a rapid (∼40 min per sample) and label-free histopathological method based on metabolic fingerprinting of tissue using nanoparticle-enhanced laser desorption/ionization mass spectrometry. Applied to gastric cancer (GC, n = 284 paired tissue), this approach distinguishes malignant from benign tissues (area under the curve [AUC] of 0.979), identifies tumor subtypes (AUC of 0.963), and assesses prognosis (p < 0.05) without specialized pathologists. External validation on 238 samples from an independent cohort confirmed its robustness. This method advances histopathological analysis, offering potential for scalable clinical use.</p>\",\"PeriodicalId\":9822,\"journal\":{\"name\":\"Cell Reports Medicine\",\"volume\":\"6 7\",\"pages\":\"102238\"},\"PeriodicalIF\":11.7000,\"publicationDate\":\"2025-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cell Reports Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.xcrm.2025.102238\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Reports Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.xcrm.2025.102238","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
Metabolic fingerprinting enables rapid, label-free histopathology in gastric cancer diagnosis and prognostic prediction.
Histopathological evaluation is a cornerstone of cancer identification but often involves time-consuming labeling processes (∼days per sample) and experience-dependent interpretation. Herein, we introduce a rapid (∼40 min per sample) and label-free histopathological method based on metabolic fingerprinting of tissue using nanoparticle-enhanced laser desorption/ionization mass spectrometry. Applied to gastric cancer (GC, n = 284 paired tissue), this approach distinguishes malignant from benign tissues (area under the curve [AUC] of 0.979), identifies tumor subtypes (AUC of 0.963), and assesses prognosis (p < 0.05) without specialized pathologists. External validation on 238 samples from an independent cohort confirmed its robustness. This method advances histopathological analysis, offering potential for scalable clinical use.
Cell Reports MedicineBiochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
15.00
自引率
1.40%
发文量
231
审稿时长
40 days
期刊介绍:
Cell Reports Medicine is an esteemed open-access journal by Cell Press that publishes groundbreaking research in translational and clinical biomedical sciences, influencing human health and medicine.
Our journal ensures wide visibility and accessibility, reaching scientists and clinicians across various medical disciplines. We publish original research that spans from intriguing human biology concepts to all aspects of clinical work. We encourage submissions that introduce innovative ideas, forging new paths in clinical research and practice. We also welcome studies that provide vital information, enhancing our understanding of current standards of care in diagnosis, treatment, and prognosis. This encompasses translational studies, clinical trials (including long-term follow-ups), genomics, biomarker discovery, and technological advancements that contribute to diagnostics, treatment, and healthcare. Additionally, studies based on vertebrate model organisms are within the scope of the journal, as long as they directly relate to human health and disease.