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Lipid Droplets as Cellular Sensors of Lipid Metabolic Reprogramming in Colon Cancer: Insights from Essential Amino
Monika Kopeć1, Karolina Beton-Mysur1, Beata Brożek-Płuska1
1Laboratory of Laser Molecular Spectroscopy, Institute of Applied Radiation Chemistry, Faculty of Chemistry, Lodz University of Technology, Wroblewskiego 15, 93-590 Lodz, Poland.
Molecules (Basel, Switzerland)
|March 14, 2026
Summary
Raman spectroscopy reveals how amino acids like leucine, threonine, and arginine alter metabolism in normal and cancerous colon cells. This label-free technique distinguishes cell types by their unique biochemical fingerprints, aiding cancer research.
Area of Science:
- Biochemistry
- Cell Biology
- Spectroscopy
Background:
- Colorectal cancer involves significant metabolic reprogramming.
- Understanding nutrient-cancer cell interactions is crucial for diagnostics and therapeutics.
- Label-free, high-resolution techniques are needed to study cellular metabolism.
Purpose of the Study:
- To investigate the single-cell biochemical and metabolic responses of colon fibroblasts and adenocarcinoma cells to amino acid supplementation.
- To utilize Raman spectroscopy and imaging for label-free, high-spatial-resolution analysis of intracellular components.
- To discriminate between normal and malignant colon cells based on their intrinsic vibrational fingerprints after amino acid treatment.
Main Methods:
- Single-cell Raman spectroscopy and Raman imaging of CCD-18Co (normal fibroblasts) and Caco-2 (adenocarcinoma) cells.
- Supplementation with leucine, threonine, and arginine.
- Label-free, noninvasive methodology for mapping intracellular components.
- Integration of Raman data with chemometric methods, including Partial Least Squares Discriminant Analysis (PLS-DA) and ANOVA.
- Analysis of diagnostic Raman band intensity ratios.
Main Results:
- Robust discrimination between normal and malignant colon cells was achieved based on intrinsic vibrational fingerprints.
- Perturbations in lipid metabolism and protein composition were identified as key determinants of phenotypic divergence.
- Amino acid supplementation induced significant, measurable alterations in metabolic pathways at the single-cell level.
- Raman imaging visualized spatially resolved biochemical shifts and differential responses in subcellular domains.
Conclusions:
- Raman spectroscopy combined with chemometric analysis is a powerful platform for decoding amino acid-induced metabolic reprogramming in colorectal cells.
- The study deepens mechanistic understanding of nutrient-cancer cell interactions.
- This approach offers potential for Raman-based strategies in cancer diagnostics and therapeutic response assessment.
