Association of Single Nucleotide Polymorphisms of ABCB1,OPRM1 and COMT with Pain Perception in Cancer Patients

Pain perception is influenced by multiple factors. The single nucleotide polymorphisms（SNPs） of some genes were found associated with pain perception. This study aimed to examine the association of the genotypes of ABCB1 C3435 T,OPRM1 A118 G and COMT V108/158M（valine 108/158 methionine） with pain perception in cancer patients. We genotyped 146 cancer pain patients and 139 cancer patients without pain for ABCB1 C3435T（rs1045642）,OPRM1 A118G（rs1799971） and COMT V108/158M（rs4680） by the fluorescent dye-terminator cycle sequencing method,and compared the genotype distribution between groups with different pain intensities by chi-square test and pain scores between groups with different genotypes by non-parametric test. The results showed that in these cancer patients,the frequency of variant T allele of ABCB1 C3435 T was 40.5%; that of G allele of OPRM1 A118 G was 38.5% and that of A allele of COMT V108/158 M was 23.3%. No significant difference in the genotype distribution of ABCB1 C3435T（rs1045642） and OPRM1 A118G（rs1799971） was observed between cancer pain group and control group（P=0.364 and 0.578）; however,significant difference occurred in the genotype distribution of COMT V108/158M（rs4680） between the two groups（P=0.001）. And the difference could not be explained by any other confounding factors. Moreover,we found that the genotypes of COMT V108/158 M and ABCB1 C3435 T were associated with the intensities of pain in cancer patients. In conclusion,our results indicate that the SNPs of COMT V108/158 M and ABCB1 C3435 T significantly influence the pain perception in Chinese cancer patients.

Analysis of Allele Specific Expression——A Survey

Allele specific expression is essential for cellular programming and development and the diversity of cellular phenotypes. Traditional analysis methods utilize RNA and depend on single nucleotide polymorphisms,thus to suffer from limited amount of materials for analysis. The rapid development of next-generation sequencing technologies provides more comprehensive and powerful approaches to analyze the genomic, epigenetic, and transcriptomic data, and further to detect and measure allele specific expressions. It will potentially enhance the understanding of the allele specific expressions, their complexities, and the effect on biological processes. In this paper, we extensively review the state-of-art enabling technologies and tools to analyze, detect, and measure allele specific expressions, compare their features, and point out the future trend of the methods.