Cancer is a complex and multifaceted disease characterized by the uncontrolled growth and spread of abnormal cells, leading to significant challenges in diagnosis, treatment, and management. As one of the primary causes of death worldwide, understanding the underlying mechanisms of cancer is crucial for developing more effective therapies and improving patient outcomes. Cancer mathematical models are essential in the quest to understand the complex mechanisms underlying cancer development and progression. By replicating various aspects of the disease in a controlled environment, these models enable researchers to investigate the efficacy of potential treatments, explore disease mechanisms, and identify novel therapeutic targets. This study analyzes the fractional profiles of three different cancer models using various therapies such as chemotherapy and immunotherapy, and depression effects at both primary and secondary levels of the fatal disease in order to examine their effects from a new perspective. All three models consist of fractional differential systems containing effector cells, tumor cells, and chemotherapy concentration in blood with fractional derivatives in Caputo sense. For solution and analysis purposes, a framework has been developed that includes multiple homotopies related to the perturbation process and incorporates the use of the Laplace transform. The solution profiles for chemo-concentration, effector, and tumor cells are provided and inspected to view the impact of immune cells on tumor cells and vice versa, along with creating a profile for the decrement or increment of chemo-concentration during the entire therapy. A comprehensive graphical examination is done by varying the different parameters involved such as depression, chemotherapy degradation rate, logistic growth rate, etc. The fractional parameter involved is inspected along the constraints and conditions and portrayed with the help of visual analysis through 2D and 3D plots, and gradient contour charts. The thorough analysis confirms the consistency and reliability of the proposed approach, suggesting that it could be applied to other complex fractional cancer treatment models in the future to enhance understanding of the ongoing challenges in cancer treatment.