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Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer

BACKGROUND: Prostate cancer (PCa) is among the leading causes of cancer mortality. Dicycloplatin is a newer generation platinum-based drug that has less side effects than cisplatin and carboplatin. However, its effects in PCa is mixed due to lack of appropriate stratifying biomarkers. Aiming to sear...

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Autores principales: Liu, Minglu, Zhou, Xiaoyu, Liu, Jun, Lu, Chelong, Zhang, Guoqing, Zhang, Jing, Jiao, Shunchang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353331/
https://www.ncbi.nlm.nih.gov/pubmed/34386035
http://dx.doi.org/10.3389/fgene.2021.669605
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author Liu, Minglu
Zhou, Xiaoyu
Liu, Jun
Lu, Chelong
Zhang, Guoqing
Zhang, Jing
Jiao, Shunchang
author_facet Liu, Minglu
Zhou, Xiaoyu
Liu, Jun
Lu, Chelong
Zhang, Guoqing
Zhang, Jing
Jiao, Shunchang
author_sort Liu, Minglu
collection PubMed
description BACKGROUND: Prostate cancer (PCa) is among the leading causes of cancer mortality. Dicycloplatin is a newer generation platinum-based drug that has less side effects than cisplatin and carboplatin. However, its effects in PCa is mixed due to lack of appropriate stratifying biomarkers. Aiming to search for such biomarkers, here, we analyze a group of PCa patients with different responses to dicycloplatin. METHODS: We carried out whole-exome sequencing on cell-free DNA (cfDNA) and matched leukocyte DNA from 16 PCa patients before treatment with dicycloplatin. We then compared the clinical characteristics, somatic mutations, copy number variants (CNVs), and mutational signatures between the dicycloplatin-sensitive (nine patients) and dicycloplatin-resistant (seven patients) groups and tested the identified mutations, CNV, and their combinations as marker of dicycloplatin response. RESULTS: The mutation frequency of seven genes (SP8, HNRNPCL1, FRG1, RBM25, MUC16, ASTE1, and TMBIM4) and CNV rate of four genes (CTAGE4, GAGE2E, GAGE2C, and HORMAD1) were higher in the resistant group than in the sensitive group, while the CNV rate in six genes (CDSN, DPCR1, MUC22, TMSB4Y, VARS, and HISTCH2AC) were lower in the resistant group than in the sensitive group. A combination of simultaneous mutation in two genes (SP8/HNRNPCL1 or SP8/FRG1) and deletion of GAGE2C together were found capable to predict dicycloplatin resistance with 100% sensitivity and 100% specificity. CONCLUSION: We successfully used cfDNA to monitor mutational profiles of PCa and designed an effective composite marker to select patients for dicycloplatin treatment based on their mutational profile.
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spelling pubmed-83533312021-08-11 Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer Liu, Minglu Zhou, Xiaoyu Liu, Jun Lu, Chelong Zhang, Guoqing Zhang, Jing Jiao, Shunchang Front Genet Genetics BACKGROUND: Prostate cancer (PCa) is among the leading causes of cancer mortality. Dicycloplatin is a newer generation platinum-based drug that has less side effects than cisplatin and carboplatin. However, its effects in PCa is mixed due to lack of appropriate stratifying biomarkers. Aiming to search for such biomarkers, here, we analyze a group of PCa patients with different responses to dicycloplatin. METHODS: We carried out whole-exome sequencing on cell-free DNA (cfDNA) and matched leukocyte DNA from 16 PCa patients before treatment with dicycloplatin. We then compared the clinical characteristics, somatic mutations, copy number variants (CNVs), and mutational signatures between the dicycloplatin-sensitive (nine patients) and dicycloplatin-resistant (seven patients) groups and tested the identified mutations, CNV, and their combinations as marker of dicycloplatin response. RESULTS: The mutation frequency of seven genes (SP8, HNRNPCL1, FRG1, RBM25, MUC16, ASTE1, and TMBIM4) and CNV rate of four genes (CTAGE4, GAGE2E, GAGE2C, and HORMAD1) were higher in the resistant group than in the sensitive group, while the CNV rate in six genes (CDSN, DPCR1, MUC22, TMSB4Y, VARS, and HISTCH2AC) were lower in the resistant group than in the sensitive group. A combination of simultaneous mutation in two genes (SP8/HNRNPCL1 or SP8/FRG1) and deletion of GAGE2C together were found capable to predict dicycloplatin resistance with 100% sensitivity and 100% specificity. CONCLUSION: We successfully used cfDNA to monitor mutational profiles of PCa and designed an effective composite marker to select patients for dicycloplatin treatment based on their mutational profile. Frontiers Media S.A. 2021-07-27 /pmc/articles/PMC8353331/ /pubmed/34386035 http://dx.doi.org/10.3389/fgene.2021.669605 Text en Copyright © 2021 Liu, Zhou, Liu, Lu, Zhang, Zhang and Jiao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Liu, Minglu
Zhou, Xiaoyu
Liu, Jun
Lu, Chelong
Zhang, Guoqing
Zhang, Jing
Jiao, Shunchang
Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer
title Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer
title_full Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer
title_fullStr Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer
title_full_unstemmed Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer
title_short Predictive Biomarkers of Dicycloplatin Resistance or Susceptibility in Prostate Cancer
title_sort predictive biomarkers of dicycloplatin resistance or susceptibility in prostate cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8353331/
https://www.ncbi.nlm.nih.gov/pubmed/34386035
http://dx.doi.org/10.3389/fgene.2021.669605
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