Gastric cancer (GC) is one of the most common malignant tumors worldwide. No fundamental improvements in the five-year survival rates of patients with GC have been reported due to a low early diagnosis rate. Therefore, the identification of novel biomarkers is urgently required for an early diagnosis of GC. A total of 86 patients were selected for the present study, including 44 patients with early stage GC (T1-T2 according to TNM staging criteria) and 42 normal gastric mucosa samples from non-cancer patients as controls. A total of 18 samples were used for the microRNA (miRNA) microarray experiments, including nine early GC and nine normal gastric mucosa samples. Bioinformatics algorithms, significant analysis of microarray (SAM), top scoring pair (TSP) and statistical receiver operating characteristic curves were used to identify the best signatures. Finally, quantitative PCR was used to validate the candidate biomarkers for early gastric cancer in the test samples (35 cancer and 33 normal samples). Using the SAM algorithm, 14 differential miRNAs were selected as candidate biomarkers. Using the TSP algorithm, hsa-miR-196a and hsa-miR-148a were obtained as a signature to differentiate between the early GC and normal samples. A coincidental result was observed in the test samples. hsa-miR-196a was upregulated and hsa-miR-148a was downregulated in the early GC samples. hsa-miR-196a and hsa-miR-148a have the potential to serve as candidate biomarkers for early GC.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3919894PMC
http://dx.doi.org/10.3892/ol.2014.1797DOI Listing

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