Raman Spectroscopy: An Exploratory Study to Identify Post-Radiation Cell Survival

Abstract

Resistance to radiotherapy has been an impediment in the treatment of cancer, and the inability to detect it at an early stage further exacerbates the prognosis. We have assessed the feasibility of Raman spectroscopy as a rapid assay for predicting radiosensitivity of cancer cells in comparison to the conventional biological assays. Cell lines derived from breast adenocarcinoma (MCF7), gingivobuccal squamous cell carcinoma (ITOC-03), and human embryonic kidney (HEK293) were subjected to varying doses of ionizing radiation. Cell viability of irradiated cells was assessed at different time points using MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) assay and Raman spectroscopy, and colony-forming capability was evaluated by clonogenic assay. Radiosensitivity observed using MTT assay was limited by the finding of similar cell viability in all the three cell lines 24 h post-irradiation. However, cell survival assessed using clonogenic assay and principal component linear discriminant analysis (PC-LDA) classification of Raman spectra showed correlating patterns. Irradiated cells showed loss of nucleic acid features and enhancement of 750 cm−1 peak probably attributing to resonance Raman band of cytochromes in all three cell lines. PC-LDA analysis affirmed MCF7 to be a radioresistant cell line as compared to ITOC-03 and HEK293 to be the most radiosensitive cell line. Raman spectroscopy is shown to be a rapid and alternative assay for identification of radiosensitivity as compared to the gold standard clonogenic assay.

Radiation treatment response and hypoxia biomarkers revealed by machine learning assisted Raman spectroscopy in tumour cells and xenograft tissues

“…In previous research, RS has demonstrated the potential to be incorporated into radiation therapy as a label-free technique to reveal the biochemical dynamics and assess the treatment response for various types of cancer. [9][10][11][12][13][14][15][16][17][59][60][61][62][63] Nevertheless, conventional unsupervised dimension reduction techniques can provide limited resolution in distinguishing responses from different chemicals. [9][10][11][12][13][14][15][16][17][59][60][61][62][63] In this manuscript, the GBR-NMF-RF-SHAP data analytical framework has demonstrated an outstanding capability to resolve signals such as radiation response and hypoxia indicators corresponding to constrained chemicals.…”

“…[9][10][11][12][13][14][15][16][17][59][60][61][62][63] Nevertheless, conventional unsupervised dimension reduction techniques can provide limited resolution in distinguishing responses from different chemicals. [9][10][11][12][13][14][15][16][17][59][60][61][62][63] In this manuscript, the GBR-NMF-RF-SHAP data analytical framework has demonstrated an outstanding capability to resolve signals such as radiation response and hypoxia indicators corresponding to constrained chemicals. Moreover, GBR-NMF-RF-SHAP also exhibited efficiency in analyses across various types of cancer data (cell and tissue).…”

Noncannonical functions of Ku may underlie essentiality in human cells

“…Previous work demonstrated that in the absence of Ku80 protein, there is a significant increase γH2AX foci, a marker of DSBs, in knockout cells [34]. We analyzed not reach the level induced by 2 Gy of IR which was reported to result in more than 70% survival using a colony forming assay in HEK293 cells [35]. These findings lead us to conclude that it is not the accumulation of DSBs that is the driving factor behind the loss of cell viability in Ku70 knockout cells.…”

Living Sample Viability Measurement Methods from Traditional Assays to Nanomotion

“…RS enables sample archiving and retesting for more precise therapy response assessment. The advantages of RS maps have been harnessed to quantify dynamic changes at the single-cell level in terms of sensitivity, for spatial and temporal resolution of multiplexed metabolic changes, and for quantitative analysis [ 64 , 68 ].…”