Abstract 3520: Immunogenomic landscape of grade group 5 prostate cancer predicts risk of lethal outcomes and may inform treatment response

Introduction Prognostic and therapeutic implications of the immunogenomic landscape in poorly differentiated Grade Group 5 (GG5) prostate cancer (PCa) remains largely unknown. While novel treatment strategies including immuno-radiotherapy have been hypothesized to attenuate disease progression in ad...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Ill.), 2020-08, Vol.80 (16_Supplement), p.3520-3520
Hauptverfasser: Yamoah, Kosj, Awasthi, Shivanshu, Mahal, Brandon, Zhao, Shuang G., Abraham-Miranda, Julieta, Gerke, Travis A., Davicioni, Elai, Rounbehler, Robert J., Berglund, Anders E., Grass, Daniel G., Park, Jong Y., Pow-Sang, Julio M., Fernandez, Daniel, Jain, Rohit K., Schaeffer, Edward M., Freedland, Stephen, Spratt, Daniel E., Den, Robert B., Kohli, Manish, Rebbeck, Timothy R., Fang, Felix Y.
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Sprache:eng
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Zusammenfassung:Introduction Prognostic and therapeutic implications of the immunogenomic landscape in poorly differentiated Grade Group 5 (GG5) prostate cancer (PCa) remains largely unknown. While novel treatment strategies including immuno-radiotherapy have been hypothesized to attenuate disease progression in advanced PCa, limited data exist to show underlying mechanisms related to immunogenomcis and its role in the management of GG5 PCa. Method This retrospective analysis includes 822 PCa patients who underwent radical prostatectomy (RP) with pathologic GG5 disease. Immunogenomic interaction between the immune content score (ICS) and Decipher score was used to predict the metastasis and Prostate cancer specific mortality (PCSM). Immunogenomic interaction categories were used to assess patient response to radiation therapy, measured by the PORTOS score. Additionally, 135 biopsy based tumor samples were also used to validate the immunogenomic correlation between ICS and Decipher as well as the association with PORTOS score. A Kruskal-Wallis test was used to compare median scores whereas methods of survival analysis were used for time dependent endpoints. Principal component analysis (PCA) was used to show sample clustering based on PORTOS score. Results Among GG5 patients 64.8% had high Decipher risk score (> 0.60) whereas 35.5% had low-average risk score (≤ 0.60). When comparing Decipher risk categories with ICS, a linear association was observed with the highest ICS quartile showing the highest Decipher score (Spearman's correlation 0.23, p < 2.4e−11). In a multivariable model, high Decipher score was associated with risk metastasis (HR = 1.63, 95% CI: 1.12 - 2.37, p = 0.01) and PCSM (HR = 1.61, 95% CI: 0.93 – 2.78, p = 0.08) whereas high ICS did not show significant effect on lethal outcomes. However, in the interaction model, effect of decipher on lethal outcomes was augmented in relation with higher ICS. Patients with ICSHigh and DecipherHigh showed significantly higher risk of metastasis (HR = 3.29, 95% CI: 1.53 - 7.07, p = 0.002) and PCSM (HR = 4.15, 95% CI: 1.55 - 11.0, p = 0.004). Additionally, ICSHigh and DecipherHigh also showed higher PORTOS score compared to those with ICSLow and DecipherLow (p < 2.2e−16). Similar to RP cases, in the validation biopsy data Decipher score and ICS were associated (p = 0.01). Likewise, the association of immunogenomic categories with PORTOS score was also consistent in the validation dataset (p = 0.0002). PCA in both RP and va
ISSN:0008-5472
1538-7445
DOI:10.1158/1538-7445.AM2020-3520