Metabolites 2026, 16(5), 293; https://doi.org/10.3390/metabo16050293 - 24 Apr 2026
Abstract
Background/Objectives: Colorectal cancer (CRC) is a leading cause of cancer-related mortality, with colorectal liver metastasis (CRLM) being the major determinant of poor prognosis. Tumor metabolic reprogramming and spatial heterogeneity complicate biomarker discovery and clinical management. This study aimed to characterize the spatial
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Background/Objectives: Colorectal cancer (CRC) is a leading cause of cancer-related mortality, with colorectal liver metastasis (CRLM) being the major determinant of poor prognosis. Tumor metabolic reprogramming and spatial heterogeneity complicate biomarker discovery and clinical management. This study aimed to characterize the spatial metabolomic landscape of CRC and identify progression-associated metabolic alterations and potential metabolic signatures for liver metastasis. Methods: A total of 23 tissue samples were collected from patients with CRC, with and without liver metastasis. Air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) was used to map the spatial metabolite distributions. Region-of-interest analysis guided by histopathology enabled comparative metabolomic profiling across different tissue types. Multivariate statistical analysis, pathway enrichment, and receiver operating characteristic (ROC) curve analyses were performed to identify key metabolic alterations and evaluate potential biomarker performance. Results: Distinct spatial metabolomic profiles were observed across normal mucosa, primary tumors, liver metastases, and normal liver tissues. In primary colorectal tumors, amino acid, purine, and choline metabolism were significantly upregulated, whereas liver metastases were characterized by elevated levels of triglycerides, diglycerides, cholesteryl esters, and acylcarnitines, indicating enhanced lipid synthesis, incomplete fatty acid oxidation, and/or mitochondrial dysfunction. Progression-associated analyses across tissue types revealed consistently increasing trends in glycerides and acylcarnitines, along with heterogeneous alterations in amino acids and phospholipids. Furthermore, 122 differential metabolites were identified between metastatic and non-metastatic CRC, and a four-lipid panel demonstrated strong discriminatory performance. Conclusions: This study provides a spatially resolved characterization of metabolic reprogramming during CRC progression and liver metastasis, highlighting lipid and amino acid metabolism as key features and revealing the metabolic signatures of CRLM.
Full article
(This article belongs to the Section Endocrinology and Clinical Metabolic Research)
