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Adiposity is associated with p53 gene mutations in breast cancer.

ABSTRACT: Mutations in the p53 gene are among the most frequent genetic events in human cancer and may be triggered by environmental and occupational exposures. We examined the association of clinical and pathological characteristics of breast tumors and breast cancer risk factors according to the prevalence and type of p53 mutations. Using tumor blocks from incident cases from a case-control study in western New York, we screened for p53 mutations in exons 2-11 using the Affymetrix p53 Gene Chip array and analyzed case-case comparisons using logistic regression. The p53 mutation frequency among cases was 28.1 %; 95 % were point mutations (13 % of which were silent) and the remainder were single base pair deletions. Sixty seven percent of all point mutations were transitions; 24 % of them are G:C>A:T at CpG sites. Positive p53 mutation status was associated with poorer differentiation (OR, 95 % CI 2.29, 1.21-4.32), higher nuclear grade (OR, 95 % CI 1.99, 1.22-3.25), and increased Ki-67 status (OR, 95 % CI 1.81, 1.10-2.98). Cases with P53 mutations were more likely to have a combined ER-positive and PR-negative status (OR, 95 % CI 1.65, 1.01-2.71), and a combined ER-negative and PR-negative status (OR, 95 % CI 2.18, 1.47-3.23). Body mass index >30 kg/m(2), waist circumference >79 cm, and waist-to-hip ratio >0.86 were also associated with p53 status; obese breast cancer cases are more likely to have p53 mutations (OR, 95 % CI 1.78, 1.19-2.68). We confirmed that p53 mutations are associated with less favorable tumor characteristics and identified an association of p53 mutation status and adiposity.

SUBMITTER: Ochs-Balcom HM

PROVIDER: S-EPMC5512545 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Adiposity is associated with p53 gene mutations in breast cancer.

Ochs-Balcom Heather M HM Marian Catalin C Nie Jing J Brasky Theodore M TM Goerlitz David S DS Trevisan Maurizio M Edge Stephen B SB Winston Janet J Berry Deborah L DL Kallakury Bhaskar V BV Freudenheim Jo L JL Shields Peter G PG

Breast cancer research and treatment 20150912 3

Mutations in the p53 gene are among the most frequent genetic events in human cancer and may be triggered by environmental and occupational exposures. We examined the association of clinical and pathological characteristics of breast tumors and breast cancer risk factors according to the prevalence and type of p53 mutations. Using tumor blocks from incident cases from a case-control study in western New York, we screened for p53 mutations in exons 2-11 using the Affymetrix p53 Gene Chip array an ...[more]

PMID: 26364297

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Project description:Breast cancer subtypes identified in genomic studies have different underlying genetic defects. Mutations in the tumor suppressor p53 occur more frequently in estrogen receptor (ER) negative, basal-like and HER2-amplified tumors than in luminal, ER positive tumors. Thus, because p53 mutation status is tightly linked to other characteristics of prognostic importance, it is difficult to identify p53's independent prognostic effects. The relation between p53 status and subtype can be better studied by combining data from primary tumors with data from isogenic cell line pairs (with and without p53 function).The p53-dependent gene expression signatures of four cell lines (MCF-7, ZR-75-1, and two immortalized human mammary epithelial cell lines) were identified by comparing p53-RNAi transduced cell lines to their parent cell lines. Cell lines were treated with vehicle only or doxorubicin to identify p53 responses in both non-induced and induced states. The cell line signatures were compared with p53-mutation associated genes in breast tumors.Each cell line displayed distinct patterns of p53-dependent gene expression, but cell type specific (basal vs. luminal) commonalities were evident. Further, a common gene expression signature associated with p53 loss across all four cell lines was identified. This signature showed overlap with the signature of p53 loss/mutation status in primary breast tumors. Moreover, the common cell-line tumor signature excluded genes that were breast cancer subtype-associated, but not downstream of p53. To validate the biological relevance of the common signature, we demonstrated that this gene set predicted relapse-free, disease-specific, and overall survival in independent test data.In the presence of breast cancer heterogeneity, experimental and biologically-based methods for assessing gene expression in relation to p53 status provide prognostic and biologically-relevant gene lists. Our biologically-based refinements excluded genes that were associated with subtype but not downstream of p53 signaling, and identified a signature for p53 loss that is shared across breast cancer subtypes.

Project description:BackgroundIt is unclear whether germline breast cancer susceptibility gene mutations affect breast cancer related outcomes. We wanted to evaluate mutation patterns in 20 breast cancer susceptibility genes and correlate the mutations with clinical characteristics to determine the effects of these germline mutations on breast cancer prognosis.MethodsThe study cohort included 480 ethnic Chinese individuals in Taiwan with at least one of the six clinical risk factors for hereditary breast cancer: family history of breast or ovarian cancer, young age of onset for breast cancer, bilateral breast cancer, triple negative breast cancer, both breast and ovarian cancer, and male breast cancer. PCR-enriched amplicon-sequencing on a next generation sequencing platform was used to determine the germline DNA sequences of all exons and exon-flanking regions of the 20 genes. Protein-truncating variants were identified as pathogenic.ResultsWe detected a 13.5% carrier rate of pathogenic germline mutations, with BRCA2 being the most prevalent and the non-BRCA genes accounting for 38.5% of the mutation carriers. BRCA mutation carriers were more likely to be diagnosed of breast cancer with lymph node involvement (66.7% vs 42.6%; P = 0.011), and had significantly worse breast cancer specific outcomes. The 5-year disease-free survival was 73.3% for BRCA mutation carriers and 91.1% for non-carriers (hazard ratio for recurrence or death 2.42, 95% CI 1.29-4.53; P = 0.013). After adjusting for clinical prognostic factors, BRCA mutation remained an independent poor prognostic factor for cancer recurrence or death (adjusted hazard ratio 3.04, 95% CI 1.40-6.58; P = 0.005). Non-BRCA gene mutation carriers did not exhibit any significant difference in cancer characteristics or outcomes compared to those without detected mutations. Among the risk factors for hereditary breast cancer, the odds of detecting a germline mutation increased significantly with having bilateral breast cancer (adjusted odds ratio 3.27, 95% CI 1.64-6.51; P = 0.0008) or having more than one risk factor (odds ratio 2.07, 95% CI 1.22-3.51; P = 0.007).ConclusionsWithout prior knowledge of the mutation status, BRCA mutation carriers had more advanced breast cancer on initial diagnosis and worse cancer-related outcomes. Optimal approach to breast cancer treatment for BRCA mutation carriers warrants further investigation.

Project description:BackgroundClinical characteristics including estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 (HER2) are important biomarkers in the treatment of breast cancer, but how genomic mutations affect their status is rarely studied. This study aimed at finding genomic mutations associated with these clinical characteristics.MethodsThere were 160 patients with breast cancer enrolled in this study. Samples from those patients were used for next-generation sequencing, targeting a panel of 624 pan-cancer genes. Short nucleotide mutations, copy number variations, and gene fusions were identified for each sample. Fisher's exact test compared each pair of genes. A similarity score was constructed with the resulting P-values. Genes were clustered with the similarity scores. The identified gene clusters were compared to the status of clinical characteristics including ER, PR, HER2, and a family history of cancer (FH) in terms of the mutations in patients.ResultsGene-by-gene analysis found that CCND1 mutations were positively correlated with ER status while ERBB2 and CDK12 mutations were positively correlated with HER2 status. Mutation-based clustering identified four gene clusters. Gene cluster 1 (ADGRA2, ZNF703, FGFR1, KAT6A, and POLB) was significantly associated with PR status; gene cluster 2 (COL1A1, AXIN2, ZNF217, GNAS, and BRIP1) and gene cluster 3 (FGF3, FGF4, FGF19, and CCND1) were significantly associated with ER status; gene cluster 2 was also negatively associated with a family history of cancer; and gene cluster 4 was significantly negatively associated with age. Patients were classified into four corresponding groups. Patient groups 1, 2, 3, and 4 had 24.1%, 36.5%, 38.7%, and 41.3% of patients with an FDA-recognized biomarker predictive of response to an FDA-approved drug, respectively.ConclusionThis study identified genomic mutations positively associated with ER and PR status. These findings not only revealed candidate genes in ER and PR status maintenance but also provided potential treatment targets for patients with endocrine therapy resistance.

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Adiposity is associated with p53 gene mutations in breast cancer.

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Adiposity is associated with p53 gene mutations in breast cancer.

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