Potential use of quantitative tissue phenotype to predict malignant risk for oral premalignant lesions.

Abstract

The importance of early diagnosis in improving mortality and morbidity rates of oral squamous cell carcinoma (SCC) has long been recognized. However, a major challenge for early diagnosis is our limited ability to differentiate oral premalignant lesions (OPL) at high risk of progressing into invasive SCC from those at low risk. We investigated the potential of quantitative tissue phenotype (QTP), measured by high-resolution image analysis, to identify severe dysplasia/carcinoma in situ (CIS; known to have an increased risk of progression) and to predict progression to cancer within hyperplasia or mild/moderate dysplasia. We generated a nuclear phenotype score (NPS), a combination of five nuclear morphometric features that best discriminate 4,027 "normal" nuclei (selected from 29 normal oral biopsies) from 4,298 "abnormal" nuclei (selected from 30 SCC biopsies). This NPS was then determined for a set of 69 OPLs. Severe dysplasia/CIS showed a significant increase in NPS compared with hyperplasia or mild/moderate dysplasia. However, within the latter group, elevated NPS was strongly associated with the presence of high-risk loss of heterozygosity (LOH) patterns. There was a statistical difference between NPS of hyperplasia or mild/moderate dysplasia that progressed to cancer and those that did not. Individuals with a high NPS had a 10-fold increase in relative risk of progression. In the multivariate Cox model, LOH and NPS together were the strongest predictors for cancer development. These data suggest that QTP could be used to identify lesions that require molecular evaluation and should be integrated with such approaches to facilitate the identification of hyperplasia or mild/moderate dysplasia OPLs at high risk of progression.