Deconvolution Analysis for Classifying Gastric Adenocarcinoma Patients Based on Differential Scanning Calorimetry Serum Thermograms

• Published in: Scientific reports Vol. 5; no. 1; p. 7988
• Main Authors: Vega, Sonia, Garcia-Gonzalez, María Asuncion, Lanas, Angel, Velazquez-Campoy, Adrian, Abian, Olga
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 23.01.2015; Nature Publishing Group
• Subjects: 631/57/2272/951; 631/67/1504/1829; 82; Adenocarcinoma; Adenocarcinoma - blood; Adenocarcinoma - diagnosis; Biomarkers; Blood; Blood Proteins - chemistry; Calorimetry; Calorimetry, Differential Scanning; Cancer; Case-Control Studies; Classification; Data analysis; Differential scanning calorimetry; Disease; Experiments; Gastric cancer; Hospitals; Humanities and Social Sciences; Humans; Metabolites; multidisciplinary; Neoplasm Staging; Patients; Plasma; Protein Denaturation; Protein Folding; Protein Unfolding; Proteins; Science; Spain; Stomach Neoplasms - blood; Stomach Neoplasms - diagnosis; Thermal denaturation; Thermography; Tumors; Spain
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/srep07988

Recently, differential scanning calorimetry (DSC) has been acknowledged as a novel tool for diagnosing and monitoring several diseases. This highly sensitive technique has been traditionally used to study thermally induced protein folding/unfolding transitions. In previous research papers, DSC profiles from blood samples of patients were analyzed and they exhibited marked differences in the thermal denaturation profile. Thus, we investigated the use of this novel technology in blood serum samples from 25 healthy subjects and 30 patients with gastric adenocarcinoma (GAC) at different stages of tumor development with a new multiparametric approach. The analysis of the calorimetric profiles of blood serum from GAC patients allowed us to discriminate three stages of cancer development (I to III) from those of healthy individuals. After a multiparametric analysis, a classification of blood serum DSC parameters from patients with GAC is proposed. Certain parameters exhibited significant differences (P < 0.05) and allowed the discrimination of healthy subjects/patients from patients at different tumor stages. The results of this work validate DSC as a novel technique for GAC patient classification and staging and offer new graphical tools and value ranges for the acquired parameters in order to discriminate healthy from diseased subjects with increased disease burden.