Combinatorial Characterization of Saliva for Oral Precancer Diagnostics

Abstract

Background: Saliva based diagnostic can play an important role in the translational research related to cancer diagnostics and treatment. It is easily available, noninvasive, low storage cost, has less contamination chances with simple collection procedure. Cancers related to tobacco use, including oral cancer account for about 30% of all cancers in males and females. Five years' survival rate remains the same even after decades of advancement of detection, prevention, and treatment of OSCC (oral squamous cell carcinoma) mainly due to late diagnosis of oral potentially malignant disorders (OPMDs). Aim: Combinatorial characterization of saliva, endorsing multidimensional spectroscopic signatures using suitably designed biochamber. Methods: Eighteen saliva samples (6 normal, 6 OSF [oral submucous fibrosis, a type of OPMD] and 6 confirmed OSCC) were collected from GNIDSR (Guru Nanak Institute of Dental Science and Research) Kolkata. Ethical approval was obtained for the study and all the participants were explained the objectives of the study and a written informed consent was obtained from them. Participant's demographic detail and clinical characteristics were also recorded. The participants were asked not to consume food 1 hour before sample collection and were suggested to rinse their mouth 30 minutes prior to saliva expectoration to minimize the contamination of food in saliva. Empty, sterile, graded tubes were used for this purpose. The subjects were asked not to clear nose or throat during the process of saliva expectoration to avoid forced phlegm from other part of the respiratory tract. The saliva samples were then immediately transferred to −20 degrees and later in −80 degrees for long storage. The electrical impedance (EI) of saliva was measured in custom made biochambers with copper electrodes. The EI was measured for the frequency sweep from 20 Hz to 2 MHz using an impedance analyzer. Apart from EI measurement, the corresponding samples were subjected to FTIR (Fourier-transform IR spectroscopy) analysis. SPSS and OMNIC software were used for the data analysis of EI and FTIR respectively. Results: [Table: see text][Table: see text][Table: see text][ Table A , B & C represents descriptive statistics, correlation matrix and component matrix respectively. The multivariate analysis of the FTIR data indicates the significant differences ( P < 0.005) among the different study groups such as normal, OSF and OSCC. The eigen values (normal 0.917, OSF 0.962, OSCC 0.975) from component matrix analysis also indicate the same. Conclusion: The spectroscopic characterization (EI and FTIR) of saliva was effective in evaluating normal and OPMD condition. This noninvasive paradigm can serve as a complimentary technique to the existing gold standard methods for the early detection of oral cancer.