BUSCADOR RECOLECTA

The rapid diagnosis of cancer, especially in its early stages, is crucial for on-time medical treatment and for increasing the patient survival rate. Lung cancer shows the highest mortality rate and the lowest 5-year survival rate due to the late diagnosis in advanced cancer stages. Providing rapid and reliable diagnostic tools is a top priority to address the problem of a delayed cancer diagnosis. We introduce a nanophotonic biosensor for the direct and real-time detection in human plasma of the microRNA-21-5p biomarker related to lung cancer. The biosensor employs a silicon photonic bimodal interferometric waveguide that provides a highly sensitive detection in a label-free format. We demonstrate a very competitive detectability for direct microRNA-21-5p biomarker assays in human plasma samples (estimated LOD: 25 pM). The diagnostic capability of our biosensor was validated by analyzing 40 clinical samples from healthy individuals and lung cancer patients, previously analyzed by reverse-transcription quantitative polymerase chain reaction (qRT-PCR). We could successfully identify and quantify the levels of microRNA in a one-step assay, without the need for DNA extraction or amplification steps. The study confirmed the significance of implementing this biosensor technique compared to the benchmarking molecular analysis and showed excellent agreement with previous results employing the traditional qRT-PCR. This work opens new possibilities for the true implementation of point-of-care biosensors that enable fast, simple, and efficient early diagnosis of cancer diseases.

The rapid diagnosis of cancer, especially in its early stages, is crucial for on-time medical treatment and for increasing the patient survival rate. Lung cancer shows the highest mortality rate and the lowest 5-year survival rate due to the late diagnosis in advanced cancer stages. Providing rapid and reliable diagnostic tools is a top priority to address the problem of a delayed cancer diagnosis. We introduce a nanophotonic biosensor for the direct and real-time detection in human plasma of the microRNA-21-5p biomarker related to lung cancer. The biosensor employs a silicon photonic bimodal interferometric waveguide that provides a highly sensitive detection in a label-free format. We demonstrate a very competitive detectability for direct microRNA-21-5p biomarker assays in human plasma samples (estimated LOD: 25 pM). The diagnostic capability of our biosensor was validated by analyzing 40 clinical samples from healthy individuals and lung cancer patients, previously analyzed by reverse-transcription quantitative polymerase chain reaction (qRT-PCR). We could successfully identify and quantify the levels of microRNA in a one-step assay, without the need for DNA extraction or amplification steps. The study confirmed the significance of implementing this biosensor technique compared to the benchmarking molecular analysis and showed excellent agreement with previous results employing the traditional qRT-PCR. This work opens new possibilities for the true implementation of point-of-care biosensors that enable fast, simple, and efficient early diagnosis of cancer diseases., The ICN2 acknowledges the financial support from the Spanish Research Agency (AEI), Ministry of Science, Innovation, and Universities through the PREDICT (TEC2016-78515-R) and EROICA PID2019-105132RB-I00) projects. ICN2 is funded by the CERCA Program/Generalitat de Catalunya and supported by the Severo Ochoa Centres of Excellence program funded by the Spanish Research Agency (AEI, grant no. SEV-2017-0706). O.C-L. acknowledges the economic support from the Spanish Ministry of Science and Innovation and the Spanish Research Agency and the European Social Fund (ESF) (ref. BES-2017-080527) linked to the PREDICT project. Research Center for Functional Genomics, Biomedicine and Translational Medicine acknowledges “Clinical and economic impact of personalized targeted anti-microRNA therapies in reconverting lung cancer chemoresistance”, CANTEMIR, no. POC-P_37_796/2016. This work was supported by the FLAG-ERA grant LEGOCHIP, funded by the Italian National Research Council and the Spanish National Research Agency (PCI2019-111890-2)., Peer reviewed