Networks of bio-nanomachines that communicate through molecular communication are expected to perform complex functionalities within biological systems. The natural history of malignant tumors can be defined by the evolution of growing bio-nanomachine networks within an interplay between proliferation or self-renewal (Grow) and invasion (Go) potential of mutually exclusive phenotypes. Herein we present a model of two populations of bio-nanomachines representing distinct phenotypes propagating throughout the progression of malignant gliomas within spatiotemporally evolving bionanomachine networks, driven by either attractive and linkforming or repulsive and cluster-forming forces. This model is further applied in computer simulations to examine the growth of bio-nanomachine networks in terms of size and network connectivity. Understanding the mechanisms by which malignant cells form bio-nanomachine networks and controlling network connectivity can contribute to deciphering mechanisms of tumor evolution and progression and provide new nanonetwork-based therapeutic approaches.