Prognostic value of tissue-based biomarker signature in clear cell renal cell carcinoma

Ahmed Q. Haddad, Jun Hang Luo, Laura Maria Krabbe, Oussama Darwish, Bishoy Gayed, Ramy Youssef, Payal Kapur, Dinesh Rakheja, Yair Lotan, Arthur I Sagalowsky, Vitaly Margulis

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

Objective: To improve risk stratification for recurrence prognostication in patients with localised clear cell renal cell carcinoma (ccRCC). Patients and Methods: In all, 367 patients with non-metastatic ccRCC were included. The cohort was divided into a training and validation set. Using tissue microarrays, immunostaining was performed for 24 biomarkers representative of key pathways in ccRCC. Using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we identified several markers that were used to construct a risk classifier for risk of disease recurrence. Results: The median (interquartile range) follow-up was 63.5 (24.0-85.3) months. Five out of 24 markers were selected by LASSO Cox regression for the risk classifier: N-cadherin, E-cadherin, Ki67, cyclin D1 and phosphorylated eukaryotic initiation factor 4E binding protein-1 (p-4EBP1). Patients were classified as either low, intermediate or high risk of disease recurrence by tertiles of risk score. The 5-year recurrence-free survival (RFS) was 93.8%, 87.7% and 70% for patients with low-, intermediate- and high-risk scores, respectively (P < 0.001). Patients with a high marker score had worse RFS on multivariate analysis adjusted for age, gender, race and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score (hazard ratio 3.66, 95% confidence interval 1.58-8.49, P = 0.003 for high vs low marker score in the overall cohort). The five-marker classifier increased the concordance index of the clinical model in both the training and validation sets. Conclusion: We developed a five-marker-based prognostic tool that can effectively classify patients with ccRCC according to risk of disease recurrence after surgery. This tool, if prospectively validated, could provide individualised risk estimation for patients with ccRCC.

Original languageEnglish (US)
JournalBJU International
DOIs
StateAccepted/In press - 2017

Fingerprint

Renal Cell Carcinoma
Biomarkers
Recurrence
Cadherins
Eukaryotic Initiation Factor-4E
Survival
Cyclin D1
Carrier Proteins
Necrosis
Multivariate Analysis
Confidence Intervals

Keywords

  • Biomarkers
  • Cell cycle
  • Epithelial mesenchymal transition
  • Mammalian target of rapamycin
  • Prognosis
  • Renal cell carcinoma

ASJC Scopus subject areas

  • Urology

Cite this

Prognostic value of tissue-based biomarker signature in clear cell renal cell carcinoma. / Haddad, Ahmed Q.; Luo, Jun Hang; Krabbe, Laura Maria; Darwish, Oussama; Gayed, Bishoy; Youssef, Ramy; Kapur, Payal; Rakheja, Dinesh; Lotan, Yair; Sagalowsky, Arthur I; Margulis, Vitaly.

In: BJU International, 2017.

Research output: Contribution to journalArticle

@article{3ae025ba4c2a42dd9b85540d0b0192bc,
title = "Prognostic value of tissue-based biomarker signature in clear cell renal cell carcinoma",
abstract = "Objective: To improve risk stratification for recurrence prognostication in patients with localised clear cell renal cell carcinoma (ccRCC). Patients and Methods: In all, 367 patients with non-metastatic ccRCC were included. The cohort was divided into a training and validation set. Using tissue microarrays, immunostaining was performed for 24 biomarkers representative of key pathways in ccRCC. Using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we identified several markers that were used to construct a risk classifier for risk of disease recurrence. Results: The median (interquartile range) follow-up was 63.5 (24.0-85.3) months. Five out of 24 markers were selected by LASSO Cox regression for the risk classifier: N-cadherin, E-cadherin, Ki67, cyclin D1 and phosphorylated eukaryotic initiation factor 4E binding protein-1 (p-4EBP1). Patients were classified as either low, intermediate or high risk of disease recurrence by tertiles of risk score. The 5-year recurrence-free survival (RFS) was 93.8{\%}, 87.7{\%} and 70{\%} for patients with low-, intermediate- and high-risk scores, respectively (P < 0.001). Patients with a high marker score had worse RFS on multivariate analysis adjusted for age, gender, race and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score (hazard ratio 3.66, 95{\%} confidence interval 1.58-8.49, P = 0.003 for high vs low marker score in the overall cohort). The five-marker classifier increased the concordance index of the clinical model in both the training and validation sets. Conclusion: We developed a five-marker-based prognostic tool that can effectively classify patients with ccRCC according to risk of disease recurrence after surgery. This tool, if prospectively validated, could provide individualised risk estimation for patients with ccRCC.",
keywords = "Biomarkers, Cell cycle, Epithelial mesenchymal transition, Mammalian target of rapamycin, Prognosis, Renal cell carcinoma",
author = "Haddad, {Ahmed Q.} and Luo, {Jun Hang} and Krabbe, {Laura Maria} and Oussama Darwish and Bishoy Gayed and Ramy Youssef and Payal Kapur and Dinesh Rakheja and Yair Lotan and Sagalowsky, {Arthur I} and Vitaly Margulis",
year = "2017",
doi = "10.1111/bju.13776",
language = "English (US)",
journal = "BJU International",
issn = "1464-4096",
publisher = "Wiley-Blackwell",

}

TY - JOUR

T1 - Prognostic value of tissue-based biomarker signature in clear cell renal cell carcinoma

AU - Haddad, Ahmed Q.

AU - Luo, Jun Hang

AU - Krabbe, Laura Maria

AU - Darwish, Oussama

AU - Gayed, Bishoy

AU - Youssef, Ramy

AU - Kapur, Payal

AU - Rakheja, Dinesh

AU - Lotan, Yair

AU - Sagalowsky, Arthur I

AU - Margulis, Vitaly

PY - 2017

Y1 - 2017

N2 - Objective: To improve risk stratification for recurrence prognostication in patients with localised clear cell renal cell carcinoma (ccRCC). Patients and Methods: In all, 367 patients with non-metastatic ccRCC were included. The cohort was divided into a training and validation set. Using tissue microarrays, immunostaining was performed for 24 biomarkers representative of key pathways in ccRCC. Using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we identified several markers that were used to construct a risk classifier for risk of disease recurrence. Results: The median (interquartile range) follow-up was 63.5 (24.0-85.3) months. Five out of 24 markers were selected by LASSO Cox regression for the risk classifier: N-cadherin, E-cadherin, Ki67, cyclin D1 and phosphorylated eukaryotic initiation factor 4E binding protein-1 (p-4EBP1). Patients were classified as either low, intermediate or high risk of disease recurrence by tertiles of risk score. The 5-year recurrence-free survival (RFS) was 93.8%, 87.7% and 70% for patients with low-, intermediate- and high-risk scores, respectively (P < 0.001). Patients with a high marker score had worse RFS on multivariate analysis adjusted for age, gender, race and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score (hazard ratio 3.66, 95% confidence interval 1.58-8.49, P = 0.003 for high vs low marker score in the overall cohort). The five-marker classifier increased the concordance index of the clinical model in both the training and validation sets. Conclusion: We developed a five-marker-based prognostic tool that can effectively classify patients with ccRCC according to risk of disease recurrence after surgery. This tool, if prospectively validated, could provide individualised risk estimation for patients with ccRCC.

AB - Objective: To improve risk stratification for recurrence prognostication in patients with localised clear cell renal cell carcinoma (ccRCC). Patients and Methods: In all, 367 patients with non-metastatic ccRCC were included. The cohort was divided into a training and validation set. Using tissue microarrays, immunostaining was performed for 24 biomarkers representative of key pathways in ccRCC. Using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we identified several markers that were used to construct a risk classifier for risk of disease recurrence. Results: The median (interquartile range) follow-up was 63.5 (24.0-85.3) months. Five out of 24 markers were selected by LASSO Cox regression for the risk classifier: N-cadherin, E-cadherin, Ki67, cyclin D1 and phosphorylated eukaryotic initiation factor 4E binding protein-1 (p-4EBP1). Patients were classified as either low, intermediate or high risk of disease recurrence by tertiles of risk score. The 5-year recurrence-free survival (RFS) was 93.8%, 87.7% and 70% for patients with low-, intermediate- and high-risk scores, respectively (P < 0.001). Patients with a high marker score had worse RFS on multivariate analysis adjusted for age, gender, race and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score (hazard ratio 3.66, 95% confidence interval 1.58-8.49, P = 0.003 for high vs low marker score in the overall cohort). The five-marker classifier increased the concordance index of the clinical model in both the training and validation sets. Conclusion: We developed a five-marker-based prognostic tool that can effectively classify patients with ccRCC according to risk of disease recurrence after surgery. This tool, if prospectively validated, could provide individualised risk estimation for patients with ccRCC.

KW - Biomarkers

KW - Cell cycle

KW - Epithelial mesenchymal transition

KW - Mammalian target of rapamycin

KW - Prognosis

KW - Renal cell carcinoma

UR - http://www.scopus.com/inward/record.url?scp=85013436850&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85013436850&partnerID=8YFLogxK

U2 - 10.1111/bju.13776

DO - 10.1111/bju.13776

M3 - Article

C2 - 28075543

AN - SCOPUS:85013436850

JO - BJU International

JF - BJU International

SN - 1464-4096

ER -