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Full-Text Articles in Oncology
Unraveling The Mechanism Of 2,4-Dinitrofluorobenzene-Associated Cell Death, Franklin Thelmo
Unraveling The Mechanism Of 2,4-Dinitrofluorobenzene-Associated Cell Death, Franklin Thelmo
Summer Training Program in Cancer Immunotherapy
The mechanism by which the hapten 2,4-dinitrophenyl (DNP) mediates cell death is unclear according to current literature. To determine how DNP mediates death in the B16F10 murine melanoma cell line in vitro, cells were modified with 2,4-dinitro-1-fluorobenzene (DNFB). Following modification, cell lysates were collected and analyzed via Western blottings with known apoptotic or necrotic markers. Our results indicated that DNFB treated cells do not express the apoptotic marker Cleaved Caspase-3 and have no change in levels of the necrotic marker Cyclophilin A. We conclude that DNFB is not inducing apoptosis in B16F10 cells. Future research will further examine the …
Survival Associated Pathway Identification With Group Lp Penalized Global Auc Maximization., Zhenqiu Liu, Laurence S Magder, Terry Hyslop, Li Mao
Survival Associated Pathway Identification With Group Lp Penalized Global Auc Maximization., Zhenqiu Liu, Laurence S Magder, Terry Hyslop, Li Mao
Department of Pharmacology and Experimental Therapeutics Faculty Papers
It has been demonstrated that genes in a cell do not act independently. They interact with one another to complete certain biological processes or to implement certain molecular functions. How to incorporate biological pathways or functional groups into the model and identify survival associated gene pathways is still a challenging problem. In this paper, we propose a novel iterative gradient based method for survival analysis with group Lp penalized global AUC summary maximization. Unlike LASSO, Lp (p < 1) (with its special implementation entitled adaptive LASSO) is asymptotic unbiased and has oracle properties 1. We first extend Lp for individual gene identification to group Lp penalty for pathway selection, and then develop a novel iterative gradient algorithm for penalized global AUC summary maximization (IGGAUCS). This method incorporates the genetic pathways into global AUC summary maximization and identifies survival associated pathways instead of individual genes. The tuning parameters are determined using 10-fold cross validation with training data only. The prediction performance is evaluated using test data. We apply the proposed method to survival outcome analysis with gene expression profile and identify multiple pathways simultaneously. Experimental results with simulation and gene expression data demonstrate that the proposed procedures can be used for identifying important biological pathways that are related to survival phenotype and for building a parsimonious model for predicting the survival times.