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Transcriptomic heterogeneity in multifocal prostate cancer
Simpa S. Salami, Daniel H. Hovelson, Jeremy B. Kaplan, Romain Mathieu, Aaron M. Udager, Nicole E. Curci, Matthew Lee, Komal R. Plouffe, Lorena Lazo de la Vega, Martin Susani, Nathalie Rioux-Leclercq, Daniel E. Spratt, Todd M. Morgan, Matthew S. Davenport, Arul M. Chinnaiyan, Joanna Cyrta, Mark A. Rubin, Shahrokh F. Shariat, Scott A. Tomlins, Ganesh S. Palapattu
Simpa S. Salami, Daniel H. Hovelson, Jeremy B. Kaplan, Romain Mathieu, Aaron M. Udager, Nicole E. Curci, Matthew Lee, Komal R. Plouffe, Lorena Lazo de la Vega, Martin Susani, Nathalie Rioux-Leclercq, Daniel E. Spratt, Todd M. Morgan, Matthew S. Davenport, Arul M. Chinnaiyan, Joanna Cyrta, Mark A. Rubin, Shahrokh F. Shariat, Scott A. Tomlins, Ganesh S. Palapattu
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Clinical Research and Public Health Oncology

Transcriptomic heterogeneity in multifocal prostate cancer

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Abstract

BACKGROUND. Commercial gene expression assays are guiding clinical decision making in patients with prostate cancer, particularly when considering active surveillance. Given heterogeneity and multifocality of primary prostate cancer, such assays should ideally be robust to the coexistence of unsampled higher grade disease elsewhere in the prostate in order to have clinical utility. Herein, we comprehensively evaluated transcriptomic profiles of primary multifocal prostate cancer to assess robustness to clinically relevant multifocality. METHODS. We designed a comprehensive, multiplexed targeted RNA-sequencing assay capable of assessing multiple transcriptional classes and deriving commercially available prognostic signatures, including the Myriad Prolaris Cell Cycle Progression score, the Oncotype DX Genomic Prostate Score, and the GenomeDX Decipher Genomic Classifier. We applied this assay to a retrospective, multi-institutional cohort of 156 prostate cancer samples. Derived commercial biomarker scores for 120 informative primary prostate cancer samples from 44 cases were determined and compared. RESULTS. Derived expression scores were positively correlated with tumor grade (rS = 0.53–0.73; all P < 0.001), both within the same case and across the entire cohort. In cases of extreme grade-discordant multifocality (co-occurrence of grade group 1 [GG1] and ≥GG4 foci], gene expression scores were significantly lower in low- (GG1) versus high-grade (≥GG4) foci (all P < 0.001). No significant differences in expression scores, however, were observed between GG1 foci from prostates with and without coexisting higher grade cancer (all P > 0.05). CONCLUSIONS. Multifocal, low-grade and high-grade prostate cancer foci exhibit distinct prognostic expression signatures. These findings demonstrate that prognostic RNA expression assays performed on low-grade prostate cancer biopsy tissue may not provide meaningful information on the presence of coexisting unsampled aggressive disease. FUNDING. Prostate Cancer Foundation, National Institutes of Health (U01 CA214170, R01 CA183857, University of Michigan Prostate Specialized Program of Research Excellence [S.P.O.R.E.] P50 CA186786-05, Weill Cornell Medicine S.P.O.R.E. P50 CA211024-01A1), Men of Michigan Prostate Cancer Research Fund, University of Michigan Comprehensive Cancer Center core grant (2-P30-CA-046592-24), A. Alfred Taubman Biomedical Research Institute, and Department of Defense.

Authors

Simpa S. Salami, Daniel H. Hovelson, Jeremy B. Kaplan, Romain Mathieu, Aaron M. Udager, Nicole E. Curci, Matthew Lee, Komal R. Plouffe, Lorena Lazo de la Vega, Martin Susani, Nathalie Rioux-Leclercq, Daniel E. Spratt, Todd M. Morgan, Matthew S. Davenport, Arul M. Chinnaiyan, Joanna Cyrta, Mark A. Rubin, Shahrokh F. Shariat, Scott A. Tomlins, Ganesh S. Palapattu

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Figure 2

Derivation and assessment of clinically available prognostic signatures.

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Derivation and assessment of clinically available prognostic signatures....
(A) mxRNAseq-derived CCP (mxCCP), Decipher Genomic Classifier (mxGC), and Oncotype Dx GPS (mxGPS) scores are plotted stratified by grade group (GG1–5) for 125 FFPE primary prostate cancer tissue samples. Derived scores significantly increase with ascending GG (Spearman rank [rs] correlation, and 1-sided ANOVA P values are shown). (B) Due to both intratumoral grade heterogeneity as well as true multifocality, diagnostic prostate biopsy sampling of only low-grade prostate cancer (GG1, yellow) may reflect a lack of high-grade (HG) tumor component (top), undersampling of a high-grade (blue) component (GG2 or GG3 tumor focus, middle), or unsampling of a separate high-grade prostate cancer focus (bottom). As the most concerning scenario for a patient considering active surveillance (AS) is the latter, we tested the robustness of derived prognostic scores from GG1 to multifocality through several analyses. (C) Derived prognostic scores do not differ between GG1 prostate cancer when present in isolation or when other HG tumor foci are present. Derived prognostic mxCCP, mxGC, and mxGPS scores were plotted from samples of pT2 GG1 prostate cancer without HG foci (clinically indolent, light brown, n = 8 from 6 cases) versus scores from GG1 prostate cancer foci (n = 21 from 15 cases) where other HG foci were present. No significant differences between the 2 groups for any derived prognostic score were observed (2-sample, unpaired 2-sided t test P values are shown). (D) Derived prognostic scores differ between GG1 prostate cancer foci and concurrent HG foci. Derived prognostic scores were plotted for all samples from the 15 cases from C where samples were taken from both GG1 prostate cancer foci as well as other concurrent higher grade foci. Samples were stratified by the GG of the profiled component. Spearman rank (rs) correlation and 1-sided ANOVA P values for scores stratified by GG are shown, demonstrating significantly increased derived prognostic scores by GG of the profiled component (similar to findings from our entire cohort, including these samples as shown in Supplemental Figure 7C).

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