Literature DB >> 25933217

Correction: A Systems Genetics Approach Identifies CXCL14, ITGAX, and LPCAT2 as Novel Aggressive Prostate Cancer Susceptibility Genes.

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Abstract

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Year:  2015        PMID: 25933217      PMCID: PMC4416811          DOI: 10.1371/journal.pgen.1005127

Source DB:  PubMed          Journal:  PLoS Genet        ISSN: 1553-7390            Impact factor:   5.917


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The authors made an error in analysis, with SNPs being mapped to human genome build hg18 and genes to human genome build hg19. Consequently, there are errors in Table 5, S15 Table, and the accompanying text on pages 9 and 11. Corrected text and tables are provided here.
Table 5

QTL candidate gene SNPs associated with aggressive prostate cancer in CGEMS GWAS.

Chr.Candidate GeneSNP Distance From Gene (bp)SNPPLCO VariableOdds Ratio (95% C.I.)Minor Allele Frequencyt stat P valuePermutation P value
Aggressive DiseaseNon-Aggressive Disease
5q31.1 CXCL14 0rs2547pros_gleason_prost0.61 (0.43-0.85)0.0540.033-2.8890.0040.003
0rs2237061pros_gleason_prost0.61 (0.43-0.88)0.0480.030-2.6850.0070.008
19118rs10515473pros_gleason_prost0.72 (0.59-0.88)0.1630.122-3.1480.0020.002
24155rs4463175pros_gleason_prost1.42 (1.12-1.81)0.0870.1012.8780.0040.003
69386rs801564pros_stage_n1.05 (1.01-1.09)0.0010.2822.5870.0100.010
92585rs2067000pros_stage_n1.05 (1.02-1.09)0.0010.2882.8830.0040.004
6p22.1 PGBD1 76094rs1233708pros_stage1.08 (1.02-1.13)0.0420.2132.9210.0040.003
6p22.2 HIST1H2AB 59345rs1800562pros_gleason1.40 (1.16-1.70)0.0250.0413.4590.0010.001
79097rs933199pros_gleason0.75 (0.62-0.92)0.0320.025-2.7590.0060.007
6p22.3 GPLD1 43164rs811103pros_gleason_prost1.32 (1.09-1.60)0.1860.1952.8550.0040.005
56546rs793663pros_gleason_prost1.32 (1.09-1.60)0.1860.1952.8540.0040.006
6q15 AKIRIN2 0rs4707385pros_gleason1.16 (1.05-1.29)0.1350.1642.9090.0040.003
ORC3 0rs6930600pros_gleason0.86 (0.78-0.95)0.2460.222-3.0950.0020.002
0rs7755167pros_gleason0.86 (0.78-0.95)0.2460.221-3.1070.0020.002
0rs7772351pros_gleason1.14 (1.04-1.26)0.1640.1932.7680.0060.007
0rs9450765pros_gleason1.17 (1.06-1.29)0.1710.2023.1180.0020.002
43692rs7757636pros_gleason0.86 (0.79-0.95)0.2460.222-3.0890.0020.003
96943rs9450716pros_gleason1.16 (1.05-1.28)0.1610.1893.0420.0020.002
9p13.3 CCL19 70925rs3802427pros_stage_m1.09 (1.04-1.15)0.0000.1623.5573.89E-041.00E-04
CCL21 75161rs277606pros_gleason_prost1.35 (1.11-1.65)0.1790.1872.9860.0030.002
KIAA1045 68052rs10123308pros_gleason_prost1.30 (1.08-1.57)0.2120.2162.7730.0060.006
9p21.2 MOB3B 0rs868856pros_stage0.94 (0.89-0.98)0.0640.215-2.7480.0060.006
0rs868856pros_stage_t2.02 (1.34-3.04)0.1910.0883.3710.0010.001
0rs3739530pros_gleason0.80 (0.70-0.93)0.0750.056-2.9960.0030.004
0rs4879515pros_stage_t1.68 (1.16-2.41)0.3200.1302.7840.0050.005
0rs7046653pros_stage_t2.01 (1.34-3.02)0.1920.0883.3460.0010.001
0rs7046653pros_stage0.94 (0.89-0.98)0.0640.216-2.7070.0070.007
0rs10121765pros_gleason_prost0.77 (0.64-0.93)0.2600.209-2.7760.0060.005
6547rs2814707pros_stage_t2.09 (1.38-3.19)0.1620.0753.4580.0010.001
13431rs3849942pros_stage_t2.15 (1.41-3.28)0.1610.0753.5643.80E-040.001
31199rs774359pros_stage_t1.99 (1.32-3.01)0.1760.0793.2840.0010.001
64176rs1853186pros_stage0.94 (0.90-0.98)0.0790.272-2.7300.0060.006
16p11.2 ITGAX 55680rs8045738pros_gleason_prost1.33 (1.08-1.62)0.1410.1482.7530.0060.005
16q12.2 LPCAT2 0rs10521319pros_stage_m1.11 (1.03-1.20)0.0000.0572.6190.0090.009
86077rs9302667pros_gleason_prost1.35 (1.11-1.64)0.1560.1702.9940.0030.003
98065rs893260pros_gleason_prost1.30 (1.07-1.58)0.1750.1842.6790.0070.006
20p11.21 GZF1 52836rs6076072pros_stage0.90 (0.84-0.97)0.0280.075-2.9140.0040.003
52836rs6076072pros_stage_t2.17 (1.21-3.92)0.0680.0352.5890.0100.009
20p13 NSFL1C 22006rs6042568pros_gleason0.75 (0.62-0.90)0.0370.029-3.0070.0030.004
The third paragraph of the section ‘Analysis of Human Prostate Cancer GWAS Data Reveals That QTL Candidate Gene SNPs Are Associated with Aggressive Prostate Cancer’ should read: In the study, 1,372 SNPs mapped within a 100 kb radius of the 29 QTL candidate genes were tested in the CGEMS cohort. Analysis of aggressive vs. non-aggressive disease phenotypes were performed as per the comparisons described in Table 4. Correction for multiple testing was performed using permutation testing (n = 10,000 permutations). Fourteen of the 29 candidate genes exhibited evidence for association with clinical characteristics of aggressive prostate cancer (Table 5). Most notably, SNPs in three of the five genes associated with poor clinical outcomes in TCGA (Provisional) and GSE21032 prostate cancer gene expression datasets (CXCL14, ITGAX, and LPCAT2) were all associated with aggressive prostate cancer: For CXCL14, the following SNPs were associated with Gleason score at prostatectomy: rs2547 (permutation P = 0.003; OR = 0.61 [0.43–0.85]), rs2237061 (permutation P = 0.008; OR = 0.61 [0.43–0.88]), rs10515473 (permutation P = 0.002; OR = 0.72 [0.59–0.88]), and rs4463175 (permutation P = 0.003; OR = 1.42 [1.12–1.81]); and the following with metastasis to regional lymph nodes: rs801564 (permutation P = 0.010; OR = 1.05 [1.01–1.09]) and rs2067000 (permutation P = 0.004; OR = 1.05 [1.02–1.09]). For ITGAX, an association was apparent between rs8045738 and Gleason score at prostatectomy (permutation P = 0.005; OR = 1.33 [1.08–1.62]). Finally, for LPCAT2, rs10521319 was associated with distant metastasis (permutation P = 0.009; OR = 1.11 [1.03–1.20]), and rs9302667 (permutation P = 0.003; OR = 1.35 [1.11–1.64]) and rs893260 (permutation P = 0.006; OR = 1.30 [1.07–1.58]) with Gleason score at prostatectomy. Manhattan plots for all relevant genomic regions are shown in S5 Fig. Additionally, haplotypes in LD with these three QTL candidate genes were associated with clinical markers of prostate cancer aggressiveness (S15 Table).

Statistically significant aggressive disease-associated haplotypes for QTL candidate genes in the CGEMS prostate cancer cohort.

(XLSX) Click here for additional data file.
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1.  A systems genetics approach identifies CXCL14, ITGAX, and LPCAT2 as novel aggressive prostate cancer susceptibility genes.

Authors:  Kendra A Williams; Minnkyong Lee; Ying Hu; Jonathan Andreas; Shashank J Patel; Suiyuan Zhang; Peter Chines; Abdel Elkahloun; Settara Chandrasekharappa; J Silvio Gutkind; Alfredo A Molinolo; Nigel P S Crawford
Journal:  PLoS Genet       Date:  2014-11-20       Impact factor: 5.917

  1 in total

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