Nascent Prostate Cancer Heterogeneity Drives Evolution and Resistance to Intense Hormonal Therapy.
Androgen deprivation therapy
Diversity
Enzalutamide
Evolution
Genomics
Immunohistochemistry
Neoadjuvant
Prostate cancer
Journal
European urology
ISSN: 1873-7560
Titre abrégé: Eur Urol
Pays: Switzerland
ID NLM: 7512719
Informations de publication
Date de publication:
Dec 2021
Dec 2021
Historique:
received:
09
10
2020
accepted:
11
03
2021
pubmed:
1
4
2021
medline:
19
4
2022
entrez:
31
3
2021
Statut:
ppublish
Résumé
Patients diagnosed with high risk localized prostate cancer have variable outcomes following surgery. Trials of intense neoadjuvant androgen deprivation therapy (NADT) have shown lower rates of recurrence among patients with minimal residual disease after treatment. The molecular features that distinguish exceptional responders from poor responders are not known. To identify genomic and histologic features associated with treatment resistance at baseline. Targeted biopsies were obtained from 37 men with intermediate- to high-risk prostate cancer before receiving 6 mo of ADT plus enzalutamide. Biopsy tissues were used for whole-exome sequencing and immunohistochemistry (IHC). We assessed the relationship of molecular features with final pathologic response using a cutpoint of 0.05 cm Loss of chromosome 10q (containing PTEN) and alterations to TP53 were predictive of poor response, as were the expression of nuclear ERG on IHC and the presence of intraductal carcinoma of the prostate. Patients with incompletely and nonresponding tumors harbored greater tumor diversity as estimated via phylogenetic tree reconstruction from DNA sequencing and analysis of IHC staining. Our four-factor binary model (area under the receiver operating characteristic curve [AUC] 0.89) to predict poor response correlated with greater diversity in our cohort and a validation cohort of 57 Gleason score 8-10 prostate cancers from The Cancer Genome Atlas. When baseline tumor volume was added to the model, it distinguished poor response to NADT with an AUC of 0.98. Prospective use of this model requires further retrospective validation with biopsies from additional trials. A subset of prostate cancers exhibit greater histologic and genomic diversity at the time of diagnosis, and these localized tumors have greater fitness to resist therapy. Some prostate cancer tumors do not respond well to a hormonal treatment called androgen deprivation therapy (ADT). We used tumor volume and four other parameters to develop a model to identify tumors that will not respond well to ADT. Treatments other than ADT should be considered for these patients.
Sections du résumé
BACKGROUND
BACKGROUND
Patients diagnosed with high risk localized prostate cancer have variable outcomes following surgery. Trials of intense neoadjuvant androgen deprivation therapy (NADT) have shown lower rates of recurrence among patients with minimal residual disease after treatment. The molecular features that distinguish exceptional responders from poor responders are not known.
OBJECTIVE
OBJECTIVE
To identify genomic and histologic features associated with treatment resistance at baseline.
DESIGN, SETTING, AND PARTICIPANTS
METHODS
Targeted biopsies were obtained from 37 men with intermediate- to high-risk prostate cancer before receiving 6 mo of ADT plus enzalutamide. Biopsy tissues were used for whole-exome sequencing and immunohistochemistry (IHC).
OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS
METHODS
We assessed the relationship of molecular features with final pathologic response using a cutpoint of 0.05 cm
RESULTS AND LIMITATIONS
CONCLUSIONS
Loss of chromosome 10q (containing PTEN) and alterations to TP53 were predictive of poor response, as were the expression of nuclear ERG on IHC and the presence of intraductal carcinoma of the prostate. Patients with incompletely and nonresponding tumors harbored greater tumor diversity as estimated via phylogenetic tree reconstruction from DNA sequencing and analysis of IHC staining. Our four-factor binary model (area under the receiver operating characteristic curve [AUC] 0.89) to predict poor response correlated with greater diversity in our cohort and a validation cohort of 57 Gleason score 8-10 prostate cancers from The Cancer Genome Atlas. When baseline tumor volume was added to the model, it distinguished poor response to NADT with an AUC of 0.98. Prospective use of this model requires further retrospective validation with biopsies from additional trials.
CONCLUSIONS
CONCLUSIONS
A subset of prostate cancers exhibit greater histologic and genomic diversity at the time of diagnosis, and these localized tumors have greater fitness to resist therapy.
PATIENT SUMMARY
RESULTS
Some prostate cancer tumors do not respond well to a hormonal treatment called androgen deprivation therapy (ADT). We used tumor volume and four other parameters to develop a model to identify tumors that will not respond well to ADT. Treatments other than ADT should be considered for these patients.
Identifiants
pubmed: 33785256
pii: S0302-2838(21)00207-4
doi: 10.1016/j.eururo.2021.03.009
pmc: PMC8473585
mid: NIHMS1684972
pii:
doi:
Substances chimiques
Androgen Antagonists
0
Androgens
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, N.I.H., Intramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
746-757Subventions
Organisme : Intramural NIH HHS
ID : ZIA BC010666
Pays : United States
Organisme : CCR NIH HHS
ID : HHSN261200800001C
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIA BC011838
Pays : United States
Organisme : Intramural NIH HHS
ID : Z99 CA999999
Pays : United States
Organisme : NCI NIH HHS
ID : HHSN261200800001E
Pays : United States
Organisme : Intramural NIH HHS
ID : ZIA BC011679
Pays : United States
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Informations de copyright
Published by Elsevier B.V.
Références
J Clin Oncol. 2019 Apr 10;37(11):923-931
pubmed: 30811282
J Urol. 2021 Jun;205(6):1689-1697
pubmed: 33502237
Cancer Cell. 2010 Jul 13;18(1):11-22
pubmed: 20579941
Cancer Res. 2018 Aug 15;78(16):4716-4730
pubmed: 29921690
Eur Urol. 2019 Dec;76(6):719-728
pubmed: 31447077
Nature. 2015 Apr 16;520(7547):353-357
pubmed: 25830880
Nat Rev Urol. 2021 Feb;18(2):79-92
pubmed: 33328650
Eur Urol Oncol. 2021 Jun;4(3):370-395
pubmed: 33272865
Lancet Oncol. 2019 May;20(5):686-700
pubmed: 30987939
Cell. 2013 Apr 25;153(3):666-77
pubmed: 23622249
Eur Urol. 2014 Nov;66(5):799-802
pubmed: 24985962
Nat Med. 2016 Mar;22(3):298-305
pubmed: 26855148
Nat Genet. 2018 May;50(5):645-651
pubmed: 29610475
Clin Cancer Res. 2017 May 1;23(9):2169-2176
pubmed: 28151719
Cell. 2015 Nov 5;163(4):1011-25
pubmed: 26544944
Nat Commun. 2020 Feb 13;11(1):837
pubmed: 32054861
Curr Opin Urol. 2016 May;26(3):219-24
pubmed: 26885716
Cell. 2015 May 21;161(5):1215-1228
pubmed: 26000489
Nature. 2020 Feb;578(7793):122-128
pubmed: 32025013
J Clin Oncol. 2014 Nov 20;32(33):3705-15
pubmed: 25311217
Cancer Res. 2013 Feb 1;73(3):1050-5
pubmed: 23204237
N Engl J Med. 2016 Oct 13;375(15):1415-1424
pubmed: 27626136
Clin Cancer Res. 2017 Jul 15;23(14):3823-3833
pubmed: 28119368
N Engl J Med. 2020 Sep 10;383(11):1040-1049
pubmed: 32905676
Cell. 2018 May 3;173(4):1003-1013.e15
pubmed: 29681457
Clin Cancer Res. 2015 Mar 15;21(6):1273-80
pubmed: 25320358
Clin Cancer Res. 2021 Jan 15;27(2):429-437
pubmed: 33023952
Cell. 2018 Apr 5;173(2):321-337.e10
pubmed: 29625050
Prostate. 2016 Sep;76(13):1227-36
pubmed: 27272561