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Transcriptomic Heterogeneity of Androgen Receptor Activity Defines a de novo low AR-Active Subclass in Treatment Naive Primary Prostate Cancer.

ABSTRACT: PURPOSE:The heterogeneity of androgen receptor (AR)-activity (AR-A) is well-characterized in heavily treated metastatic castration-resistant prostate cancer (mCRPC). However, the diversity and clinical implications of AR-A in treatment-naïve primary prostate cancer is largely unknown. We sought to characterize AR-A in localized prostate cancer and understand its molecular and clinical implications. EXPERIMENTAL DESIGN:Genome-wide expression profiles from prostatectomy or biopsy samples from 19,470 patients were used, all with independent pathology review. This was comprised of prospective discovery (n = 5,239) and validation (n = 12,728) cohorts, six retrospective institutional cohorts with long-term clinical outcomes data (n = 1,170), and The Cancer Genome Atlas (n = 333). RESULTS:A low AR-active subclass was identified, which comprised 9%-11% of each cohort, and was characterized by increased immune signaling, neuroendocrine expression, and decreased DNA repair. These tumors were predominantly ERG and basal subtype. Low AR-active tumors had significantly more rapid development of recurrence or metastatic disease across cohorts, which was maintained on multivariable analysis [HR, 2.61; 95% confidence interval (CI), 1.22-5.60; P = 0.014]. Low AR-active tumors were predicted to be more sensitive to PARP inhibition, platinum chemotherapy, and radiotherapy, and less sensitive to docetaxel and androgen-deprivation therapy. This was validated clinically, in that low AR-active tumors were less sensitive to androgen-deprivation therapy (OR, 0.41; 95% CI, 0.21-0.80; P = 0.008). CONCLUSIONS:Leveraging large-scale transcriptomic data allowed the identification of an aggressive subtype of treatment-naïve primary prostate cancer that harbors molecular features more analogous to mCRPC. This suggests that a preexisting subgroup of patients may have tumors that are predisposed to fail multiple current standard-of-care therapies and warrant dedicated therapeutic investigation.

SUBMITTER: Spratt DE

PROVIDER: S-EPMC6858964 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Transcriptomic Heterogeneity of Androgen Receptor Activity Defines a <i>de novo</i> low AR-Active Subclass in Treatment Naïve Primary Prostate Cancer.

Spratt Daniel E DE Alshalalfa Mohammed M Fishbane Nick N Weiner Adam B AB Mehra Rohit R Mahal Brandon A BA Lehrer Jonathan J Liu Yang Y Zhao Shuang G SG Speers Corey C Morgan Todd M TM Dicker Adam P AP Freedland Stephen J SJ Karnes R Jeffery RJ Weinmann Sheila S Davicioni Elai E Ross Ashley E AE Den Robert B RB Nguyen Paul L PL Feng Felix Y FY Lotan Tamara L TL Chinnaiyan Arul M AM Schaeffer Edward M EM

Clinical cancer research : an official journal of the American Association for Cancer Research 20190912 22

<h4>Purpose</h4>The heterogeneity of androgen receptor (AR)-activity (AR-A) is well-characterized in heavily treated metastatic castration-resistant prostate cancer (mCRPC). However, the diversity and clinical implications of AR-A in treatment-naïve primary prostate cancer is largely unknown. We sought to characterize AR-A in localized prostate cancer and understand its molecular and clinical implications.<h4>Experimental design</h4>Genome-wide expression profiles from prostatectomy or biopsy sa ...[more]

PMID: 31515456

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Project description:BackgroundGene expression-based subtyping has the potential to form a new paradigm for stratified treatment of colorectal cancer. However, current frameworks are based on the transcriptomic profiles of primary tumors, and metastatic heterogeneity is a challenge. Here we aimed to develop a de novo metastasis-oriented framework.MethodsIn total, 829 transcriptomic profiles from patients with colorectal cancer were analyzed, including primary tumors, liver metastases, and non-malignant liver samples. High-resolution microarray gene expression profiling was performed of 283 liver metastases from 171 patients treated by hepatic resection, including multiregional and/or multi-metastatic samples from each of 47 patients. A single randomly selected liver metastasis sample from each patient was used for unsupervised subtype discovery by nonnegative matrix factorization, and a random forest prediction model was trained to classify multi-metastatic samples, as well as liver metastases from two independent series of 308 additional patients.ResultsInitial comparisons with non-malignant liver samples and primary colorectal tumors showed a highly variable degree of influence from the liver microenvironment in metastases, which contributed to inter-metastatic transcriptomic heterogeneity, but did not define subtype distinctions. The de novo liver metastasis subtype (LMS) framework recapitulated the main distinction between epithelial-like and mesenchymal-like tumors, with a strong immune and stromal component only in the latter. We also identified biologically distinct epithelial-like subtypes originating from different progenitor cell types. LMS1 metastases had several transcriptomic features of cancer aggressiveness, including secretory progenitor cell origin, oncogenic addictions, and microsatellite instability in a microsatellite stable background, as well as frequent RAS/TP53 co-mutations. The poor-prognostic association of LMS1 metastases was independent of mutation status, clinicopathological variables, and current subtyping frameworks (consensus molecular subtypes and colorectal cancer intrinsic subtypes). LMS1 was also the least heterogeneous subtype in comparisons of multiple metastases per patient, and tumor heterogeneity did not confound the prognostic value of LMS1.ConclusionsWe report the first large study of multi-metastatic gene expression profiling of colorectal cancer. The new metastasis-oriented subtyping framework showed potential for clinically relevant transcriptomic classification in the context of metastatic heterogeneity, and an LMS1 mini-classifier was constructed to facilitate prognostic stratification and further clinical testing.

Project description:Androgens control male sexual development and maintenance of the adult male phenotype. They have very divergent effects on their target organs like the reproductive organs, muscle, bone, brain and skin. This is explained in part by the fact that different cell types respond differently to androgen stimulus, even when all these responses are mediated by the same intracellular androgen receptor. To understand these tissue- and cell-specific readouts of androgens, we have to learn the many different steps in the transcription activation mechanisms of the androgen receptor (NR3C4). Like all nuclear receptors, the steroid receptors have a central DNA-binding domain connected to a ligand-binding domain by a hinge region. In addition, all steroid receptors have a relatively large amino-terminal domain. Despite the overall structural homology with other nuclear receptors, the androgen receptor has several specific characteristics which will be discussed here. This receptor can bind two types of androgen response elements (AREs): one type being similar to the classical GRE/PRE-type elements, the other type being the more divergent and more selective AREs. The hormone-binding domain has low intrinsic transactivation properties, a feature that correlates with the low affinity of this domain for the canonical LxxLL-bearing coactivators. For the androgen receptor, transcriptional activation involves the alternative recruitment of coactivators to different regions in the amino-terminal domain, as well as the hinge region. Finally, a very strong ligand-induced interaction between the amino-terminal domain and the ligand-binding domain of the androgen receptor seems to be involved in many aspects of its function as a transcription factor. This review describes the current knowledge on the structure-function relationships within the domains of the androgen receptor and tries to integrate the involvement of different domains, subdomains and motifs in the functioning of this receptor as a transcription factor with tissue- and cell-specific readouts.

Dataset Information

Transcriptomic Heterogeneity of Androgen Receptor Activity Defines a de novo low AR-Active Subclass in Treatment Naive Primary Prostate Cancer.

Publications

Transcriptomic Heterogeneity of Androgen Receptor Activity Defines a <i>de novo</i> low AR-Active Subclass in Treatment Naïve Primary Prostate Cancer.

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