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Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas
Glioblastoma is a highly aggressive brain malignancy with a poor prognosis. Its high intratumor heterogeneity contributes to therapeutic resistance, tumor progression and recurrence. We sequenced 31 loci in 11 patients with glioblastoma (including one patient with samples available from the primary...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932900/ https://www.ncbi.nlm.nih.gov/pubmed/31822636 http://dx.doi.org/10.18632/aging.102526 |
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author | Yang, Chao Tan, Yanli Li, Shouwei Zhou, Junhu Wang, Qixue Wang, Yunfei Xie, Yingbin Chen, Luyue Li, Jie Fang, Chuan Kang, Chunsheng |
author_facet | Yang, Chao Tan, Yanli Li, Shouwei Zhou, Junhu Wang, Qixue Wang, Yunfei Xie, Yingbin Chen, Luyue Li, Jie Fang, Chuan Kang, Chunsheng |
author_sort | Yang, Chao |
collection | PubMed |
description | Glioblastoma is a highly aggressive brain malignancy with a poor prognosis. Its high intratumor heterogeneity contributes to therapeutic resistance, tumor progression and recurrence. We sequenced 31 loci in 11 patients with glioblastoma (including one patient with samples available from the primary and recurrent tumors) to determine the genetic basis and intratumor heterogeneity of glioblastoma. By analyzing the somatic mutations, known driver genes were identified, including EGFR, PTEN and TP53, and the MUC16 gene exhibited the highest mutation rate in the samples examined. Through an evolutionary analysis of the sequencing results, the EGFR p.L861Q mutation was determined to play a role in the progression from the primary tumor to a relapsing tumor in one patient. We analyzed 1403 genes in blood-derived ctDNA that were previously revealed to play a role in tumorigenesis and the progression of cancer. Somatic mutations identified through ctDNA sequencing that match the results of multipoint exon sequencing in tumor tissues were detected, such as EGFR p.L861Q. These findings provide new insights into the intratumor heterogeneity and evolution of glioblastoma. In addition, ctDNA detection in blood samples represents a convenient method to dynamically identify the genetic changes and new therapeutic targets during the treatment of glioblastoma. |
format | Online Article Text |
id | pubmed-6932900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-69329002020-01-03 Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas Yang, Chao Tan, Yanli Li, Shouwei Zhou, Junhu Wang, Qixue Wang, Yunfei Xie, Yingbin Chen, Luyue Li, Jie Fang, Chuan Kang, Chunsheng Aging (Albany NY) Research Paper Glioblastoma is a highly aggressive brain malignancy with a poor prognosis. Its high intratumor heterogeneity contributes to therapeutic resistance, tumor progression and recurrence. We sequenced 31 loci in 11 patients with glioblastoma (including one patient with samples available from the primary and recurrent tumors) to determine the genetic basis and intratumor heterogeneity of glioblastoma. By analyzing the somatic mutations, known driver genes were identified, including EGFR, PTEN and TP53, and the MUC16 gene exhibited the highest mutation rate in the samples examined. Through an evolutionary analysis of the sequencing results, the EGFR p.L861Q mutation was determined to play a role in the progression from the primary tumor to a relapsing tumor in one patient. We analyzed 1403 genes in blood-derived ctDNA that were previously revealed to play a role in tumorigenesis and the progression of cancer. Somatic mutations identified through ctDNA sequencing that match the results of multipoint exon sequencing in tumor tissues were detected, such as EGFR p.L861Q. These findings provide new insights into the intratumor heterogeneity and evolution of glioblastoma. In addition, ctDNA detection in blood samples represents a convenient method to dynamically identify the genetic changes and new therapeutic targets during the treatment of glioblastoma. Impact Journals 2019-12-10 /pmc/articles/PMC6932900/ /pubmed/31822636 http://dx.doi.org/10.18632/aging.102526 Text en Copyright © 2019 Yang et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Yang, Chao Tan, Yanli Li, Shouwei Zhou, Junhu Wang, Qixue Wang, Yunfei Xie, Yingbin Chen, Luyue Li, Jie Fang, Chuan Kang, Chunsheng Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas |
title | Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas |
title_full | Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas |
title_fullStr | Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas |
title_full_unstemmed | Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas |
title_short | Genomic landscapes by multiregion sequencing combined with circulation tumor DNA detection contribute to molecular diagnosis in glioblastomas |
title_sort | genomic landscapes by multiregion sequencing combined with circulation tumor dna detection contribute to molecular diagnosis in glioblastomas |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6932900/ https://www.ncbi.nlm.nih.gov/pubmed/31822636 http://dx.doi.org/10.18632/aging.102526 |
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