Cancer is a well-known horrible disease that the number of its patients is forecast to rise and reach close to 25 million over the next two decades. Uncontrolled cell division and replication, and tissue invasion are main characteristics of cancer. These results in disrupting signaling cascades within the cells, cooperation and interaction between cells, and tissue structure. According to common knowledge, mutations in oncogenes and tumor suppressor genetrigger cancer initiation. Then, the mutant cell cooperates with themselves, and with stromal cells to promote cancer disease. Finally, cancer cells become more aggressive and invade neighbor tissues and spread to other parts of the body. Although genetic mutations that beget cancer initiation are random, the process by which some cancer cells are favored is not random and is controlled by the nature selection and cells’ fitness. Cancer is the consequence of somatic evolution and have all essential elements of Darwinian evolution. Traditionally, researchers from many different backgrounds have modeled interesting and unexpected ideas in cancer promotion and progression. However, most of them have ignored the evolutionary process of the cancer. The evolutionary dynamics of the tumor’s cell population is best described in terms of frequency dependent selection, akin to Evolutionary Game Theory (EGT). There are several studies using EGT to model different cancer’s hallmarks. These models also have some drawbacks such as neglecting tumor’s structure, collective behaviors, and the existence of several public goods in tumor-stroma interactions. Each of these cases can lonely changes the evolutionary dynamics of cancer cells. In this study we have proposed a game theoretical framework (includes three models) to describe the interaction of tumor’s clones in different aspects of cancer. Our framework improves the drawback through considering collective behaviors and tumor’s structure in the evolutionary dynamics. This study has been organized in three phases. In the first phase, we propose a pairwise EGT to describe MMP-TIMP interaction in both normal tissue and invasive cancer. Our model explains how invasive cancer cells get the upper hand in MMP-TIMP imbalance scenarios. In this model, we investigate the necessary conditions to inhibit cancer invasion or prolong its course. In the second phase, we have shown that a model in which growth factors have autocrine and paracrine effects on multiple cells, a more realistic assumption for tumor-stroma interactions, leads to different results, with implications for disease progression and treatment. In particular, the model reveals that reducing the number of malignant plasma cells below a critical threshold can lead to their extinction and thus to restore a healthy balance between osteoclast and osteoblast, a result in line with current therapies against multiple myeloma. In the last phase, we detail an EGT to better understand how clones capable of secreting pro-angiogenic factors can emerge in a tumor made of non-cooperative tumor cells. Given the importance of the spatial configuration of the tumor in determining the efficacy of the secretion of pro-angiogenic factors as well as the benefits of angiogenesis we have developed a spatial game theoretic approach where interactions and public good diffusion are described by graphs. The results show that structure of the population affects the evolutionary dynamics of the pro-angiogenic clone. Specifically, when the benefit of angiogenesis is represented by sigmoid function. Generally, in this study we have extended the evolutionary theory of cancer cells by considering tumor’s structure and collective behavior that leads to different results rather than other models.