Davicioni, Elai

Abstract Purpose: This multicenter, single-arm, phase II trial evaluated the safety and efficacy of cabazitaxel and carboplatin followed by abiraterone, plus androgen deprivation therapy (ADT), in patients with high-volume metastatic castration-sensitive prostate cancer (mCSPC). Patients and Methods: Eligible patients had high-volume mCSPC and ≤3 months of prior ADT. Patients received six 21-day cycles of cabazitaxel (20 mg/m2) and carboplatin (AUC 4) with continuous ADT, followed by maintenance abiraterone (1,000 mg daily) and prednisone (5 mg daily). The primary endpoint was the proportion of patients free of prostate-specific antigen (PSA) or radiographic progression at 12 months. Secondary endpoints included complete PSA response (≤0.2 ng/mL), objective response, progression-free survival (PFS), and safety. Overall survival (OS) was also reported. Results: Sixty-one participants were enrolled at eight sites. The median age was 64 years, median baseline PSA was 6.6 ng/mL (0.07–745.7 ng/mL), 73.3% had Gleason grade group 5, 69.5% had 10 or more metastases, and 19.6% had a homologous recombination repair (HRR) mutation. PSA PFS at 12 months was 84.6% [95% confidence interval (CI), 72.5%–91.7%], and OS at 12 months was 94.8% (84.7%–98.3%). Complete PSA response was 66.7%, and complete objective response was 30.7%. Contrary to our hypothesis, relative to HRR wild-type patients, HRR-mutated patients (19.6%) had numerically fewer complete PSA responses (33.3% vs. 70.3%) and inferior PFS (HR, 2.43; 95% CI, 0.93–6.39). Common side effects of this quadruplet regimen included fatigue, nausea, and diarrhea. Conclusions: Cabazitaxel and carboplatin followed by abiraterone, together with ADT, were feasible, safe, and efficacious in patients with high-volume mCSPC and warrant further study in larger randomized trials.

Abstract Metastasis accounts for the overwhelming majority of cancer deaths. In prostate cancer and many other solid tumors, progression to metastasis is associated with drastically reduced survival outcomes, yet the mechanisms behind this progression remain largely unknown. ATPase family AAA domain containing 2 (ATAD2) is an epigenetic reader of acetylated histones that is overexpressed in multiple cancer types and usually associated with poor patient outcomes. However, the functional role of ATAD2 in cancer progression and metastasis has been relatively understudied. Here, we employ genetically engineered mouse models of prostate cancer bone metastasis, as well as multiple independent human cohorts, to show that ATAD2 is highly enriched in bone metastasis compared with primary tumors and significantly associated with the development of metastasis. We show that ATAD2 expression is associated with MYC pathway activation in patient datasets and that, at least in a subset of tumors, MYC and ATAD2 can regulate each other’s expression. Using functional studies on mouse bone metastatic cell lines and innovative organ-on-a-chip bone invasion assays, we establish a functional role for ATAD2 inhibition in reducing prostate cancer metastasis and growth in bone. Implications: Our study highlights ATAD2 as a driver of prostate cancer progression and metastasis and suggests it may constitute a promising novel therapeutic target.

Abstract Molecular drivers of metastasis in patients with high-risk localized prostate cancer are poorly understood. Therefore, we aim to study molecular drivers of metastatic progression in patients with high-risk prostate cancer. A retrospective matched case-control study of two clinico-pathologically identical groups of patients with high-risk prostate cancer was undertaken. One group developed metastatic recurrence (n = 19) while the other did not (n = 25). The primary index tumor was identified by a uro-pathologist, followed by DNA and RNA extraction for somatic copy-number aberration (SCNA) analysis and whole-transcriptome gene expression analysis. In vitro and in vivo studies included cell line manipulation and xenograft models. The integrative CNA and gene expression analyses identified an increase in Antizyme Inhibitor 1 (AZIN1) gene expression within a focal amplification of 8q22.3, which was associated with metastatic recurrence of patients with high-risk prostate cancer in four independent cohorts. The effects of AZIN1 knockdown were evaluated, due to its therapeutic potential. AZIN1 knockdown effected proliferation and metastatic potential of prostate cancer cells and xenograft models. RNA sequencing after AZIN1 knockdown in prostate cancer cells revealed upregulation of genes coding for collagen subunits. The observed effect on cell migration after AZIN1 knockdown was mimicked when exposing prostate cancer cells to bio-active molecules deriving from COL4A1 and COL4A2. Our integrated CNA and gene expression analysis of primary high-risk prostate cancer identified the AZIN1 gene as a novel driver of metastatic progression, by altering collagen subunit expression. Future research should further investigate its therapeutic potential in preventing metastatic recurrence. Implications: AZIN1 was identified as driver of metastatic progression in high-risk prostate cancer through matrikine regulation.

PURPOSE Pretreatment estimates of seminal vesicle invasion (SVI) are challenging and significantly influence the management of prostate cancer. We sought to improve current models to predict SVI through the development of an SVI prediction genomic signature. PATIENTS AND METHODS A total of 15,889 patients who underwent radical prostatectomy (RP) with available baseline clinical, pathology, and transcriptome data were retrieved from the GRID registry (ClinicalTrials.gov identifier: NCT02609269 ) and other retrospective cohorts. These data were divided into a training (n = 6,766), test (n = 3,363), and two validation (n = 5,062 and 698) cohorts. Multivariable logistic regression was performed to assess the predictive effect of the genomic SVI (gSVI) classifier in the presence of established nomograms (Partin Tables and Memorial Sloan Kettering Cancer Center [MSKCC]). RESULTS In the training cohort, univariable filtering identified 2,132 genes that were differentially expressed between RP tumors with and without SVI. Model parameters were tuned to maximize the area under the curve (AUC) in the testing cohort, resulting in a logistic generalized linear model with 581 genes. The gSVI model scores range from 0 to 1. In the first validation set, gSVI showed superior discrimination of patients with and without SVI at RP compared with other prognostic signatures trained to predict distant metastasis or clinical recurrence. Of the 698 patients in the second validation set, gSVI combined with the MSKCC nomogram had a superior AUC (0.86) compared with either nomogram individually (0.81). CONCLUSION The gSVI represents a novel and validated expression signature to predict the presence of SVI before treatment with surgery. This genomic tool adds discriminatory power to existing clinical predictive nomograms and may help with pretreatment counseling and decision making.

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.

Abstract Background: Inflammation is linked to prostate cancer progression and is mediated by NF-κB. Tristetraprolin is a key node of NF-κB activation and we investigated its biological and prognostic role in lethal prostate cancer. Methods: In vitro assays assessed the function of tristetraprolin and the association between low mRNA tristetraprolin levels and lethal prostate cancer (metastatic disease or death) was assessed across independent prostatectomy cohorts: (i) nested case-control studies from Health Professionals Follow-up Study and Physicians’ Health Study, and (ii) prostatectomy samples from Cleveland Clinic, Mayo Clinic, Johns Hopkins and Memorial Sloan Kettering Cancer Center. Tristetraprolin expression levels in prostatectomy samples from patients with localized disease and biopsies of metastatic castration–resistant prostate cancer (mCRPC) were assessed in a Cornell University cohort. Results: In vitro tristetraprolin expression was inversely associated with NF-κB–controlled genes, proliferation, and enzalutamide sensitivity. Men with localized prostate cancer and lower quartile of tumor tristetraprolin expression had a significant, nearly two-fold higher risk of lethal prostate cancer after adjusting for known clinical and histologic prognostic features (age, RP Gleason score, T-stage). Tristetraprolin expression was also significantly lower in mCRPC compared with localized prostate cancer. Conclusions: Lower levels of tristetraprolin in human prostate cancer prostatectomy tissue are associated with more aggressive prostate cancer and may serve as an actionable prognostic and predictive biomarker. Impact: There is a clear need for improved biomarkers to identify patients with localized prostate cancer in need of treatment intensification, such as adjuvant testosterone suppression, or treatment de-intensification, such as active surveillance. Tristetraprolin levels may serve as informative biomarkers in localized prostate cancer.

AbstractBackground: We studied the utility of the tumor suppressor Tristetraprolin (TTP, ZFP36) as a clinically relevant biomarker of aggressive disease in prostate cancer patients after radical prostatectomy (RP).Methods: TTP RNA expression was measured in an RP cohort of patients treated at Moffitt Cancer Center (MCC) and obtained from six publically available RP datasets with biochemical recurrence (BCR; total n = 1,394) and/or metastatic outcome data (total n = 1,222). TTP protein expression was measured by immunohistochemistry in a tissue microarray of 153 MCC RP samples. The time to BCR or metastasis based on TTP RNA or protein levels was calculated using the Kaplan–Meier analysis. Univariable and multivariable Cox proportional hazard models were performed on multiple cohorts to evaluate if TTP is a clinically relevant biomarker and to assess if TTP improves upon the Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score for predicting clinical outcomes.Results: In all of the RP patient cohorts, prostate cancer with low TTP RNA or protein levels had decreased time to BCR or metastasis versus TTP-high tumors. Further, the decreased time to BCR in TTP-low prostate cancer was more pronounced in low-grade tumors. Finally, pooled survival analysis suggests that TTP RNA expression provides independent information beyond CAPRA-S to predict BCR.Conclusions: TTP is a promising prostate cancer biomarker for predicting which RP patients will have poor outcomes, especially for low-grade prostate cancer patients.Impact: This study suggests that TTP RNA expression can be used to enhance the accuracy of CAPRA-S to predict outcomes in patients treated with RP. Cancer Epidemiol Biomarkers Prev; 27(11); 1376–83. ©2018 AACR.

Abstract Introduction: Multivariable models that predict biochemical recurrence (BCR) can indicate patients at higher risk for developing clinical progression after prostatectomy. However, most patients that experience BCR do not metastasize or die from prostate cancer, making BCR an unreliable surrogate endpoint. In this study we compared the clinical and genomic characteristics of prostatectomy patients in order to better delineate the relationship between BCR and aggressive prostate cancer. Methods: Postoperative patients were retrospectively classified into three outcome groups: NED (no evidence of disease recurrence); BCR-only (patients that experienced BCR but didn't have progressive disease as evidenced by bone or CT scans); and CP (clinical progression with BCR plus positive CT or bone scans). Patient specimens were from the Mayo Clinic Radical Prostatectomy Registry, selected using a nested case-control design with 14 years median follow-up. RNA expression levels from FFPE tumor specimens were measured with 1.4 million feature whole-transcriptome oligonucleotide microarrays on 106 matching patients from each outcome group (total 318 patients). We analyzed the clinical covariates of the outcome groups in a pairwise manner (NED vs. BCR-only; NED vs. CP; CP vs. BCR-only), using a conditional logistic model in univariable and multivariable analyses. We performed feature reduction for the genomic data set using Kruskal-Wallis tests and regularized logistic regression. Principal Component Analysis (PCA) was used to quantify the variance of the genomic data with respect to the patient outcome groups. Results: Our initial hypothesis was that all three outcome groups would have different clinical and genomic characteristics. Univariable analysis of clinical variables failed to show statistically significant differences between NED and BCR-only groups. Multivariable analysis of the clinical variables also failed to show statistically significant differences between NED and BCR-only groups. Among the clinical variables only pathological Gleason score was statistically significant when comparing the BCR-only vs. CP and NED vs. CP groups. Genomic analysis found 363 coding and non-coding features that passed thresholds for differential expression between the three outcome groups. PCA established that the primary source of variance in the genomic data stemmed from the separation of CP from NED and BCR-only patients; whereas only a small amount of variance separates NED and BCR-only groups. The 363 features were further compared in the three outcome groups using Wilcoxon tests, adjusting for false-discovery using Benjamini-Hochberg. At a cutoff of p < 0.001 there were no features differentially expressed between NED and BCR-only, while 52 and 34 statistically significant features were found in the NED vs. CP and CP vs. BCR-only comparisons, respectively. Conclusion: Considering the clinical and genomic results together, we find that: 1) Patients that developed clinical progression were significantly different from those that did not, irrespective of whether they experienced BCR or not; 2) the NED and BCR-only groups were statistically very similar to each other. We therefore conclude that BCR may not be the most appropriate endpoint for predictive models that attempt to stratify patients at risk for progression. This abstract is also presented as Poster B44. Citation Format: Anamaria Crisan, Elai Davicion, R. Jeffery Karnes, Robert B. Jenkins, Mercedeh H. Ghadessi, Christine Buerki, Eric J. Bergstrahl, Nicholas Erho, Ismael A. Vergara, Karla V. Ballman, Peter C. Black, Timothy J. Triche. Biochemical recurrence is not a definitive surrogate endpoint for development of clinically useful predictive models for post-prostatectomy patients [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr PR4.

Abstract Motivations: Gleason score is the most prognostic variable in prostate cancer pathology. Patients with high Gleason (8+) are the most likely to experience biochemical recurrence (BCR), clinical progression (CP) and prostate-cancer specific mortality (PCSM), whereas patients with Gleason ≤6 are expected to have excellent long-term outcomes. However, the majority of prostate cancer patients are diagnosed with Gleason score 7, a heterogeneous group in terms of patient outcomes. In the absence of adverse pathological factors (APF, such as preoperative PSA, SM+, ECE and SVI) most Gleason 7 patients will have excellent outcomes. In contrast, Gleason 7 patients with APF are considered at high-risk for recurrence and therefore are candidates for adjuvant therapy. In this study, we have investigated whether a classifier based on differentially expressed genomic features could be used to improve prognostication of Gleason 7 patients, independent of APF. Methods: Two whole-transcriptome (1.4 million feature) oligonucleotide microarray expression datasets from radical prostatectomy specimens were analyzed. The first one (GEO accession: GSE21032) consisted of 125 fresh frozen (FF) samples from the MSKCC Oncogenome Project and the second dataset had 545 formalin-fixed-paraffin- embedded (FFPE) samples from the Mayo Clinic tumor registry. For genomic feature selection, differential expression in the FF dataset between Gleason ≤6 (n=40) and ≥8 (n=15) was assessed with false discovery rate adjusted t-tests (p<0.05). Next, a k-nearest neighbor (KNN) classifier was trained and tuned using the selected features to predict clinical progression (i.e., positive bone or CT scans after BCR) in the FFPE dataset, again using samples with Gleason score ≤6 (n=63) and ≥8 (n=211). The KNN classifier was evaluated on Gleason score 7 (n=209) FFPE samples (not used for training) using multivariable logistic regression. Results: The KNN classifier segregated the Gleason 7 samples into high and low risk CP groups. The KNN odds ratios were 2.9 (p<0.005), 2.1 (p<0.05) and 2.8 (p<0.05) for BCR, CP and PCSM end-points, respectively when comparing high and low risk groups. Multivariable analysis revealed that the KNN classifier was independently prognostic. Conclusions: A KNN classifier developed using differentially expressed genomic features significantly stratified Gleason score 7 patients for several clinically relevant endpoints. Future validation studies will address the utility of this classifier in predicting pathological Gleason score from biopsy specimens, which may be particularly useful for evaluation of biopsy Gleason 6 cases. In these patients, deferring prostatectomy in favour of active surveillance is an appealing treatment option unless the ‘true’ Gleason of the index lesion is in fact a Gleason 7 or higher, where immediate surgery is likely a life-saving procedure. Citation Format: Nicholas Erho, Thomas Sierocinski, Elai Davicioni, Robert B. Jenkins, Mercedeh Gadhessi, Christine Buerki, Ismael A. Vergara, Anamaria Crisan, Zaid Haddad, Benedikt Zimmermann, Anirban Mitra, Timothy J. Triche. Identification of biomarkers for stratification of Gleason score 7 patients using whole-transcriptome expression profiling [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr B46.