Optical spectroscopic methods are being contemplated as adjunct/ alternative to existing 'Gold standard' of cancer
diagnosis, histopathological examination. Several groups are actively pursuing diagnostic applications of Ramanspectroscopy
in cancers. We have developed Raman spectroscopic models for diagnosis of breast, oral, stomach, colon
and larynx cancers. So far, specificity and applicability of spectral- models has been limited to particular tissue origin. In
this study we have evaluated explicitly of spectroscopic-models by analyzing spectra from already developed spectralmodels
representing normal and malignant tissues of breast (46), cervix (52), colon (25), larynx (53), and oral (47).
Spectral data was analyzed by Principal Component Analysis (PCA) using scores of factor, Mahalanobis distance and
Spectral residuals as discriminating parameters. Multiparametric limit test approach was also explored. The preliminary
unsupervised PCA of pooled data indicates that normal tissue types were always exclusive from their malignant
counterparts. But when we consider tissue of different origin, large overlap among clusters was found. Supervised
analysis by Mahalanobis distance and spectral residuals gave similar results. The 'limit test' approach where
classification is based on match / mis-match of the given spectrum against all the available spectra has revealed that
spectral models are very exclusive and specific. For example breast normal spectral model show matches only with
breast normal spectra and mismatch to rest of the spectra. Same pattern was seen for most of spectral models. Therefore,
results of the study indicate the exclusiveness and efficacy of Raman spectroscopic-models. Prospectively, these findings
might open new application of Raman spectroscopic models in identifying a tumor as primary or metastatic.