Improved prediction of prostate cancer recurrence through systems pathology Journal Article

Authors: Cordon-Cardo, C.; Kotsianti, A.; Verbel, D. A.; Teverovskiy, M.; Capodieci, P.; Hamann, S.; Jeffers, Y.; Clayton, M.; Elkhettabi, F.; Khan, F. M.; Sapir, M.; Bayer-Zubek, V.; Vengrenyuk, Y.; Fogarsi, S.; Saidi, O.; Reuter, V. E.; Scher, H. I.; Kattan, M. W.; Bianco, F. J. Jr; Wheeler, T. M.; Ayala, G. E.; Scardino, P. T.; Donovan, M. J.
Article Title: Improved prediction of prostate cancer recurrence through systems pathology
Abstract: We have developed an integrated, multidisciplinary methodology, termed systems pathology, to generate highly accurate predictive tools for complex diseases, using prostate cancer for the prototype. To predict the recurrence of prostate cancer following radical prostatectomy, defined by rising serum prostate-specific antigen (PSA), we used machine learning to develop a model based on clinicopathologic variables, histologic tumor characteristics, and cell type-specific quantification of biomarkers. The initial study was based on a cohort of 323 patients and identified that high levels of the androgen receptor, as detected by immunohistochemistry, were associated with a reduced time to PSA recurrence. The model predicted recurrence with high accuracy, as indicated by a concordance index in the validation set of 0.82, sensitivity of 96%, and specificity of 72%. We extended this approach, employing quantitative multiplex immunofluorescence, on an expanded cohort of 682 patients. The model again predicted PSA recurrence with high accuracy, concordance index being 0.77, sensitivity of 77% and specificity of 72%. The androgen receptor was selected, along with 5 clinicopathologic features (seminal vesicle invasion, biopsy Gleason score, extracapsular extension, preoperative PSA, and dominant prostatectomy Gleason grade) as well as 2 histologic features (texture of epithelial nuclei and cytoplasm in tumor only regions). This robust platform has broad applications in patient diagnosis, treatment management, and prognostication.
Keywords: immunohistochemistry; adult; controlled study; human tissue; aged; disease-free survival; survival rate; human cell; major clinical study; cancer recurrence; sensitivity and specificity; biological marker; prostate specific antigen; neoplasm recurrence, local; models, biological; immunofluorescence; pathology; cell type; prostate cancer; gleason score; prostate-specific antigen; prostatic neoplasms; prostatectomy; tissue array analysis; androgen receptor; cell nucleus; receptors, androgen; kaplan meier method; seminal vesicle; systems biology
Journal Title: Journal of Clinical Investigation
Volume: 117
Issue: 7
ISSN: 0021-9738
Publisher: American Society for Clinical Investigation  
Date Published: 2007-07-01
Start Page: 1876
End Page: 1883
Language: English
DOI: 10.1172/jci31399
PUBMED: 17557117
PROVIDER: scopus
PMCID: PMC1884691
Notes: --- - "Cited By (since 1996): 46" - "Export Date: 17 November 2011" - "CODEN: JCINA" - "Source: Scopus"
Citation Impact
MSK Authors
  1. Peter T Scardino
    636 Scardino
  2. Victor Reuter
    1073 Reuter
  3. Howard Scher
    979 Scher
  4. Fernando J Bianco
    72 Bianco
  5. Michael W Kattan
    218 Kattan