Nonlinear optical response of cancer cells following conventional and nano-technology based treatment strategies: Results of chemo-, thermo-and radiation therapies‏

The aim of this study was to evaluate the capability of nonlinear optical response of cells to determine cellular damages during conventional and nano-technology based treatments...

Abstract

Background

Although traditional treatments are able to increase cancer survival rate, undesirable impact on off-target tissues are considered a limitation of these approaches. Nanotechnology-based treatments have been proposed as a possible option to enhance targeting. Further, current methods for evaluating cellular damage, are time consuming, highly dependent on the operator skills, and expensive. The aim of this study was to evaluate the capability of nonlinear optical response of cells to determine cellular damages during conventional and nano-technology based treatments.

Methods

Three different cancer cell lines, CT26, KB, and MCF-7 were used in this study. The alginate hydrogel co-loaded with cisplatin and Au nanoparticle (ACA) nanocomplex and gold-coated iron oxide nanoparticle (Au@IONP) were considered for chemo- and chemo-photothermal therapies, and thermo-radiation therapy, respectively. The sign and value of nonlinear optical absorption coefficient and imaginary part of the third-order nonlinear susceptibility of cells were computed. MTT assay was utilized as a reference method.

Results

The value of nonlinear optical indices increased with increasing cellular damage and cell death. The linear regression analysis indicated high correlation between nonlinear optical indices and MTT results, in all treatments.

Conclusion

The nonlinear optical indices are robust from confounding factors, namely treatment approach (traditional and nano-technology based), treatment modality (chemotherapy, thermotherapy, photothermal therapy, and radiation therapy), and cell types. Nonlinear optical properties of cells can be used as a rapid estimation method for cell damage, at the nanoscale level.

The schematic illustration of steps involved in this study at a glance.
Picture of Ardakani AA

Ardakani AA

He received his Ph.D. in Medical Physics in 2018 from the Iran University of Medical Sciences (IUMS), specializing in medical imaging and using artificial intelligence in radiological diagnosis. His research interests focus on the physics of medical imaging systems, quantitative analysis of medical images, and applying artificial intelligence in diagnostic radiology procedures. He is an assistant professor of Medical Physics at Shahid Beheshti University of Medical Sciences.

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