Cargando…
Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing
BACKGROUND: Investigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma sam...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7336456/ https://www.ncbi.nlm.nih.gov/pubmed/32631448 http://dx.doi.org/10.1186/s13059-020-02045-9 |
_version_ | 1783554323835256832 |
---|---|
author | Ramesh, Naveen Sei, Emi Tsai, Pei Ching Bai, Shanshan Zhao, Yuehui Troncoso, Patricia Corn, Paul G. Logothetis, Christopher Zurita, Amado J. Navin, Nicholas E. |
author_facet | Ramesh, Naveen Sei, Emi Tsai, Pei Ching Bai, Shanshan Zhao, Yuehui Troncoso, Patricia Corn, Paul G. Logothetis, Christopher Zurita, Amado J. Navin, Nicholas E. |
author_sort | Ramesh, Naveen |
collection | PubMed |
description | BACKGROUND: Investigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma samples. This approach is applied to study longitudinal blood plasma samples from prostate cancer patients, where longitudinal tissue biopsies from the bone and other metastatic sites have been challenging to collect. RESULTS: A molecular characterization of archival plasma DNA from 233 patients and genomic profiling of 101 patients identifies clinical correlations of aneuploid plasma DNA profiles with poor survival, increased plasma DNA concentrations, and lower plasma DNA size distributions. Deep-exome sequencing and genomic copy number profiling are performed on 23 patients, including 9 patients with matched metastatic tissues and 12 patients with serial plasma samples. These data show a high concordance in genomic alterations between the plasma DNA and metastatic tissue samples, suggesting the plasma DNA is highly representative of the tissue alterations. Longitudinal sequencing of 12 patients with 2–5 serial plasma samples reveals clonal dynamics and genome evolution in response to hormonal and chemotherapy. By performing an integrated evolutionary analysis, minor subclones are identified in 9 patients that expanded in response to therapy and harbored mutations associated with resistance. CONCLUSIONS: This study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer. |
format | Online Article Text |
id | pubmed-7336456 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-73364562020-07-08 Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing Ramesh, Naveen Sei, Emi Tsai, Pei Ching Bai, Shanshan Zhao, Yuehui Troncoso, Patricia Corn, Paul G. Logothetis, Christopher Zurita, Amado J. Navin, Nicholas E. Genome Biol Research BACKGROUND: Investigating genome evolution in response to therapy is difficult in human tissue samples. To address this challenge, we develop an unbiased whole-genome plasma DNA sequencing approach that concurrently measures genomic copy number and exome mutations from archival cryostored plasma samples. This approach is applied to study longitudinal blood plasma samples from prostate cancer patients, where longitudinal tissue biopsies from the bone and other metastatic sites have been challenging to collect. RESULTS: A molecular characterization of archival plasma DNA from 233 patients and genomic profiling of 101 patients identifies clinical correlations of aneuploid plasma DNA profiles with poor survival, increased plasma DNA concentrations, and lower plasma DNA size distributions. Deep-exome sequencing and genomic copy number profiling are performed on 23 patients, including 9 patients with matched metastatic tissues and 12 patients with serial plasma samples. These data show a high concordance in genomic alterations between the plasma DNA and metastatic tissue samples, suggesting the plasma DNA is highly representative of the tissue alterations. Longitudinal sequencing of 12 patients with 2–5 serial plasma samples reveals clonal dynamics and genome evolution in response to hormonal and chemotherapy. By performing an integrated evolutionary analysis, minor subclones are identified in 9 patients that expanded in response to therapy and harbored mutations associated with resistance. CONCLUSIONS: This study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer. BioMed Central 2020-07-06 /pmc/articles/PMC7336456/ /pubmed/32631448 http://dx.doi.org/10.1186/s13059-020-02045-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Ramesh, Naveen Sei, Emi Tsai, Pei Ching Bai, Shanshan Zhao, Yuehui Troncoso, Patricia Corn, Paul G. Logothetis, Christopher Zurita, Amado J. Navin, Nicholas E. Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
title | Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
title_full | Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
title_fullStr | Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
title_full_unstemmed | Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
title_short | Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
title_sort | decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7336456/ https://www.ncbi.nlm.nih.gov/pubmed/32631448 http://dx.doi.org/10.1186/s13059-020-02045-9 |
work_keys_str_mv | AT rameshnaveen decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT seiemi decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT tsaipeiching decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT baishanshan decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT zhaoyuehui decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT troncosopatricia decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT cornpaulg decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT logothetischristopher decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT zuritaamadoj decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing AT navinnicholase decodingtheevolutionaryresponsetoprostatecancertherapybyplasmagenomesequencing |