ASB3 knockdown promotes mitochondrial apoptosis via activating the interdependent cleavage of Beclin1 and caspase-8 in hepatocellular carcinoma

Apoptosis and autophagy are distinct cellular processes that can be highly interconnected. The cross talk between the two processes is indispensable in determining the overall cell fate. Although the apoptosis-promoting effect of caspases has been demonstrated, the roles of autophagy-related proteins and even autophagy itself in regulating apoptosis remain poorly understood. In our present study, we found that downregulation of ubiquitin E3 ligase ASB3 led to enhanced mitochondrial apoptosis as well as autophagy, which synergistically promoted cell death in hepatocellular carcinoma(HCC). We observed the activation of caspase-8 and decrease of autophagy protein Beclin1 in apoptotic cells that were depleted of ASB3. Beclin1 was mainly cleaved by activated caspase-8 and active Beclin1 initiated mitochondrial apoptosis via locating its C-terminal fragment to mitochondria. In addition, knocking down of Beclin1 markedly blocked the apoptosis, indicating its essential role in the process.Notably, our study indicated that enhanced autophagy level might be involved in the activation of caspase-8 and promote the apoptosis. Taken together, our results demonstrated that ASB3 can regulate mitochondrial pathway of apoptosis by controlling caspase-8 mediated cleavage of Beclin1 in HCC. Therefore, ASB3 may potentially serve as a novel target for HCC therapy,especially when combined with autophagy agonist.

Bivariate association analysis for quantitative traits using generalized estimation equation

Quantitative traits often underlie risk for complex diseases. Many studies collect multiple correlated quantitative phenotypes and perform univariate analyses on each of them respectively. However, this strategy may not be powerful and has limitations to detect plei- otropic genes that may underlie correlated quantitative traits. In addition, testing multiple traits individually will exacerbate perplexing problem of multiple testing. In this study, generalized estimating equation 2 （GEE2） is applied to association mapping of two correlated quantitative traits. We suppose that a quantitative trait locus is located in a chromosome region that exerts pleiotropic effects on multiple quantitative traits. In that region, multiple SNPs are genotyped. Genotypes of these SNPs and the two quantitative traits affected by a causal SNP were simulated under various parameter values： residual correlation coefficient between two traits, causal SNP heritability, minor allele frequency of the causal SNP, extent of linkage disequilibrium with the causal SNP, and the test sample size. By power ana- lytical analyses, it is showed that the bivariate method is generally more powerful than the univariate method. This method is robust and yields false-positive rates close to the pre-set nominal significance level. Our real data analyses attested to the usefulness of the method.