Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Genome-wide detection of allelic genetic variation to predict advanced-stage prostate cancer after radical prostatectomy using an exome SNP chip.

Authors
Oh, Jong JinPark, SeunghyunLee, Sang EunHong, Sung KyuLee, SangchulJo, Jung KiLee, Jung KeunHo, Jin-NyoungYoon, SungrohByun, Seok-Soo
Issue Date
Sep-2015
Publisher
Elsevier
Keywords
Prostate cancel; Exome array; Stage; Predictive value
Citation
Urologic Oncology: Seminars and Original Investigations, v.33, no.9, pp.385.e7 - 385.e13
Indexed
SCIE
SCOPUS
Journal Title
Urologic Oncology: Seminars and Original Investigations
Volume
33
Number
9
Start Page
385.e7
End Page
385.e13
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/156359
DOI
10.1016/j.urolonc.2015.05.016
ISSN
1078-1439
Abstract
Objectives: Genetic variations among patients with prostate cancer (PCa) who underwent radical prostatectomies were evaluated to predict advanced stage above T3 using an exome single nucleotide polymorphism (SNP) chip array. Materials and methods: We collected data of genetic SNP variants from 820 patients with PCa who underwent radical prostatectomy (RP) using a custom HumanExome BeadChip v1.0 (Illumina Inc.). We selected the SNPs that were most significantly associated with advanced-stage PCa (>= T3) among the 242,186 SNPs that were genotyped, and we compared the accuracies of the associations using a multivariate logistic model that incorporated clinical factors and clinicogenetic factors. Results: Among the total cohort, 360 patients (43.9%) had advanced pathologic stage (>= T3) after RP, of whom 262 (32.0%) had extracapsular extensions, 79 (9.6%) had seminal vesicle invasions, and 10 (1.3%) had bladder neck invasions. The exome array analysis indicated that 5 SNPs (rs6804162, rs8055236, rs56335308, rs6104, and rs12618769) were significant for predicting T3 stage after RP in patients with PCa. These genetic markers were significant factors after adjusting for other clinical parameters, and they increased the accuracy of a multivariate model for predicting advanced stage of PCa (83.9%-87.2%, P = 0.0001). Conclusions: Based on a genetic array, the selected SNPs were found to be independent predictors for advanced stage after RP, and the addition of individualized genetic information effectively enhanced the accuracy of predicting advanced-stage disease. These results should be validated in another independent cohort.
Files in This Item
There are no files associated with this item.
Appears in
Collections
서울 의과대학 > 서울 비뇨의학교실 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Jo, Jung Ki photo

Jo, Jung Ki
COLLEGE OF MEDICINE (DEPARTMENT OF UROLOGY)
Read more

Altmetrics

Total Views & Downloads

BROWSE