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Determination of the Minimum Sample Amount for Capillary Electrophoresis-Fourier Transform Mass Spectrometry (CE-FTMS)-Based Metabolomics of Colorectal Cancer Biopsies
The minimum sample volume for capillary electrophoresis-Fourier transform mass spectrometry (CE-FTMS) useful for analyzing hydrophilic metabolites was investigated using samples obtained from colorectal cancer patients. One, two, five, and ten biopsies were collected from tumor and nontumor parts of...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10296550/ https://www.ncbi.nlm.nih.gov/pubmed/37371800 http://dx.doi.org/10.3390/biomedicines11061706 |
Sumario: | The minimum sample volume for capillary electrophoresis-Fourier transform mass spectrometry (CE-FTMS) useful for analyzing hydrophilic metabolites was investigated using samples obtained from colorectal cancer patients. One, two, five, and ten biopsies were collected from tumor and nontumor parts of the surgically removed specimens from each of the five patients who had undergone colorectal cancer surgery. Metabolomics was performed on the collected samples using CE-FTMS. To determine the minimum number of specimens based on data volume and biological interpretability, we compared the number of annotated metabolites in each sample with different numbers of biopsies and conducted principal component analysis (PCA), hierarchical cluster analysis (HCA), quantitative enrichment analysis (QEA), and random forest analysis (RFA). The number of metabolites detected in one biopsy was significantly lower than those in 2, 5, and 10 biopsies, whereas those detected among 2, 5, and 10 pieces were not significantly different. Moreover, a binary classification model developed by RFA based on 2-biopsy data perfectly distinguished tumor and nontumor samples with 5- and 10-biopsy data. Taken together, two biopsies would be sufficient for CE-FTMS-based metabolomics from a data content and biological interpretability viewpoint, which opens the gate of biopsy metabolomics for practical clinical applications. |
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