Interactive visualization tools are highly desirable to biologist and cancer researchers to explore the complex structures, detect patterns and find out the relationships among bio-molecules responsible for a cancer type. A pathway contains various bio-molecules in different layers of the cell which are responsible for specific cancer type. Researchers are highly interested in understanding the relationships among the proteins of different pathways and furthermore want to know how those proteins are interacting in different pathways for various cancer types. Biologists find it useful to merge the data of different cancer studies in a single network and see the relationships among the different proteins which can help them to detect the common proteins in cancer studies and hence reveal the pattern of interaction of those proteins. We introduce CancerLinker, a visual analytic system that helps researchers to explore cancer study interaction network. We merge twenty-six cancer studies to explore pathway data and bio-molecules relationships that can provide the answers to some significant questions which are helpful in cancer research. CancerLinkeralso helps biologists explore the critical mutated proteins in multiple cancer studies. A bubble graph is constructed to visualize common protein based on its frequency and biological assemblies. Parallel coordinates highlight patterns of patient profiles (obtained from cBioportal by WebAPI services) on different attributes for a specified cancer study.