Qingyi Wei

ATM (ataxia-telangiectasia mutated) is an important cell-cycle checkpoint kinase required for cellular response to DNA damage. Activated by DNA double strand breaks, ATM regulates the activities of many downstream proteins involved in various carcinogenic events. Therefore, ATM or its genetic variants may have a pleiotropic effect in cancer development. We conducted a pleiotropic analysis to evaluate associations between genetic variants of ATM and risk of multiple cancers. With genotyping data extracted from previously published genome-wide association studies of various cancers, we performed multivariate logistic regression analysis, followed by a meta-analysis for each cancer site, to identify cancer risk-associated single-nucleotide polymorphisms (SNPs). In the ASSET two-sided analysis, we found that two ATM SNPs were significantly associated with risk of multiple cancers. One tagging SNP (rs1800057 C>G) was associated with risk of multiple cancers (two-sided P=5.27×10 -7). Because ATM rs1800057 is a missense variant, we also explored the intermediate phenotypes through which this variant may confer risk of multiple cancers and identified a possible immune-mediated effect of this variant. Our findings indicate that genetic variants of ATM may have a pleiotropic effect on cancer risk and thus provide an important insight into common mechanisms of carcinogenesis.

Forkhead box class O (FOXO) transcription factors play a pivotal role in regulating a variety of biological processes, including organismal development, cell signaling, cell metabolism, and tumorigenesis. Therefore, we hypothesize that genetic variants in FOXO pathway genes are associated with breast cancer (BC) risk. To test this hypothesis, we conducted a large meta-analysis using 14 published genome-wide association study (GWAS) data sets in the Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) study. We assessed associations between 5214 (365 genotyped in DRIVE and 4849 imputed) common single-nucleotide polymorphisms (SNPs) in 55 FOXO pathway genes and BC risk. After multiple comparison corrections by the Bayesian false-discovery probability method, we found five SNPs to be significantly associated with BC risk. In stepwise multivariate logistic regression analysis with adjustment for age, principal components, and previously published SNPs in the same data set, three independent SNPs (i.e., FBXO32 rs10093411 A>G, FOXO6 rs61229336 C>T, and FBXO32 rs62521280 C>T) remained to be significantly associated with BC risk (p = 0.0008, 0.0011, and 0.0017, respectively). Additional expression quantitative trait loci analysis revealed that the FBXO32 rs62521280 T allele was associated with decreased messenger RNA (mRNA) expression levels in breast tissue, while the FOXO6 rs61229336 T allele was found to be associated with decreased mRNA expression levels in the whole blood cells. Once replicated by other investigators, these genetic variants may serve as new biomarkers for BC risk.

Mitosis is a prognostic factor for cutaneous melanoma (CM), but accurate mitosis detection in CM tissues is difficult. Therefore, the 8th Edition of the American Joint Committee on Cancer staging system has removed the mitotic rate as a category criterion of the tumor T-category, based on the evidence that the mitotic rate was not an independent prognostic factor for melanoma survival. As single-nucleotide polymorphisms (SNPs) have been shown to be potential predictors for cutaneous melanoma-specific survival (CMSS), we investigated the potential prognostic value of SNPs in mitosis-related pathway genes in CMSS by analyzing their associations with outcomes of 850 CM patients from The University of Texas MD Anderson Cancer Center in a discovery dataset and validated the findings in another dataset of 409 CM patients from the Harvard University Nurses' Health Study and Health Professionals Follow-up Study. In both datasets, we identified two SNPs (SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T) as independent prognostic factors for CMSS, with adjusted allelic hazards ratios of 1.49 (95% confidence interval = 1.17-1.90, P = .001) and 1.45 (1.13-1.86, P = .003), respectively. Furthermore, their combined unfavorable alleles also predicted a poor survival in both discovery and validation datasets in a dose-response manner (Ptrend  = .0006 and .0001, respectively). Additional functional analysis revealed that both SDCCAG8 rs10803138 A and MAGI2 rs3807694 T alleles were associated with elevated mRNA expression levels in normal tissues. Therefore, these findings suggest that SDCCAG8 rs10803138 G>A and MAGI2 rs3807694 C>T are independent prognostic biomarkers for CMSS, possibly by regulating the mRNA expression of the corresponding genes involved in mitosis.

The mitotic phase is a vital step in cell division and may be involved in cancer progression, but it remains unclear whether genetic variants in mitotic phase-related pathways genes impact the survival of these patients. Here, we investigated associations between 31 032 single nucleotide polymorphisms (SNPs) in 368 mitotic phase-related pathway genes and overall survival (OS) of patients with nonsmall cell lung cancer (NSCLC). We assessed the associations in a discovery data set of 1185 NSCLC patients from the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial and validated the findings in another data set of 984 patients from the Harvard Lung Cancer Susceptibility Study. As a result, we identified three independent SNPs (ie, CHEK1 rs76744140 T>C, PRIM2 rs6939623 G>T and CDK6 rs113181986 G>C) to be significantly associated with NSCLC OS with an adjusted hazard ratio of 1.29 (95% confidence interval = 1.11-1.49, P = 8.26 × 10-4 ), 1.26 (1.12-1.42, 1.10 × 10-4 ) and 0.73 (0.63-0.86, 1.63 × 10-4 ), respectively. Moreover, the number of combined unfavorable genotypes of these three SNPs was significantly associated with NSCLC OS and disease-specific survival in the PLCO data set (Ptrend  < .0001 and .0003, respectively). Further expression quantitative trait loci analysis showed that the rs76744140C allele predicted CHEK1 mRNA expression levels in normal lung tissues and that rs113181986C allele predicted CDK6 mRNA expression levels in whole blood tissues. Additional analyses indicated CHEK1, PRIM2 and CDK6 may impact NSCLC survival. Taken together, these findings suggested that these genetic variants may be prognostic biomarkers of patients with NSCLC.

Cancer site-specific polygenic risk scores (PRS) effectively identify individuals at high risk of individual cancers, but the effectiveness of PRS on overall cancer risk assessment and the extent to which a high genetic risk of overall cancer can be offset by a healthy lifestyle remain unclear. Here, we constructed an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific PRSs. Lifestyle was determined according to smoking, alcohol consumption, physical activity, body mass index, and diet. Cox regression by sex was used to analyze associations of genetic and lifestyle factors with cancer incidence using UK Biobank data (N = 442,501). Compared with participants at low genetic risk (bottom quintile of CPRS), those at intermediate (quintiles 2 to 4) or high (top quintile) genetic risk had HRs of 1.27 (95% confidence interval, 1.21-1.34) or 1.91 (1.81-2.02) for overall cancer, respectively, for men, and 1.21 (1.16-1.27) or 1.62 (1.54-1.71), respectively, for women. A joint effect of genetic and lifestyle factors on overall cancer risk was observed, with HRs reaching 2.99 (2.45-3.64) for men and 2.38 (2.05-2.76) for women with high genetic risk and unfavorable lifestyle compared with those with low genetic risk and favorable lifestyle. Among participants at high genetic risk, the standardized 5-year cancer incidence was significantly reduced from 7.23% to 5.51% for men and from 5.77% to 3.69% for women having a favorable lifestyle. In summary, individuals at high genetic risk of overall cancer can be identified by CPRS, and risk can be attenuated by adopting a healthy lifestyle. SIGNIFICANCE: A new indicator of cancer polygenic risk score measures genetic risk for overall cancer, which could identify individuals with high cancer risk to facilitate decision-making about lifestyle modifications for personalized prevention.