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Integration of transcriptomics, proteomics, and metabolomics data to reveal HER2-associated metabolic heterogeneity in gastric cancer with response to immunotherapy and neoadjuvant chemotherapy

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机构: [1]Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China, [2]Clinical Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, China, [3]Department of Hepato-Biliary-Pancreas, Affiliated Hospital of North Sichuan Medical College, Nanchong, China, [4]Department of General Surgery, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China, [5]Department of Oncology, First Affiliated Hospital of Dalian Medical University, Dalian, China, [6]iPhenome Biotechnology (Yun Pu Kang) Inc., Dalian, China, [7]Institute of Integrative Medicine, Dalian Medical University, Dalian, China
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关键词: gastric cancer HER2 multi-omics analysis metabolic classification precision medicine

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BackgroundCurrently available prognostic tools and focused therapeutic methods result in unsatisfactory treatment of gastric cancer (GC). A deeper understanding of human epidermal growth factor receptor 2 (HER2)-coexpressed metabolic pathways may offer novel insights into tumour-intrinsic precision medicine. MethodsThe integrated multi-omics strategies (including transcriptomics, proteomics and metabolomics) were applied to develop a novel metabolic classifier for gastric cancer. We integrated TCGA-STAD cohort (375 GC samples and 56753 genes) and TCPA-STAD cohort (392 GC samples and 218 proteins), and rated them as transcriptomics and proteomics data, resepectively. 224 matched blood samples of GC patients and healthy individuals were collected to carry out untargeted metabolomics analysis. ResultsIn this study, pan-cancer analysis highlighted the crucial role of ERBB2 in the immune microenvironment and metabolic remodelling. In addition, the metabolic landscape of GC indicated that alanine, aspartate and glutamate (AAG) metabolism was significantly associated with the prevalence and progression of GC. Weighted metabolite correlation network analysis revealed that glycolysis/gluconeogenesis (GG) and AAG metabolism served as HER2-coexpressed metabolic pathways. Consensus clustering was used to stratify patients with GC into four subtypes with different metabolic characteristics (i.e. quiescent, GG, AAG and mixed subtypes). The GG subtype was characterised by a lower level of ERBB2 expression, a higher proportion of the inflammatory phenotype and the worst prognosis. However, contradictory features were found in the mixed subtype with the best prognosis. The GG and mixed subtypes were found to be highly sensitive to chemotherapy, whereas the quiescent and AAG subtypes were more likely to benefit from immunotherapy. ConclusionsTranscriptomic and proteomic analyses highlighted the close association of HER-2 level with the immune status and metabolic features of patients with GC. Metabolomics analysis highlighted the co-expressed relationship between alanine, aspartate and glutamate and glycolysis/gluconeogenesis metabolisms and HER2 level in GC. The novel integrated multi-omics strategy used in this study may facilitate the development of a more tailored approach to GC therapy.

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出版当年[2022]版:
大类 | 2 区 医学
小类 | 2 区 免疫学
最新[2023]版:
大类 | 2 区 医学
小类 | 2 区 免疫学
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出版当年[2022]版:
Q1 IMMUNOLOGY
最新[2023]版:
Q1 IMMUNOLOGY

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第一作者机构: [1]Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China, [2]Clinical Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, China,
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通讯机构: [1]Department of General Surgery, First Affiliated Hospital of Dalian Medical University, Dalian, China, [2]Clinical Laboratory of Integrative Medicine, First Affiliated Hospital of Dalian Medical University, Dalian, China, [7]Institute of Integrative Medicine, Dalian Medical University, Dalian, China
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