Micro-Raman spectroscopy is a very promising tool for medical applications, thanks to its sensitivity to subtle changes in the chemical and structural characteristics of biological specimens. To fully exploit these promises, building a method of data analysis properly suited for the case under study is crucial. Here, a linear or univariate approach using a R2 determination coefficient is proposed for discriminating Raman spectra even with small differences. The validity of the proposed approach has been tested using Raman spectra of high purity glucose solutions collected in the 600 to 1,600 cm？1 region and also from solutions with two known solutes at different concentrations. After this validation step, the proposed analysis has been applied to Raman spectra from oral human tissues affected by Pemphigus Vulgaris (PV), a rare life-threatening autoimmune disease, for monitoring disease follow-up. Raman spectra have been obtained in the wavenumber regions from 1,050 to 1,700 cm？1 and 2,700 to 3,200 cm？1 from tissues of patients at different stages of pathology (active PV, under therapy and PV in remission stage) as confirmed by histopathological and immunofluorescence analysis. Differences in the spectra depending on tissue illness stage have been detected at 1,150–1,250 cm？1 (amide III) and 1,420–1,450 cm？1 (CH3 deformation) regions and around 1,650 cm？1 (amide I) and 2,930 cm？1 (CH3 symmetric stretch). The analysis of tissue Raman spectra by the proposed univariate method has allowed us to effectively differentiate tissues at different stages of pathology.
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