Abstract Purpose: We previously reported that postmenopausal women with estrogen receptor-α–positive breast cancer receiving adjuvant anastrozole 1 mg/day (ANA1) with estrone (E1) ≥1.3 pg/mL and estradiol (E2) ≥0.5 pg/mL [inadequate estrogen suppression (IES)] had a threefold increased risk of a breast cancer event. The objective of this study was to determine if increasing anastrozole to 10 mg/day (ANA10) could result in adequate estrogen suppression (AES: E1 <1.3 pg/mL and/or E2 <0.5 pg/mL) among those with IES on ANA1. Patients and Methods: Postmenopausal women with estrogen receptor-α–positive breast cancer planning to receive adjuvant ANA1 were eligible. E1 and E2 were assessed pre- and post-8 to 10 weeks of ANA1. Those with IES were switched to 8- to 10-week cycles of ANA10 followed by letrozole 2.5 mg/day. E1 and E2 were assessed after each cycle. Anastrozole concentrations were measured post-ANA1 and post-ANA10. Primary analyses included patients who documented taking at least 80% of the planned treatment (adherent cohort). Results: In total, 132 (84.6%) of 156 eligible patients were ANA1 adherent. IES occurred in 40 (30.3%) adherent patients. Twenty-five (78.1%) of 32 patients who began ANA10 were adherent, and AES was achieved in 19 (76.0%; 90% confidence interval, 58.1%–89.0%) patients. Anastrozole concentrations post-ANA1 and post-ANA10 did not differ by estrogen suppression status among adherent patients. AES was maintained/attained in 21 (91.3%) of 23 letrozole-adherent patients. Conclusions: Approximately 30% of ANA1-adherent patients had IES. Among those who switched to ANA10 and were adherent, 76% had AES. Further studies are required to validate emerging data that ANA1 results in IES for some patients and to determine the clinical benefit of switching to ANA10 or an alternative aromatase inhibitor.
Bayesian Machine Learning Enables Identification of Transcriptional Network Disruptions Associated with Drug-Resistant Prostate Cancer
Abstract Survival rates of patients with metastatic castration-resistant prostate cancer (mCRPC) are low due to lack of response or acquired resistance to available therapies, such as abiraterone (Abi). A better understanding of the underlying molecular mechanisms is needed to identify effective targets to overcome resistance. Given the complexity of the transcriptional dynamics in cells, differential gene expression analysis of bulk transcriptomics data cannot provide sufficient detailed insights into resistance mechanisms. Incorporating network structures could overcome this limitation to provide a global and functional perspective of Abi resistance in mCRPC. Here, we developed TraRe, a computational method using sparse Bayesian models to examine phenotypically driven transcriptional mechanistic differences at three distinct levels: transcriptional networks, specific regulons, and individual transcription factors (TF). TraRe was applied to transcriptomic data from 46 patients with mCRPC with Abi-response clinical data and uncovered abrogated immune response transcriptional modules that showed strong differential regulation in Abi-responsive compared with Abi-resistant patients. These modules were replicated in an independent mCRPC study. Furthermore, key rewiring predictions and their associated TFs were experimentally validated in two prostate cancer cell lines with different Abi-resistance features. Among them, ELK3, MXD1, and MYB played a differential role in cell survival in Abi-sensitive and Abi-resistant cells. Moreover, ELK3 regulated cell migration capacity, which could have a direct impact on mCRPC. Collectively, these findings shed light on the underlying transcriptional mechanisms driving Abi response, demonstrating that TraRe is a promising tool for generating novel hypotheses based on identified transcriptional network disruptions. Significance: The computational method TraRe built on Bayesian machine learning models for investigating transcriptional network structures shows that disruption of ELK3, MXD1, and MYB signaling cascades impacts abiraterone resistance in prostate cancer.
Pharmacological Targeting of Androgen Receptor Elicits Context-Specific Effects in Estrogen Receptor–Positive Breast Cancer
Abstract Androgen receptor (AR) is expressed in 80% to 90% of estrogen receptor α–positive (ER+) breast cancers. Accumulated evidence has shown that AR is a tumor suppressor and that its expression is associated with improved prognosis in ER+ breast cancer. However, both a selective AR agonist (RAD140) and an AR inhibitor (enzalutamide, ENZ) have shown a therapeutic effect on ER+ breast cancer, so the potential for clinical application of AR-targeting therapy for ER+ breast cancer is still in dispute. In this study, we evaluated the efficacy of ENZ and RAD140 in vivo and in vitro in AR+/ER+ breast cancer models, characterizing the relationship of AR and ER levels to response to AR-targeting drugs and investigating the alterations of global gene expression and chromatin binding of AR and ERα after ENZ treatment. In the AR-low setting, ENZ directly functioned as an ERα antagonist. Cell growth inhibition by ENZ in breast cancer with low AR expression was independent of AR and instead dependent on ER. In AR-high breast cancer models, AR repressed ERα signaling and ENZ promoted ERα signaling by antagonizing AR. In contrast, RAD140 activated AR signaling and suppressed AR-high tumor growth by deregulating ERα expression and blocking ERα function. Overall, analysis of the dynamic efficacies and outcomes of AR agonist, and antagonist in the presence of different AR and ERα levels reveals regulators of response and supports the clinical investigation of ENZ in selected ER+ tumors with a low AR/ER ratio and AR agonists in tumors with a high AR/ER ratio. Significance: The ratio of androgen receptor to estrogen receptor in breast cancer dictates the response to AR-targeted therapies, providing guidelines for developing AR-directed treatment strategies for patients with breast cancer.
Molecular Profile Changes in Patients with Castrate-Resistant Prostate Cancer Pre- and Post-Abiraterone/Prednisone Treatment
Abstract We identified resistance mechanisms to abiraterone acetate/prednisone (AA/P) in patients with metastatic castration-resistant prostate cancer (mCRPC) in the Prostate Cancer Medically Optimized Genome-Enhanced Therapy (PROMOTE) study. We analyzed whole-exome sequencing (WES) and RNA-sequencing data from 83 patients with metastatic biopsies before (V1) and after 12 weeks of AA/P treatment (V2). Resistance was determined by time to treatment change (TTTC). At V2, 18 and 11 of 58 patients had either short-term (median 3.6 months; range 1.4–4.5) or long-term (median 29 months; range 23.5–41.7) responses, respectively. Nonresponders had low expression of TGFBR3 and increased activation of the Wnt pathway, cell cycle, upregulation of AR variants, both pre- and posttreatment, with further deletion of AR inhibitor CDK11B posttreatment. Deletion of androgen processing genes, HSD17B11, CYP19A1 were observed in nonresponders posttreatment. Genes involved in cell cycle, DNA repair, Wnt-signaling, and Aurora kinase pathways were differentially expressed between the responder and non-responder at V2. Activation of Wnt signaling in nonresponder and deactivation of MYC or its target genes in responders was detected via SCN loss, somatic mutations, and transcriptomics. Upregulation of genes in the AURKA pathway are consistent with the activation of MYC regulated genes in nonresponders. Several genes in the AKT1 axis had increased mutation rate in nonresponders. We also found evidence of resistance via PDCD1 overexpression in responders. Implications: Finally, we identified candidates drugs to reverse AA/P resistance: topoisomerase inhibitors and drugs targeting the cell cycle via the MYC/AURKA/AURKB/TOP2A and/or PI3K_AKT_MTOR pathways.
Glucocorticoids mediate transcriptome‐wide alternative polyadenylation: Potential mechanistic and clinical implications
AbstractAlternative polyadenylation (APA) is a common genetic regulatory mechanism that generates distinct 3′ ends for RNA transcripts. Changes in APA have been associated with multiple biological processes and disease phenotypes. However, the role of hormones and their drug analogs in APA remains largely unknown. In this study, we investigated transcriptome‐wide the impact of glucocorticoids on APA in 30 human B‐lymphoblastoid cell lines. We found that glucocorticoids could regulate APA for a subset of genes, possibly by changing the expression of 142 RNA‐binding proteins, some with known APA‐regulating properties. Interestingly, genes with glucocorticoid‐mediated APA were enriched in viral translation‐related pathways, while genes with glucocorticoid‐mediated expression were enriched in interferon and interleukin pathways, suggesting that glucocorticoid‐mediated APA might result in functional consequences distinct from gene expression. For example, glucocorticoids, a pharmacotherapy for severe COVID‐19, were found to change the APA but not the expression of LY6E, an important antiviral inhibitor in coronavirus diseases. Glucocorticoid‐mediated APA was also cell‐type‐specific, suggesting an action of glucocorticoids that may be unique to immune regulation. We also observed evidence for genotype‐dependent glucocorticoid‐mediated APA (referred to as pharmacogenomic‐alterative polyadenylation quantitative trait loci), providing potential functional mechanisms for a series of common genetic variants that had previously been associated with immune disorders, but without a clear mechanism. In summary, this study reports a series of observations regarding the impact of glucocorticoids on APA, raising the possibility that this mechanism might have implications for both disease pathophysiology and drug therapy.