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 language | English (US) |
|---|---|
| Pages (from-to) | 125-132 |
| Number of pages | 8 |
| Journal | Journal of Urology |
| Volume | 182 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jul 2009 |
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Keywords
- androgen
- biological markers
- biopsy
- prostate
- prostatic neoplasms
- receptors
ASJC Scopus subject areas
- Urology
Cite this
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 journal › Article
}
TY - JOUR
T1 - Personalized Prediction of Tumor Response and Cancer Progression on Prostate Needle Biopsy
AU - Donovan, Michael J.
AU - Khan, Faisal M.
AU - Fernandez, Gerardo
AU - Mesa-Tejada, Ricardo
AU - Sapir, Marina
AU - Zubek, Valentina Bayer
AU - Powell, Douglas
AU - Fogarasi, Stephen
AU - Vengrenyuk, Yevgen
AU - Teverovskiy, Mikhail
AU - Segal, Mark R.
AU - Karnes, Robert Jeffrey
AU - Gaffey, Thomas A.
AU - Busch, Christer
AU - Haggman, Michael
AU - Hlavcak, Peter
AU - Freedland, Stephen J.
AU - Vollmer, Robin T.
AU - Albertsen, Peter
AU - Costa, Jose
AU - Cordon-Cardo, Carlos
PY - 2009/7
Y1 - 2009/7
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.
AB - 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.
KW - androgen
KW - biological markers
KW - biopsy
KW - prostate
KW - prostatic neoplasms
KW - receptors
UR - http://www.scopus.com/inward/record.url?scp=67349084186&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=67349084186&partnerID=8YFLogxK
U2 - 10.1016/j.juro.2009.02.135
DO - 10.1016/j.juro.2009.02.135
M3 - Article
C2 - 19450827
AN - SCOPUS:67349084186
VL - 182
SP - 125
EP - 132
JO - Journal of Urology
JF - Journal of Urology
SN - 0022-5347
IS - 1
ER -