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Multiplexed nanomaterial-assisted laser desorption/ionization for pan-cancer diagnosis and classification.

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机构： [1]National Engineering Research Center for Biomaterials, Sichuan University, Chengdu 610064, China [2]Department of Endocrinology and Metabolism, FudanInstitute of Metabolic Diseases, Zhongshan Hospital, Fudan University, Shanghai 200032, China [3]State Key Laboratory of Information Engineering inSurveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China [4]Department of Liver Surgery and Transplantation, Liver CancerInstitute, Zhongshan Hospital, Fudan University, Shanghai 200032, China [5]Department of Oncology, Zhongshan Hospital, Fudan University, Shanghai200032, China [6]Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai 200032, China [7]Department of Thoracic Surgery,Zhongshan Hospital, Fudan University, Shanghai 200032, China [8]School of Pharmaceutical Sciences, Tsinghua University, 100084 Beijing, China [9]Department of Orthopaedic Surgery, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu 610041, China [10]School of Software, Tsinghua University, 100084 Beijing, China [11]CAS Key Laboratory of Nutrition, Metabolism and Food safety, Shanghai Institute ofNutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China [12]Department of Oncology, the First Affiliated Hospital, Institute for LiverDiseases of Anhui Medical University, Hefei 230032, China [13]Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095,USA [14]California NanoSystems Institute, University of California, Los Angeles, CA 90095, USA

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As cancer is increasingly considered a metabolic disorder, it is postulated that serum metabolite profiling can be a viable approach for detecting the presence of cancer. By multiplexing mass spectrometry fingerprints from two independent nanostructured matrixes through machine learning for highly sensitive detection and high throughput analysis, we report a laser desorption/ionization (LDI) mass spectrometry-based liquid biopsy for pan-cancer screening and classification. The Multiplexed Nanomaterial-Assisted LDI for Cancer Identification (MNALCI) is applied in 1,183 individuals that include 233 healthy controls and 950 patients with liver, lung, pancreatic, colorectal, gastric, thyroid cancers from two independent cohorts. MNALCI demonstrates 93% sensitivity at 91% specificity for distinguishing cancers from healthy controls in the internal validation cohort, and 84% sensitivity at 84% specificity in the external validation cohort, with up to eight metabolite biomarkers identified. In addition, across those six different cancers, the overall accuracy for identifying the tumor tissue of origin is 92% in the internal validation cohort and 85% in the external validation cohort. The excellent accuracy and minimum sample consumption make the high throughput assay a promising solution for non-invasive cancer diagnosis.© 2022. The Author(s).

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第一作者机构： [1]National Engineering Research Center for Biomaterials, Sichuan University, Chengdu 610064, China

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