![]() A gene expression signature from peripheral whole blood for stage I lung adenocarcinoma. ![]() ![]() Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. We envision that this DNA computational platform will inspire more clinical applications towards inexpensive, non-invasive and rapid disease screening, classification and progress monitoring.Īllemani, C. 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%. 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. A computational classifier is first trained in silico using miRNA profiles from The Cancer Genome Atlas. Here, we designed a DNA molecular computation platform for the analysis of miRNA profiles in clinical serum samples. Recent work has revealed that the levels of multiple microRNAs in serum are informative as biomarkers for the diagnosis of cancers. Early and precise cancer diagnosis substantially improves patient survival.
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