Abstract Ecological modeling provides a simple holistic view of the cancer microenvironment to study the survival of different cancer clones (phenotypes) within a microenvironment (ecosystem). Within a tumor ecosystem, different phenotypic cells have different biological properties and tasks. This heterogeneity provides tumors with an overall phenotype that is needed for robust survival in the face of environment stresses such as conventional chemotherapy. Here we propose a trade-off model for understanding the tumor microenvironment, using Pareto efficiency. The Pareto efficiency in economics describes an optimum trade-off to satisfy different task requirements. We use this concept from economics to see if the trade-offs correspond to the observed behavior in various cancer phenotypes such as epithelial and mesenchymal clones. This is based on the recent studies on using Pareto efficiency to better understand the phenotypic evolutionary pathway in the morphospace of an ecosystem. Extending this model to tumor ecosystems allows us to define cellular hybrid phenotypes as a result of trade-off on performing different tasks. Cells regulate the load of each task based on their microenvironment stimulus. We assume tumor cells find the best trade-off of phenotypes by weighted average of the canonical (specialized) phenotypes, determine which genotype needs to be more expressed, and create an overall hybrid phenotype. Studies recognize this hybrid feature in the cancer ecology. For example based on the microenvironment condition, epithelial, mesenchymal and stem cell phenotypes co-exist as a hybrid phenotype. Within a heterogeneous tumor environment, experimental observations provide quantitative values to differentiate a cell subpopulation from others. Each cancer cell phenotype is defined by certain quantitative features (traits) i that have value of vi, so the whole phenotype is defined by its feature vector v. Selection pressure forces the cancer cell to its optimal fitness function U, which can model by an evolutionary dynamics. Although the fitness function is usually unknown, it depends on the performance of each vital biological function, i.e. U = U(p1(v),...,pk(v)). We assume there is a canonical phenotype k that achieves task k with highest performance and all other hybrid phenotypes evolve as a mixture of different canonical phenotypes. In a tumor with three canonical phenotypes such as epithelial, mesenchymal and stem cells, each of the above canonical phenotypes is a point on a triangle of the tumor morphospace. Here, we examine if the presence of hybrid phenotypic behavior such as mesenchymal-epithelial-stem hybrid cells is the result of the tumor trade-off calculations and if all probable phenotypes can rest in a defined geometry like a polygon or a polyhedron in the morphospace of tumor ecosystems. It can help us to focus on the most probable hybrid phenotype in an evolving tumor during conventional therapies. Citation Format: Ardeshir Kianercy, Kenneth J. Pienta. A Pareto efficiency model to explain hybrid cellular behavior in tumor ecosystem. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 371. doi:10.1158/1538-7445.AM2014-371