Bayesian Network Inference. Enables Unbiased Phenotypic Anchoring of Transcriptomic Responses to Cigarette Smoke in Humans

Microarray-based transcriptomic analysis has been demonstrated to hold the opportunity to study the effects of human exposure to, e.g., chemical carcinogens at the whole genome level, thus yielding broad-ranging molecular information on possible carcinogenic effects. Since genes do not operate individually but rather through concerted interactions, analyzing and visualizing networks of genes should provide important mechanistic information, especially upon connecting them to functional parameters, such as those derived from measurements of biomarkers for exposure and carcinogenic risk. Conventional methods such as hierarchical clustering and correlation analyses are frequently used to address these complex interactions but are limited as they do not provide directional causal dependence relationships. Therefore, our aim was to apply Bayesian network inference with the purpose of phenotypic anchoring of modified gene expressions. We investigated a use case on transcriptomic responses to cigarette smoking in humans, in association with plasma cotinine levels as biomarkers of exposure and aromatic DNA-adducts in blood cells as biomarkers of carcinogenic risk. Many of the genes that appear in the Bayesian networks surrounding plasma cotinine, and to a lesser extent around aromatic DNA-adducts, hold biologically relevant functions in inducing severe adverse effects of smoking. In conclusion, this study shows that Bayesian network inference enables unbiased phenotypic anchoring of transcriptomics responses. Furthermore, in all inferred Bayesian networks several dependencies are found which point to known but also to new relationships between the expression of specific genes, cigarette smoke exposure, DNA damaging-effects, and smoking-related diseases, in particular associated with apoptosis, DNA repair, and tumor suppression, as well as with autoimmunity

Recording of hormone therapy and breast density in breast screening programs: summary and recommendations of the International Cancer Screening Network.

Item does not contain fulltextBreast density and the use of hormone therapy (HT) for menopausal symptoms alter the risk of breast cancer and both factors influence screening mammography performance. The International Cancer Screening Network (ICSN) surveyed its 29 member countries and found that few programs record breast density or the use of HT among screening participants. This may affect the ability of programs to assess their effectiveness in reducing breast cancer mortality. Seven countries recorded the use of HT at screening, and some were able to link screening records to individual prescribing records of HT. Eight countries reported recording breast density at screening mammography for some or all women screened. The recommendations of the ICSN for recording information about breast density and HT are presented.1 december 201