Evolutionary metabolic landscape from preneoplasia to invasive lung adenocarcinoma
Autor: | Peng Li, Xinsheng Zhu, Peng Zhang, Ke Yao, Zeping Hu, Na Chen, Nan Xiao, LiAng Yao, Meng Nie, Yi Wang, Bo Peng |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
Lung Neoplasms
Science General Physics and Astronomy Early detection Adenocarcinoma of Lung Adenocarcinoma in Situ Biology General Biochemistry Genetics and Molecular Biology Article Metabolomics medicine Humans Neoplasm Invasiveness Atypical adenomatous hyperplasia Predictive biomarker Multidisciplinary Lung Cancer General Chemistry medicine.disease Cancer metabolism Metabolic pathway medicine.anatomical_structure Cancer research Adenocarcinoma Precancerous Conditions Non-small-cell lung cancer |
Zdroj: | Nature Communications Nature Communications, Vol 12, Iss 1, Pp 1-13 (2021) |
ISSN: | 2041-1723 |
Popis: | Metabolic reprogramming evolves during cancer initiation and progression. However, thorough understanding of metabolic evolution from preneoplasia to lung adenocarcinoma (LUAD) is still limited. Here, we perform large-scale targeted metabolomics on resected lesions and plasma obtained from invasive LUAD and its precursors, and decipher the metabolic trajectories from atypical adenomatous hyperplasia (AAH) to adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC), revealing that perturbed metabolic pathways emerge early in premalignant lesions. Furthermore, three panels of plasma metabolites are identified as non-invasive predictive biomarkers to distinguish IAC and its precursors with benign diseases. Strikingly, metabolomics clustering defines three metabolic subtypes of IAC patients with distinct clinical characteristics. We identify correlation between aberrant bile acid metabolism in subtype III with poor clinical features and demonstrate dysregulated bile acid metabolism promotes migration of LUAD, which could be exploited as potential targetable vulnerability and for stratifying patients. Collectively, the comprehensive landscape of the metabolic evolution along the development of LUAD will improve early detection and provide impactful therapeutic strategies. Metabolic reprogramming occurs during tumor progression. Here the authors decipher metabolic trajectories from preneoplasia to lung adenocarcinoma in tumor samples and identify plasma metabolites as potential predictive biomarkers for early detection. |
Databáze: | OpenAIRE |
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