Figure 5

Comparative statistics of the normalized frequency distributions observed for different cellular states in master aNSC and general glioma models with and without the inputs of TCGA-LGG and TCGA-GBM RNA-Seq expression data. (A) A significant difference (Chi-Square goodness-of-fit test, P-Value < 0.001) is observed in the normalized frequency distributions while comparing the effect of TCGA-LGG expression profile in aNSC model simulation. Cellular states such as Apoptosis and NSC Renewal/Apoptosis are found to be absent in the aNSC model with TCGA-LGG expression profile. Normalized frequencies of ASPC Differentiation and GSC Renewal are also slightly increased in this scenario as compared to the master aNSC model simulation. (B) The normalized frequency distribution of the cellular states of general glioma model is well fitted with the simulation outcomes of general glioma model with transcriptomics profile of TCGA-LGG patient cohort. Similar to these analyses, mRNA expressions profile of the TCGA-GBM patient cohort is also given as inputs in (C) aNSC and (D) general glioma models. In both the scenarios, significant differences are observed between the expected and observed (outcomes from TCGA-GBM) normalized frequency distributions of the cellular states. These results prove that the developed aNSC and general glioma models are capable of differentiating the mRNA expression profiles of LGG and GBM patient cohorts correctly.