Purpose: In dose painting, it is uncertain which of a tumor's biological properties should be targeted, and if plans for different tumor histologies are equally sensitive to the choice of biological target. This study characterizes the relationships between three potential biological targets ‐ glucose metabolism, proliferation, and hypoxia — in two different tumor histologies using PET/CT imaging. Methods: Twenty canine patients with sinonasal tumors (7 sarcomas and 13 carcinomas) were imaged using FDG, FLT, and Cu‐ATSM PET/CT on three consecutive days. Patients were immobilized and precisely positioned, and resulting images were rigidly registered. Within each tumor volume, voxel SUV distributions from different tracers were compared and inter‐tracer correlations were evaluated using voxel‐based Spearman correlation coefficients. Correlation coefficients were then Fisher‐transformed, and a two‐sided t‐test was applied to determine if sarcoma and carcinoma populations differed significantly in inter‐tracer correlations. SUV measures such as SUVmax, SUVpeak, and SUVmean were also compared between sarcomas and carcinomas using Mann‐Whitney U‐tests. Results: Significant differences in inter‐tracer correlations were observed between sarcoma and carcinoma tumors. Population‐averaged Spearman correlation coefficients were significantly higher for carcinoma tumors than sarcoma tumors in comparisons of FLT:Cu‐ATSM (0.83 vs. 0.38; p<0.0001), FDG:FLT (0.80 vs. 0.61; p=0.02), and FDG:Cu‐ATSM (0.82 vs. 0.69; p=0.04). Tracer distributions generally overlapped in carcinomas; in sarcomas, however, different tracers clustered in different tumor regions. Carcinomas also had significantly higher average FDG SUVmax (11.1 vs. 5.0; p=0.01) and higher Cu‐ATSM SUVmean (2.6 vs. 1.2; p=0.02) than sarcoma tumors. Conclusion: Carcinoma tumors, with high spatial correlations between tumor metabolism, proliferation, and hypoxia, are robust targets for therapies that target a single biological property. Sarcomas may not be well‐suited for such therapies. Histology‐specific robustness in biological target definition has large implications for dose painting strategies, as well as for other biologically targeted therapies.