Biosensors based on stanniocalcin-1 protein antibodies thin films for prostate cancer diagnosis

• Autor(a) principal: Ferreira, Renato
• Data de Publicação: 2023
• Outros Autores: Ribeiro, Paulo A., Canário, Adelino V. M., Raposo, Maria
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.1/20215
• topic: Prostate cancer; Electronic tongue; Stanniocalcin; STC1; Layer-by-layer films; Polyelectrolytes; Impedance spectroscopy; Principal component analysis

Prostate cancer is one of the most prevalent tumors in men, accounting for about 7.3% of cancer deaths. Although there are several strategies for diagnosing prostate cancer, these are only accurate when the tumor is already at a very advanced stage, so early diagnosis is essential. Stanniocalcin 1 (STC1) is a secreted glycoprotein, which has been suggested as a tumor marker as its increased expression is associated with the development and/or progression of different types of malignant tumors. In this work, an electronic tongue (ET) prototype, based on a set of four sensors prepared from thin films that included STC1 antibodies for detecting prostate cancer, was developed. In the preparation of the thin films, polyelectrolytes of polyallylamine hydrochloride, polystyrene sulfonate of sodium and polyethyleneimine, and the biomolecules chitosan, protein A, and STC1 antibody were used. These films were deposited on quartz lamellae and on solid supports using layer-on-layer and self-assembly techniques. The deposition of the films was analyzed by ultraviolet-visible spectroscopy, and the detection of STC1 in aqueous solutions of PBS was analyzed by impedance spectroscopy. The impedance data were statistically analyzed using principal component analysis. The ETs formed by the four sensors and the three best sensors could detect the antigen at concentrations in the range from 5 × 10⁻¹¹ to 5 × 10⁻⁴ M. They showed a linear dependence with the logarithm of the antigen concentration and a sensitivity of 5371 ± 820 and 4863 ± 634 per decade of concentration, respectively. Finally, the results allow us to conclude that this prototype can advance to the calibration phase with patient samples.