A monolithic single-chip point-of-care platform for metabolomic prostate cancer detection
| Autor: | Rónán Daly, David R. S. Cumming, Thomas R. Jeffry Evans, Christos Giagkoulovits, David J. Clayton, Yash D. Shah, V. F. Annese, James Grant, Martin Macleod, Michael P. Barrett, James Beeley, Mohammed A. Al-Rawhani, Robert Jones, Liam M. Heaney, Samadhan B. Patil, Chunxiao Hu, Claudio Accarino, Boon Chong Cheah |
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| Rok vydání: | 2021 |
| Předmět: |
Single chip
Oncology medicine.medical_specialty Materials Science (miscellaneous) Diagnostic tools lcsh:Technology Industrial and Manufacturing Engineering Unmet needs 03 medical and health sciences Prostate cancer 0302 clinical medicine Metabolomics Microfluidic channel Internal medicine Medicine Electrical and Electronic Engineering 030304 developmental biology Point of care 0303 health sciences lcsh:T business.industry Condensed Matter Physics medicine.disease Atomic and Molecular Physics and Optics Biomarker (cell) lcsh:TA1-2040 030220 oncology & carcinogenesis lcsh:Engineering (General). Civil engineering (General) business |
| Zdroj: | Microsystems & Nanoengineering, Vol 7, Iss 1, Pp 1-15 (2021) |
| ISSN: | 2055-7434 2096-1030 |
| DOI: | 10.1038/s41378-021-00243-4 |
| Popis: | There is a global unmet need for rapid and cost-effective prognostic and diagnostic tools that can be used at the bedside or in the doctor’s office to reduce the impact of serious disease. Many cancers are diagnosed late, leading to costly treatment and reduced life expectancy. With prostate cancer, the absence of a reliable test has inhibited the adoption of screening programs. We report a microelectronic point-of-care metabolite biomarker measurement platform and use it for prostate cancer detection. The platform, using an array of photodetectors configured to operate with targeted, multiplexed, colorimetric assays confined in monolithically integrated passive microfluidic channels, completes a combined assay of 4 metabolites in a drop of human plasma in under 2 min. A preliminary clinical study using l-amino acids, glutamate, choline, and sarcosine was used to train a cross-validated random forest algorithm. The system demonstrated sensitivity to prostate cancer of 94% with a specificity of 70% and an area under the curve of 0.78. The technology can implement many similar assay panels and hence has the potential to revolutionize low-cost, rapid, point-of-care testing. |
| Databáze: | OpenAIRE |
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