INVITED REVIEW
Year : 2016  |  Volume : 18  |  Issue : 4  |  Page : 575-579

Clinically available RNA profiling tests of prostate tumors: utility and comparison


1 Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai; Department of Urology, Huashan Hospital, Fudan University, Shanghai, China
2 Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai, China; Department of Urology, Huashan Hospital, Fudan University, Shanghai, China; Program for Personalized Cancer Care, NorthShore University HealthSystem, Evanston, IL, USA

Correspondence Address:
Dr. Rong Na
Fudan Institute of Urology, Huashan Hospital, Fudan University, Shanghai; Department of Urology, Huashan Hospital, Fudan University, Shanghai
China
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/1008-682X.175096

Rights and Permissions

In the postscreening era, physicians are in need of methods to discriminate aggressive from nonaggressive prostate cancer (PCa) to reduce overdiagnosis and overtreatment. However, studies have shown that prognoses (e.g., progression and mortality) differ even among individuals with similar clinical and pathological characteristics. Existing risk classifiers (TMN grading system, Gleason score, etc.) are not accurately enough to represent the biological features of PCa. Using new genomic technologies, novel biomarkers and classifiers have been developed and shown to add value to clinical or pathological risk factors for predicting aggressive disease. Among them, RNA testing (gene expression analysis) is useful because it can not only reflect genetic variations but also reflect epigenetic regulations. Commercially available RNA profiling tests (Oncotype Dx, Prolaris, and Decipher) have demonstrated strong abilities to discriminate PCa with poor prognosis from less aggressive diseases. For instance, these RNA profiling tests can predict disease progression in active surveillance patients or early recurrence after radical treatments. These tests may offer more dependable methods for PCa prognosis prediction to make more accurate and personal medical decisions.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed1778    
    Printed126    
    Emailed0    
    PDF Downloaded306    
    Comments [Add]    
    Cited by others 3    

Recommend this journal