Head and neck squamous cell carcinoma (HNSCC) encompasses tumors arising from several locations (oral and nasal cavities, paranasal sinuses, salivary glands, pharynx, and larynx) and currently stands as the sixth most common cancer worldwide. The most important risk factors identified so far are tobacco and alcohol consumption, and, for a subgroup of HNSCCs, infection with high-risk types of human papillomavirus (HPV). Despite several improvements in the treatment of these tumors in the last decades, overall survival rates have only improved marginally, mainly due to the advanced clinical stage at diagnosis and the high rates of treatment failure associated with this late diagnosis. Areas covered: This review will focus on the feasibility of evaluating molecular-based biomarkers (mRNA, microRNA, lncRNA, DNA methylation and protein expression) in body fluids (serum, plasma, and saliva) as markers for diagnosis, prognosis, and surveillance. Expert commentary: The potential use of those markers in the clinical setting would allow for early diagnosis, prediction of treatment response, improvement in treatment selection and provide disease monitoring for early detection of tumor recurrence. It can ultimately be translated into better survival rates and improved quality of life for HNSCC patients.

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The need for analytical devices for detecting cancer at early stages has motivated research into nanomaterials where synergy is sought to achieve high sensitivity and selectivity in low-cost biosensors. In this study, we developed a film architecture combining self-assembled monolayer (SAM) and layer-by-layer (LbL) films of polysaccharide chitosan and the protein concanavalin A, on which a layer of anti-CA19-9 antibody was adsorbed. Using impedance spectroscopy with this biosensor, we were capable of detecting low concentrations of the antigen CA19-9, an important biomarker for pancreatic cancer. The limit of detection of 0.69U/mL reached is sufficient for detecting pancreatic cancer at very early stages. The selectivity of the biosensor was inferred from a series of control experiments with samples of cell lines that were tested positive (HT29) and negative (SW620) for the biomarker CA19-9, in addition to the lack of changes in the capacitance value for other analytes and antigen that are not related to this type of cancer. The high sensitivity and selectivity are ascribed to the very specific antigen-antibody interaction, which was confirmed with PM-IRRAS and atomic force microscopy. Also significant is that used information visualization methods to show that different cell lines and commercial samples containing distinct concentrations of CA19-9 and other analytes can be easily distinguished from each other. These computational methods are generic and may be used in optimization procedures to tailor biosensors for specific purposes, as we demonstrated here by comparing the performance of two film architectures in which the concentration of chitosan was varied.

Biosensors for early detection of cancer biomarkers normally depend on specific interactions between such biomarkers and immobilized biomolecules in the sensing units. Though these interactions are expected to yield specific, irreversible adsorption, the underlying mechanism appears not to have been studied in detail. In this paper, we show that adsorption explained with the Langmuir-Freundlich model is responsible for detection of the antigen p53 associated with various types of cancers. Irreversible adsorption was proven between anti-p53 antibodies immobilized on the biosensors and the antigen p53, with the adequacy of the Langmuir-Freundlich model being confirmed with three independent experimental methods, viz. polarization-modulated infrared reflection absorption spectroscopy (PM-IRRAS), nanogravimetry using a quartz crystal microbalance and electrochemical impedance spectroscopy. The method based on this irreversible adsorption was sufficiently sensitive (limit of detection of 1.4 pg mL(-1)) for early diagnosis of Hodgkin lymphoma, pancreatic and colon carcinomas, and bladder, ovarian and lung cancers, and could distinguish between MCF7 cells containing the antigen p53 from Saos-2 cells that do not contain it.