Cancer development results from a complex interplay of different phenomena that span a wide range of time and length scales. Mathematical and computational modeling may help to unfold the role of multiple evolving factors that exist and interact in the tumor microenvironment. Understanding these complex multiscale interactions is a crucial step towards developing effective drug therapies. Here we show a general framework for the multiscale modeling of the cancer development that encompasses different mathematical and computational approaches. We discuss challenges and opportunities of ongoing cancer research towards application to clinical practice and personalized clinical decision support.