Cell signaling pathway is an important facet of biological life. The integration of protein interaction and gene expression data is suitable to uncover the regulation of pathway. However, these methods are still confined to a partial region of large-scale genomics and whole-proteomics. In previous studies for this topic, researches usually focused on the gene level or some limited groups, thus several cancer-related genes cannot appear to known pathway maps. This study presents an approach to finding potential fragments of activated pathways around known pathways between the different stages of cancers. We used a maximum score-based function that integrates genomics and proteomics information. The quantification of the strength of gene expression change was implemented and the global status pathway maps were illustrated. The resulting map shows a possible correspondence between known pathway and cancer-related genes that are not on the known pathway. Comparing diverse status pathway map reveals a global change of diverse disease states pathway level. In this study, the data of bladder cancer was analyzed to explain which potential fragments of pathway play important role at different cancer stages. The insight we gain from the pathway map of different disease statuses helps us to understand the progress of cancer.