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The identification of significant chromosomal regions correlated with oral tongue cancer progression

Abstract

Purpose

Oral squamous cell carcinoma (OSCC) is associated with substantial mortality and morbidity, and oral tongue squamous cell carcinoma (SCC) is representative in OSCC. Early detection of oral premalignant lesions (OPLs) that will develop into invasive tumors is necessary to improve the poor prognosis of this cancer.

Methods

To identify potential biomarkers that could be used for early detection, we compared the gene expression of incident primary oral tongue SCC, severe dysplasia, mild and moderate dysplasia. For this, we used three expression datasets obtained from a public database and selected chromosomal locations related with the progress of oral tongue cancer from a dataset. We then evaluated the gene set, which is included in the selected chromosomal locations, using out of bag (OOB) error and plots in two validation datasets.

Results

Sixty-two chromosomal locations were detected, and most genomic aberrations were shown in chromosome 3. We identified 62 genes included in those locations, and three precancerous and SCC groups were well classified with low OOB error rates. These were also discriminative in the two validation datasets.

Conclusions

The selected probes with genomic alteration in low-grade dysplasia can be used as an effective predictor for disease progression.

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Acknowledgments

This work was supported by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2011-0031396).

Conflict of interest

None.

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Correspondence to In-Ho Cha.

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Kim, KY., Cha, IH. The identification of significant chromosomal regions correlated with oral tongue cancer progression. J Cancer Res Clin Oncol 138, 1667–1677 (2012). https://doi.org/10.1007/s00432-012-1241-z

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Keywords

  • Oral tongue squamous cell carcinoma
  • Cancer progression
  • Biomarker
  • Array comparative genomic hybridization
  • cDNA micoroarray data
  • Prognostic factor