Item request has been placed!
×
Item request cannot be made.
×
![loading](/sites/all/modules/hf_eds/images/loading.gif)
Processing Request
MIMESIS: minimal DNA-methylation signatures to quantify and classify tumor signals in tissue and cell-free DNA samples.
Item request has been placed!
×
Item request cannot be made.
×
![loading](/sites/all/modules/hf_eds/images/loading.gif)
Processing Request
- المؤلفون: Romagnoli, Dario1 (AUTHOR); Nardone, Agostina2 (AUTHOR); Galardi, Francesca2 (AUTHOR); Paoli, Marta1,3 (AUTHOR); Luca, Francesca De2 (AUTHOR); Biagioni, Chiara1,4 (AUTHOR); Franceschini, Gian Marco3 (AUTHOR); Pestrin, Marta5 (AUTHOR); Sanna, Giuseppina6 (AUTHOR); Moretti, Erica4 (AUTHOR); Demichelis, Francesca3,7 (AUTHOR); Migliaccio, Ilenia2 (AUTHOR); Biganzoli, Laura4 (AUTHOR); Malorni, Luca2,4 (AUTHOR); Benelli, Matteo1,4 (AUTHOR)
- المصدر:
Briefings in Bioinformatics. Mar2023, Vol. 24 Issue 2, p1-13. 13p.
- الموضوع:
- معلومة اضافية
- نبذة مختصرة :
DNA-methylation alterations are common in cancer and display unique characteristics that make them ideal markers for tumor quantification and classification. Here we present MIMESIS, a computational framework exploiting minimal DNA-methylation signatures composed by a few dozen informative DNA-methylation sites to quantify and classify tumor signals in tissue and cell-free DNA samples. Extensive analyses of multiple independent and heterogenous datasets including >7200 samples demonstrate the capability of MIMESIS to provide precise estimations of tumor content and to enable accurate classification of tumor type and molecular subtype. To assess our framework for clinical applications, we designed a MIMESIS-informed assay incorporating the minimal signatures for breast cancer. Using both artificial samples and clinical serial cell-free DNA samples from patients with metastatic breast cancer, we show that our approach provides accurate estimations of tumor content, sensitive detection of tumor signal and the ability to capture clinically relevant molecular subtype in patients' circulation. This study provides evidence that our extremely parsimonious approach can be used to develop cost-effective and highly scalable DNA-methylation assays that could support and facilitate the implementation of precision oncology in clinical practice. [ABSTRACT FROM AUTHOR]
- نبذة مختصرة :
Copyright of Briefings in Bioinformatics is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
No Comments.