Segregation of ovarian cancer stage exploiting spectral biomarkers derived from blood plasma or serum analysis: ATR-FTIR spectroscopy coupled with variable selection methods.

Ovarian cancer is a solid tumor and a leading cause of mortality. Diagnostic tools for the detection of early stage (stage I) ovarian cancer are urgently needed. For this purpose, attenuated total reflection Fourier-transform infrared spectroscopy (ATR-FTIR) coupled with variable selection methods, successive projection algorithm or genetic algorithm (GA) combined with linear discriminant analysis (LDA), were employed to identify spectral biomarkers in blood plasma or serum samples for accurate diagnosis of different stages of ovarian cancer, histological type and segregation based on age. Three spectral datasets (stage I vs. stage II-IV; serous vs. non-serous carcinoma; and, ≤60 years vs. >60 years) were processed: sensitivity and specificity required for real-world diagnosis of ovarian cancer was achieved. Toward segregating stage I vs. stage II-IV, sensitivity and specificity (plasma blood) of 100% was achieved using a GA-LDA model with 33 wavenumbers. For serous vs. non-serous category (plasma blood), the sensitivity and specificity levels, using 29 wavenumbers by GA-LDA, were remarkable (up to 94%). For ≤60 years and >60 years categories (plasma blood), the sensitivity and specificity, using 42 wavenumbers by GA-LDA, gave complete accuracy (100%). For serum samples, sensitivity and specificity results gave relatively high accuracy (up to 91.6% stage I vs. stage II-IV; up to 93.0% serous vs. non-serous; and, up to 96.0% ≤60 years vs. >60 years) using several wavenumbers. These findings justify a prospective population-based assessment of biomarkers signatures using ATR-FTIR spectroscopy as a screening tool for stage of ovarian cancer.

Vibrational spectroscopy of biofluids for disease screening or diagnosis: translation from the laboratory to a clinical setting.

There remains a need for objective and cost-effective approaches capable of diagnosing early-stage disease in point-of-care clinical settings. Given an increasingly ageing population resulting in a rising prevalence of chronic diseases, the need for screening to facilitate the personalising of therapies to prevent or slow down pathology development will increase. Such a tool needs to be robust but simple enough to be implemented into clinical practice. There is interest in extracting biomarkers from biofluids (e.g., plasma or serum); techniques based on vibrational spectroscopy provide an option. Sample preparation is minimal, techniques involved are relatively low-cost, and data frameworks are available. This review explores the evidence supporting the applicability of vibrational spectroscopy to generate spectral biomarkers of disease in biofluids. We extend the inter-disciplinary nature of this approach to hypothesise a microfluidic platform that could allow such measurements. With an appropriate lightsource, such engineering could revolutionize screening in the 21(st) century.