Metabolic fingerprinting enables rapid, label-free histopathology in gastric cancer diagnosis and prognostic prediction.

IF 11.7 1区医学 Q1 CELL BIOLOGY

Cell Reports Medicine Pub Date : 2025-07-15 DOI:10.1016/j.xcrm.2025.102238

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

{"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}

引用次数: 0

Abstract

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.

查看原文本刊更多论文

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。

组织病理学评估是癌症鉴定的基石，但往往涉及耗时的标记过程（每个样本约几天）和依赖经验的解释。在此，我们介绍了一种快速（每个样品约40分钟）和无标记的组织病理学方法，该方法基于使用纳米颗粒增强激光解吸/电离质谱法对组织进行代谢指纹识别。该方法应用于胃癌（n = 284对组织），在没有专业病理学家的情况下，可区分良恶性组织（曲线下面积[AUC]为0.979），识别肿瘤亚型（AUC为0.963），评估预后（p < 0.05）。来自独立队列的238个样本的外部验证证实了其稳健性。这种方法促进了组织病理学分析，为可扩展的临床应用提供了潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Cell Reports Medicine Biochemistry, 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.