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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 New approaches are needed to overcome intrinsic therapy resistance in glioblastoma (GBM). Because GBMs exhibit sexual dimorphism and are reported to express steroid hormone receptors, we reasoned that signaling through the androgen receptor (AR) could mediate therapy resistance in GBM, much as it does in AR-positive prostate and breast cancers. We found that nearly half of GBM cell lines, patient-derived xenografts (PDX), and human tumors expressed AR at the transcript and protein level—with expression levels overlapping those of primary prostate cancer. Analysis of gene expression datasets also revealed that AR expression is higher in GBM patient samples than normal brain tissue. Multiple clinical-grade antiandrogens slowed the growth of and radiosensitized AR-positive GBM cell lines and PDXs in vitro and in vivo. Antiandrogens blocked the ability of AR-positive GBM PDXs to engage adaptive transcriptional programs following radiation and slowed the repair of radiation-induced DNA damage. These results suggest that combining blood–brain barrier permeable antiandrogens with radiation may have promise for patients with AR-positive GBMs.

5584 Background: The timing of systemic therapy in relation to radiotherapy (RT) is important in most malignancies. In contrast, androgen deprivation therapy (ADT) has largely been investigated in relation to its duration rather than its sequencing with RT. Herein, we conduct the first combined individual patient analysis of two phase III randomized trials to determine the optimal timing of ADT with RT in localized prostate cancer (PCa). Methods: Individual patient data was obtained from the Malone et al trial (JCO 2019), which randomized patients to receive neoadjuvant/concurrent or concurrent/adjuvant ADT for 6 months with prostate only RT. This was combined with the prostate only RT arms of RTOG 9413 that randomized patients to 4 months of neoadjuvant/concurrent or adjuvant ADT. The neoadjuvant/concurrent arms of both trials were combined into the “neoadjuvant” group, and the concurrent/adjuvant (Malone) and adjuvant arm (RTOG 9413) were combined in the “adjuvant” group. The Kaplan-Meier method was used to estimate overall survival (OS) and progression-free survival (PFS). Cumulative incidence of distant metastasis (DM), PCa-specific mortality (PCSM) and biochemical failure (BF) were calculated using the Fine-Gray method with non-PCa deaths as competing events. Late genitourinary (GU) and gastrointestinal (GI) toxicity are also reported. Results: The median follow-up was 14.9 years (yrs) and 1065 patients were included (n=531 neoadjuvant, 534 adjuvant). Groups were well balanced for all baseline characteristics. Adjuvant ADT was superior to neoadjuvant ADT in terms of BF (15yr: 33% vs 43%, HR: 1.37 (95%CI: 1.12-1.68), p=0.002), DM (15yr: 12% vs 18%, HR: 1.40 (95%CI: 1.00-1.95), p=0.04), and PFS (15yr: 36% vs 29%, HR: 1.25 (95%CI: 1.07-1.47), p=0.01). Adjuvant ADT yielded lower PCSM (15yr: 15% vs 20%, HR: 1.29 (95%CI: 0.95-1.75), p=0.10), but did not reach statistical significance. This approached statistical significance in high risk PCa (HR 1.39 (95%CI 1.00-1.93), p=0.053). OS was not significantly different between arms (15yr: 39% vs 34%, HR: 1.11 (95%CI: 0.95-1.30), p=0.20). There was no significant difference in either late grade ≥3 GI (p=0.21) or GU (p=0.98) toxicity. Conclusions: We demonstrate for the first time that sequencing of ADT with RT significantly impacts long-term oncologic outcomes in localized PCa, favoring an adjuvant rather than neoadjuvant approach, without increasing late toxicity. This data has important implications to ongoing and future clinical trial design. Clinical trial information: NCT00769548 .

Plazomicin was tested against 697 recently acquired carbapenem-resistant Klebsiella pneumoniae isolates from the Great Lakes region of the United States. Plazomicin MIC 50 and MIC 90 values were 0.25 and 1 mg/liter, respectively; 680 isolates (97.6%) were susceptible (MICs of ≤2 mg/liter), 9 (1.3%) intermediate (MICs of 4 mg/liter), and 8 (1.1%) resistant (MICs of >32 mg/liter). Resistance was associated with rmtF -, rmtB -, or armA -encoded 16S rRNA methyltransferases in all except 1 isolate.

337 Background: Current risk stratification schema have limited prognostic performance in predicting outcome within National Comprehensive Cancer Network (NCCN) high-risk to very high-risk prostate cancer. Methods: Two multicenter high-risk cohorts were used for training (n = 214) and validation (n = 151) of a novel RNA microarray-based integrated clinical-genomic Classifier Optimized for Outcome in High-risk Prostate cancer (COOHP) to classify patients as COOHP favorable high-risk, standard high-risk, or very high-risk. Cox analysis was used to model metastasis-free survival (MFS), prostate cancer-specific survival (PCSS), and overall survival (OS). Model performance was compared to prior sub-classification systems using time-dependent c-indices. Results: Among NCCN high/very high-risk patients in the training cohort, 11% were classified as COOHP favorable high-risk, 70% as COOHP standard high-risk, and 18% as COOHP very high-risk. Patients with COOHP favorable high-risk disease had better rates of 5-year MFS compared to those with COOHP standard high-risk disease (94% vs 76%, hazard ratio [HR] 0.10, p = 0.02), and patients with COOHP very high-risk disease had worse 5-year MFS compared to those with COOHP standard high-risk disease (34% vs 76%, HR 3.5, p < 0.0001). Similarly, patients with COOHP very high-risk disease had worse 10-year PCSS compared to those with COOHP standard high-risk disease (36% vs 82%, HR 4.4, p < 0.0001). The c-indices for 5-year MFS and 10-year PCSS in the training cohort were 0.80 and 0.74, significantly improved compared to prior clinical and clinical-genomic risk stratification systems (0.62-0.69 for 5-year MFS and 0.56-0.63 for 10-year PCSS). These results were consistent in the validation cohort, where 5-year MFS significantly varied among the three COOHP subgroups (100% vs 89% vs 79%, p = 0.020), as did 10-year OS (100% vs 71% vs 53%, p = .040). Conclusions: A clinical-genomic risk stratification system specifically designed to discriminate prognosis in high-risk prostate cancer better identified favorable high-risk and very high-risk subsets of disease compared to prior clinical and clinical-genomic stratification systems.

327 Background: Though Black men with prostate cancer are more likely to have aggressive disease features than White men, race-specific differences in initial treatment responses in localized disease remains unknown. Methods: Individual patient data were obtained for 9259 patients (including 1674 [18.1%] Black men and 7585 [81.9%] White men) enrolled on eight randomized controlled trials evaluating definitive radiotherapy (RT) ± short-term or long-term androgen deprivation therapy (STADT and LTADT). The primary endpoints were biochemical recurrence (BCR), distant metastasis (DM), and prostate cancer-specific mortality (PCSM). Fine-Gray subdistribution HR (sHR) models were developed to evaluate the cumulative incidences of all endpoints after stratification by National Comprehensive Cancer Network risk grouping. A meta-analysis was done to estimate pair-wise comparisons of treatments within and between Black and White men, after adjusting for age, Gleason score, clinical T stage, and initial PSA. Results: Black men were more likely to have NCCN high-risk disease at enrollment (656/1674 [39.2%] vs 2506/7585 [33%], p<0.001). However, within the high-risk stratum Black men had lower 10-year rates of BCR (46.1% vs. 50.4%, p=0.02), DM (14% vs. 21.6%, p<0.001), and PCSM (4.9% vs. 9.8%, p<0.001). After adjusting for age and disease characteristics, Black men with high-risk prostate receiving RT+STADT had lower rates of BCR (sHR 0.73, 95% CI 0.62-0.86, p<0.001), DM (sHR 0.64, 95% CI 0.49-0.84, p=0.001) and PCSM (sHR 0.49, 95% CI 0.25-0.95, p=0.04). There were no differences in BCR, DM, or PCSM among men receiving RT+LTADT. The interaction between race and the impact of adding STADT to RT alone on BCR was statistically significant (p=0.003). Conclusions: Black men enrolled on randomized trials with long-term follow-up have higher risk disease at enrollment, but have better BCR, DM, and PCSM outcomes with RT-based therapy compared with White men, particularly with the addition of STADT.