Evidence map›Paper›PMID 25764380›Full record

ArticleJournal of cancer research and clinical oncology2015

Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip.

Jong Jin Oh, Seunghyun Park, Sang Eun Lee, Sung Kyu Hong, Sangchul Lee, Hak Min Lee, Jung Keun Lee, Jin-Nyoung Ho, Sungroh Yoon, Seok-Soo Byun

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Article in Journal of cancer research and clinical oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 39% of its field
1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed, 1 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors at 3 institutions in 1 country.

Jong Jin OhDepartment of Urology, Seoul National University Bundang Hospital, 300, Gumi-dong, Bundang-gu, Seongnam-Si, Kyunggi-do, 463-707, Korea.
Seunghyun Park
Sang Eun Lee
Sung Kyu Hong
Sangchul Lee
Hak Min Lee
Jung Keun Lee
Jin-Nyoung Ho
Sungroh Yoon
Seok-Soo Byun
Seoul National University Bundang Hospital · KRKorea University · KRSeoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposesGenetic variations among prostate cancer patients who underwent radical prostatectomies were evaluated to predict biochemical recurrence, and used to develop a clinical-genetic model that combines data on clinicopathological factors of prostate cancer and individual genetic variations. MATERIALS AND

methodsWe genotyped 242,186 SNPs on a custom HumanExome BeadChip v1.0 (Illuminam Inc.) from the blood DNA of 776 PCa patients who underwent radical prostatectomy. Genetic data were analyzed to calculate an odds ratio as an estimate of the relative risk of biochemical recurrence. And we compared accuracies from the multivariate model incorporating clinicopathological factors between included and excluded selected lead single nucleotide polymorphisms. Biochemical recurrence-free survival outcomes also analyzed using these genetic variations.

resultsGenetic array analysis indicated that eight single nucleotide polymorphisms (rs77080351, rs200944490, rs2071292, rs117237810, rs191118242, rs4965121, rs61742396, and rs6573513) were significant to predict biochemical recurrence after radical prostatectomy. When a multivariate model incorporating clinicopathological factors was devised to predict biochemical recurrence, the predictive accuracy of model was 85.1 %. By adding in two individual variations of single nucleotide polymorphisms in the multivariate model, the predictive accuracy increased to 87.7 % (P = 0.045). With three variations of single nucleotide polymorphisms, the predictive accuracy further improved to 89.0 % (P = 0.025). These genetic variations had a significantly decreased biochemical recurrence-free survival rate.

conclusionsBased on exome array, the selected single nucleotide polymorphisms were predictors for biochemical recurrence. The addition of individualized genetic information effectively enhanced the predictive accuracy of biochemical recurrence among prostate cancer patients who underwent radical prostatectomy.

Indexed as

Polymorphism, Single NucleotideProstatectomyAgedAllelesBiomarkers, TumorGenome, HumanGenotypeHumansMaleMiddle AgedNeoplasm Recurrence, LocalOligonucleotide Array Sequence AnalysisPrognosisProstatic NeoplasmsBiomarkers, Tumor

Identifiers

PMID25764380
PMCPMC11824058
OpenAlexW1986989368

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.