The precision relationships between eight GWAS-identified genetic variants and breast cancer in a Chinese population

Genetic and lifestyle factors for breast cancer risk assessment in Southeast China

BACKGROUND

Despite the rising incidence and mortality of breast cancer among women in China, there are currently few predictive models for breast cancer in the Chinese population and with low accuracy. This study aimed to identify major genetic and life-style risk factors in a Chinese population for potential application in risk assessment models.

METHODS

A case-control study in southeast China was conducted including 1321 breast cancer patients and 2045 controls during 2013-2016, in which the data were randomly divided into a training set and a test set on a 7:3 scale. The association between genetic and life-style factors and breast cancer was examined using logistic regression models. Using AUC curves, we also compared the performance of the logistic model to machine learning models, namely LASSO regression model and support vector machine (SVM), and the scores calculated from CKB, Gail and Tyrer-Cuzick models in the test set.

RESULTS

Among all factors considered, the best model was achieved when polygenetic risk score, lifestyle, and reproductive factors were considered jointly in the logistic regression model (AUC = 0.73; 95% CI: 0.70-0.77). The models created in this study performed better than those using scores calculated from the CKB, Gail, and Tyrer-Cuzick models. However, the logistic model and machine learning models did not significantly differ from one another.

CONCLUSION

In summary, we have found genetic and lifestyle risk predictors for breast cancer with moderate discrimination, which might provide reference for breast cancer screening in southeast China. Further population-based studies are needed to validate the model for future applications in personalized breast cancer screening programs.

The association of CASC16 variants with breast Cancer risk in a northwest Chinese female population

Purpose

Genetic variants play a critical role in the development of breast cancer. This investigation aimed to explore the association between CASC16 polymorphisms and breast cancer susceptibility.

Methods

We conducted a case-control study of 681 patients and 680 healthy individuals to investigate the correlation of five SNPs with breast cancer in a Northwest Chinese female population. Odds ratios (OR) and 95% confidence intervals (CIs) were used to assess the association.

Results

Our study found that rs4784227 and rs12922061 were significantly related to an increased susceptibility to breast cancer (OR 1.22, p = 0.022; OR 1.21, p = 0.026). While rs3803662 was a protective role in breast cancer risk (OR 0.69, p = 0.042). Stratified analyses indicated that rs4784227 and rs12922061 would increase breast cancer susceptibility at age >  50 years. Rs3803662 was a reduced factor of breast cancer risk by age ≤ 50 years. Rs4784227 was significantly increased risk of breast cancer in stage III/IV. The rs45544231 and rs3112612 had a protective effect on breast cancer with tumor size > 2 cm. Rs4784227 and rs12922061 could enhance breast cancer risk in lymph node metastasis positive individuals. CASC16 rs12922061 and rs4784227 polymorphisms correlated with an increased risk of breast cancer in BMI >  24 kg/m². Haplotype analyses revealed that G_rs45544231 T_rs12922061 A_rs3112612 and G_rs45544231 C_rs12922061 A_rs3112612 haplotypes decreased breast cancer risk.

Conclusion

Our study revealed that CASC16 genetic variants were significantly related to breast cancer susceptibility, which might give scientific evidence for exploring the molecular mechanism of breast cancer.

ClickGene: an open cloud-based platform for big pan-cancer data genome-wide association study, visualization and exploration

Tremendous amount of whole-genome sequencing data have been provided by large consortium projects such as TCGA (The Cancer Genome Atlas), COSMIC and so on, which creates incredible opportunities for functional gene research and cancer associated mechanism uncovering. While the existing web servers are valuable and widely used, many whole genome analysis functions urgently needed by experimental biologists are still not adequately addressed. A cloud-based platform, named CG (ClickGene), therefore, was developed for DIY analyzing of user's private in-house data or public genome data without any requirement of software installation or system configuration. CG platform provides key interactive and customized functions including Bee-swarm plot, linear regression analyses, Mountain plot, Directional Manhattan plot, Deflection plot and Volcano plot. Using these tools, global profiling or individual gene distributions for expression and copy number variation (CNV) analyses can be generated by only mouse button clicking. The easy accessibility of such comprehensive pan-cancer genome analysis greatly facilitates data mining in wide research areas, such as therapeutic discovery process. Therefore, it fills in the gaps between big cancer genomics data and the delivery of integrated knowledge to end-users, thus helping unleash the value of the current data resources. More importantly, unlike other R-based web platforms, Dubbo, a cloud distributed service governance framework for 'big data' stream global transferring, was used to develop CG platform. After being developed, CG is run on an independent cloud-server, which ensures its steady global accessibility. More than 2 years running history of CG proved that advanced plots for hundreds of whole-genome data can be created through it within seconds by end-users anytime and anywhere. CG is available at http://www.clickgenome.org/.

LINC01585 functions as a regulator of gene expression by the CAMP/CREB signaling pathway in breast cancer

OBJECTIVE

Breast cancer is the leading cause of cancer death among women. Nowadays, long non-coding RNAs (lncRNAs) have been identified and emerged as critical bio-markers in breast cancer tumorigenesis and progression. However, only a handful of lncRNAs which are implicated in BC have been characterized. The underlying molecular mechanisms are still largely unknown.

METHODS

In this study, we explored 12 nominated lncRNAs at breast cancer susceptibility loci identified by genome-wide association studies to contribute to the risk and effects of breast cancer. We then analyzed these lncRNAs in a total of 132 pairs of breast cancer tissues and surrounding non-tumor tissues from southern China population.

RESULTS

Here, we report a novel lncRNA, LINC01585, is aberrantly down regulated during breast cancer (BC). Next, to explore the molecular mechanisms underlying the biological activity of LINC01585, we identified LINC01585 binding protein by RNA pull-down experiments. Functionally, we found that LINC01585 overexpression inhibited breast cancer proliferation and growth by prototypical experiments. Mechanistically, LINC01585 was located in nuclear and binding with NONO protein. Interestingly, when LINC01585 was down-expressed, NONO separated from LINC01585 and then interacted with CRTC. The complex promotes CAMP/CREB target gene transcription and thus promotes the growth of breast cancer.

CONCLUSIONS

A series of discoveries suggest to us that LINC01585 has a potential value in anti-carcinoma therapy and deserves further investigation.

Subtype-specific associations between breast cancer risk polymorphisms and the survival of early-stage breast cancer

BACKGROUND

Limited evidence suggests that inherited predisposing risk variants might affect the disease outcome. In this study, we analyzed the effect of genome-wide association studies-identified breast cancer-risk single nucleotide polymorphisms on survival of early-stage breast cancer patients in a Chinese population.

METHODS

This retrospective study investigated the relationship between 21 GWAS-identified breast cancer-risk single nucleotide polymorphisms and the outcome of 1177 early stage breast cancer patients with a long median follow-up time of 174 months. Cox proportional hazards regression models were used to estimate the hazard ratios and their 95% confidence intervals. Primary endpoints were breast cancer special survival and overall survival while secondary endpoints were invasive disease free survival and distant disease free survival.

RESULTS

Multivariate survival analysis showed only the rs2046210 GA genotype significantly decreased the risk of recurrence and death for early stage breast cancer. After grouping breast cancer subtypes, significantly reduced survival was associated with the variant alleles of rs9485372 for luminal A and rs4415084 for triple negative breast cancer. Importantly, all three single-nucleotide polymorphisms, rs889312, rs4951011 and rs9485372 had remarkable effects on survival of luminal B EBC, either individually or synergistically. Furthermore, statistically significant multiplicative interactions were found between rs4415084 and age at diagnosis and between rs3803662 and tumor grade.

CONCLUSIONS

Our results demonstrate that breast cancer risk susceptibility loci identified by GWAS may influence the outcome of early stage breast cancer patients' depending on intrinsic tumor subtypes in Chinese women.

Polymorphisms in the TOX3/LOC643714 and risk of breast cancer in south China

OBJECTIVE

Breast cancer is the most widespread cancer in women, with a high mortality rate. This study aims to assess the association between single nucleotide polymorphisms (SNPs) of LOC643714 (rs12922061) and TOX3 (rs3803662) and breast cancer, as well as the clinical characteristics of tumors.

MATERIALS AND METHODS

In total, 104 breast cancer patients and 118 healthy controls were recruited to our study. The genotyping was performed by the SNP scan method. General characteristics, the clinical characteristics of tumors and reproductive factors were included in the analysis. Statistical tests included the Student t-test, the Chi-square test (X2) or Fisher's exact test, and unconditional logistic regression analysis. The receiver operating characteristic curves were used to evaluate the predictive role of rs12922061 in breast cancer.

RESULTS

The LOC643714 polymorphism was a risk factor for breast cancer under a dominant model (TT+TC vs. CC: OR 1.801; 95% CI 1.048, 3.095; statistical power=60%), recessive model (TT vs. TC + CC: OR 4.297; 95% CI 1.164, 15.867; statistical power=64%) and log-additive (TT vs. CC: OR 5.163; 95% CI 1.368, 19.485; statistical power= 73%). Furthermore, the rs12922061 polymorphism was associated with menopause status in patients ( P=0.005). No statistically significant association was found between the rs3803662 polymorphism and breast cancer in patients or healthy controls.

CONCLUSIONS

Our study found that rs12922061 of LOC643714 was related to breast cancer risk. With a limited sample size and statistical power, further multi-center studies are needed to confirm the influence of the LOC643714 polymorphisms on breast cancer based on larger populations.

Evaluation of three polygenic risk score models for the prediction of breast cancer risk in Singapore Chinese

Genome-wide association studies (GWAS) have proven highly successful in identifying single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. The majority of these studies are on European populations, with limited SNP association data in other populations. We genotyped 51 GWAS-identified SNPs in two independent cohorts of Singaporean Chinese. Cohort 1 comprised 1294 BC cases and 885 controls and was used to determine odds ratios (ORs); Cohort 2 had 301 BC cases and 243 controls for deriving polygenic risk scores (PRS). After age-adjustment, 11 SNPs were found to be significantly associated with BC risk. Five SNPs were present in <1% of Cohort 1 and were excluded from further PRS analysis. To assess the cumulative effect of the remaining 46 SNPs on BC risk, we generated three PRS models: Model-1 included 46 SNPs; Model-2 included 11 statistically significant SNPs; and Model-3 included the SNPs in Model-2 but excluded SNPs that were in strong linkage disequilibrium with the others. Across Models-1, -2 and -3, women in the highest PRS quartile had the greatest ORs of 1.894 (95% CI = 1.157–3.100), 2.013 (95% CI = 1.227–3.302) and 1.751 (95% CI = 1.073–2.856) respectively, suggesting a direct correlation between PRS and BC risk. Given the potential of PRS in BC risk stratification, our findings suggest the need to tailor the selection of SNPs to be included in an ethnic-specific PRS model.

Polymorphisms of long non-coding RNA HOTAIR with breast cancer susceptibility and clinical outcomes for a southeast Chinese Han population

Hox transcript antisense intergenic RNA (HOTAIR) is a well-known long non-coding RNA (lncRNA) which participates in tumorigenesis and progress of multiple cancers. However, the associations among polymorphisms on HOTAIR, breast cancer (BC) susceptibility and clinical outcomes have remained obscure. In this case-control study, we assessed the interaction between three lncRNA HOTAIR single nucleotide polymorphisms (SNPs) (rs1899663, rs4759314 and rs7958904) on the risk and clinical outcome of breast cancer in a Chinese Han population. In total, 969 breast cancer cases and 970 healthy controls were enrolled in this study. Associations among genotypes, BC risk and survival were evaluated by univariate and multivariate logistic regression to estimate the odds ratio (OR), hazard ratio (HR) and its 95% confidence interval (CI). The disease-free survival (DFS) and overall survival (OS) was calculated by the Kaplan–Meier method. We found that the T allele of rs1899663 and C allele of rs7958904 both achieved significant differences between cases and controls in the single locus analyses (P = 0.017 and 0.010, respectively). Multivariate analyses also revealed the rs1899663 TT genotype and rs7958904 CC genotype were both at higher risk of breast cancer compared with the GG homozygotes (OR = 2.08, 95% CI = 1.20–3.60 and OR = 1.45, 95% CI = 1.01–2.08, respectively). In survival analysis, we observed that the T allele of rs1899663 presented significant differences for both DFS (HR = 1.64, 95% CI = 1.12–2.40) and OS (HR = 2.10, 95% CI = 1.29–3.42) in younger subjects (age ≤ 40). Our findings may provide new insights into the associations among the genetic susceptibility, the fine classifications and the prognosis of breast cancer. Further studies with larger sample size and functional research should also be conducted to validate our findings and better elucidate the underlying biological mechanisms.

IL-8 -251A/T and +781C/T polymorphisms were associated with risk of breast cancer in a Chinese population

Breast cancer is the leading cause of death of women in worldwide. The real mechanism of breast cancer is still unclear. IL-8 is a member of the chemokine superfamily, which plays an important role in regulating both inflammatory and immune processes. We performed a hospital-based case-control study to estimate the association between IL-8 -251A/T, -353A/T and +781C/T polymorphisms and risk of breast cancer in a Chinese population, and interaction between IL-8 polymorphism and environmental factors. During January 2014 and July 2016, a total of 442 patients with breast cancer and 447 normal control subjects were enrolled into our study. The IL-8 -251A/T, -353A/T and +781C/T polymorphisms were analyzed by the polymerase chain reaction (PCR)-restriction fragment length polymorphism (RFLP). The TT genotype of IL-8 -251A/T was associated with higher risk of breast cancer as compared with the AA genotype (adjusted OR=1.96, 95% CI=1.26-3.05). Individuals carrying TT genotype of IL-8 -251A/T was correlated with an elevated risk of breast cancer in recessive model, when compared with the AA+AT genotype (adjusted OR=1.91, 95% CI=1.26-2.90). For the IL-8 +781C/T, the TT genotype showed lower association with risk of breast cancer in comparison to the CC genotype (adjusted OR=0.49, 95% CI=0.26-0.91); the TT genotype was also correlated with a decreased risk of breast cancer in recessive model (adjusted OR=0.46, 95% CI=0.25-0.84), as compared with the CC+CT genotype. In conclusion, our study suggests that IL-8 -251A/T and +781C/T could potentially be a biomarker for susceptibility to breast cancer risk.