Literature DB >> 17003782

Case-control, kin-cohort and meta-analyses provide no support for STK15 F31I as a low penetrance colorectal cancer allele.

E L Webb1, M F Rudd, R S Houlston.   

Abstract

Recently, homozygosity for T91A single-nucleotide polymorphism (SNP) in the serine/threonine kinase (STK15) gene, which generates the substitution F31I has been proposed to increase the risk of a number of tumours including colorectal cancer (CRC). To further evaluate the relationship between STK15 F31I and risk of CRC, we genotyped 2558 CRC cases and 2680 controls for this polymorphism. We found no evidence that homozygosity for the STK15 31I genotype confers an increased risk of CRC (odds ratio=0.95, 95% confidence interval (CI): 0.74-1.24). We also conducted a kin-cohort analysis to assess risk among first-degree relatives of the CRC cases. The hazard ratio for I/I homozygotes compared to F/F homozygotes was 1.65 (95% CI: 0.39-3.17). A meta-analysis of our case-control data and three previous studies also provided no evidence of an elevated risk of CRC associated with homozygosity. These data provide no support for the hypothesis that sequence variation in STK15 defined by SNP F31I per se confers an elevated risk of CRC.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 17003782      PMCID: PMC2360710          DOI: 10.1038/sj.bjc.6603382

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Serine/threonine kinase (STK15; MIM:603072) is a regulator of mitotic chromosomal segregation (Dutertre ) and plays a role in the development of malignancy (Bischoff ; Zhou ; Ewart-Toland ). Recently, the T91A single-nucleotide polymorphism (SNP) in STK15, which generates the substitution F31I, and has been reported to influence genomic instability (Ewart-Toland ; Kimura ), has been proposed as a low penetrance variant for a number of tumours including colorectal cancer (CRC) (Ewart-Toland , 2005). To further evaluate the relationship between STK15 F31I and risk of CRC, we genotyped 2558 CRC cases and 2680 controls for this polymorphism. We also conducted a kin-cohort analysis to assess risk among first-degree relatives of the CRC cases.

MATERIALS AND METHODS

Unselected CRC cases with histologically confirmed colorectal adenocarcinomas (1471 men; 1087 women; mean age at diagnosis 61 years; standard deviation (s.d.)±11.4) were ascertained through over 100 centres in the UK. Detailed family histories were obtained from cases by previously validated questionnaire. Controls (836 men; 1844 women; mean age 59 years; s.d.±10.9) were the spouses or friends of patients with malignancies ascertained as part of ongoing National Cancer Research Network genetic epidemiological studies (1999–2004; n=1067), the Royal Marsden Hospital Trust/Institute of Cancer Research Family History and DNA Registry (1999–2004; n=1021) and UK Study of Breast Cancer Genetics (1999–2004; n=592) all established within the UK. None of the controls had a personal history of malignancy at time of ascertainment. As we are not seeking to evaluate environmental interactive effects, the theoretical possibility of ‘overmatching’ on environmental factors by using spouse and friend controls is unlikely to impact on study findings. All cases and controls were British Caucasians, and there were no obvious differences in the demography of cases and controls in terms of place of residence within the UK. Blood samples were obtained with informed consent and ethical review board approval in accordance with the tenets of the Declaration of Helsinki. Analysis of STK15 F31I was undertaken as part of our ongoing analyses to identify low penetrance alleles based on the National Study of Colorectal Cancer Genetics Trial (2004). DNA was extracted from blood samples using conventional methodologies and quantified using PicoGreen (Invitrogen, Carlsbad, CA, USA). Genotyping was performed using the Illumina Sentrix Bead Array system according to the manufacturer's protocols. Further information on the assays is available on request. Risks were estimated by odds ratios (ORs) using unconditional logistic regression, and associated 95% confidence intervals (CIs) computed. Meta-analysis of this and other published studies was conducted using standard methods for combining estimates of ORs based on the weighted sum of the log estimates with the inverse of the variance of the estimate of the weight. Cochran's Q statistic (Cochran, 1954) to test for heterogeneity and the I2 statistic (Higgins ) to quantify the proportion of the total variation owing to heterogeneity were calculated. To incorporate within-study and between-study variability, we used DerSimioian and Laird's method (DerSimonian and Laird, 1986) for calculating random effects summary ORs and their associated 95% CIs. All computations were undertaken in STATA (version 8.2, Stata Corporation, College Station, TX, USA). We also performed a kin-cohort analysis to compare the CRC risk in first-degree relatives of STK15 I homozygotes with that in first-degree relatives of F homozygotes. Proband genotypes and the SNP allele frequency were used to infer genotypes of relatives. Age-specific cumulative CRC distributions in first-degree relatives were estimated using a marginal likelihood approach (Chatterjee and Wacholder, 2001), implemented in MatLab version 7.0.1 (MathWorks, Natick, MA, USA). Bootstrap estimates for the hazard ratio (HR) were then computed, using 1000 resamples of the data, and used to generate a 95% CI.

RESULTS

There was no evidence of population stratification as the genotype distribution of F31I in controls satisfied Hardy–Weinberg equilibrium (P=0.63). We found no evidence that homozygosity for the STK15 I genotype confers an increased risk of CRC (cases: F/F=1564, F/I=880 and I/I=114; controls: F/F=1667, F/I=888, I/I=125; OR=0.95, 95% CI: 0.74–1.24). As there is no a priori reason to assume a recessive model of CRC susceptibility, we also computed the risk associated with heterozygotes using the F/F genotype as the reference group. The OR under this model was 1.06 (95% CI: 0.94–1.19). Three other studies have compared the frequency of STK15 F31I genotypes in cases and controls (Ewart-Toland ); two based on predominantly Caucasians and one based on Han Chinese. Figure 1 shows estimates of the recessive homozygote risk from this study and from published studies. The study based on Han Chinese was alone in showing a significant positive association and was the only study where results differed significantly from our analysis. The pooled OR estimate was 1.31 (95% CI: 0.96–1.78); interpretation of this is not, however, clear as the estimates in different studies are clearly heterogeneous (Cochran's Q=8.21, P=0.042, I=64%). Restricting the meta-analysis to the three studies based on Caucasians, between-study heterogeneity was less evident (Cochran's Q=3.1, P=0.21, I=35%). The pooled estimate of the OR was 1.15 (95% CI: 0.87–1.51).
Figure 1

Forest plot of the risk of CRC associated with STK15-I/I homozygosity from comparison of I/I vs I/F and F/F genotypes combined for (A) all studies and (B) all Caucasian studies. Shaded squares denote ORs, with their size being proportional to the inverse variance of the study-specific estimate. Horizontal lines represent 95% CIs. The diamond denotes the combined random effects estimate and its associated 95% CI. The vertical line indicates the null effect (OR=1.0).

The 2558 cases reported a total of 14 649 first-degree relatives of whom 445 (3.0%) had been diagnosed with CRC. The HR for I/I homozygotes compared to F/F homozygotes was 1.65 (95% CI: 0.39–3.17).

DISCUSSION

It has previously been proposed that the STK15 F31I polymorphism confers a 1.5-fold increase in risk of CRC (Ewart-Toland ). Even though our study had over 90% power to detect this magnitude of increased risk at significance level 5%, we found no evidence to support the hypothesis that F31I is a CRC susceptibility allele. Moreover, the meta-analysis we conducted of 9309 subjects also provides no evidence of an increased risk. There was, however, a high degree of variation in the ORs estimated by individual studies. The frequency of the I-allele is markedly different in Caucasians and Han Chinese (21 and 61% respectively), thus it may be inappropriate to regard the different ethnic groups as genetically similar. As the frequency of genotypes in controls in the other studies are not significantly different from those expected, there is little evidence that overt population stratification underpins study heterogeneity. Although there is some data to suggest that F31I has functional cellular consequences (Ewart-Toland ; Kimura ), direct causality has not been demonstrated. It is possible that population-specific linkage disequilibrium with another functional variant could be operating. Some support for this is provided by the observation of Lo that in the Taiwanese population the risk of breast cancer associated with F31I is mediated through an extended haplotype. Finally, as with all association studies a simple but unattractive explanation for the observed heterogeneity is publication bias. In summary, collectively these data provide no support for the hypothesis that sequence variation in STK15 defined by the nonsynonymous SNP F31I per se confers an elevated risk of CRC.
  10 in total

1.  A marginal likelihood approach for estimating penetrance from kin-cohort designs.

Authors:  N Chatterjee; S Wacholder
Journal:  Biometrics       Date:  2001-03       Impact factor: 2.571

Review 2.  Measuring inconsistency in meta-analyses.

Authors:  Julian P T Higgins; Simon G Thompson; Jonathan J Deeks; Douglas G Altman
Journal:  BMJ       Date:  2003-09-06

3.  A homologue of Drosophila aurora kinase is oncogenic and amplified in human colorectal cancers.

Authors:  J R Bischoff; L Anderson; Y Zhu; K Mossie; L Ng; B Souza; B Schryver; P Flanagan; F Clairvoyant; C Ginther; C S Chan; M Novotny; D J Slamon; G D Plowman
Journal:  EMBO J       Date:  1998-06-01       Impact factor: 11.598

4.  Meta-analysis in clinical trials.

Authors:  R DerSimonian; N Laird
Journal:  Control Clin Trials       Date:  1986-09

5.  Two functional coding single nucleotide polymorphisms in STK15 (Aurora-A) coordinately increase esophageal cancer risk.

Authors:  Makoto T Kimura; Takahiro Mori; Jeffrey Conroy; Norma J Nowak; Susumu Satomi; Katsuyuki Tamai; Hiroki Nagase
Journal:  Cancer Res       Date:  2005-05-01       Impact factor: 12.701

6.  Breast cancer risk associated with genotypic polymorphism of the mitosis-regulating gene Aurora-A/STK15/BTAK.

Authors:  Yen-Li Lo; Jyh-Cherng Yu; Shou-Tung Chen; Hsin-Chou Yang; Cathy S J Fann; Yi-Chien Mau; Chen-Yang Shen
Journal:  Int J Cancer       Date:  2005-06-10       Impact factor: 7.396

7.  Identification of Stk6/STK15 as a candidate low-penetrance tumor-susceptibility gene in mouse and human.

Authors:  Amanda Ewart-Toland; Paraskevi Briassouli; John P de Koning; Jian-Hua Mao; Jinwei Yuan; Florence Chan; Lucy MacCarthy-Morrogh; Bruce A J Ponder; Hiroki Nagase; John Burn; Sarah Ball; Maria Almeida; Spiros Linardopoulos; Allan Balmain
Journal:  Nat Genet       Date:  2003-08       Impact factor: 38.330

8.  Tumour amplified kinase STK15/BTAK induces centrosome amplification, aneuploidy and transformation.

Authors:  H Zhou; J Kuang; L Zhong; W L Kuo; J W Gray; A Sahin; B R Brinkley; S Sen
Journal:  Nat Genet       Date:  1998-10       Impact factor: 38.330

Review 9.  On the role of aurora-A in centrosome function.

Authors:  Stéphanie Dutertre; Simon Descamps; Claude Prigent
Journal:  Oncogene       Date:  2002-09-09       Impact factor: 9.867

10.  Aurora-A/STK15 T+91A is a general low penetrance cancer susceptibility gene: a meta-analysis of multiple cancer types.

Authors:  Amanda Ewart-Toland; Qi Dai; Yu-Tang Gao; Hiroki Nagase; Malcolm G Dunlop; Susan M Farrington; Rebecca A Barnetson; Hoda Anton-Culver; David Peel; Argyrios Ziogas; Dongxin Lin; Xiaoping Miao; Tong Sun; Elaine A Ostrander; Janet L Stanford; Mariela Langlois; June M Chan; Jinwei Yuan; Curtis C Harris; Elise D Bowman; Gary L Clayman; Scott M Lippman; J Jack Lee; Wei Zheng; Allan Balmain
Journal:  Carcinogenesis       Date:  2005-03-31       Impact factor: 4.944

  10 in total
  8 in total

1.  Association between the STK15 polymorphisms and risk of cancer: a meta-analysis.

Authors:  Jun Qin; Xiao-Feng He; Wu Wei; Zhi-Zhong Liu; Jian-Jun Xie; Wei Wang; Ya-Ping Du; Yu Chen; Hui-Qiang Si
Journal:  Mol Genet Genomics       Date:  2014-08-26       Impact factor: 3.291

2.  Efficient distribution estimation for data with unobserved sub-population identifiers.

Authors:  Yanyuan Ma; Yuanjia Wang
Journal:  Electron J Stat       Date:  2012       Impact factor: 1.125

3.  Breast Cancer Risk Associated with Genotype Polymorphisms of the Aurora Kinase a Gene (AURKA): a Case-Control Study in a High Altitude Ecuadorian Mestizo Population.

Authors:  Andrés López-Cortés; Alejandro Cabrera-Andrade; Fabián Oña-Cisneros; Carolina Echeverría; Felipe Rosales; Malena Ortiz; Eduardo Tejera; César Paz-Y-Miño
Journal:  Pathol Oncol Res       Date:  2017-06-24       Impact factor: 3.201

4.  Estimation of genotype relative risks from pedigree data by retrospective likelihoods.

Authors:  Daniel J Schaid; Shannon K McDonnell; Shaun M Riska; Erin E Carlson; Stephen N Thibodeau
Journal:  Genet Epidemiol       Date:  2010-05       Impact factor: 2.135

5.  Association between the STK15 F31I polymorphism and cancer susceptibility: a meta-analysis involving 43,626 subjects.

Authors:  Weifeng Tang; Hao Qiu; Hao Ding; Bin Sun; Lixin Wang; Jun Yin; Haiyong Gu
Journal:  PLoS One       Date:  2013-12-13       Impact factor: 3.240

6.  Serine/threonine kinase 15 gene polymorphism and risk of digestive system cancers: A meta-analysis.

Authors:  Jianfei Luo; Ruicheng Yan; Li Zou
Journal:  Exp Ther Med       Date:  2014-11-14       Impact factor: 2.447

7.  National study of colorectal cancer genetics.

Authors:  S Penegar; W Wood; S Lubbe; I Chandler; P Broderick; E Papaemmanuil; G Sellick; R Gray; J Peto; R Houlston
Journal:  Br J Cancer       Date:  2007-09-25       Impact factor: 7.640

8.  AURKA rs2273535 T>A Polymorphism Associated With Cancer Risk: A Systematic Review With Meta-Analysis.

Authors:  Shujie Wang; Jian Qi; Meiling Zhu; Meng Wang; Jinfu Nie
Journal:  Front Oncol       Date:  2020-06-30       Impact factor: 6.244

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.