p53MutaGene: Tutorial

p53Mutagene allows statistical validation in clinical settings of mut-p53 effects on gene networks.
A) Mut-p53 has been associated with its ability to interact with proteins and altering their physiological activity. Therefore, in a tumour carrying a mutation in p53 the presence of mut-p53 proteins can affect the ability of transcriptional factors (TFs) to regulate their targets. This working model would predict that correlation between a mut-p53 sensitive TF and its TF targets is different when computed in a wt p53-expressing cohort or in a mut-p53 expressing cohort of cancer patients.
B) By using clinical cancer datasets, p53Mutagene single mode computes TF/TF target correlation in the two cohorts and estimates whether a statistically significant shift is observed.
C) Workflow of p53Mutagene Discovery Mode: The user inputs data obtained from omics experiments. The input gene list can be divided into lists of putative TFs and putative Targets. p53Mutagene will compute correlations of for all TF/target pairs in wt p53 and mut-p53 expressing patient samples, using clinical datasets selected by the user. Based on the number of models (TF/TF target) significantly affected in the two cohorts, the tool ranks the TF list. The final output will be a ranked list of TFs, associated with putative targets, whose activity could be potentially affected by mut-p53.

Feel free to use other BioProfiling tools: