Tristetraprolin is a prognostic biomarker for poor outcomes among patients with low-grade prostate cancer

Robert J. Rounbehler, Anders E. Berglund, Travis Gerke, Mandeep M. Takhar, Shivanshu Awasthi, Weimin Li, Elai Davicioni, Nicholas G. Erho, Ashley E. Ross, Edward M. Schaeffer, Eric A. Klein, Robert Jeffrey Karnes, Robert Brian Jenkins, John L. Cleveland, Jong Y. Park, Kosj Yamoah

Research output: Contribution to journalArticle

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Abstract

Background: We studied the utility of the tumor suppressor Tristetraprolin (TTP, ZFP36) as a clinically relevant biomarker of aggressive disease in prostate cancer patients after radical prostatectomy (RP). Methods: TTP RNA expression was measured in an RP cohort of patients treated at Moffitt Cancer Center (MCC) and obtained from six publically available RP datasets with biochemical recurrence (BCR; total n = 1,394) and/or metastatic outcome data (total n = 1,222). TTP protein expression was measured by immunohistochemistry in a tissue microarray of 153 MCC RP samples. The time to BCR or metastasis based on TTP RNA or protein levels was calculated using the Kaplan-Meier analysis. Univariable and multivariable Cox proportional hazard models were performed on multiple cohorts to evaluate if TTP is a clinically relevant biomarker and to assess if TTP improves upon the Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score for predicting clinical outcomes. Results: In all of the RP patient cohorts, prostate cancer with low TTP RNA or protein levels had decreased time to BCR or metastasis versus TTP-high tumors. Further, the decreased time to BCR in TTP-low prostate cancer was more pronounced in low-grade tumors. Finally, pooled survival analysis suggests that TTP RNA expression provides independent information beyond CAPRA-S to predict BCR. Conclusions: TTP is a promising prostate cancer biomarker for predicting which RP patients will have poor outcomes, especially for low-grade prostate cancer patients. Impact: This study suggests that TTP RNA expression can be used to enhance the accuracy of CAPRA-S to predict outcomes in patients treated with RP.

Original languageEnglish (US)
Pages (from-to)1376-1383
Number of pages8
JournalCancer Epidemiology Biomarkers and Prevention
Volume27
Issue number11
DOIs
StatePublished - Nov 1 2018

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Tristetraprolin
Prostatic Neoplasms
Biomarkers
Prostatectomy
RNA
Neoplasms
thymidine 5'-triphosphate
Neoplasm Metastasis
Proteins
Kaplan-Meier Estimate
Survival Analysis
Tumor Biomarkers

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

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Tristetraprolin is a prognostic biomarker for poor outcomes among patients with low-grade prostate cancer. / Rounbehler, Robert J.; Berglund, Anders E.; Gerke, Travis; Takhar, Mandeep M.; Awasthi, Shivanshu; Li, Weimin; Davicioni, Elai; Erho, Nicholas G.; Ross, Ashley E.; Schaeffer, Edward M.; Klein, Eric A.; Karnes, Robert Jeffrey; Jenkins, Robert Brian; Cleveland, John L.; Park, Jong Y.; Yamoah, Kosj.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 27, No. 11, 01.11.2018, p. 1376-1383.

Research output: Contribution to journalArticle

Rounbehler, RJ, Berglund, AE, Gerke, T, Takhar, MM, Awasthi, S, Li, W, Davicioni, E, Erho, NG, Ross, AE, Schaeffer, EM, Klein, EA, Karnes, RJ, Jenkins, RB, Cleveland, JL, Park, JY & Yamoah, K 2018, 'Tristetraprolin is a prognostic biomarker for poor outcomes among patients with low-grade prostate cancer', Cancer Epidemiology Biomarkers and Prevention, vol. 27, no. 11, pp. 1376-1383. https://doi.org/10.1158/1055-9965.EPI-18-0369
Rounbehler, Robert J. ; Berglund, Anders E. ; Gerke, Travis ; Takhar, Mandeep M. ; Awasthi, Shivanshu ; Li, Weimin ; Davicioni, Elai ; Erho, Nicholas G. ; Ross, Ashley E. ; Schaeffer, Edward M. ; Klein, Eric A. ; Karnes, Robert Jeffrey ; Jenkins, Robert Brian ; Cleveland, John L. ; Park, Jong Y. ; Yamoah, Kosj. / Tristetraprolin is a prognostic biomarker for poor outcomes among patients with low-grade prostate cancer. In: Cancer Epidemiology Biomarkers and Prevention. 2018 ; Vol. 27, No. 11. pp. 1376-1383.
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title = "Tristetraprolin is a prognostic biomarker for poor outcomes among patients with low-grade prostate cancer",
abstract = "Background: We studied the utility of the tumor suppressor Tristetraprolin (TTP, ZFP36) as a clinically relevant biomarker of aggressive disease in prostate cancer patients after radical prostatectomy (RP). Methods: TTP RNA expression was measured in an RP cohort of patients treated at Moffitt Cancer Center (MCC) and obtained from six publically available RP datasets with biochemical recurrence (BCR; total n = 1,394) and/or metastatic outcome data (total n = 1,222). TTP protein expression was measured by immunohistochemistry in a tissue microarray of 153 MCC RP samples. The time to BCR or metastasis based on TTP RNA or protein levels was calculated using the Kaplan-Meier analysis. Univariable and multivariable Cox proportional hazard models were performed on multiple cohorts to evaluate if TTP is a clinically relevant biomarker and to assess if TTP improves upon the Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score for predicting clinical outcomes. Results: In all of the RP patient cohorts, prostate cancer with low TTP RNA or protein levels had decreased time to BCR or metastasis versus TTP-high tumors. Further, the decreased time to BCR in TTP-low prostate cancer was more pronounced in low-grade tumors. Finally, pooled survival analysis suggests that TTP RNA expression provides independent information beyond CAPRA-S to predict BCR. Conclusions: TTP is a promising prostate cancer biomarker for predicting which RP patients will have poor outcomes, especially for low-grade prostate cancer patients. Impact: This study suggests that TTP RNA expression can be used to enhance the accuracy of CAPRA-S to predict outcomes in patients treated with RP.",
author = "Rounbehler, {Robert J.} and Berglund, {Anders E.} and Travis Gerke and Takhar, {Mandeep M.} and Shivanshu Awasthi and Weimin Li and Elai Davicioni and Erho, {Nicholas G.} and Ross, {Ashley E.} and Schaeffer, {Edward M.} and Klein, {Eric A.} and Karnes, {Robert Jeffrey} and Jenkins, {Robert Brian} and Cleveland, {John L.} and Park, {Jong Y.} and Kosj Yamoah",
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T1 - Tristetraprolin is a prognostic biomarker for poor outcomes among patients with low-grade prostate cancer

AU - Rounbehler, Robert J.

AU - Berglund, Anders E.

AU - Gerke, Travis

AU - Takhar, Mandeep M.

AU - Awasthi, Shivanshu

AU - Li, Weimin

AU - Davicioni, Elai

AU - Erho, Nicholas G.

AU - Ross, Ashley E.

AU - Schaeffer, Edward M.

AU - Klein, Eric A.

AU - Karnes, Robert Jeffrey

AU - Jenkins, Robert Brian

AU - Cleveland, John L.

AU - Park, Jong Y.

AU - Yamoah, Kosj

PY - 2018/11/1

Y1 - 2018/11/1

N2 - Background: We studied the utility of the tumor suppressor Tristetraprolin (TTP, ZFP36) as a clinically relevant biomarker of aggressive disease in prostate cancer patients after radical prostatectomy (RP). Methods: TTP RNA expression was measured in an RP cohort of patients treated at Moffitt Cancer Center (MCC) and obtained from six publically available RP datasets with biochemical recurrence (BCR; total n = 1,394) and/or metastatic outcome data (total n = 1,222). TTP protein expression was measured by immunohistochemistry in a tissue microarray of 153 MCC RP samples. The time to BCR or metastasis based on TTP RNA or protein levels was calculated using the Kaplan-Meier analysis. Univariable and multivariable Cox proportional hazard models were performed on multiple cohorts to evaluate if TTP is a clinically relevant biomarker and to assess if TTP improves upon the Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score for predicting clinical outcomes. Results: In all of the RP patient cohorts, prostate cancer with low TTP RNA or protein levels had decreased time to BCR or metastasis versus TTP-high tumors. Further, the decreased time to BCR in TTP-low prostate cancer was more pronounced in low-grade tumors. Finally, pooled survival analysis suggests that TTP RNA expression provides independent information beyond CAPRA-S to predict BCR. Conclusions: TTP is a promising prostate cancer biomarker for predicting which RP patients will have poor outcomes, especially for low-grade prostate cancer patients. Impact: This study suggests that TTP RNA expression can be used to enhance the accuracy of CAPRA-S to predict outcomes in patients treated with RP.

AB - Background: We studied the utility of the tumor suppressor Tristetraprolin (TTP, ZFP36) as a clinically relevant biomarker of aggressive disease in prostate cancer patients after radical prostatectomy (RP). Methods: TTP RNA expression was measured in an RP cohort of patients treated at Moffitt Cancer Center (MCC) and obtained from six publically available RP datasets with biochemical recurrence (BCR; total n = 1,394) and/or metastatic outcome data (total n = 1,222). TTP protein expression was measured by immunohistochemistry in a tissue microarray of 153 MCC RP samples. The time to BCR or metastasis based on TTP RNA or protein levels was calculated using the Kaplan-Meier analysis. Univariable and multivariable Cox proportional hazard models were performed on multiple cohorts to evaluate if TTP is a clinically relevant biomarker and to assess if TTP improves upon the Cancer of the Prostate Risk Assessment postsurgical (CAPRA-S) score for predicting clinical outcomes. Results: In all of the RP patient cohorts, prostate cancer with low TTP RNA or protein levels had decreased time to BCR or metastasis versus TTP-high tumors. Further, the decreased time to BCR in TTP-low prostate cancer was more pronounced in low-grade tumors. Finally, pooled survival analysis suggests that TTP RNA expression provides independent information beyond CAPRA-S to predict BCR. Conclusions: TTP is a promising prostate cancer biomarker for predicting which RP patients will have poor outcomes, especially for low-grade prostate cancer patients. Impact: This study suggests that TTP RNA expression can be used to enhance the accuracy of CAPRA-S to predict outcomes in patients treated with RP.

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U2 - 10.1158/1055-9965.EPI-18-0369

DO - 10.1158/1055-9965.EPI-18-0369

M3 - Article

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SP - 1376

EP - 1383

JO - Cancer Epidemiology Biomarkers and Prevention

JF - Cancer Epidemiology Biomarkers and Prevention

SN - 1055-9965

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