Issue 7, 2015

Recurrence prediction in oral cancers: a serum Raman spectroscopy study

Abstract

High mortality rates associated with oral cancers can be primarily attributed to the failure of current histological procedures in predicting recurrence. Identifying recurrence related factors can lead to improved prognosis, optimized treatment and enhanced overall outcomes. Serum Raman spectroscopy has previously shown potential in the diagnosis of cancers, such as head and neck, cervix, breast, oral cancers, and also in predicting treatment response. In the present study, serum was collected from 22 oral cancer subjects [with recurrence (n = 10) and no-recurrence (n = 12)] before and after surgery and spectra were acquired using a Raman microprobe coupled with a 40× objective. Spectral acquisition parameters were as follows: λex = 785 nm, laser power = 30 mW, integration time: 12 s and averages: 3. Data was analyzed in a patient-wise approach using unsupervised PCA and supervised PC-LDA, followed by LOOCV. PCA and PC-LDA findings suggest that recurrent and non-recurrent cases cannot be classified in before surgery serum samples; an average classification efficiency of ∼78% was obtained in after-surgery samples. Mean and difference spectra and PCA loadings indicate that DNA and protein markers may be potential spectral markers for recurrence. RS of post surgery serum samples may have the potential to predict the probability of recurrence in clinics, after prospective large-scale validation.

Graphical abstract: Recurrence prediction in oral cancers: a serum Raman spectroscopy study

Article information

Article type
Paper
Submitted
16 Қаз. 2014
Accepted
05 Қаң. 2015
First published
05 Қаң. 2015

Analyst, 2015,140, 2294-2301

Author version available

Recurrence prediction in oral cancers: a serum Raman spectroscopy study

A. Sahu, N. Nandakumar, S. Sawant and C. M. Krishna, Analyst, 2015, 140, 2294 DOI: 10.1039/C4AN01860E

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