Previous GWAS hits in relation to young-onset breast cancer

Obesity in early onset breast cancer in African American patients

Obesity is a modifiable risk factor in breast cancer patients and is predictive of disease outcomes in early-onset breast cancer survivors. The purpose of this review is to summarize the current evidence in the association between early-onset breast cancer and obesity, specifically in African-American women. Reviewing the molecular mechanisms and social determinants of disease in this population can provide a foundation for future interventions in prevention, detection, and treatment aiming at improving outcomes for young breast cancer patients.

Machine Learning Supports Long Noncoding RNAs as Expression Markers for Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is the second most common type of gynecological tumor. Several research studies have recently shown the potential of different ncRNAs as biomarkers for prognostics and diagnosis in different types of cancers, including UCEC. Thus, we hypothesized that long noncoding RNAs (lncRNAs) could serve as efficient factors to discriminate solid primary (TP) and normal adjacent (NT) tissues in UCEC with high accuracy. We performed an in silico differential expression analysis comparing TP and NT from a set of samples downloaded from the Cancer Genome Atlas (TCGA) database, targeting highly differentially expressed lncRNAs that could potentially serve as gene expression markers. All analyses were performed in R software. The receiver operator characteristics (ROC) analyses and both supervised and unsupervised machine learning indicated a set of 14 lncRNAs that may serve as biomarkers for UCEC. Functions and putative pathways were assessed through a coexpression network and target enrichment analysis.

DOT: Gene-set analysis by combining decorrelated association statistics

Historically, the majority of statistical association methods have been designed assuming availability of SNP-level information. However, modern genetic and sequencing data present new challenges to access and sharing of genotype-phenotype datasets, including cost of management, difficulties in consolidation of records across research groups, etc. These issues make methods based on SNP-level summary statistics particularly appealing. The most common form of combining statistics is a sum of SNP-level squared scores, possibly weighted, as in burden tests for rare variants. The overall significance of the resulting statistic is evaluated using its distribution under the null hypothesis. Here, we demonstrate that this basic approach can be substantially improved by decorrelating scores prior to their addition, resulting in remarkable power gains in situations that are most commonly encountered in practice; namely, under heterogeneity of effect sizes and diversity between pairwise LD. In these situations, the power of the traditional test, based on the added squared scores, quickly reaches a ceiling, as the number of variants increases. Thus, the traditional approach does not benefit from information potentially contained in any additional SNPs, while our decorrelation by orthogonal transformation (DOT) method yields steady gain in power. We present theoretical and computational analyses of both approaches, and reveal causes behind sometimes dramatic difference in their respective powers. We showcase DOT by analyzing breast cancer and cleft lip data, in which our method strengthened levels of previously reported associations and implied the possibility of multiple new alleles that jointly confer disease risk.

Interactions between a Polygenic Risk Score and Non-genetic Risk Factors in Young-Onset Breast Cancer

Most gene-environmental studies have focused on breast cancers generally, the preponderance of which occur after age 50. Young-onset breast cancers (YOBC) tend to be aggressive and may be etiologically different. The goal of this analysis was to assess interactions between an established 77-SNP polygenic risk score (PRS) and non-genetic risk factors for YOBC. We constructed the PRS using a family-based study of 1,291 women diagnosed with breast cancer before age 50 and their parents and unaffected sisters. We used conditional logistic regression to analyze interactions between the PRS and 14 established risk factors. In further analyses we assessed the same interactions, but for invasive cancer, estrogen receptor (ER) positive cancer and with broader inclusion of racial/ethnic groups. Results showed a decreased association between the PRS and YOBC risk for women who had ever used hormonal birth control (odds ratio [OR] = 2.20 versus 3.89) and a stronger association between the PRS and YOBC risk in pre-menopausal women (OR = 2.46 versus 1.23). Restricting the analysis to ER+ cancers or invasive cancers or using samples from all ethnic groups produced similar results. In conclusion, the PRS may interact with hormonal birth control use and with menopausal status on risk of YOBC.

Evaluation of significant genome-wide association studies risk - SNPs in young breast cancer patients

Purpose

Genome-wide-association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. Most of these studies were conducted primarily in postmenopausal breast cancer patients. Therefore, we set out to assess whether or not these breast cancer variants are also associated with an elevated risk of breast cancer in young premenopausal patients.

Methods

In 451 women of European ancestry who had prospectively enrolled in a longitudinal cohort study for women diagnosed with breast cancer at or under age 40, we genotyped 44 SNPs that were previously associated with breast cancer risk. A control group was comprised of 1142 postmenopausal healthy women from the Nurses’ Health Study (NHS). We assessed if the frequencies of the adequately genotyped SNPs differed significantly (p≤0.05) between the cohort of young breast cancer patients and postmenopausal controls, and then we corrected for multiple testing.

Results

Genotyping of the controls or cases was inadequate for comparisons between the groups for seven of the 44 SNPs. 9 of the remaining 37 were associated with breast cancer risk in young women with a p-value <0.05: rs10510102, rs1219648, rs13387042, rs1876206, rs2936870, rs2981579, rs3734805, rs3803662 and rs4973768. The directions of these associations were consistent with those in postmenopausal women. However, after correction for multiple testing (Benjamini Hochberg) none of the results remained statistically significant.

Conclusion

After correction for multiple testing, none of the alleles for postmenopausal breast cancer were clearly associated with risk of premenopausal breast cancer in this relatively small study.

Significant association of TOX3/LOC643714 locus-rs3803662 and breast cancer risk in a cohort of Iranian population

Genome-wide association studies normally focus on low penetrance and moderate to high-frequency single nucleotide polymorphisms (SNPs), which lead to genetic susceptibility to breast cancer. In this regard, the T allele of rs3803662 has been associated with breast cancer risk and with lower expression level of TOX3. We aimed to assess the risk of breast cancer associated with this polymorphism in an Iranian population. Using Tetra Primer ARMS PCR, rs3803662 was analyzed in a total of 943 individuals (430 cases and 513 healthy controls form North East of Iran). Allele frequencies and genotype distribution were analyzed in case and control samples to find out any association using the Chi-squared test and Logistic regression. All cases were pathologically confirmed; all controls were mainly healthy individuals. Genotype frequencies were found to be in agreement with HWE in controls and cases. TOX3-rs3803662 SNP was associated with breast cancer risk in our study (T vs. C allele contrast model: OR 1.36, 95% CI 1.12-1.64, P_value = 0.002; TT vs. CT + TT dominant model: OR 0.67, 95% CI 0.51-0.87, P_value = 0.003; TT vs. CT + CC recessive model: OR 1.54, 95% CI 1.02-2.30, P_vlue = 0.036). Moreover, after adjusting for age, BMI, history of previous cancer and also family history of cancer, all results, except for the recessive model, were remained significant. TOX3-rs3803662, may confer some degrees of risk of breast cancer in Iranian population. This finding is in line with similar results in other populations. It highlights the importance of TOX3 pathway in tumorigenesis.

Significant association between ERCC2 and MTHR polymorphisms and breast cancer susceptibility in Moroccan population: genotype and haplotype analysis in a case-control study

Background

Genetic determinants of breast cancer (BC) remained largely unknown in the majority of Moroccan patients. The purpose of this study was to explore the association of ERCC2 and MTHFR polymorphisms with genetic susceptibility to breast cancer in Moroccan population.

Methods

We genotyped ERCC2 polymorphisms (rs1799793 (G934A) and rs13181 (A2251C)) and MTHFR polymorphisms (rs1801133 (C677T) and rs1801131 (A1298C)) using TaqMan SNP Genotyping Assays. Genotypes were compared in 151 BC cases and 156 population-matched controls. Allelic, genotypic and haplotype associations with the risk and clinicopathological features of BC were assessed using logistic regression analyses.

Results

ERCC2-rs1799793-AA genotype was associated with high risk of BC compared to wild type genotype (recessive model: OR: 2.90, 95% CI: 1.34–6.26, p = 0.0069) even after Bonferroni correction (p < 0,0125). MTHFR rs1801133-TT genotype was associated with increased risk of BC (recessive model, OR: 2.49, 95% CI: 1.17–5.29, p = 0.017) but the association turned insignificant after Bonferroni correction. For the rest of SNPs, no statistical associations to BC risk were detected.

Significant association with clinical features was detected for MTHFR-rs1801133-TC genotype with early age at diagnosis and familial BC. Following Bonferroni correction, only association with familial BC remained significant. MTHFR-rs1801131-CC genotype was associated with sporadic BC. ERCC2-rs1799793-AA genotype correlated with ER+ and PR+ breast cancer. ERCC2-rs13181-CA genotype was significantly associated large tumors (T ≥ 3) in BC patients. None of these associations passed Bonferroni correction.

Haplotype analysis showed that ERCC2 A-C haplotype was significantly associated with increased BC risk (OR: 3.71, 95% CI: 1.7–8.12, p = 0.0002 and p = 0.0008 before and after Bonferroni correction, respectively) and positive expression of ER and PR in BC patients. ERCC2 G-C haplotype was correlated with PR negative and larger tumor (T4). We did not find any MTHFR haplotypes associated with BC susceptibility. However, the less common haplotype MTHFR T-C was more frequent in young patients and in familial breast cancer, while MTHFR C-C haplotype was associated with sporadic BC form.

Conclusions

Our findings are a first observation of association between ERCC2 SNPs and breast cancer in Moroccan population. The results suggested that ERCC2 and MTHFR polymorphisms may be reliable for assessing risk and prognosis of BC in Moroccan population.

Fibroblast Growth Factor Receptor 2 Signaling in Breast Cancer

Fibroblast growth factor receptor 2 (FGFR2) is a membrane-spanning tyrosine kinase that mediates signaling for FGFs. Recent studies detected various point mutations of FGFR2 in multiple types of cancers, including breast cancer, lung cancer, gastric cancer, uterine cancer and ovarian cancer, yet the casual relationship between these mutations and tumorigenesis is unclear. Here we will discuss possible interactions between FGFR2 signaling and several major pathways through which the aberrantly activated FGFR2 signaling may result in breast cancer development. We will also discuss some recent developments in the discovery and application of therapies and strategies for breast cancers by inhibiting FGFR2 activities.