A linear mixed-effects model approach was used to estimate and compare tumor growth rate between treatment groups. Each experiment was analyzed separately. Logarithmic transformation was applied to the original measurements on tumor volume to assure approximate normality and to satisfy linear mixed-effects model assumptions. Random coefficient regression models allowed us to estimate and compare the exponential parameters that governed growth rate. Treatment groups’ comparisons were prespecified. Testing for differences in groups’ slopes was done using appropriate contrasts in the regression models. OS functions were estimated using the Kaplan-Meier method. General linear models, one-way and two-way analysis of variance (ANOVA), as well as Student’s t test were used to summarize the laboratory measurements and to compare their distributions between treatment groups. Testing was done at the 0.05 type I error level. All P values reported are nominal. Statistical analysis was conducted using R Studio (http://rstudio.com/, v. 1.1.453), SAS (SAS Institute Inc., Cary, NC), and GraphPad Software. Tests used are indicated in the figure legends.

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