Genetic Testing in Predicting Biomarkers of Recurrence in Patients With Prostate Cancer Undergoing Surgery

Prostate Cancer Clinical Trial

Official title:

Pre-Surgical EPS Biomarkers as Predictors of Biochemical Recurrence

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT00977457
• Other study ID #: 06072
• Secondary ID: P30CA033572CHNMC
• Status: Active, not recruiting
• Phase: Phase 1
• Start date: November 26, 2007
• Est. completion date: December 30, 2024

Study information

• Verified date: March 2024
• Source: City of Hope Medical Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This trial studies the side effects and best way to perform genetic testing in predicting biomarkers of recurrence in patients with prostate cancer undergoing surgery. Collecting and storing samples of tissue, blood, and other body fluids from patients to test in the laboratory and collecting information about the patient's health and treatment may help doctors learn more about cancer and help predict the recurrence of prostate cancer

Description:

PRIMARY OBJECTIVES: I. To explore the performance of these models in predicting the likelihood of biochemical recurrence (BCR).

SECONDARY OBJECTIVES: I. To explore the performance of these models in predicting upgrading and upstaging prior to surgery. II. To explore the performance of these models in improving risk stratification among patients eligible for active surveillance. III. To determine whether prostatic massage or surgery raises the count of circulating tumor cells (CTC) in post-digital rectal exam (DRE) blood specimens.

OUTLINE: Patients receive prostatic massage and undergo a digital rectal exam (DRE). Laboratory assessments are performed and blood samples are collected for molecular biology testing. On the day of the scheduled prostatectomy, a second blood collection is performed prior to surgery.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 1045
• Est. completion date: December 30, 2024
• Est. primary completion date: July 13, 2016
• Accepts healthy volunteers: No
• Gender: Male
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• All men undergoing robotic prostatectomy or cystoprostatectomy at City of Hope will be eligible for the study

Exclusion Criteria:

• Men who undergo neoadjuvant treatment with Androgen Deprivation Therapy (ADT) or salvage prostatectomy including those who have had brachytherapy will be excluded

Related Conditions & MeSH terms

• Prostate Cancer
• Prostatic Neoplasms
• Recurrence

Intervention

Genetic:
• DNA analysis
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
• DNA methylation analysis
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
• RNA analysis
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
• gene expression analysis
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery
• polymerase chain reaction
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery

Other:
• diagnostic laboratory biomarker analysis
Performed on Post-massage urine (PMU) and/or expressed prostatic secretions (EPS) samples obtained at the time of surgery

Procedure:
• therapeutic conventional surgery

Locations

Country	Name	City	State
United States	City of Hope Medical Center	Duarte	California

Sponsors (2)

Lead Sponsor	Collaborator
City of Hope Medical Center	National Cancer Institute (NCI)

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Performance of these models in predicting the likelihood of BCR	Logistic regression and artificial neural networks will be used.	Visit 2 (intraoperative setting)
Secondary	Comparison of the performance in these models in predicting upgrading and upstaging prior to surgery	Logistic regression and artificial neural networks will be used.	Visit 2 (intraoperative setting)
Secondary	Comparison of the performance of these models in improving risk stratification among patients eligible for active surveillance	Logistic regression and artificial neural networks will be used.	Visit 2 (intraoperative setting)
Secondary	Determination whether prostatic massage or surgery raises the count of circulating tumor cells (CTCs) in post-DRE blood specimens	Logistic regression and artificial neural networks will be used.	Visit 2 (intraoperative setting)