ArticleGenome biology2020
Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing.
Article in Genome biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- Longitudinal Profiling of Circulating Tumor DNA Reveals the Evolutionary Dynamics of Metastatic Prostate Cancer during Serial Therapy.Cancer research · 2025Article
- Apolipoprotein E promotes primary resistance to AR-targeted therapy via inducing TRIM25-mediated AR ubiquitination and sensitizes immunotherapy in prostate cancer.Theranostics · 2025Article
- cfSNV: a software tool for the sensitive detection of somatic mutations from cell-free DNA.Nature protocols · 2023Review
- Urinary DNA as a Tool for Germline and Somatic Mutation Detection in Castration-Resistant Prostate Cancer Patients.Biomedicines · 2023Article
- Genomic Profiling of Prostate Cancer: An Updated Review.The world journal of men's health · 2022Review
- NucPosDB: a database of nucleosome positioning in vivo and nucleosomics of cell-free DNA.Chromosoma · 2022Article
- cfTrack: A Method of Exome-Wide Mutation Analysis of Cell-free DNA to Simultaneously Monitor the Full Spectrum of Cancer Treatment Outcomes Including MRD, Recurrence, and Evolution.Clinical cancer research : an official journal of the American Association for Cancer Research · 2022Article
- Use of apps in the COVID-19 response and the loss of privacy protection.Nature medicine · 2020Article
- Decoding the evolutionary response to prostate cancer therapy by plasma genome sequencing.Genome biology · 2020Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundInvestigating 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.
resultsA 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.
conclusionsThis study provides an unbiased evolutionary approach to non-invasively delineate clonal dynamics and identify clones with mutations associated with resistance in prostate cancer.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.