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Background Cardiac hypertrophy is a common response to circulatory or neurohumoral stressors as a mechanism to augment contractility. When the heart is under sustained stress, the hypertrophic response can evolve into decompensated heart failure, although the mechanism(s) underlying this transition remain largely unknown. Because phosphorylation of cardiac myosin light chain 2 (MLC2v), bound to myosin at the head-rod junction, facilitates actin-myosin interactions and enhances contractility, we hypothesized that phosphorylation of MLC2v plays a role in adaptation of the heart to stress. We previously identified an enzyme that predominantly phosphorylates MLC2v in cardiomyocytes, cardiac-MLCK (cMLCK); yet the role(s) played by cMLCK in regulating cardiac function in health and disease remain to be determined. Methods and Results We found that pressure-overload induced by transaortic constriction in wildtype mice reduced phosphorylated-MLC2v levels by ~40% and cMLCK levels by ~85%. To examine how a reduction in cMLCK and the corresponding reduction in pMLC2v affect function, we generated Mylk3 gene-targeted mice as well as transgenic mice overexpressing cMLCK specifically in cardiomyocytes. Pressure-overload led to severe heart failure in cMLCK knockout mice, but not in mice with cMLCK overexpression in which cMLCK protein synthesis exceeded degradation. The reduction in cMLCK protein during pressure-overload was attenuated by inhibition of ubiquitin-proteasome protein degradation systems. Conclusions Our results suggest the novel idea that accelerated cMLCK-protein turnover by the ubiquitin-proteasome system underlie the transition from compensated hypertrophy to decompensated heart failure due to reduced phosphorylation of MLC2v.

Background Hepatocellular carcinoma (HCC) remains a major challenge for public health worldwide. Considering the great heterogeneity of HCC, more accurate prognostic models are urgently needed. To identify a robust prognostic gene signature, we conduct this study. Materials and methods Level 3 mRNA expression profiles and clinicopathological data were obtained in The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC). GSE14520 dataset from the gene expression omnibus (GEO) database was downloaded to further validate the results in TCGA. Differentially expressed mRNAs between HCC and normal tissue were investigated. Univariate Cox regression analysis and lasso Cox regression model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic (ROC), Kaplan–Meier curve, multivariate Cox regression analysis, nomogram, and decision curve analysis (DCA) were used to assess the prognostic capacity of the six-gene signature. The prognostic value of the gene signature was further validated in independent GSE14520 cohort. Gene Set Enrichment Analyses (GSEA) was performed to further understand the underlying molecular mechanisms. The performance of the prognostic signature in differentiating between normal liver tissues and HCC were also investigated. Results A novel six-gene signature (including CSE1L, CSTB, MTHFR, DAGLA, MMP10, and GYS2) was established for HCC prognosis prediction. The ROC curve showed good performance in survival prediction in both the TCGA HCC cohort and the GSE14520 validation cohort. The six-gene signature could stratify patients into a high- and low-risk group which had significantly different survival. Cox regression analysis showed that the six-gene signature could independently predict OS. Nomogram including the six-gene signature was established and shown some clinical net benefit. Furthermore, GSEA revealed several significantly enriched oncological signatures and various metabolic process, which might help explain the underlying molecular mechanisms. Besides, the prognostic signature showed a strong ability for differentiating HCC from normal tissues. Conclusions Our study established a novel six-gene signature and nomogram to predict overall survival of HCC, which may help in clinical decision making for individual treatment. Electronic supplementary material The online version of this article (10.1186/s12935-019-0858-2) contains supplementary material, which is available to authorized users.