The exponential growth of biological datasets in recent years has increased the dependency of cancer research on AI and computational analysis. Cancer evolves through the accumulation of genetic events over time, which are represented through different types of data. Integration of machine learning methods with temporal modeling and genomic methods has the potential to improve our understanding and treatment of cancer. In this talk, we will discuss emerging data science challenges for cancer research and opportunities to address these challenges using integrated AI frameworks.