Breast cancer (BC) is the most prevalent cancer worldwide. The prognosis and survival of these patients are directly related to the diagnostic stage. Even so, the gold standard screening method (mammography) has a long waiting period, high rates of false positives, anxiety for patients, and consequently delays the diagnosis by core needle biopsy (invasive method). Alternatively, the Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy is a noninvasive, low-cost, rapid, and reagent-free technique that generates the spectral metabolomic profile of biomolecules. This makes it possible to assess systemic repercussions, such as the BC carcinogenesis process. Blood plasma samples (n = 56 BC and n = 18 controls) were analyzed in the spectrophotometer in the ATR-FTIR mode. For the exploratory analysis of the data, interval Principal Component Analysis (iPCA) was used, and for predictive chemometric modeling, the Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) algorithm with validation by leave-one-out cross-validation. iPCA in the region of 1118-1052 cm-1 (predominantly DNA/RNA bands) showed significant clustering of molecular subtypes and control. The OPLS-DA model achieved 100% accuracy with only 1 latent variable and Root Mean Square Error of Cross-Validation (RMSECV) < 0.005 for all molecular subtypes and control. The wavenumbers (cm-1) with the highest iPCA peaks (loadings: 1117, 1089, 1081, 1075, 1057, and 1052) were used as input to MANOVA (Wilks' Lambda, p < 0.001 between molecular subtypes and control). The rapid and low-cost detection of BC molecular subtypes by ATR-FTIR spectroscopy would plausibly allow initial screening and clinical management, improving prognosis, reducing mortality and costs for the health system.
Keywords: Breast cancer; Chemometrics; Infrared spectroscopy; Liquid biopsy; Orthogonal partial least squares discriminant analysis.
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