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Dicker, Adam P

0000-0003-0733-3337

Mayo Clinic

Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania, USA.

Citations 27

Efficacy of early and delayed radiation in a prostatectomy cohort adjusted for genomic and clinical risk.
Yousefi, Kasra, Tosoian, Jeffrey J. , Thompson, Darby J. S., Choeurng, Voleak, Haddad, Zaid , Trabulsi, Edouard J. , Gomella, Leonard G. , Lallas, Costas D. , Feng, Felix Y. , Dicker, Adam P. , Freedland, Stephen J. , Karnes, Jeffrey , Ross, Ashley E. , Den, Robert B. , Trock, Bruce J , Davicioni, Elai , Tran, Phuoc T , Abdollah, Firas , Schaeffer, Edward M. , Dicker, Adam P

Journal of Clinical Oncology | February 24, 2017 | Volume: 34 | Issue: 2_suppl | Pages: 12-12

10.1200/jco.2016.34.2_suppl.12 Get It

12 Background: In 3 published randomized trials, adjuvant radiation therapy (ART) for prostate cancer (PCa) resulted in improved progression free survival. However, the impact on metastases and overall survival is unclear. To date, there have been no published prospective trials examining the impact of salvage radiation therapy (SRT) in this disease state. Hence, we conducted a retrospective, nonrandomized comparative study of ART, SRT, or no radiation following radical prostatectomy (RP) for men with pT3 disease or positive margins (adverse pathologic features, APF). Methods: 422 PCa men treated at 4 institutions with RP and having APF were analyzed with a primary end point of clinical metastasis. ART (n = 111), early SRT (n = 70) and delayed SRT (n = 83) were defined by PSA levels of < 0.2, 0.2 to 0.5, and ≥ 0.5 ng/mL, respectively, prior to RT initiation. Remaining 157 men who did not receive additional therapy prior to metastatic onset formed the no RT arm. Clinical-genomic risk was assessed by CAPRA-S and Decipher. Cox multivariable (MVA) model was used to evaluate the impact of treatment on outcome. Results: During study follow-up, 37 men developed metastasis with a median follow-up of 8 years. Both CAPRA-S and Decipher had independent predictive value on MVA for metastatic outcome (both p < 0.05). On MVA adjusting for clinical-genomic risk, delayed SRT and no RT had an HR of 4.31 (95%CI, 1.20-15.47) and 5.42 (95% CI, 1.59-18.44) for metastasis compared to ART. No significance difference was observed between early SRT and ART (p = 0.28). Men with low to intermediate CAPRA-S and low Decipher have a low rate of metastatic events regardless of treatment selection. In contrast, men with high CAPRA-S and Decipher benefit from ART, however the cumulative incidence of metastasis remains high. Conclusions: The decision as to the timing and need for additional local therapy following RP is nuanced and requires providers and men to balance risks of morbidity with improved oncologic outcomes. This analysis provides the most robust and accurate quantification of risk for these men. Post-RP treatment can be safely avoided for men who are low risk by clinical-genomic risk, whereas those at high risk should favor enrollment in clinical trials.
Development and validation of an ADT resistance signature to predict adjuvant hormone treatment failure.
Karnes, Jeffrey , Ashab, Hussam Al-Deen, Ross, Ashley E. , Tosoian, Jeffrey J. , Erho, Nicholas , Choeurng, Voleak, Yousefi, Kasra, Haddad, Zaid , Feng, Felix Y. , Dicker, Adam P. , Jenkins, Robert B. , Trock, Bruce J , Tsai, Harrison , Abdollah, Firas , Klein, Eric A. , Nguyen, Paul L. , Den, Robert B. , Davicioni, Elai , Lotan, Tamara Levin , Schaeffer, Edward M. , Dicker, Adam P

Journal of Clinical Oncology | February 24, 2017 | Volume: 34 | Issue: 2_suppl | Pages: 106-106

10.1200/jco.2016.34.2_suppl.106 Get It

106 Background: Androgen deprivation therapy (ADT) is one of the main treatment options for locally advanced and metastatic prostate cancer. Neuroendocrine prostate cancer (NEPC) is inherently less sensitive or even resistant to ADT. NEPC can be observed de novo (e.g., small cell prostate cancer) but more commonly arises after exposure to ADT. We hypothesized that a gene expression signature of NEPC when measured in primary tumor specimens (RP) of prostatic adenocarcinoma may be useful for predicting patients with innate resistance to ADT. Methods: Expression profiles of 1023 PCa patients treated with RP were obtained from the Decipher GRID database. These were split into training (n=529) and validation (n=494) sets and stratified by the receipt of adjuvant ADT (n=243) or no adjuvant ADT (n=780). A literature review of ADT resistance and neuroendocrine genes identified 1,557 genes as candidates. This set was further filtered, using logistic regression to select a 52-gene ADT resistance signature (ARS). ARS was trained using a generalized linear model with lasso regularization. Survival c-index and Kaplan Meier was used to compare survival differences between treated and untreated patients with high and low ARS scores (defined by median split). Results: In validation cohorts, the ARS was predictive of metastasis in cohorts receiving adjuvant ADT (10-year metastasis free survival c-index of 0.69 (95% CI 0.59-0.78) as compared to 0.45 (95% CI 0.29-0.61) in patients not treated with ADT). Similarly in a separate cohort of untreated patients that received no ADT until after metastatic onset, ARS was not prognostic (c-index 0.53). Among ADT treated patients, those with low ARS scores had a 10 year MFS of 87%, versus 70% in those with high ARS scores (p<0.001). In the subset of men who received ADT after metastatic onset and who developed castrate-resistant prostate cancer (CRPC, n = 41), median time to treatment failure was 1 year in patients with high ARS compared to 2 years for those with low ARS scores (p=0.07). Conclusions: A 52-gene ADT resistance signature was developed which showed significant differences in metastasis-free survival among adjuvant hormone treated but not untreated patients.
Molecular Analysis of Low Grade Prostate Cancer Using a Genomic Classifier of Metastatic Potential
Klein, Eric A. , Santiago‐Jiménez, María , Yousefi, Kasra, Robbins, Bruce A., Schaeffer, Edward M. , Tosoian, Jeffrey J. , Haddad, Zaid , Ra, Seong, Karnes, R. Jeffrey , Jenkins, Robert B. , Cheville, John C. , Den, Robert B. , Dicker, Adam P. , Freedland, Stephen J. , Ross, Ashley E. , Trock, Bruce J , Davicioni, Elai , Den, Robert B , Klein, Eric A , Dicker, Adam P

Journal of Urology | August 31, 2016 | Volume: 197 | Issue: 1 | Pages: 122-128

10.1016/j.juro.2016.08.091 Get It

The Landscape of Prognostic Outlier Genes in High-Risk Prostate Cancer
Zhao, Shuang G. , Evans, Joseph R. , Kothari, Vishal , Sun, Grace Y. , Larm, Ashley, Mondine, Victor, Schaeffer, Edward M. , Ross, Ashley E. , Klein, Eric A. , Den, Robert B. , Dicker, Adam P. , Karnes, R. Jeffrey , Erho, Nicholas , Nguyen, Paul L. , Feng, Felix Y. , Zhao, Shuang G , Davicioni, Elai , Den, Robert B , Klein, Eric A , Dicker, Adam P

Clinical Cancer Research | December 2, 2015 | Volume: 22 | Issue: 7 | Pages: 1777-1786

10.1158/1078-0432.ccr-15-1250 Get It

Abstract Purpose: There is a clear need to improve risk stratification and to identify novel therapeutic targets in aggressive prostate cancer. The goal of this study was to investigate genes with outlier expression with prognostic association in high-risk prostate cancer patients as potential biomarkers and drug targets. Experimental Design: We interrogated microarray gene expression data from prostatectomy samples from 545 high-risk prostate cancer patients with long-term follow-up (mean 13.4 years). Three independent clinical datasets totaling an additional 545 patients were used for validation. Novel prognostic outlier genes were interrogated for impact on oncogenic phenotypes in vitro using siRNA-based knockdown. Association with clinical outcomes and comparison with existing prognostic instruments was assessed with multivariable models using a prognostic outlier score. Results: Analysis of the discovery cohort identified 20 prognostic outlier genes. Three top prognostic outlier genes were novel prostate cancer genes; NVL, SMC4, or SQLE knockdown reduced migration and/or invasion and outlier expression was significantly associated with poor prognosis. Increased prognostic outlier score was significantly associated with poor prognosis independent of standard clinicopathologic variables. Finally, the prognostic outlier score prognostic association is independent of, and adds to existing genomic and clinical tools for prognostication in prostate cancer (Decipher, the cell-cycle progression signature, and CAPRA-S). Conclusions: To our knowledge, this study represents the first unbiased high-throughput investigation of prognostic outlier genes in prostate cancer and demonstrates the potential biomarker and therapeutic importance of this previously unstudied class of cancer genes. Clin Cancer Res; 22(7); 1777–86. ©2015 AACR.
Abstract A1-64: Molecular and clinical characterization of 1,577 primary prostate cancer tumors reveals novel clinical and biological insights into its subtypes
Alshalalfa, Mohammed , Tomlins, Scott A. , Erho, Nicholas , Yousefi, Kasra, Zhao, Shuang G. , Dicker, Adam P. , Ross, Ashley E. , Karnes, Jeffery, Jenkins, Robert B. , Feng, Felix Y. , Zhao, Shuang G , Den, Robert B. , Trock, Bruce J , Marzo, Angelo M. De , Schaeffer, Edward M. , Klein, Eric A. , Magi‐Galluzzi, Cristina , Davicioni, Elai , Dicker, Adam P

Cancer Research | November 20, 2015 | Volume: 75 | Issue: 22_Supplement_1 | Pages: A1-64-A1-64

10.1158/1538-7445.transcagen-a1-64 Get It

Abstract Background: Prostate cancer molecular subtypes based on ETS gene fusions and SPINK1 were originally identified through distinct gene expression profiles. Such molecular subtypes may have utility in disease stratification and clonality assessment, complementing available purely prognostic tests. Hence, we determined the analytical validity of molecular subtyping and explored clinical associations using global gene expression profiles in a large cohort of PCa. Methods: We analyzed 1,577 patient Affymetrix Human Exon 1.0ST GeneChip expression profiles from 8 radical prostatectomy (RP) cohorts; 5 of them generated as part of the Decipher® platform for the Decipher® discovery or validation. Multi-feature random forest classifiers and outlier analysis were used to define microarray-based molecular subtypes and characterize clinical associations. Results: A random forest (RF) classifier (m-ERG) was trained and validated to predict ERG fusion status using separate subsets of a single-institution RP cohort (total n=407) with known ERG rearrangement status defined by FISH, achieving &gt;95% sensitivity and specificity in the validation subset. The model was then applied to 7 independent RP cohorts to predict ERG rearrangement status. Less frequent rearrangements involving other ETS genes (ETV1, ETV4, ETV5, FLI1) or SPINK1 over-expression were predicted based on gene expression outlier analysis. Across cohorts, 45%, 9% 8% and 38% of PCa were classified as ERG+, ERG—ETS+, ERG—SPINK+, and Triple Negative (ERG—/ETS—/SPINK1—), respectively. Global gene expression analysis shows that the four subtypes could be collapsed into three entities (ERG+, ERG—ETS+ and SPINK+/Triple Negative) based on expression patterns and clinical characteristics similarity. Based on multivariable analysis, ERG+ is significantly associated with lower pre-PSA (p&lt;0.001), lower Gleason score (p&lt;0.001), the presence of extraprostatic extension (p&lt;0.001) and European Americans (p&lt;0.001), but not associated with outcome. ERG—ETS+ is significantly associated with SVI (p=0.01) and ERG—SPINK+ is enriched in African Americans (p&lt;0.001). Conclusions: The Decipher® platform can accurately determine ERG rearrangement status and PCa molecular subtypes. Inclusion of molecular subtyping, such as m-ERG status, may enable additional precision medicine opportunities in prognostic tests and provides insights into the development of novel therapeutic approaches. Citation Format: Mohammed Alshalalfa, Scott A. Tomlins, Nicholas Erho, Kasra Yousefi, Shuang Zhao, Robert B. Den, Adam P. Dicker, Bruce Trock, Angelo DeMarzo, Edward M. Schaeffer, Ashley Ross, Eric A. Klein, Cristina Magi-Galluzzi, Jeffery R. Karnes, Robert B Jenkins, Elai Davicioni, Felix Feng. Molecular and clinical characterization of 1,577 primary prostate cancer tumors reveals novel clinical and biological insights into its subtypes. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-64.
Genomic Classifier Identifies Men With Adverse Pathology After Radical Prostatectomy Who Benefit From Adjuvant Radiation Therapy
Den, Robert B. , Yousefi, Kasra, Trabulsi, Edouard J. , Abdollah, Firas , Choeurng, Voleak, Feng, Felix Y. , Dicker, Adam P. , Lallas, Costas D. , Gomella, Leonard G. , Karnes, R. Jeffrey , Davicioni, Elai , Den, Robert B , Abdollah, Firas , Dicker, Adam P

Journal of Clinical Oncology | February 10, 2015 | Volume: 33 | Issue: 8 | Pages: 944-951

10.1200/jco.2014.59.0026 Get It

Purpose 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. Patients and Methods 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. Results 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). Conclusion 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.