Cancer diagnosis with DNA molecular computation
Menée à l'aide d'échantillons sériques et à partir de données de séquençage de microARNs du projet "The Cancer Genome Atlas" portant sur 900 patients atteints d'un cancer du poumon non à petites cellules et 90 témoins sains, cette étude évalue la performance d'un système de classification informatisé, basé sur l'analyse de l'ADN moléculaire issu de l'amplification de microARNs sériques, pour diagnostiquer une tumeur
Early and precise cancer diagnosis substantially improves patient survival. Recent work has revealed that the levels of multiple microRNAs in serum are informative as biomarkers for the diagnosis of cancers. Here, we designed a DNA molecular computation platform for the analysis of miRNA profiles in clinical serum samples. A computational classifier is first trained in silico using miRNA profiles from The Cancer Genome Atlas. This is followed by a computationally powerful but simple molecular implementation scheme using DNA, as well as an effective in situ amplification and transformation method for miRNA enrichment in serum without perturbing the original variety and quantity information. We successfully achieved rapid and accurate cancer diagnosis using clinical serum samples from 22 healthy people (8) and people with lung cancer (14) with an accuracy of 86.4%. We envision that this DNA computational platform will inspire more clinical applications towards inexpensive, non-invasive and rapid disease screening, classification and progress monitoring.
Nature Nanotechnology , résumé, 2020