Chemoresistance Characterization Using Raman Spectroscopy: A Pilot Study

*Corresponding author: (e-mail: [e-mail]/[e-mail]

Abstract

Background: Chemoresistance is a major hurdle in cancer therapy and it is necessary to understand and develop methods to predict chemoresistance to ensure better patient survival. Vibrational spectroscopy techniques such as Raman spectroscopy (RS) is widely explored as a tool to achieve this outcome.

Material and methods: We have used RS to characterize chemoresistant cell lines—HeLa, SiHa, HepG2, and Hep3B. Doxorubicin-resistant cell lines were developed from the parental counterparts. Raman spectra were recorded from the cell pellets and mean spectra were computed. The data were used to perform multivariate analyses PCA and PC-LDA.

Results: The Raman spectra revealed changes in important biomolecules—proteins, nucleic acids, cytochromes, and lipids (Table 1). The mean spectra of parental cell lines were different than the resistant cell types. The PC-LDA scatter plot in HeLa gave 82.53% accuracy with 75% sensitivity and 89% specificity. SiHa LDA accuracy was 91.67% with 100% sensitivity and 83% specificity. In the case of HepG2 cells, accuracy was around 89% with 100% sensitivity and 78% specificity. For Hep3B cell lines, both the cell populations were classified with 83% efficiency. Thus, RS is capable of segregating parental and resistant lines with good efficiency.

Table 1 Important spectral peaks obtained using RS and their differences in parental and resistant cell populations

Features (in cm−1)	Assignment	P/R
1005, 1260, 1660	Proteins	High in P
1305,17421448	LipidsCH2 bending	High in RHigh in R
1586	Cytochromes	High in R
786, 7201096	Nucleic acidNucleic acid	High in PHigh in P

Note: P indicates Parental and R indicates Resistant.

Conclusion: Our study demonstrates that Raman spectroscopic profiles of resistant cells are characteristically distinct from the parental cells. This study highlights the prospective application of RS for better stratification of patients in clinics. A further validation of model accuracy achieved is required using a large sample size.

Publication History

Article published online:
08 July 2024