This study focuses on modeling and analyzing the growth and diffusion dynamics of two cancer cell populations, one characterized by rapid growth and the other by fast diffusion. A (2+1)-dimensional heterogeneous system is developed to represent cancer-tumor growth and diffusion under varying conditions. The system is formulated within a fuzzy-fractional framework using triangular and Gaussian fuzzy numbers to capture irregular growth patterns, diffusion behaviors, and memory effects. To solve and analyze the system, the He-Laplace-Carson algorithm is modified for the fuzzy-fractional setting. The accuracy of the results is validated by residual error analysis, which demonstrates minimal errors. Solution profiles are visualized through 2D, 3D, and contour plots. The findings reveal that the initially fast-growing population mutates into a fast-diffusing one, which subsequently transitions into a fast-growing state over time. This study provides a robust framework for researchers and medical practitioners to analyze and predict similar phenomena while showcasing the efficiency and reliability of the proposed hybrid methodology.