Competitive learning suggests circulating miRNA profiles for cancers decades prior to diagnosis
| Autor: | Trine B. Rounge, Fabian Kern, Andreas Keller, Eckart Meese, Tobias Fehlmann, Nicole Ludwig, Christina Backes, Hilde Langseth, Randi Elin Gislefoss |
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| Rok vydání: | 2020 |
| Předmět: |
Oncology
medicine.medical_specialty Colorectal cancer Population Biology Bioinformatics 03 medical and health sciences 0302 clinical medicine Breast cancer Artificial Intelligence Neoplasms Internal medicine microRNA Biomarkers Tumor Humans Medicine Circulating MicroRNA Liquid biopsy Lung cancer education Molecular Biology Gene Early Detection of Cancer 030304 developmental biology 0303 health sciences education.field_of_study Lung business.industry Liquid Biopsy Computational Biology Cancer Cell Biology Non-coding RNA medicine.disease MicroRNAs medicine.anatomical_structure 030220 oncology & carcinogenesis Analysis of variance business Research Paper Blood drawing |
| Zdroj: | RNA Biol |
| DOI: | 10.1101/2020.03.26.009597 |
| Popis: | Small non-coding RNAs such as microRNAs are master regulators of gene expression. One of the most promising applications of miRNAs is the use as liquid biopsy. Especially early diagnosis is an effective means to increase patients’ overall survival. E.g. in oncology a tumor is detected at best prior to its clinical manifestation. We generated genome-wide miRNA profiles from serum of patients and controls from the population-based Janus Serum Bank (JSB) and analyzed them by bioinformatics and artificial intelligence approaches. JSB contains sera from 318,628 originally healthy persons, more than 96,000 of whom later developed cancer. We selected 210 serum samples of patients with lung, colon or breast cancer at three time points prior to diagnosis, after cancer diagnosis and controls. The controls were matched with regard to age of the blood donor and to the time points of blood drawing, which were 27, 32, or 38 years prior to diagnosis. Using ANOVA we report 70 significantly deregulated markers (adjusted p-value−10). Further, 91miRNAs were differently expressed in pre-diagnostic samples as compared to controls (nominal p |
| Databáze: | OpenAIRE |
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