Publications Search - Abstract View
||Germline variation in TP53 regulatory network genes associates with breast cancer survival and treatment outcome.
||Jamshidi M, Schmidt MK, Dörk T, Garcia-Closas M, Heikkinen T, Cornelissen S, van den Broek AJ, Schürmann P, Meyer A, Park-Simon TW, Figueroa J, Sherman M, Lissowska J, Keong GT, Irwanto A, Laakso M, Hautaniemi S, Aittomäki K, Blomqvist C, Liu J, Nevanlinna H
||Int J Cancer
||2013 May 1
||MEB, OD, OEEB
||Germline variation in the TP53 network genes PRKAG2, PPP2R2B, CCNG1, PIAS1 and YWHAQ was previously suggested to have an impact on drug response in vitro. Here, we investigated the effect on breast cancer survival of germline variation in these genes in 925 Finnish breast cancer patients and further analyzed five single nucleotide polymorphisms (SNPs) in PRKAG2 (rs1029946, rs4726050, rs6464153, rs7789699) and PPP2R2B (rs10477313) for 10-year survival in breast cancer patients, interaction with TP53 R72P and MDM2-SNP309, outcome after specific adjuvant therapy and correlation to tumor characteristics in 4,701 invasive cases from four data sets. We found evidence for carriers of PRKAG2-rs1029946 and PRKAG2-rs4726050 having improved survival in the pooled data (HR 0.53, 95% CI 0.3-0.9; p = 0.023 for homozygous carriers of the rare G-allele and HR 0.85, 95% CI 0.7-0.9; p = 0.049 for carriers of the rare G allele, respectively). PRKAG2-rs4726050 showed a significant interaction with MDM2-SNP309, with PRKAG2-rs4726050 rare G-allele having a dose-dependent effect for better breast cancer survival confined only to MDM2 SNP309 rare G-allele carriers (HR 0.45, 95% CI 0.2-0.7; p = 0.001). This interaction also emerged as an independent predictor of better survival (p = 0.047). PPP2R2B-rs10477313 rare A-allele was found to predict better survival (HR 0.82, 95% CI 0.6-0.9; p = 0.018), especially after hormonal therapy (HR 0.66, 95% CI 0.5-0.9; p = 0.048). These findings warrant further studies and suggest that genetic markers in TP53 network genes such as PRKAG2 and PPP2R2B might affect prognosis and treatment outcome in breast cancer patients.