Monreal-Trigo Javier, Alcañiz Miguel, Martínez-Bisbal M Carmen, Loras Alba, Pascual Lluís, Ruiz-Cerdá José Luis, Ferrer Alberto, Martínez-Máñez Ramón
Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico (IDM), Universitat Politècnica de València - Universitat de València, Camino de Vera, s/n, 46022 Valencia, Spain.
CIBER de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III, Madrid, Spain.
iScience. 2022 Aug 4;25(9):104829. doi: 10.1016/j.isci.2022.104829. eCollection 2022 Sep 16.
Bladder cancer (BC) is the sixth leading cause of death by cancer. Depending on the invasiveness of tumors, patients with BC will undergo surgery and surveillance lifelong, owing the high rate of recurrence and progression. In this context, the development of strategies to support non-invasive BC diagnosis is focusing attention. Voltammetric electronic tongue (VET) has been demonstrated to be of use in the analysis of biofluids. Here, we present the implementation of a VET to study 207 urines to discriminate BC and non-BC for diagnosis and surveillance to detect recurrences. Special attention has been paid to the experimental setup to improve reproducibility in the measurements. PLSDA analysis together with variable selection provided a model with high sensitivity, specificity, and area under the ROC curve AUC (0.844, 0.882, and 0.917, respectively). These results pave the way for the development of non-invasive low-cost and easy-to-use strategies to support BC diagnosis and follow-up.
膀胱癌（BC）是癌症导致死亡的第六大主要原因。根据肿瘤的侵袭性，膀胱癌患者将终身接受手术和监测，因为其复发和进展率很高。在这种情况下，支持非侵入性膀胱癌诊断策略的开发正受到关注。伏安电子舌（VET）已被证明可用于生物流体分析。在此，我们展示了一种伏安电子舌用于研究207份尿液样本，以鉴别膀胱癌和非膀胱癌，用于诊断和监测复发情况。我们特别关注实验设置，以提高测量的重现性。偏最小二乘判别分析（PLSDA）结合变量选择提供了一个具有高灵敏度、特异性和ROC曲线下面积（AUC）的模型（分别为0.844、0.882和0.917）。这些结果为开发支持膀胱癌诊断和随访的非侵入性低成本且易于使用的策略铺平了道路。
