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Diagnosis and prognosis of breast cancer by high-performance serum metabolic fingerprints.
Huang, Yida; Du, Shaoqian; Liu, Jun; Huang, Weiyi; Liu, Wanshan; Zhang, Mengji; Li, Ning; Wang, Ruimin; Wu, Jiao; Chen, Wei; Jiang, Mengyi; Zhou, Tianhao; Cao, Jing; Yang, Jing; Huang, Lin; Gu, An; Niu, Jingyang; Cao, Yuan; Zong, Wei-Xing; Wang, Xin; Liu, Jun; Qian, Kun; Wang, Hongxia.
Afiliación
  • Huang Y; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Du S; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Liu J; State Key Laboratory of Oncogenes and Related Genes, Department of Oncology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
  • Huang W; Department of Breast-Thyroid Surgery, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
  • Liu W; State Key Laboratory of Oncogenes and Related Genes, Department of Oncology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
  • Zhang M; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Li N; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Wang R; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Wu J; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Chen W; State Key Laboratory of Oncogenes and Related Genes, Department of Oncology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
  • Jiang M; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Zhou T; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Cao J; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Yang J; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Huang L; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Gu A; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Niu J; State Key Laboratory of Oncogenes and Related Genes, Department of Oncology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
  • Cao Y; State Key Laboratory of Oncogenes and Related Genes, Department of Oncology, Shanghai General Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200080, China.
  • Zong WX; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Wang X; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Liu J; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
  • Qian K; Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, China.
  • Wang H; State Key Laboratory for Oncogenes and Related Genes, School of Biomedical Engineering and Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200030, China.
Proc Natl Acad Sci U S A ; 119(12): e2122245119, 2022 03 22.
Article en En | MEDLINE | ID: mdl-35302894
ABSTRACT
High-performance metabolic analysis is emerging in the diagnosis and prognosis of breast cancer (BrCa). Still, advanced tools are in demand to deliver the application potentials of metabolic analysis. Here, we used fast nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI-MS) to record serum metabolic fingerprints (SMFs) of BrCa in seconds, achieving high reproducibility and low consumption of direct serum detection without treatment. Subsequently, machine learning of SMFs generated by NPELDI-MS functioned as an efficient readout to distinguish BrCa from non-BrCa with an area under the curve of 0.948. Furthermore, a metabolic prognosis scoring system was constructed using SMFs with effective prediction performance toward BrCa (P < 0.005). Finally, we identified a biomarker panel of seven metabolites that were differentially enriched in BrCa serum and their related pathways. Together, our findings provide an efficient serum metabolic tool to characterize BrCa and highlight certain metabolic signatures as potential diagnostic and prognostic factors of diseases including but not limited to BrCa.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Female / Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2022 Tipo del documento: Article País de afiliación: China
Texto completo
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Female / Humans Idioma: En Revista: Proc Natl Acad Sci U S A Año: 2022 Tipo del documento: Article País de afiliación: China