A functional polymorphism in the epidermal growth factor gene predicts hepatocellular carcinoma risk in Japanese hepatitis C patients

Background: A single nucleotide polymorphism (SNP) in the epidermal growth factor (EGF) gene (rs4444903) has been associated with increased risk of cancer, including hepatocellular carcinoma (HCC). The aim of this study was to examine the relationship between the EGF SNP genotype and the development and prognosis of HCC, in a Japanese population. Methods: Restriction fragment-length polymorphism was used to determine the presence of the EGF SNP genotype in 498 patients, including 208 patients with HCC. The level of EGF messenger ribonucleic acid (mRNA) expression in cancerous tissues was measured by quantitative reverse transcription polymerase chain reaction. The correlation between the EGF SNP genotype and prognosis was statistically analyzed in the patients with HCC. Results: The proportion of the A/A, A/G, and G/G genotypes were 5.3%, 42.8%, and 51.9%, respectively, in the patients with HCC, whereas in those without HCC, they were 8.6%, 35.9%, and 55.5%, respectively, revealing that the odds ratio (OR) of developing HCC was higher in patients with a G allele (OR =1.94, P=0.080 for A/G patients and OR =1.52, P=0.261 for G/G patients, as compared with A/A patients). In particular, when the analysis was limited to the 363 patients with hepatitis C, the OR for developing HCC was 3.54 (P=0.014) for A/G patients and was 2.85 (P=0.042) for G/G patients, as compared with A/A patients. Tumoral EGF mRNA expression in G/G patients was significantly higher than that in A/A patients (P=0.033). No statistically significant differences were observed between the EGF SNP genotype and diseasefree or overall survival. Conclusion: The EGF SNP genotype might be associated with a risk for the development of HCC in Japanese patients but not with prognosis. Of note, the association is significantly stronger in patients with hepatitis C, which is the main risk factor for HCC in Japan

Chromobox 2 Expression Predicts Prognosis after Curative Resection of Oesophageal Squamous Cell Carcinoma

Background/Aim: To investigate the function of chromobox 2 (CBX2) in oesophageal squamous cell carcinoma (OSCC). Materials and Methods: We used real-time quantitative reverse transcription PCR (qRT-PCR) and immunohisto - chemistry to determine CBX2 expression levels in 13 human OSCC cell lines and clinical specimens of two independent cohorts of patients with OSCC. Results: PCR array analysis revealed that CBX2 was co-ordinately expressed with WNT5B in OSCC cell lines. RT-qPCR analysis of clinical samples revealed a high tumour-specific CBX2 expression compared with normal oesophageal tissues. High CBX2 expression was significantly associated with shorter disease-specific survival, hematogenous recurrence, and overall recurrence. Analysis of tissue microarrays of one cohort revealed that patients with higher CBX2 levels tended to have a shorter disease-specific survival. Conclusion: CBX2 overexpression in OSCC tissues may serve as a novel biomarker for predicting survival and hematogenous recurrence

Genomic-Wide Analysis with Microarrays in Human Oncology

DNA microarray technologies have advanced rapidly and had a profound impact on examining gene expression on a genomic scale in research. This review discusses the history and development of microarray and DNA chip devices, and specific microarrays are described along with their methods and applications. In particular, microarrays have detected many novel cancer-related genes by comparing cancer tissues and non-cancerous tissues in oncological research. Recently, new methods have been in development, such as the double-combination array and triple-combination array, which allow more effective analysis of gene expression and epigenetic changes. Analysis of gene expression alterations in precancerous regions compared with normal regions and array analysis in drug-resistance cancer tissues are also successfully performed. Compared with next-generation sequencing, a similar method of genome analysis, several important differences distinguish these techniques and their applications. Development of novel microarray technologies is expected to contribute to further cancer research