The optimal timing of postoperative radiotherapy (RT) after radical prostatectomy (RP) is unclear. We hypothesized that a genomic classifier (GC) would provide prognostic and predictive insight into ...the development of clinical metastases in men receiving post-RP RT and inform decision making.
GC scores were calculated from 188 patients with pT3 or margin-positive prostate cancer, who received post-RP RT at Thomas Jefferson University and Mayo Clinic between 1990 and 2009. The primary end point was clinical metastasis. Prognostic accuracy of the models was tested using the concordance index for censored data and decision curve analysis. Cox regression analysis tested the relationship between GC and metastasis.
The cumulative incidence of metastasis at 5 years after RT was 0%, 9%, and 29% for low, average, and high GC scores, respectively (P = .002). In multivariable analysis, GC and pre-RP prostate-specific antigen were independent predictors of metastasis (both P < .01). Within the low GC score (< 0.4), there were no differences in the cumulative incidence of metastasis comparing patients who received adjuvant or salvage RT (P = .79). However, for patients with higher GC scores (≥ 0.4), cumulative incidence of metastasis at 5 years was 6% for patients treated with adjuvant RT compared with 23% for patients treated with salvage RT (P < .01).
In patients treated with post-RP RT, GC is prognostic for the development of clinical metastasis beyond routine clinical and pathologic features. Although preliminary, patients with low GC scores are best treated with salvage RT, whereas those with high GC scores benefit from adjuvant therapy. These findings provide the first rational selection of timing for post-RP RT.
To test the hypothesis that a genomic classifier (GC) would predict biochemical failure (BF) and distant metastasis (DM) in men receiving radiation therapy (RT) after radical prostatectomy (RP).
...Among patients who underwent post-RP RT, 139 were identified for pT3 or positive margin, who did not receive neoadjuvant hormones and had paraffin-embedded specimens. Ribonucleic acid was extracted from the highest Gleason grade focus and applied to a high-density-oligonucleotide microarray. Receiver operating characteristic, calibration, cumulative incidence, and Cox regression analyses were performed to assess GC performance for predicting BF and DM after post-RP RT in comparison with clinical nomograms.
The area under the receiver operating characteristic curve of the Stephenson model was 0.70 for both BF and DM, with addition of GC significantly improving area under the receiver operating characteristic curve to 0.78 and 0.80, respectively. Stratified by GC risk groups, 8-year cumulative incidence was 21%, 48%, and 81% for BF (P<.0001) and for DM was 0, 12%, and 17% (P=.032) for low, intermediate, and high GC, respectively. In multivariable analysis, patients with high GC had a hazard ratio of 8.1 and 14.3 for BF and DM. In patients with intermediate or high GC, those irradiated with undetectable prostate-specific antigen (PSA ≤0.2 ng/mL) had median BF survival of >8 years, compared with <4 years for patients with detectable PSA (>0.2 ng/mL) before initiation of RT. At 8 years, the DM cumulative incidence for patients with high GC and RT with undetectable PSA was 3%, compared with 23% with detectable PSA (P=.03). No outcome differences were observed for low GC between the treatment groups.
The GC predicted BF and metastasis after post-RP irradiation. Patients with lower GC risk may benefit from delayed RT, as opposed to those with higher GC; however, this needs prospective validation. Genomic-based models may be useful for improved decision-making for treatment of high-risk prostate cancer.
Abstract Background Clinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for ...identification of biomarkers that can more accurately stratify patients with primary PCa. Objective To identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa). Design, setting, and participants To develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes. Multiple independent clinical cohorts including an intermediate-risk cohort were used to validate the biomarkers. Outcome measurements and statistical analysis The outcome measurement defining aggressive PCa was metastasis following radical prostatectomy. A generalized linear model with lasso regularization was used to build a 93-gene stroma-derived metastasis signature (SDMS). The SDMS association with metastasis was assessed using a Wilcoxon rank-sum test. Performance was evaluated using the area under the curve (AUC) for the receiver operating characteristic, and Kaplan-Meier curves. Univariable and multivariable regression models were used to compare the SDMS alongside clinicopathological variables and reported signatures. AUC was assessed to determine if SDMS is additive or synergistic to previously reported signatures. Results and limitations A close association between stromal gene expression and metastatic phenotype was observed. Accordingly, the SDMS was modeled and validated in multiple independent clinical cohorts. Patients with higher SDMS scores were found to have worse prognosis. Furthermore, SDMS was an independent prognostic factor, can stratify risk in intermediate-risk PCa, and can improve the performance of other previously reported signatures. Conclusions Profiling of stromal gene expression led to development of an SDMS that was validated as independently prognostic for the metastatic potential of prostate tumors. Patient summary Our stroma-derived metastasis signature can predict the metastatic potential of early stage disease and will strengthen decisions regarding selection of active surveillance versus surgery and/or radiation therapy for prostate cancer patients. Furthermore, profiling of stroma cells should be more consistent than profiling of diverse cellular populations of heterogeneous tumors.
Purpose To perform the first meta-analysis of the performance of the genomic classifier test, Decipher, in men with prostate cancer postprostatectomy. Methods MEDLINE, EMBASE, and the Decipher ...genomic resource information database were searched for published reports between 2011 and 2016 of men treated by prostatectomy that assessed the benefit of the Decipher test. Multivariable Cox proportional hazards models fit to individual patient data were performed; meta-analyses were conducted by pooling the study-specific hazard ratios (HRs) using random-effects modeling. Extent of heterogeneity between studies was determined with the I
test. Results Five studies (975 total patients, and 855 patients with individual patient-level data) were eligible for analysis, with a median follow-up of 8 years. Of the total cohort, 60.9%, 22.6%, and 16.5% of patients were classified by Decipher as low, intermediate, and high risk, respectively. The 10-year cumulative incidence metastases rates were 5.5%, 15.0%, and 26.7% ( P < .001), respectively, for the three risk classifications. Pooling the study-specific Decipher HRs across the five studies resulted in an HR of 1.52 (95% CI, 1.39 to 1.67; I
= 0%) per 0.1 unit. In multivariable analysis of individual patient data, adjusting for clinicopathologic variables, Decipher remained a statistically significant predictor of metastasis (HR, 1.30; 95% CI, 1.14 to 1.47; P < .001) per 0.1 unit. The C-index for 10-year distant metastasis of the clinical model alone was 0.76; this increased to 0.81 with inclusion of Decipher. Conclusion The genomic classifier test, Decipher, can independently improve prognostication of patients postprostatectomy, as well as within nearly all clinicopathologic, demographic, and treatment subgroups. Future study of how to best incorporate genomic testing in clinical decision-making and subsequent treatment recommendations is warranted.
Prostate cancer (PCa) remains a leading cause of cancer-related death in the USA. While localized lesions are effectively treated through radical prostatectomy and/or radiation therapy, treatment for ...metastatic disease leverages the addiction of these tumors on the androgen receptor (AR) signaling axis for growth and disease progression. Though initially effective, tumors resistant to AR-directed therapeutics ultimately arise (a stage of the disease known as castration-resistant prostate cancer) and are responsible for PCa-specific mortality. Importantly, an abundance of clinical and preclinical evidence strongly implicates AR signaling cascades in the development of metastatic disease in both early and late stages, and thus a concerted effort has been made to delineate the AR-specific programs that facilitate progression to metastatic PCa. A multitude of downstream AR targets as well as critical AR cofactors have been identified which impinge upon both the AR pathway as well as associated metastatic phenotypes. This review will highlight the functional significance of these pathways to disseminated disease and define the molecular underpinnings behind these unique, AR-driven, metastatic signatures.
Grade group 4 and 5 (GG-45) prostate cancer (PCa) patients are at the highest risk of lethal outcomes, yet lack genomic risk stratification for prognosis and treatment selection. Here, we assess ...whether transcriptomic interactions between tumor immune content score (ICS) and the Decipher genomic classifier can identify most lethal subsets of GG-45 PCa. We utilized whole transcriptome data from 8071 tumor tissue (6071 prostatectomy and 2000 treatment-naïve biopsy samples) to derive four immunogenomic subtypes using ICS and Decipher. When compared across all grade groups, GG-45 samples had the highest proportion of most aggressive subtype—ICSHigh/DecipherHigh. Subsequent analyses within the GG-45 patient samples (n = 1420) revealed that the ICSHigh/DecipherHigh subtype was associated with increased genomic radiosensitivity. Additionally, in a multivariable model (n = 335), ICSHigh/DecipherHigh subtype had a significantly higher risk of distant metastasis (hazard ratio HR = 5.41; 95% confidence interval CI, 2.76–10.6; p ≤ 0.0001) and PCa-specific mortality (HR = 10.6; 95% CI, 4.18–26.94; p ≤ 0.0001) as compared with ICSLow/DecipherLow. The novel immunogenomic subtypes establish a very strong synergistic interaction between ICS and Decipher in identifying GG-45 patients who experience the most lethal outcomes.
In this analysis, we identified a novel interaction between the total immune content of prostate tumors and genomic classifier to identify the most lethal subset of patients with grade groups 4 and 5. Our results will aid in the subtyping of aggressive prostate cancer patients who may benefit from combined immune-radiotherapy modalities.
In this analysis, we identified a novel interaction between the total immune content of prostate tumors and genomic classifier to identify the most lethal subset of grade group 4 and 5 patients. Our results will aid in the subtyping of aggressive prostate cancer patients who may benefit from combined immune-radiotherapy modalities.
Most prostate cancer in African American men lacks the ETS (E26 transforming specific) family fusion event (ETS-). We aimed to establish clinically relevant biomarkers in African American men by ...studying ETS dependent gene expression patterns to identified race specific genes predictive of outcomes.
Two multicenter cohorts of a total of 1,427 men were used for the discovery and validation (635 and 792 men, respectively) of race specific predictive biomarkers. We used false discovery rate adjusted q values to identify race and ETS dependent genes which were differentially expressed in African American men who experienced biochemical recurrence within 5 years. Principal component modeling along with survival analysis was done to assess the accuracy of the gene panel in predicting recurrence.
We identified 3,047 genes which were differentially expressed based on ETS status. Of these genes 362 were differentially expressed in a race specific manner (false discovery rate 0.025 or less). A total of 81 genes were race specific and over expressed in African American men who experienced biochemical recurrence. The final gene panel included APOD, BCL6, EMP1, MYADM, SRGN and TIMP3. These genes were associated with 5-year biochemical recurrence (HR 1.97, 95% CI 1.27-3.06, p = 0.002) and they improved the predictive accuracy of clinicopathological variables only in African American men (60-month time dependent AUC 0.72).
In an effort to elucidate biological features associated with prostate cancer aggressiveness in African American men we identified ETS dependent biomarkers predicting early onset biochemical recurrence only in African American men. Thus, these ETS dependent biomarkers representing ideal candidates for biomarkers of aggressive disease in this patient population.
Ankylosing spondylitis (AS) is the historic term used for decades for the HLA-B27-associated inflammatory disease affecting mainly the sacroiliac joints (SIJ) and spine. Classification criteria for ...AS have radiographic sacroiliitis as a dominant characteristic. However, with the availability of MRI of SIJ, it could be demonstrated that the disease starts long before definite SIJ changes become visible on radiographs. The Assessment of SpondyloArthritis international Society, representing a worldwide group of experts reached consensus on changes in the nomenclature pertaining to axial spondyloarthritis (axSpA), such as the terminology of diagnosis and of assessment of disease activity tools. These are important changes in the field, as experts in axSpA are now in agreement that the term axSpA is the overall term for the disease. A further differentiation, of which
versus
is only one aspect, may be relevant for research purposes. Another important decision was that the terms AS and radiographic axSpA (r-axSpA) can be used interchangeably, but that the preferred term is r-axSpA. Based on the decision that axSpA is the correct terminology, a proposal was made to officially change the meaning of the ASDAS acronym to 'Axial Spondyloarthritis Disease Activity Score'. In addition, for simplification it was proposed that the term ASDAS (instead of ASDAS-CRP) should be preferred and applied to the ASDAS calculated with C reactive protein (CRP). It is hoped that these changes will be used consequently for education, in textbooks, manuscripts and presentations.
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.
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 (
= 5,239) and validation (
= 12,728) cohorts, six retrospective institutional cohorts with long-term clinical outcomes data (
= 1,170), and The Cancer Genome Atlas (
= 333).
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
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;
= 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;
= 0.008).
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.
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