Microbiome analyses of blood and tissues suggest cancer diagnostic approach
| العنوان: | Microbiome analyses of blood and tissues suggest cancer diagnostic approach |
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| المؤلفون: | Carolina S. Carpenter, Gregory D. Poore, Qiyun Zhu, Rana R. McKay, Stefan Janssen, Stephen Wandro, Austin D. Swafford, Serena Fraraccio, Jessica L. Metcalf, Evguenia Kopylova, Rob Knight, Se Jin Song, Sandrine Miller-Montgomery, Tomasz Kosciolek, Robert K. Heaton, Jad N. Kanbar, Sandip Pravin Patel |
| المصدر: | Nature. 579:567-574 |
| بيانات النشر: | Springer Science and Business Media LLC, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | 0301 basic medicine, Multidisciplinary, Melanoma, Case-control study, Cancer, Computational biology, Biology, medicine.disease, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, medicine.anatomical_structure, Prostate, 030220 oncology & carcinogenesis, medicine, Nucleic acid, Microbiome, Liquid biopsy, Stage (cooking) |
| الوصف: | Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1–10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration. Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach. |
| تدمد: | 1476-4687 0028-0836 |
| DOI: | 10.1038/s41586-020-2095-1 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::d0bfec9637dc5f250feed0f3c014c204 https://doi.org/10.1038/s41586-020-2095-1 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi...........d0bfec9637dc5f250feed0f3c014c204 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 14764687 00280836 |
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| DOI: | 10.1038/s41586-020-2095-1 |