Related Experiment Video
Updated: Mar 28, 2026
07:54
Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting
Published on: March 25, 2019
8.8K
Quantifying Glycogen and Lipid Droplet Synthesis in Ovarian and Cervical Cancer Cells using Deuterated Raman Probes
Ryan N Pierson1, Shovit A Gupta1, Mingyuan Zhang1
1Department of Biomedical Engineering, Thomas J. Watson College of Engineering and Applied Science, Binghamton University, State University of New York, Binghamton, NY 13902, USA.
Biorxiv : the Preprint Server for Biology
|March 27, 2026
Summary
Stimulated Raman scattering (SRS) microscopy with deuterium labeling reveals distinct metabolic differences in ovarian and cervical cancer cells. This technique can identify cancer metabolic phenotypes for improved diagnostics and targeted therapies.
Area of Science:
- Biomedical Optics
- Cancer Biology
- Metabolic Imaging
Background:
- Epithelial ovarian cancer has poor survival rates due to late diagnosis.
- Tumor microenvironment metabolic heterogeneity necessitates rapid, specific phenotyping methods.
- Stimulated Raman scattering (SRS) microscopy offers non-invasive metabolic pathway interrogation.
Purpose of the Study:
- To profile fatty acid and glycogen metabolism in ovarian (SKOV-3) and cervical (HeLa) cancer cells using SRS microscopy.
- To investigate cell-line-specific metabolic strategies and heterogeneity.
- To identify potential metabolic markers for cancer phenotyping.
Main Methods:
- Utilized SRS microscopy combined with deuterium-labeled metabolites (glucose).
- Analyzed glycogen synthesis, intracellular distribution, and lipid droplet dynamics.
- Examined metabolic strategies under nutrient starvation in cancer cell models.
Main Results:
- Deuterium-labeled glucose highlighted significant differences in glycogen metabolism and distribution between SKOV-3 and HeLa cells.
- SKOV-3 cells displayed greater single-cell heterogeneity in glycogen synthesis compared to HeLa cells.
- Lipid droplet dynamics revealed distinct, cell-line-specific metabolic adaptations.
Conclusions:
- SRS microscopy with metabolic labeling can sensitively resolve metabolic diversity in cancer cell subpopulations.
- Glycogen and lipid droplet dynamics show potential as diagnostic markers for cancer metabolic phenotypes.
- Metabolic phenotyping may guide early diagnostics and combination therapies targeting metabolic disruption.
