To analyze the presence of malignancy associated changes (MACs) in normal buccal mucosa cells of lung and breast cancer patients and their relationship to tumor subtype, stage and size. Buccal mucosa smears of 107 lung cancer and 100 breast cancer patients and corresponding healthy subjects were collected, stained by the DNA-specific Feulgen-thionin method and scanned using an automated high-resolution cytometer. Nuclear texture features of a minimum of 500 nuclei per slide were calculated, and statistical classifiers using Gaussian models of class-probability distribution were designed, trained and tested in 3 parts: (1) ability to separate cancer patient samples from controls, (2) cross-validation of classifiers for different cancer types, and (3) correlation of MAC expression with tumor subtype, stage and size. Lung and breast cancer induce MACs in normal buccal mucosa cells. The classifiers based on the selected nuclear features correctly recognized >80% of lung and breast cancer cases. The results indicate that MAC detection is not dependent on the tumor subtype, stage or size. The presence of MACs in buccal mucosa cells offers the potential for developing a new noninvasive cancer screening test.