Comparative metabolomics reveals specific metabolic signatures in colorectal cancer cell line models

Colorectal cancer (CRC) exhibits substantial metabolic heterogeneity, which plays a critical role in tumor progression and treatment response. However, systematic comparisons of metabolic profiles among widely used CRC cell lines are still lacking. Understanding these metabolic differences is essential for improving the translational relevance of preclinical studies. The study aims to conduct a comprehensive metabolomic analysis on three widely used CRC cell lines (HT-29, Caco-2, SW480) to identify their metabolic differences and explore their biological significance and origins. We conducted a metabolomic analysis using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) to measure intracellular and extracellular metabolites. Multivariate statistical approaches, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), were applied to identify metabolic variations. Pathway enrichment analysis was then performed to uncover dysregulated metabolic pathways. Our analysis revealed distinct metabolic profiles among the three CRC cell lines, with 25 differential metabolites identified. Pathway enrichment analysis highlighted three significantly dysregulated pathways: glycerophospholipid metabolism, ether lipid metabolism, and pantothenate and CoA biosynthesis. These findings demonstrate intrinsic metabolic heterogeneity at both intracellular and extracellular levels. These findings confirm intrinsic metabolic heterogeneity of the three CRC cell lines by intracellular and extracellular profiling, highlighting the importance of validating results across multiple models to address the limitations intrinsic to single cell lines in mechanistic and translational studies.

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Publication Details

Journal
Discover Oncology
Published
2025-12-01
DOI
https://doi.org/10.1007/s12672-025-04183-7
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
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article

Comparative metabolomics reveals specific metabolic signatures in colorectal cancer cell line models

Xinxin Du, Manshan Li, Jiaru Wang, Han Sun et al.
Discover Oncology
Metabolomics and Mass Spectrometry Studies
article

Comparative metabolomics reveals specific metabolic signatures in colorectal cancer cell line models

Xinxin Du, Manshan Li, Jiaru Wang, Han Sun, Caizheng Yu, Ran Zheng, Xingchen Shang, Liming Xiong, Yanhong Chang, Zhihua Li
article en

Abstract

Colorectal cancer (CRC) exhibits substantial metabolic heterogeneity, which plays a critical role in tumor progression and treatment response. However, systematic comparisons of metabolic profiles among widely used CRC cell lines are still lacking. Understanding these metabolic differences is essential for improving the translational relevance of preclinical studies. The study aims to conduct a comprehensive metabolomic analysis on three widely used CRC cell lines (HT-29, Caco-2, SW480) to identify their metabolic differences and explore their biological significance and origins. We conducted a metabolomic analysis using ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) to measure intracellular and extracellular metabolites. Multivariate statistical approaches, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), were applied to identify metabolic variations. Pathway enrichment analysis was then performed to uncover dysregulated metabolic pathways. Our analysis revealed distinct metabolic profiles among the three CRC cell lines, with 25 differential metabolites identified. Pathway enrichment analysis highlighted three significantly dysregulated pathways: glycerophospholipid metabolism, ether lipid metabolism, and pantothenate and CoA biosynthesis. These findings demonstrate intrinsic metabolic heterogeneity at both intracellular and extracellular levels. These findings confirm intrinsic metabolic heterogeneity of the three CRC cell lines by intracellular and extracellular profiling, highlighting the importance of validating results across multiple models to address the limitations intrinsic to single cell lines in mechanistic and translational studies.

Discover OncologyVol. 17(1)
Zoucheng People's Hospital (CN), Ningxia Medical University (CN), Jining University (CN)
Openalex Percentile: Top 66%
Metabolomics and Mass Spectrometry Studies
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