Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy

Michael J. Donovan, Faisal M. Khan, Gerardo Fernandez, Ricardo Mesa-Tejada, Marina Sapir, Valentina Bayer Zubek, Douglas Powell, Stephen Fogarasi, Yevgen Vengrenyuk, Mikhail Teverovskiy, Mark R. Segal, Robert Jeffrey Karnes, Thomas A. Gaffey, Christer Busch, Michael Haggman, Peter Hlavcak, Stephen J. Freedland, Robin T. Vollmer, Peter Albertsen, Jose CostaCarlos Cordon-Cardo

Research output: Contribution to journalArticle

39 Citations (Scopus)

Abstract

Purpose: To our knowledge in patients with prostate cancer there are no available tests except clinical variables to determine the likelihood of disease progression. We developed a patient specific, biology driven tool to predict outcome at diagnosis. We also investigated whether biopsy androgen receptor levels predict a durable response to therapy after secondary treatment. Materials and Methods: We evaluated paraffin embedded prostate needle biopsy tissue from 1,027 patients with cT1c-T3 prostate cancer treated with surgery and followed a median of 8 years. Machine learning was done to integrate clinical data with biopsy quantitative biometric features. Multivariate models were constructed to predict disease progression with the C index to estimate performance. Results: In a training set of 686 patients (total of 87 progression events) 3 clinical and 3 biopsy tissue characteristics were identified to predict clinical progression within 8 years after prostatectomy with 78% sensitivity, 69% specificity, a C index of 0.74 and a HR of 5.12. Validation in an independent cohort of 341 patients (total of 44 progression events) yielded 76% sensitivity, 64% specificity, a C index of 0.73 and a HR of 3.47. Increased androgen receptor in tumor cells in the biopsy highly significantly predicted resistance to therapy, ie androgen ablation with or without salvage radiotherapy, and clinical failure (p <0.0001). Conclusions: Morphometry reliably classifies Gleason pattern 3 tumors. When combined with biomarker data, it adds to the hematoxylin and eosin analysis, and prostate specific antigen values currently used to assess outcome at diagnosis. Biopsy androgen receptor levels predict the likelihood of a response to therapy after recurrence and may guide future treatment decisions.

Original languageEnglish (US)
Pages (from-to)125-132
Number of pages8
JournalJournal of Urology
Volume182
Issue number1
DOIs
StatePublished - Jul 2009

Fingerprint

Needle Biopsy
Prostate
Biopsy
Androgen Receptors
Neoplasms
Disease Progression
Prostatic Neoplasms
Therapeutics
Sensitivity and Specificity
Hematoxylin
Eosine Yellowish-(YS)
Prostate-Specific Antigen
Prostatectomy
Paraffin
Androgens
Radiotherapy
Biomarkers
Recurrence

Keywords

  • androgen
  • biological markers
  • biopsy
  • prostate
  • prostatic neoplasms
  • receptors

ASJC Scopus subject areas

  • Urology

Cite this

Donovan, M. J., Khan, F. M., Fernandez, G., Mesa-Tejada, R., Sapir, M., Zubek, V. B., ... Cordon-Cardo, C. (2009). Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy. Journal of Urology, 182(1), 125-132. https://doi.org/10.1016/j.juro.2009.02.135

Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy. / Donovan, Michael J.; Khan, Faisal M.; Fernandez, Gerardo; Mesa-Tejada, Ricardo; Sapir, Marina; Zubek, Valentina Bayer; Powell, Douglas; Fogarasi, Stephen; Vengrenyuk, Yevgen; Teverovskiy, Mikhail; Segal, Mark R.; Karnes, Robert Jeffrey; Gaffey, Thomas A.; Busch, Christer; Haggman, Michael; Hlavcak, Peter; Freedland, Stephen J.; Vollmer, Robin T.; Albertsen, Peter; Costa, Jose; Cordon-Cardo, Carlos.

In: Journal of Urology, Vol. 182, No. 1, 07.2009, p. 125-132.

Research output: Contribution to journalArticle

Donovan, MJ, Khan, FM, Fernandez, G, Mesa-Tejada, R, Sapir, M, Zubek, VB, Powell, D, Fogarasi, S, Vengrenyuk, Y, Teverovskiy, M, Segal, MR, Karnes, RJ, Gaffey, TA, Busch, C, Haggman, M, Hlavcak, P, Freedland, SJ, Vollmer, RT, Albertsen, P, Costa, J & Cordon-Cardo, C 2009, 'Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy', Journal of Urology, vol. 182, no. 1, pp. 125-132. https://doi.org/10.1016/j.juro.2009.02.135
Donovan MJ, Khan FM, Fernandez G, Mesa-Tejada R, Sapir M, Zubek VB et al. Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy. Journal of Urology. 2009 Jul;182(1):125-132. https://doi.org/10.1016/j.juro.2009.02.135
Donovan, Michael J. ; Khan, Faisal M. ; Fernandez, Gerardo ; Mesa-Tejada, Ricardo ; Sapir, Marina ; Zubek, Valentina Bayer ; Powell, Douglas ; Fogarasi, Stephen ; Vengrenyuk, Yevgen ; Teverovskiy, Mikhail ; Segal, Mark R. ; Karnes, Robert Jeffrey ; Gaffey, Thomas A. ; Busch, Christer ; Haggman, Michael ; Hlavcak, Peter ; Freedland, Stephen J. ; Vollmer, Robin T. ; Albertsen, Peter ; Costa, Jose ; Cordon-Cardo, Carlos. / Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy. In: Journal of Urology. 2009 ; Vol. 182, No. 1. pp. 125-132.
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AU - Sapir, Marina

AU - Zubek, Valentina Bayer

AU - Powell, Douglas

AU - Fogarasi, Stephen

AU - Vengrenyuk, Yevgen

AU - Teverovskiy, Mikhail

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AU - Karnes, Robert Jeffrey

AU - Gaffey, Thomas A.

AU - Busch, Christer

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AU - Hlavcak, Peter

AU - Freedland, Stephen J.

AU - Vollmer, Robin T.

AU - Albertsen, Peter

AU - Costa, Jose

AU - Cordon-Cardo, Carlos

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N2 - Purpose: To our knowledge in patients with prostate cancer there are no available tests except clinical variables to determine the likelihood of disease progression. We developed a patient specific, biology driven tool to predict outcome at diagnosis. We also investigated whether biopsy androgen receptor levels predict a durable response to therapy after secondary treatment. Materials and Methods: We evaluated paraffin embedded prostate needle biopsy tissue from 1,027 patients with cT1c-T3 prostate cancer treated with surgery and followed a median of 8 years. Machine learning was done to integrate clinical data with biopsy quantitative biometric features. Multivariate models were constructed to predict disease progression with the C index to estimate performance. Results: In a training set of 686 patients (total of 87 progression events) 3 clinical and 3 biopsy tissue characteristics were identified to predict clinical progression within 8 years after prostatectomy with 78% sensitivity, 69% specificity, a C index of 0.74 and a HR of 5.12. Validation in an independent cohort of 341 patients (total of 44 progression events) yielded 76% sensitivity, 64% specificity, a C index of 0.73 and a HR of 3.47. Increased androgen receptor in tumor cells in the biopsy highly significantly predicted resistance to therapy, ie androgen ablation with or without salvage radiotherapy, and clinical failure (p <0.0001). Conclusions: Morphometry reliably classifies Gleason pattern 3 tumors. When combined with biomarker data, it adds to the hematoxylin and eosin analysis, and prostate specific antigen values currently used to assess outcome at diagnosis. Biopsy androgen receptor levels predict the likelihood of a response to therapy after recurrence and may guide future treatment decisions.

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