Oncology Commons^™

Clinical Pharmacology Of Tisagenlecleucel In B-Cell Acute Lymphoblastic Leukemia., Karen Thudium Mueller, Edward Waldron, Stephan A. Grupp, John E. Levine, Theodore W. Laetsch, Michael A. Pulsipher, Michael W. Boyer, Keith August, Jason Hamilton, Rakesh Awasthi, Andrew M. Stein, Denise Sickert, Abhijit Chakraborty, Bruce L. Levine, Carl H. June, Lori Tomassian, Sweta S. Shah, Mimi Leung, Tetiana Taran, Patricia A. Wood, Shannon L. Maude

Manuscripts, Articles, Book Chapters and Other Papers

PURPOSE: Tisagenlecleucel is an anti-CD19 chimeric antigen receptor (CAR19) T-cell therapy approved for the treatment of children and young adults with relapsed/refractory (r/r) B-cell acute lymphoblastic leukemia (B-ALL).

PATIENTS AND METHODS: We evaluated the cellular kinetics of tisagenlecleucel, the effect of patient factors, humoral immunogenicity, and manufacturing attributes on its kinetics, and exposure-response analysis for efficacy, safety and pharmacodynamic endpoints in 79 patients across two studies in pediatric B-ALL (ELIANA and ENSIGN).

RESULTS: Using quantitative polymerase chain reaction to quantify levels of tisagenlecleucel transgene, responders (N = 62) had ≈2-fold higher tisagenlecleucel expansion in peripheral blood than nonresponders ( …

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.