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Carroll, Peter R

0000-0002-1086-4334

Mayo Clinic

University of California, San Francisco

Citations 9

A Clinician's Guide to Targeted Precision Imaging in Patients With Prostate Cancer (RADAR VI)
Crawford, E. David , Albala, David , Harris, Richard G., Slovin, Susan F. , Finkelstein, Steven E., Garnick, Marc B. , Gomella, Leonard G. , Higano, Celestia S. , Koo, Sonya J., Petrylak, Daniel P. , Sellinger, Scott B., McKay, Rana R. , Crosby, Mike, Koo, Phillip J. , Bryce, Alan H. , Carroll, Peter R , Yu, Evan Y , Cooperberg, Matthew R

JU Open Plus | January 27, 2023 | Volume: 1 | Issue: 1 | Pages: No page available

10.1097/ju9.0000000000000003 Get It

Purpose: The advent of new imaging agents offers enhanced sensitivity and specificity in the detection and staging of prostate cancer. A growing array of treatment options and ongoing advancements in imaging technologies allow earlier and more extensive detection of metastatic disease and shifting the boundaries between disease states previously defined by conventional imaging. This review seeks to synthesize existing data and expert opinion to better guide patient management in the new era of targeted precision imaging (TPI). Materials and Methods: The Radiographic Assessments for Detection of Advanced Recurrence VI Group gathered to develop pathways/recommendations regarding how TPI could best be deployed, given approvals of key radiotracers including 18F-fluciclovine, 68Ga-PSMA, and 18F-DCFPyL positron emission tomography/CT. Results: Radiographic Assessments for Detection of Advanced Recurrence VI Group members developed consensus pathways/suggestions based on the best available evidence for use of TPI in prostate cancer. Conclusions: Patients with prostate cancer have the potential to benefit from judicious use of TPI. However, additional research is needed to ensure that TPI is used appropriately and provides actionable findings that inform treatment decisions for these patients.
Development and Validation of a Genomic Tool to Predict Seminal Vesicle Invasion in Adenocarcinoma of the Prostate
Hall, William A. , Fishbane, Nick , Xu, Melody, Davicioni, Elai , Den, Robert B. , Dess, Robert T. , Wong, Anthony , Schaeffer, Edward M. , Karnes, R. Jeffrey , Kim, Hyung L. , Klein, Eric A. , Davis, John W. , Ross, Ashley E. , Tosoian, Jeffrey J. , Mehra, Rohit , Salami, Simpa S. , Nguyen, Paul L. , Lawton, C.A., Spratt, Daniel E. , Feng, Felix Y. , Xu, Melody J , Davicioni, Elai , Den, Robert B , Dess, Robert T , Jackson, William C , Wong, Anthony C , Carroll, Peter R , Bismar, Tarek A , Kim, Hyung L , Klein, Eric A , Tosoian, Jeffrey J , Morgan, Todd M , Salami, Simpa S , Spratt, Daniel E , Liu, Yang , Mahal, Brandon A. , Jackson, Will , Cooperberg, Matthew R , Morgan, Todd M.

JCO Precision Oncology | October 16, 2020 | Volume: No volume available | Issue: 4 | Pages: 1228-1238

10.1200/po.20.00013 Get It

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.
Implementation of Germline Testing for Prostate Cancer: Philadelphia Prostate Cancer Consensus Conference 2019
Kelly, William Kevin, Cheng, Heather H. , Cookson, Michael S. , Dahut, William L. , Weissman, Scott M., Soule, Howard R. , Petrylak, Daniel P. , Dicker, Adam P. , AlDubayan, Saud H. , Pettaway, Curtis A. , Daly, Mary B., Mohler, James L. , Parsons, J. Kellogg , Pilarski, Robert , Blanco, Amie , Woodson, Ashley, Taplin, Mary-Ellen, Polascik, Thomas J. , Hyatt, Colette, Feng, Felix Y. , Mullane, Michael P., Powers, Jacqueline, Concepcion, Raoul S. , Lin, Daniel W. , Wender, Richard C. , Mark, James Ryan , Costello, Anthony J. , Isaacs, William B. , Xu, Jianfeng , Weitzel, Jeffrey N. , Andriole, Gerald L. , Beltran, Himisha , Briganti, Alberto , Byrne, Lindsey , Calvaresi, Anne, Chandrasekar, Thenappan , Chen, David Y.T. , Dobi, Albert , Crawford, E. David , Eastham, James A., Eggener, Scott E. , Freedman, Matthew L. , Garnick, Marc B. , Gomella, Patrick T. , Handley, Nathan , Hurwitz, Mark , Izes, Joseph K. , Karnes, R. Jeffrey , Lallas, Costas D. , Languino, Lucia R. , Loughlin, Kevin R. , Lu‐Yao, Grace , Malkowicz, S. Bruce, Mann, Mark, Mille, Patrick , Miner, Martin , Morgan, Todd M. , Mucci, Lorelei A. , Nielsen, Sarah M. , O’Neil, Brock , Pinover, Wayne H., Pinto, Peter A. , Poage, Wendy, Raj, Ganesh V. , Ryan, Charles J. , Schiewer, Matthew J. , Szymaniak, Brittany M. , Tester, William , Trabulsi, Edouard J. , Vapiwala, Neha , Gomella, Leonard G. , Weitzel, Jeffrey N , Morgan, Todd M , Cheng, Heather H , Dicker, Adam P , Giri, Veda N. , Knudsen, Karen E. , Cooney, Kathleen A. , Toland, Amanda Ewart , Pritchard, Colin C. , Carroll, Peter R , Rahm, Alanna Kulchak , Taplin, Mary‐Ellen , Helfand, Brian T. , Morgans, Alicia K. , Burnett, Arthur L. “Bud” , Sartor, Oliver , Den, Robert B. , Loeb, Stacy , López, Ana María , Moreno, Jose, Myers, Ronald E. , Rebbeck, Timothy R. , Sandler, Howard M. , Scott, E. Michael D., Yu, Evan Y , Zeigler-Johnson, Charnita M

Journal of Clinical Oncology | June 9, 2020 | Volume: 38 | Issue: 24 | Pages: 2798-2811

10.1200/jco.20.00046 Get It

PURPOSE Germline testing (GT) is a central feature of prostate cancer (PCA) treatment, management, and hereditary cancer assessment. Critical needs include optimized multigene testing strategies that incorporate evolving genetic data, consistency in GT indications and management, and alternate genetic evaluation models that address the rising demand for genetic services. METHODS A multidisciplinary consensus conference that included experts, stakeholders, and national organization leaders was convened in response to current practice challenges and to develop a genetic implementation framework. Evidence review informed questions using the modified Delphi model. The final framework included criteria with strong (> 75%) agreement (Recommend) or moderate (50% to 74%) agreement (Consider). RESULTS Large germline panels and somatic testing were recommended for metastatic PCA. Reflex testing—initial testing of priority genes followed by expanded testing—was suggested for multiple scenarios. Metastatic disease or family history suggestive of hereditary PCA was recommended for GT. Additional family history and pathologic criteria garnered moderate consensus. Priority genes to test for metastatic disease treatment included BRCA2, BRCA1, and mismatch repair genes, with broader testing, such as ATM, for clinical trial eligibility. BRCA2 was recommended for active surveillance discussions. Screening starting at age 40 years or 10 years before the youngest PCA diagnosis in a family was recommended for BRCA2 carriers, with consideration in HOXB13, BRCA1, ATM, and mismatch repair carriers. Collaborative (point-of-care) evaluation models between health care and genetic providers was endorsed to address the genetic counseling shortage. The genetic evaluation framework included optimal pretest informed consent, post-test discussion, cascade testing, and technology-based approaches. CONCLUSION This multidisciplinary, consensus-driven PCA genetic implementation framework provides novel guidance to clinicians and patients tailored to the precision era. Multiple research, education, and policy needs remain of importance.
Characterization of PSMA and 18F-fluciclovine transporter gene expression in localized prostate cancer.
Alshalalfa, Mohammed , Zhao, Shuang G. , Herlemann, Annika , Mahal, Brandon A. , Kishan, Amar U. , Karnes, Jeffrey , Wong, Anthony , Feng, Felix Y. , Chu, Carissa Ellen , Sjöström, Martin , Zhao, Shuang G , Chou, Jonathan , Spratt, Daniel E. , Small, Eric J. , Porten, Sima P. , Hope, Thomas A. , Davicioni, Elai , Nguyen, Paul L. , Carroll, Peter R , Schaeffer, Edward M. , Cooperberg, Matthew R

Journal of Clinical Oncology | February 19, 2020 | Volume: 38 | Issue: 6_suppl | Pages: 295-295

10.1200/jco.2020.38.6_suppl.295 Get It

295 Background: While 18F-fluciclovine PET/CT is approved in the US and recommended by the NCCN, prostate-specific membrane antigen (PSMA) PET/CT is more common in Europe/Australia and recommended by the EAU. Less is known about the biology of lesions detected by either modality. 18F-fluciclovine PET relies on radiotracer uptake by amino acid transporters LAT1-4 and ASCT1-2. PSMA PET is dependent on surface expression of PSMA. We compared relative expression of PSMA and fluciclovine transporter genes in radical prostatectomy (RP) samples to determine their distribution across subtypes and correlation with outcomes. Methods: Gene expression data of 19,102 RP samples were analyzed using the Affymetrix Human Exon 1.0 ST microarray. 1,135 patients had long term follow up. Associations between expression of PSMA and fluciclovine transporter genes (LAT1-4 and ASCT1-2) and pathologic variables, molecular subtypes, and clinical outcomes were conducted. Results: All fluciclovine transporter genes (LAT 1-4, ASCT1-2) were expressed at lower levels than PSMA (p <0.0001). PSMA expression was positively correlated with genomic risk score and pathologic Gleason score (p<0.0001), but LAT2-3 and ASCT2 were inversely correlated with genomic risk in primary tumors (p<0.0001) and less expressed in GS 9-10 tumors (p<0.0001). PSMA expression was associated with worse metastasis-free survival (MFS) (HR 1.45, p=0.001) and lymph node involvement (HR 2.14, p<0.0001). Expression of LAT2, LAT3, ASCT2 expression was associated with better MFS (HR 0.85, 0.63, 0.74, p<0.0001-0.04). After multivariable adjustment, PSMA expression remained independently prognostic of poorer MFS (HR 1.3, p=0.028). Luminal B subtype was notable for PSMA overexpression; Luminal A was enriched in ASCT2 and LAT2 (p<0.0001). PSMA expression did not correlate with ERG fusion prostate cancers, but LAT2, ASCT1, and ASCT2 were overexpressed in ERG fusion negative tumors (p<0.0001). Conclusions: PSMA expression is associated with more aggressive disease and poorer clinical outcomes than fluciclovine transporter genes in localized prostate cancer. Molecular subtypes of prostate cancer vary in PSMA and fluciclovine transporter gene expression.
The Immune Landscape of Prostate Cancer and Nomination of PD-L2 as a Potential Therapeutic Target
Zhao, Shuang G. , Lehrer, Jonathan , Chang, S. Laura , Das, Rajdeep , Erho, Nicholas , Sjöström, Martin , Freedland, Stephen J. , Klein, Eric A. , Karnes, R. Jeffrey , Schaeffer, Edward M. , Xu, Melody, Speers, Corey , Nguyen, Paul L. , Ross, Ashley E. , Chan, June M. , Spratt, Daniel E. , Feng, Felix Y. , Speers, Corey , Spratt, Daniel E , Klein, Eric A , Zhao, Shuang G , Liu, Yang , Den, Robert B. , Cooperberg, Matthew R , Carroll, Peter R , Davicioni, Elai , Fong, Lawrence

JNCI: Journal of the National Cancer Institute | July 23, 2018 | Volume: 111 | Issue: 3 | Pages: 301-310

10.1093/jnci/djy141 Get It

Luminal and basal subtyping of prostate cancer.
Feng, Felix Y. , Zhao, Shuang G. , Erho, Nicholas , Lehrer, Jonathan , Alshalalfa, Mohammed , Ryan, Charles J. , Freedland, Stephen J. , Posadas, Edwin M. , Ross, Ashley E. , Karnes, Jeffrey , Zhao, Shuang G , Chang, S. Laura , Cooperberg, Matthew R , Kim, Won Bae , Den, Robert B. , Klein, Eric A. , Davicioni, Elai , Schaeffer, Edward M. , Nguyen, Paul L. , Carroll, Peter R , Spratt, Daniel E.

Journal of Clinical Oncology | March 29, 2017 | Volume: 35 | Issue: 6_suppl | Pages: 3-3

10.1200/jco.2017.35.6_suppl.3 Get It

3 Background: There is a clear need to develop a clinically relevant molecular subtyping approach for prostate cancer. We hypothesized that prostate cancer can be subtyped based on luminal versus basal lineage. Methods: We applied the PAM50 classifier, which is used clinically to identify luminal and basal cancers in breast cancer, to subtype a total of 3,782 prostate cancer samples using a high-density microarray platform run in a CLIA-certified laboratory. We examined the associations of these subtypes and clinical outcomes. Results: We demonstrate that PAM50 segregates prostate cancer into three reproducible subtypes in both retrospective cohorts and on prospective validation: luminal A (33.3%-34.3%), luminal B (28.5%-32.6%), and basal (34.1%-37.1%). Luminal B prostate cancers exhibited the worst clinical prognoses, followed by basal and luminal A subtypes (10-year biochemical recurrence-free survival: 29/39/41%; distant metastasis-free survival: 53/73/73%; prostate cancer-specific survival: 78/86/89%; overall survival: 69/80/82% respectively) on both univariable and multivariable analyses accounting for standard clinicopathologic prognostic factors. Known luminal lineage markers, such as NKX3.1 and KRT18, and the basal lineage CD49f signature, were enriched in luminal- and basal-like cancers respectively, demonstrating the connection between these subtypes and established prostate cancer biology. While both luminal-like subtypes were associated with increased AR expression and signaling, only luminal B prostate cancers were significantly associated with post-operative response to androgen deprivation therapy (ADT) in a subset analysis matching patients based on clinicopathologic variables (interaction p = 0.006, luminal B 10-year metastasis: 33% (treated) vs. 55% (untreated), non-luminal B: 37% (treated) vs. 21% (untreated)). Conclusions: These findings contribute novel insight into the biology of prostate cancer, and provide translatable clinical tools for personalizing post-operative ADT for patients with prostate cancer. Similar to breast cancer, these findings suggest that luminal/basal subtyping may be useful in treatment selection in prostate cancer.