Paper-based biosensors for cancer diagnostics

Supplemental information associated with this article can be found online: https://doi.org/10.1016/j.trechm.2022.03.005
The implementation of a wide diagnostic campaign to diagnose cancer early could save millions of lives and billions of dollars every year. Unfortunately, cancer diagnosis is extremely complicated and current approaches rely on the use of expensive equipment and specialized personnel, which hamper their deployment in low- and middle-income settings. Here, we analyze the technical challenges that must be overcome to achieve precise cancer diagnostics and we describe how such hurdles have limited the development of point-of-care (PoC) sensors. Then, we explain why we believe recent achievements in the field of paper-based sensors could allow their use as widely available sensing platforms for cancer detection. Finally, we present our vision of what should be done in order to make paper-based sensors widely used diagnostics platforms for cancer.
We acknowledge Agencia Estatal de Investigación (AEI) and Fondo Europeo de Desarrollo Regional (FEDER) for the project MAT2017-87202-P and through the Severo Ochoa Centres of Excellence Program under Grant SEV2201320295. This work is also funded by the CERCA Program/Generalitat de Catalunya. C. Pa. acknowledges support from the Spanish Ministry of Science and Innovation and State Research Agency through the “Centro de Excelencia Severo Ochoa 2019-2023” Program (CEX2018-000806-S). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2020 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. C.Pe. was recipient of a fellowship supported by a doctoral advanced training (call NORTE-69-2015-15) funded by the European Social Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. A.I. was supported by PROBIST postdoctoral fellowship funded by the European Research Council (Marie Skłodowska-Curie grant agreement no. 754510.
info:eu-repo/semantics/publishedVersion