Gene expression profiling predicts the development of oral cancer

Gilberto De Castro

Oral squamous cell carcinoma remains as the most prevalent head and neck cancer worldwide, with higher incidence rates in developing countries, as a consequence of a more elevated exposure to tobacco and alcohol carcinogens.

Primary prevention, based on lifestyle alterations as quitting smoking and alcohol drinking, is still essential, but secondary prevention, focused on early diagnosis and prompt treatment of suspected lesions has been shown to be effective in reducing mortality in high risk populations. Leukoplakia is the most commonly diagnosed oral preneoplastic lesion and the risk of malignant transformation is around 20% over a period of 30 years.

In the study published by Saintigny et al.1, of the University of Texas M. D. Anderson Cancer Centre, the authors aimed to determine the value of gene expression profiling as a predictor of oral cancer development among individuals with oral pre-malignant lesions.

Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6 years and 35 out of the 86 patients (40%) developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develop multivariate predictive models for oral cancer prediction.

A 29-transcript predictive model was generated and it has shown a marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinicopathologic risk factors. Among the top genes, DNA methyltransferase-3B (DNMT3B) was shown to be related to the development of oral cancer with a HR of 7.7 (95%CI 3.3-18.6, p<0.0001). DNMT3B is a de novo DNA methyltransferase associated with CpG island methylator phenotype and oral cancer development.

Another important finding was the identification of 2,182 transcripts significantly associated with oral cancer risk-associated genes (p<0.01; univariate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomal components as the top gene sets associated with oral cancer risk. Finally, in multiple independent data sets, this profiling could differentiate squamous cell carcinoma from normal mucosa.

The authors concluded that gene expression profiles may improve the prediction of oral cancer risk in these high-risk patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. In other words, if confirmed prospectively in larger cohorts, this gene signature can be helpful in the future to better stratify these patients in terms of routine follow-up (enhanced surveillance) or chemoprevention trials. Another caveat is related to the predictive value of this signature in those squamous cell carcinoma not proceeded by these preneoplastic lesions.

Reference
1 - Saintigny P, Zhang L, Fan YH, et al. Gene expression profiling predicts the development of oral cancer. Cancer Prev Res (Phila) 2011;218-29.

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