Valentín López Gayou

Detection of Premalignant Cervical Lesions via Maackia amurensis Lectin-Based Biosensors

Early detection of premalignant cervical lesions is essential for improving cervical cancer outcomes; however, current screening methods frequently lack adequate sensitivity and specificity. This research introduces a diagnostic platform that integrates lectin-based biosensors with spectral and multivariate analysis. The biosensors are composed of gold nanoparticles (AuNPs) conjugated with Maackia amurensis (MAA) lectin, which selectively binds to α2,3-linked sialic acid. Validation was performed using cervical cancer cell lines (SiHa, HeLa, C33A), fibroblasts, and cervical scrapes, and specificity was verified by enzymatic removal of sialic acids. Spectral data were obtained using attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and analyzed by principal component analysis (PCA). Application of PCA to the 1600–1350 cm−1 spectral region, using 99% confidence ellipses, enabled clear differentiation between samples negative and positive for intraepithelial lesions in a double-blind study of 58 patients. The MAA biosensors exhibited high sensitivity and specificity, comparable to established diagnostic methods. These results indicate that the combination of ATR-FTIR spectroscopy, MAA lectin-based biosensors, and chemometric analysis provides a robust and reliable approach for early detection of premalignant cervical lesions, with considerable potential to enhance patient outcomes.

Detection of Sialic Acid to Differentiate Cervical Cancer Cell Lines Using a Sambucus nigra Lectin Biosensor

Pap smear screening is a widespread technique used to detect premalignant lesions of cervical cancer (CC); however, it lacks sensitivity, leading to identifying biomarkers that improve early diagnosis sensitivity. A characteristic of cancer is the aberrant sialylation that involves the abnormal expression of α2,6 sialic acid, a specific carbohydrate linked to glycoproteins and glycolipids on the cell surface, which has been reported in premalignant CC lesions. This work aimed to develop a method to differentiate CC cell lines and primary fibroblasts using a novel lectin-based biosensor to detect α2,6 sialic acid based on attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and chemometric. The biosensor was developed by conjugating gold nanoparticles (AuNPs) with 5 µg of Sambucus nigra (SNA) lectin as the biorecognition element. Sialic acid detection was associated with the signal amplification in the 1500–1350 cm−1 region observed by the surface-enhanced infrared absorption spectroscopy (SEIRA) effect from ATR-FTIR results. This region was further analyzed for the clustering of samples by applying principal component analysis (PCA) and confidence ellipses at a 95% interval. This work demonstrates the feasibility of employing SNA biosensors to discriminate between tumoral and non-tumoral cells, that have the potential for the early detection of premalignant lesions of CC.