An R-package for the Estimation and Testing of Multiple Covariates and Biomarker Interactions for Survival Data Based on Local Partial Likelihood

When we study the variables that a ffect survival time, we usually estimate their eff ects by the Cox regression model. In biomedical research, e ffects of the covariates are often modi ed by a biomarker variable. This leads to covariates-biomarker interactions. Here biomarker is an objective measurement of the patient characteristics at baseline. Liu et al. (2015) has built up a local partial likelihood bootstrap model to estimate and test this interaction e ffect of covariates and biomarker, but the R code developed by Liu et al. (2015) can only handle one variable and one interaction term and can not t the model with adjustment to nuisance variables. In this project, we expand the model to allow adjustment to nuisance variables, expand the R code to take any chosen interaction terms, and we set up many parameters for users to customize their research. We also build up an R package called "lplb" to integrate the complex computations into a simple interface. We conduct numerical simulation to show that the new method has excellent fi nite sample properties under both the null and alternative hypothesis. We also applied the method to analyze data from a prostate cancer clinical trial with acid phosphatase (AP) biomarker.

Functional Characterization of TAFI mutants Resistant to Activation by Thrombin, Thrombin-Thrombomodulin or Plasmin

Thrombin-activatable fibrinolysis inhibitor (TAFI) is a human plasma zymogen that acts as a molecular link between the coagulation and fibrinolytic cascades. TAFI can be activated by thrombin and plasmin but the reaction is enhanced significantly when thrombin is in a complex with the endothelial cofactor thrombomodulin (TM). The in vitro properties of TAFI have been extensively characterized. Activated TAFI (TAFIa) is a thermally unstable enzyme that attenuates fibrinolysis by catalyzing the removal of basic residues from partially degraded fibrin. The in vivo role of the TAFI pathway, however, is poorly defined and very little is known about the role of different activators in regulating the TAFI pathway. In the present study, we have constructed and characterized various TAFI mutants that are resistant to activation by specific activators. Based on peptide sequence studies, these mutants were constructed by altering key amino acid residues surrounding the scissile R92-A93 bond. We measured the thermal stabilities of all our mutants and found them to be similar to wild type TAFI. We have identified that the TAFI mutants P91S, R92K, and S90P are impaired in activation by thrombin or thrombin-TM, thrombin alone, and thrombin alone or plasmin, respectively. The TAFI mutants A93V and S94V were predicted to be resistant to activation by plasmin but this was not observed. The triple mutant, DVV was not activated by any of the aforementioned activators. Finally, we have used in vitro fibrin clot lysis assays to evaluate the antifibrinolytic potential of our variants and were able to correlate their effectiveness with their respective activation kinetics. In summary, we have developed activation resistant TAFI variants that can potentially be used to explore the role of the TAFI pathway in vivo.