Pediatric cancers are the leading cause of death by disease in children despite improved survival rates overall. The contribution of germline genetic susceptibility to pediatric cancer survivors has not been extensively characterized. We assessed the frequency of pathogenic or likely pathogenic (P/LP) variants in 5451 long-term pediatric cancer survivors from the Childhood Cancer Survivor Study.
Abstract Purpose In addition to impacting incidence, risk factors for breast cancer may also influence recurrence and survival from the disease. However, it is unclear how these factors affect combinatorial biomarkers for aiding treatment decision-making in breast cancer. Methods Patients were 8179 women with histologically confirmed invasive breast cancer, diagnosed and treated in a large cancer hospital in Beijing, China. Individual clinicopathological (tumor size, grade, lymph nodes) and immunohistochemical (IHC: ER, PR, HER2, KI67) markers were used to define clinically relevant combinatorial prognostic biomarkers, including the Nottingham Prognostic Index (NPI: combining size, grade, nodes) and IHC4 score (combining ER, PR, HER2, KI67). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between breast cancer risk factors and quartiles (Q1–Q4) of NPI and IHC4 were assessed in multivariable polytomous logistic regression models. Results Overall, increasing parity (OR trend (95% CI) = 1.20(1.05–1.37); P trend = 0.007), overweight (OR(95% CI) vs normal = 1.60(1.29–1.98)), and obesity (OR(95% CI) vs normal = 2.12(1.43–3.14)) were associated with higher likelihood of developing tumors with high (Q4) versus low (Q1) NPI score. Conversely, increasing age (OR trend (95% CI) = 0.75(0.66–0.84); P trend < 0.001) and positive family history of breast cancer (FHBC) (OR(95% CI) = 0.66(0.45–0.95)) were inversely associated with NPI. Only body mass index (BMI) was associated with IHC4, with overweight (OR(95% CI) vs normal = 0.82(0.66–1.02)) and obese (OR(95% CI) vs normal = 0.52(0.36–0.76)) women less likely to develop high IHC4 tumors. Notably, elevated BMI was associated with higher NPI irrespective of hormone receptor-expression status. Conclusions Our findings indicate that factors affecting breast cancer incidence, particularly age, parity, FHBC, and BMI, may impact clinically relevant prognostic biomarkers with implications for surveillance, prognostication, and counseling.
Array comparative genomic hybridization(CGH) is a high resolution technique to assess DNA copy number variation. Identifying breakpoints where copy number changes will enhance the understanding of the pathogenesis of human diseases, such as cancers. However, the biological variation and experimental errors contained in array CGH data may lead to false positive identification of breakpoints. We propose a robust state space model for array CGH data analysis. The model consists of two equations: an observation equation and a state equation, in which both the measurement error and evolution error are specified to follow t-distributions with small degrees of freedom. The completely unspecified CGH profiles are estimated by a Markov Chain Monte Carlo(MCMC) algorithm. Breakpoints and outliers are identified by a novel backward selection procedure based on posterior draws of the CGH profiles. Compared to three other popular methods, our method demonstrates several desired features, including false positive rate control, robustness against outliers, and superior power of breakpoint detection. All these properties are illustrated using simulated and real datasets.
Background: Diesel exhaust is a complex mixture, including polycyclic aromatic hydrocarbons (PAH) and nitrated PAHs (nitro-PAH), many of which are potent mutagens and possible bladder carcinogens. To explore the association between diesel exposure and bladder carcinogenesis, we examined the relationship between exposure and somatic mutations and mutational signatures in bladder tumors. Methods: Targeted sequencing was conducted in bladder tumors from the New England Bladder Cancer Study. Using data on 797 cases and 1,418 controls, two-stage polytomous logistic regression was used to evaluate etiologic heterogeneity between bladder cancer subtypes and quantitative, lifetime estimates of respirable elemental carbon (REC), a surrogate for diesel exposure. Poisson regression was used to evaluate associations between REC and mutational signatures. Results: We observed significant heterogeneity in the diesel-bladder cancer risk relationship, with a strong positive association among cases with high-grade, nonmuscle invasive TP53-mutated tumors compared with controls [ORTop Tertile vs.Unexposed, 4.8; 95% confidence interval (CI), 2.2–10.5; Ptrend < 0.001; Pheterogeneity = 0.002]. In muscle-invasive tumors, we observed a positive association between diesel exposure and the nitro-PAH signatures of 1,6-dintropyrene (RR, 1.93; 95% CI, 1.28–2.92) and 3-nitrobenzoic acid (RR, 1.97; 95% CI, 1.33–2.92). Conclusions: The relationship between diesel exhaust and bladder cancer was heterogeneous based on the presence of TP53 mutations in tumors, further supporting the link between PAH exposure and TP53 mutations in carcinogenesis. Future studies that can identify nitro-PAH signatures in exposed tumors are warranted to add human data supporting the link between diesel and bladder cancer. Impact: This study provides additional insight into the etiology and possible mechanisms related to diesel exhaust-induced bladder cancer.
