Anti-CDKN3 (full length) polyclonal antibody

Choline dietary intake varies such that many people do not achieve adequate intakes. Diet intake of choline can modulate methylation because, via betaine homocysteine methyltransferase (BHMT), this nutrient (and its metabolite, betaine) regulate the concentrations of S-adenosylhomocysteine and S-adenosylmethionine. Some of the epigenetic mechanisms that modify gene expression without modifying the genetic code depend on the methylation of DNA or of histones; and diet availability of choline and other methyl-group donors influences both of these methylations. Examples of methyl-donor mediated epigenetic effects include the changes in coat color and body weight in offspring when pregnant agouti mice are fed high choline, high methyl diets; the changes in tail kinking in offspring when pregnant Axin(Fu) mice are fed high choline, high methyl diets; the changes in Cdkn3 methylation and altered brain development that occurs in offspring when pregnant rodents are fed low choline diets. When choline metabolism is disrupted by deleting the gene Bhmt, DNA methylation is affected (especially in a region of chromosome 13), expression of specific genes is suppressed, and liver cancers develop. Better understanding of how nutrients such as choline and methyl-donors influence epigenetic programs has importance for our understanding of not only developmental abnormalities but also for understanding the origins of chronic diseases.

Background: MUC1 protein is highly expressed in lung cancer. The cytoplasmic domain of MUC1 (MUC1-CD) induces tumorigenesis and resistance to DNA-damaging agents. We characterized MUC1-CD-induced transcriptional changes and examined their significance in lung cancer patients. Methods: Using DNA microarrays, we identified 254 genes that were differentially expressed in cell lines transformed by MUC1-CD compared to control cell lines. We then examined expression of these genes in 441 lung adenocarcinomas from a publicly available database. We employed statistical analyses independent of clinical outcomes, including hierarchical clustering, Student's t-tests and receiver operating characteristic (ROC) analysis, to select a seven-gene MUC1-associated proliferation signature (MAPS). We demonstrated the prognostic value of MAPS in this database using Kaplan-Meier survival analysis, log-rank tests and Cox models. The MAPS was further validated for prognostic significance in 84 lung adenocarcinoma patients from an independent database. Results: MAPS genes were found to be associated with proliferation and cell cycle regulation and included CCNB1, CDC2, CDC20, CDKN3, MAD2L1, PRC1 and RRM2. MAPS expressors (MAPS+) had inferior survival compared to non-expressors (MAPS-). In the initial data set, 5-year survival was 65% (MAPS-) vs. 45% (MAPS+, p < 0.0001). Similarly, in the validation data set, 5-year survival was 57% (MAPS-) vs. 28% (MAPS+, p = 0.005). Conclusions: The MAPS signature, comprised of MUC1-CD-dependent genes involved in the control of cell cycle and proliferation, is associated with poor outcomes in patients with adenocarcinoma of the lung. These data provide potential new prognostic biomarkers and treatment targets for lung adenocarcinoma.