Cutaneous squamous cell carcinoma represents the second most common cutaneous malignancy, affecting 7–11% of Caucasians in the United States. The genetic determinants of susceptibility to cutaneous squamous cell carcinoma remain largely unknown. Here we report the results of a two-stage genome-wide association study of cutaneous squamous cell carcinoma, totalling 7,404 cases and 292,076 controls. Eleven loci reached genome-wide significance (P<5 × 10⁻⁸) including seven previously confirmed pigmentation-related loci: MC1R, ASIP, TYR, SLC45A2, OCA2, IRF4 and BNC2. We identify an additional four susceptibility loci: 11q23.3 CADM1, a metastasis suppressor gene involved in modifying tumour interaction with cell-mediated immunity; 2p22.3; 7p21.1 AHR, the dioxin receptor involved in anti-apoptotic pathways and melanoma progression; and 9q34.3 SEC16A, a putative oncogene with roles in secretion and cellular proliferation. These susceptibility loci provide deeper insight into the pathogenesis of squamous cell carcinoma.

Basal cell carcinoma (BCC) is the most common cancer worldwide with an annual incidence of 2.8 million cases in the United States alone. Previous studies have demonstrated an association between 21 distinct genetic loci and BCC risk. Here, we report the results of a two-stage genome-wide association study of BCC, totalling 17,187 cases and 287,054 controls. We confirm 17 previously reported loci and identify 14 new susceptibility loci reaching genome-wide significance (P<5 × 10⁻⁸, logistic regression). These newly associated SNPs lie within predicted keratinocyte regulatory elements and in expression quantitative trait loci; furthermore, we identify candidate genes and non-coding RNAs involved in telomere maintenance, immune regulation and tumour progression, providing deeper insight into the pathogenesis of BCC.

The Gail model has been widely used and validated with conflicting results. The current study aims to evaluate the performance of different versions of the Gail model by means of systematic review and meta-analysis with trial sequential analysis (TSA). Three systematic review and meta-analyses were conducted. Pooled expected-to-observed (E/O) ratio and pooled area under the curve (AUC) were calculated using the DerSimonian and Laird random-effects model. Pooled sensitivity, specificity and diagnostic odds ratio were evaluated by bivariate mixed-effects model. TSA was also conducted to determine whether the evidence was sufficient and conclusive. Gail model 1 accurately predicted breast cancer risk in American women (pooled E/O = 1.03; 95% CI 0.76–1.40). The pooled E/O ratios of Caucasian-American Gail model 2 in American, European and Asian women were 0.98 (95% CI 0.91–1.06), 1.07 (95% CI 0.66–1.74) and 2.29 (95% CI 1.95–2.68), respectively. Additionally, Asian-American Gail model 2 overestimated the risk for Asian women about two times (pooled E/O = 1.82; 95% CI 1.31–2.51). TSA showed that evidence in Asian women was sufficient; nonetheless, the results in American and European women need further verification. The pooled AUCs for Gail model 1 in American and European women and Asian females were 0.55 (95% CI 0.53–0.56) and 0.75 (95% CI 0.63–0.88), respectively, and the pooled AUCs of Caucasian-American Gail model 2 for American, Asian and European females were 0.61 (95% CI 0.59–0.63), 0.55 (95% CI 0.52–0.58) and 0.58 (95% CI 0.55–0.62), respectively. The pooled sensitivity, specificity and diagnostic odds ratio of Gail model 1 were 0.63 (95% CI 0.27–0.89), 0.91 (95% CI 0.87–0.94) and 17.38 (95% CI 2.66–113.70), respectively, and the corresponding indexes of Gail model 2 were 0.35 (95% CI 0.17–0.59), 0.86 (95% CI 0.76–0.92) and 3.38 (95% CI 1.40–8.17), respectively. The Gail model was more accurate in predicting the incidence of breast cancer in American and European females, while far less useful for individual-level risk prediction. Moreover, the Gail model may overestimate the risk in Asian women and the results were further validated by TSA, which is an addition to the three previous systematic review and meta-analyses. PROSPERO CRD42016047215 .

Background: Mammographic density (MD) has not been systematically investigated among Chinese women. Breast cancer screening programmes provided detailed information on MD in a large number of asymptomatic women. Methods: In the Multi-modality Independent Screening Trial (MIST), we estimated the association between MD and its influential factors using logistic regression, adjusting for age, body mass index (BMI) and study area. Differences between Chinese and other ethnic groups with respect to MD were also explored with adjustment for age and BMI. Results: A total of 28 388 women aged 45 to 65 years, who had been screened by mammography, were enrolled in the study. Of these, 49.2% were categorized as having dense breasts (BI-RADS density 3 and 4) and 50.8% as fatty breasts (BI-RADS density 1 and 2). Postmenopausal status [odds ratio (OR) = 0.66; 95% confidence interval (CI): 0.62–0.70] and higher number of live births (OR = 0.56; 95% CI: 0.46–0.68) were inversely associated with MD, whereas prior benign breast disease (OR = 1.48; 95% CI: 1.40–1.56) and later age at first birth (OR = 1.17; 95% CI: 1.08–1.27) were positively associated with MD. In comparison with the data from the Breast Cancer Surveillance Consortium, we found that women in MIST were more likely to have fatty breasts than Americans (from the Breast Cancer Surveillance Consortium) in the older age group (≥50 years) but more likely to have dense breasts in the younger age group (<50 years). Conclusions: This study suggests that several risk factors for breast cancer were associated with breast density in Chinese women. Information on the determinants of mammographic density may provide valuable insights into breast cancer aetiology.

Two-stage genome-wide association study identifies a novel susceptibility locus associated with melanoma Two-stage genome-wide association study identifies a novel susceptibility locus associated with melanoma