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Differential presence of exons (DPE): sequencing liquid biopsy by NGS. A new method for clustering colorectal Cancer patients.
Rubio-Mangas, David; García-Arranz, Mariano; Torres-Rodriguez, Yaima; León-Arellano, Miguel; Suela, Javier; García-Olmo, Damián.
Afiliação
  • Rubio-Mangas D; Genómica y Medicina, NIMGenetics, Madrid, Spain. S. L, 28108, Madrid, Spain. drubio@nimgenetics.com.
  • García-Arranz M; New Therapy Laboratory, Instituto de Investigación Sanitaria Fundación Jiménez Díaz, 28040, Madrid, Spain.
  • Torres-Rodriguez Y; Department of Surgery, School of Medicine, Universidad Autónoma de Madrid, C. Arzobispo Morcillo, 4, 28029, Madrid, Spain.
  • León-Arellano M; Genómica y Medicina, NIMGenetics, Madrid, Spain. S. L, 28108, Madrid, Spain.
  • Suela J; Department of Surgery, Hospital Fundación Jiménez Díaz, 28040, Madrid, Spain.
  • García-Olmo D; Genómica y Medicina, NIMGenetics, Madrid, Spain. S. L, 28108, Madrid, Spain. jsuela@nimgenetics.com.
BMC Cancer ; 23(1): 2, 2023 Jan 03.
Article em En | MEDLINE | ID: mdl-36593457
Differential presence of exons (DPE) by next generation sequencing (NGS) is a method of interpretation of whole exome sequencing. This method has been proposed to design a predictive and diagnostic algorithm with clinical value in plasma from patients bearing colorectal cancer (CRC). The aim of the present study was to determine a common exonic signature to discriminate between different clinical pictures, such as non-metastatic, metastatic and non-disease (healthy), using a sustainable and novel technology in liquid biopsy.Through DPE analysis, we determined the differences in DNA exon levels circulating in plasma between patients bearing CRC vs. healthy, patients bearing CRC metastasis vs. non-metastatic and patients bearing CRC metastasis vs. healthy comparisons. We identified a set of 510 exons (469 up and 41 down) whose differential presence in plasma allowed us to group and classify between the three cohorts. Random forest classification (machine learning) was performed and an estimated out-of-bag (OOB) error rate of 35.9% was obtained and the predictive model had an accuracy of 75% with a confidence interval (CI) of 56.6-88.5.In conclusion, the DPE analysis allowed us to discriminate between different patho-physiological status such as metastatic, non-metastatic and healthy donors. In addition, this analysis allowed us to obtain very significant values with respect to previous published results, since we increased the number of samples in our study. These results suggest that circulating DNA in patient's plasma may be actively released by cells and may be involved in intercellular communication and, therefore, may play a pivotal role in malignant transformation (genometastasis).
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Ácidos Nucleicos Livres Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: BMC Cancer Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Ácidos Nucleicos Livres Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: BMC Cancer Ano de publicação: 2023 Tipo de documento: Article