The use of low-level visual features to assign high level labels in datasets of histopathology images is a possible solution to the problems derived from manual labeling by experts. However, in many cases, the visual cues are not enough. In this article we propose the use of features derived exclusively from the spatial distribution of the cell nuclei. These features are calculated using the weight of k-nn graphs constructed from the distances between cells. Results show that there are k values with enhanced discriminatory power, especially when comparing cancerous and non-cancerous tissue.