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Surface-enhanced Resonance Raman Scattering Nanoprobe Ratiometry for Detecting Microscopic Ovarian Cancer via Folate Receptor Targeting
Published on: March 25, 2019
Raman micro-spectroscopy applied to treatment resistant and sensitive human ovarian cancer cells
Hamid Moradi1, Abrar Ahmad1, Dean Shepherdson1
1Department of Physics, Carleton University, K1S 5B6, Ottawa, Canada.
Abstract:
Despite the many advances intended to enhance the response to treatment, the survival rate of patients with ovarian cancer has only marginally improved in the past few decades. One major cause for this, is the lack of diagnostics for platinum-resistant disease. The goal of this study was to determine whether Raman micro-spectroscopy in conjunction with multivariate statistical analysis could discriminate between chemically fixed cisplatin-resistant (A2780cp) and cisplatin-sensitive (A2780s) human ovarian carcinoma cells. Raman spectra collected from individual cells were pre-processed and subsequently analyzed with Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA). Statistically significant differences (P < 0.0001) were observed between the Raman spectra of A2780s and A2780cp cells. A diagnostic accuracy of 82% was obtained using the PCA-LDA classifier model for the discrimination between the A2780s and A2780cp cells. The loading plot analysis suggests that relative increases in proteins and glutathione in the cisplatin-resistant cells compared to the cisplatin-sensitive cells are most likely the major source of discrimination between the two types of cells. These results support the potential application of Raman spectroscopy in the identification of chemo-resistant tumors prior to treatment.
Insights
Raman spectroscopy can identify cisplatin-resistant ovarian cancer cells. This technique, using Principal Component Analysis - Linear Discriminant Analysis, achieved 82% accuracy, potentially aiding pre-treatment diagnostics for chemo-resistant tumors.
Area of Science:
- Biomedical Optics
- Chemical Biology
- Ovarian Cancer Research
Background:
- Ovarian cancer survival rates have seen minimal improvement despite treatment advances.
- A key challenge is the lack of diagnostics for platinum-resistant disease.
- Early identification of chemoresistance is crucial for effective ovarian cancer treatment.
Purpose of the Study:
- To investigate Raman micro-spectroscopy for discriminating cisplatin-resistant from cisplatin-sensitive ovarian cancer cells.
- To evaluate the efficacy of multivariate statistical analysis in conjunction with Raman spectroscopy for this discrimination.
Main Methods:
- Chemically fixed cisplatin-sensitive (A2780s) and cisplatin-resistant (A2780cp) human ovarian carcinoma cells were analyzed.
- Raman spectra from individual cells were collected, pre-processed, and analyzed using Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA).
Main Results:
- Statistically significant differences (P < 0.0001) were found between the Raman spectra of A2780s and A2780cp cells.
- The PCA-LDA model achieved an 82% diagnostic accuracy in discriminating between the two cell types.
- Increased levels of proteins and glutathione in resistant cells were identified as key discriminators.
Conclusions:
- Raman micro-spectroscopy combined with PCA-LDA shows potential for identifying chemo-resistant ovarian cancer cells.
- This approach could lead to novel diagnostic tools for predicting treatment response prior to therapy.
- Further research may enable the clinical application of Raman spectroscopy in personalized ovarian cancer treatment.
