Murine MHC-Deficient Nonobese Diabetic Mice Carrying Human HLA-DQ8 Develop Severe Myocarditis and Myositis in Response to Anti-PD-1 Immune Checkpoint Inhibitor Cancer Therapy.

Myocarditis has emerged as an immune-related adverse event of immune checkpoint inhibitor (ICI) cancer therapy associated with significant mortality. To ensure patients continue to safely benefit from life-saving cancer therapy, an understanding of fundamental immunological phenomena underlying ICI myocarditis is essential. We recently developed the NOD-cMHCI/II-/-.DQ8 mouse model that spontaneously develops myocarditis with lower mortality than observed in previous HLA-DQ8 NOD mouse strains. Our strain was rendered murine MHC class I and II deficient using CRISPR/Cas9 technology, making it a genetically clean platform for dissecting CD4+ T cell-mediated myocarditis in the absence of classically selected CD8+ T cells. These mice are highly susceptible to myocarditis and acute heart failure following anti-PD-1 ICI-induced treatment. Additionally, anti-PD-1 administration accelerates skeletal muscle myositis. Using histology, flow cytometry, adoptive transfers, and RNA sequencing analyses, we performed a thorough characterization of cardiac and skeletal muscle T cells, identifying shared and unique characteristics of both populations. Taken together, this report details a mouse model with features of a rare, but highly lethal clinical presentation of overlapping myocarditis and myositis following ICI therapy. This study sheds light on underlying immunological mechanisms in ICI myocarditis and provides the basis for further detailed analyses of diagnostic and therapeutic strategies.

Inhibition of RhoGEF/RhoA alleviates regorafenib resistance and cancer stemness via Hippo signaling pathway in hepatocellular carcinoma.

Patients with hepatocellular carcinoma (HCC) are vulnerable to drug resistance. Although drug resistance has been taken much attention to HCC therapy, little is known of regorafenib and regorafenib resistance (RR). This study aimed to determine the drug resistance pattern and the role of RhoA in RR. Two regorafenib-resistant cell lines were constructed based on Huh7 and Hep3B cell lines. In vitro and in vivo assays were conducted to study RhoA expression, the activity of Hippo signaling pathway and cancer stem cell (CSC) traits. The data showed that RhoA was highly expressed, Hippo signaling was hypoactivated and CSC traits were more prominent in RR cells. Inhibiting RhoA could reverse RR, and the alliance of RhoA inhibition and regorafenib synergistically attenuated CSC phenotype. Furthermore, inhibiting LARG/RhoA increased Kibra/NF2 complex formation, prevented YAP from shuttling into the nucleus and repressed CD44 mRNA expression. Clinically, the high expression of RhoA correlated with poor prognosis. LARG, RhoA, YAP1 and CD44 show positive correlation with each other. Thus, inhibition of RhoGEF/RhoA has the potential to reverse RR and repress CSC phenotype in HCC.

Global and tissue-specific aging effects on murine proteomes.

Maintenance of protein homeostasis degrades with age, contributing to aging-related decline and disease. Previous studies have primarily surveyed transcriptional aging changes. To define the effects of age directly at the protein level, we perform discovery-based proteomics in 10 tissues from 20 C57BL/6J mice, representing both sexes at adult and late midlife ages (8 and 18 months). Consistent with previous studies, age-related changes in protein abundance often have no corresponding transcriptional change. Aging results in increases in immune proteins across all tissues, consistent with a global pattern of immune infiltration with age. Our protein-centric data reveal tissue-specific aging changes with functional consequences, including altered endoplasmic reticulum and protein trafficking in the spleen. We further observe changes in the stoichiometry of protein complexes with important roles in protein homeostasis, including the CCT/TriC complex and large ribosomal subunit. These data provide a foundation for understanding how proteins contribute to systemic aging across tissues.

The role of daurisoline treatment in hepatocellular carcinoma: Inhibiting vasculogenic mimicry formation and enhancing sensitivity to sorafenib.

BACKGROUND: Vasculogenic mimicry (VM) is a newly described tumor vascular phenomenon that is independent of traditional angiogenesis and provides an adequate blood supply for tumor growth. VM has been consistently observed in different cancer types. Hence, inhibition of VM may be considered a new anticancer therapeutic strategy. PURPOSE: This study aimed to elucidate the potential anticancer effect of daurisoline (DS) on hepatocellular carcinoma (HCC) and the potential molecular mechanism by which DS inhibits VM. We also verified whether combination treatment with sorafenib and DS constitutes a novel therapeutic approach to prevent HCC progression. METHODS: The effects of DS on proliferation were evaluated by Cell Counting Kit-8 (CCK-8), colony formation, and 5-ethynyl-2'-deoxyuridine (EdU) incorporation assays. 4',6-Diamidino-2-phenylindole (DAPI) staining and flow cytometric analysis were employed to investigate its effects on apoptosis. Western blot analysis, Matrigel tube formation assays, pulldown assays and immunofluorescence staining were applied to validate the potential mechanism by which DS inhibits VM. Mouse xenograft models were used to evaluate anticancer activities. RESULTS: DS inhibited HCC cell proliferation, induced HCC cell apoptosis and repressed VM formation by inactivating RhoA/ROCK2-mediated AKT and ERK-p38 MAPK signaling. Additionally, DS dramatically sensitized HCC cell lines to sorafenib, a curative anticancer drug for patients with advanced HCC. CONCLUSIONS: Our study provides insights into the molecular mechanisms underlying DS-induced inhibition of VM, which may facilitate the development of a novel clinical anti-HCC drug. Moreover, our findings suggest that the combination of DS and sorafenib constitutes a potential therapeutic strategy for HCC.

Targeting cancer stem cells for reversing therapy resistance: mechanism, signaling, and prospective agents.

Cancer stem cells (CSCs) show a self-renewal capacity and differentiation potential that contribute to tumor progression and therapy resistance. However, the underlying processes are still unclear. Elucidation of the key hallmarks and resistance mechanisms of CSCs may help improve patient outcomes and reduce relapse by altering therapeutic regimens. Here, we reviewed the identification of CSCs, the intrinsic and extrinsic mechanisms of therapy resistance in CSCs, the signaling pathways of CSCs that mediate treatment failure, and potential CSC-targeting agents in various tumors from the clinical perspective. Targeting the mechanisms and pathways described here might contribute to further drug discovery and therapy.

Non-Coding RNA m6A Modification in Cancer: Mechanisms and Therapeutic Targets.

Recently, N6-methyl-adenosine (m6A) ribonucleic acid (RNA) modification, a critical and common internal RNA modification in higher eukaryotes, has generated considerable research interests. Extensive studies have revealed that non-coding RNA m6A modifications (e.g. microRNAs, long non-coding RNAs, and circular RNAs) are associated with tumorigenesis, metastasis, and other tumour characteristics; in addition, they are crucial molecular regulators of cancer progression. In this review, we discuss the relationship between non-coding RNA m6A modification and cancer progression from the perspective of various cancers. In particular, we focus on important mechanisms in tumour progression such as proliferation, apoptosis, invasion and metastasis, tumour angiogenesis. In addition, we introduce clinical applications to illustrate more vividly that non-coding RNA m6A modification has broad research prospects. With this review, we aim to summarize the latest insights and ideas into non-coding RNA m6A modification in cancer progression and targeted therapy, facilitating further research.

Identifying Mechanisms of Normal Cognitive Aging Using a Novel Mouse Genetic Reference Panel.

Developing strategies to maintain cognitive health is critical to quality of life during aging. The basis of healthy cognitive aging is poorly understood; thus, it is difficult to predict who will have normal cognition later in life. Individuals may have higher baseline functioning (cognitive reserve) and others may maintain or even improve with age (cognitive resilience). Understanding the mechanisms underlying cognitive reserve and resilience may hold the key to new therapeutic strategies for maintaining cognitive health. However, reserve and resilience have been inconsistently defined in human studies. Additionally, our understanding of the molecular and cellular bases of these phenomena is poor, compounded by a lack of longitudinal molecular and cognitive data that fully capture the dynamic trajectories of cognitive aging. Here, we used a genetically diverse mouse population (B6-BXDs) to characterize individual differences in cognitive abilities in adulthood and investigate evidence of cognitive reserve and/or resilience in middle-aged mice. We tested cognitive function at two ages (6 months and 14 months) using y-maze and contextual fear conditioning. We observed heritable variation in performance on these traits (h 2 RIx̄ = 0.51-0.74), suggesting moderate to strong genetic control depending on the cognitive domain. Due to the polygenetic nature of cognitive function, we did not find QTLs significantly associated with y-maze, contextual fear acquisition (CFA) or memory, or decline in cognitive function at the genome-wide level. To more precisely interrogate the molecular regulation of variation in these traits, we employed RNA-seq and identified gene networks related to transcription/translation, cellular metabolism, and neuronal function that were associated with working memory, contextual fear memory, and cognitive decline. Using this method, we nominate the Trio gene as a modulator of working memory ability. Finally, we propose a conceptual framework for identifying strains exhibiting cognitive reserve and/or resilience to assess whether these traits can be observed in middle-aged B6-BXDs. Though we found that earlier cognitive reserve evident early in life protects against cognitive impairment later in life, cognitive performance and age-related decline fell along a continuum, with no clear genotypes emerging as exemplars of exceptional reserve or resilience - leading to recommendations for future use of aging mouse populations to understand the nature of cognitive reserve and resilience.

Hypoxic induction of vasculogenic mimicry in hepatocellular carcinoma: role of HIF-1 α, RhoA/ROCK and Rac1/PAK signaling.

BACKGROUND: Vasculogenic mimicry (VM), defined as a capability of aggressive tumor Cells to mimic embryonic vasculogenic networks, caused poor prognosis in hepatocellular carcinoma (HCC). Rho kinases (ROCK), p21-activated kinase (PAK), hypoxia or epithelial-mesenchymal transition (EMT) contributed to the VM potential. However, the details underlying these biological behaviors have not been completely elucidated. METHODS: Kaplan-Meier analysis was conducted to predict relationship with hypoxia Inducible factor (HIF-1α), EMT related markers: Vimentin and patient prognosis. CD34/periodic acid-Schiff (PAS) double staining was examined to differentiate VM-positive (VM+) and VM-negative (VM-) samples. Cells were cultured under controlled hypoxic environments (1% O2) or normoxic conditions. The effect of hypoxia on RhoA/ROCK, Rac1/PAK and EMT were evaluated by real time-qPCR and western blot. HIF-1α small interfering RNA (siRNA), overexpressed or short hairpin RNA (shRNA) of ROCK and kinase inhibitors were used to explore the effect of HIF-1α, RhoA/ROCK, Rac1/PAK and Vimentin on VM. RESULTS: HIF-1α or Vimentin was upregulated in VM+ HCC tissues, compared to non-cancerous tissues (P < 0.01), and patients with high expression of HIF-1α or Vimentin had worse prognosis (P < 0.001). We showed hypoxia induced RhoA/ROCK and Rac1/PAK signaling transduction, and EMT could be repressed by HIF-1α siRNA. Notably, RhoA/ROCK or Rac1/PAK stabilized HIF-1α in hypoxia, whereas HIF-1α did not significantly altered RhoA/ROCK or Rac1/PAK signaling in hypoxia. Moreover, we found distinct roles of ROCK1, ROCK2 and PAK in regulating Vimentin phosphorylation. CONCLUSIONS: RhoA/ROCK and Rac/PAK signaling played crucial roles in hypoxia-induced VM via Ser72 and Ser56 Vimentin phosphorylation in HCC.

MicroRNA-425-5p promotes breast cancer cell growth by inducing PI3K/AKT signaling.

MicroRNA-425-5p (miR-425-5p) has been reported to be involved in the tumorigenesis of several tumors, but its function in breast cancer is still unknown. In this study, miR-425-5p was found significantly upregulated in breast cancer cells, and predicted a poor prognosis for breast cancer patients. Overexpression of miR-425-5p could significantly promote breast cancer cell growth. Further studies showed that overexpression of miR-425-5p upregulated the protein levels of Cyclin D1, Cyclin D3, CDK4, and CDK6. However, inhibiting miR-425-5p downregulated their expression and induced cell cycle arrest at G0/G1 phase. In mechanism, overexpression of miR-425-5p increased the phosphorylation of PI3K p85 and AKT, but inhibiting miR-425-5p displayed opposite effects. Moreover, miR-425-5p bound to the 3'UTR of PTEN mRNA, and downregulated the expression levels of PTEN in both mRNA and protein levels in breast cancer cells. Collectively, the results above demonstrated that miR-425-5p was involved in the tumorigenesis of breast cancer by inducing PI3K/AKT signaling and indicated that miR-425-5p could be as a potential target for breast cancer therapy in the future.

A Statistical Test for Differential Network Analysis Based on Inference of Gaussian Graphical Model.

Differential network analysis investigates how the network of connected genes changes from one condition to another and has become a prevalent tool to provide a deeper and more comprehensive understanding of the molecular etiology of complex diseases. Based on the asymptotically normal estimation of large Gaussian graphical model (GGM) in the high-dimensional setting, we developed a computationally efficient test for differential network analysis through testing the equality of two precision matrices, which summarize the conditional dependence network structures of the genes. Additionally, we applied a multiple testing procedure to infer the differential network structure with false discovery rate (FDR) control. Through extensive simulation studies with different combinations of parameters including sample size, number of vertices, level of heterogeneity and graph structure, we demonstrated that our method performed much better than the current available methods in terms of accuracy and computational time. In real data analysis on lung adenocarcinoma, we revealed a differential network with 3503 nodes and 2550 edges, which consisted of 50 clusters with an FDR threshold at 0.05. Many of the top gene pairs in the differential network have been reported relevant to human cancers. Our method represents a powerful tool of network analysis for high-dimensional biological data.

Overlapping and unique roles played by ROCK1 and 2 in the modulation of coding and long noncoding RNA expression.

BACKGROUND: Our previous study described the crucial role of Rho-associated coiled-coil containing-kinases (ROCK) in hepatocellular carcinoma (HCC). However, the potential significance of long noncoding RNA downstream of ROCK is largely unknown. Here, a comprehensive comparative bioinformatics analysis of a microarray of an MHCC-97H cell line overexpressing ROCK1 or ROCK2 was performed. RESULTS: Numerous lncRNAs and mRNAs were deregulated by Rho-associated coiled-coil containing kinases 1 and 2. These results were consistent with the qRT-PCR results. Compared with MHCC-97H-Con, which was transfected with a null vector, the GO analysis revealed differentially expressed mRNAs (DEmRNAs) in MHCC-97H-ROCK1 (ROCK1 was overexpressed) enriched in apoptotic cell clearance, the cyclooxygenase pathway and bone trabecula morphogenesis; the DEmRNAs in MHCC-97H-ROCK2 (ROCK2 was overexpressed) were enriched in VEGF production, chemokine-associated signaling pathways, acute inflammatory response and vasoconstriction. Compared with MHCC-97H-ROCK2, the DEmRNAs in MHCC-97H-ROCK1 were involved in the JAK-STAT cascade, the Akt signaling pathway and the activity of several different peptidases. The pathway analysis of ROCK1 and ROCK2 revealed an overlap in the VEGF signaling pathway, ECM-receptor interaction, and adhesion and differences in the PPAR signaling pathway and mismatch repair. The predicted targets of the differentially expressed lncRNA (DElncRNAs) were enriched in the p53 signaling pathway, Jak-STAT signaling pathway, etc. Several hub DElncRNAs were identified. CONCLUSIONS: ROCK1 and 2 modulate the expression of numerous mRNAs and lncRNAs and may participate in several signaling pathways in HCC. Several hub molecules were identified in the lncRNA-mRNA networks. Our results provide baseline data for ROCK1 and 2 regulation in HCC that might have implications for further research.

Genetic risk factors identified in populations of European descent do not improve the prediction of osteoporotic fracture and bone mineral density in Chinese populations.

Aiming to investigate whether genetic risk factors (GRFs) for fracture and bone mineral density (BMD) identified from people of European descent can help improve the prediction of osteoporotic fracture (OF) risk and BMD in Chinese populations, we built assessment models for femoral neck (FN)-fracture prediction and BMD value prediction using 700 elderly Chinese Han subjects and 1,620 unrelated Chinese Han subjects, respectively. 17 fracture-associated genes and 82 FN-BMD associated genes identified in people of European descent were used to build a logistic regression model with clinical risk factors (CRFs) for FN-fracture prediction in Chinese. Meanwhile 107 BMD-associated genes from people of European descent were used to build a multiple linear regression model with CRFs for BMD prediction in Chinese. A Lasso algorithm was employed for informative SNP selection to construct the genetic risk score (GRS) with ten-fold cross-validation. The results showed that, adding fracture GRF and FN-BMD GRF to the model with CRFs, the area under the receiver operating characteristic curve (AUC) decrease from 0.653 to 0.587 and 0.588, respectively, for FN fracture prediction. 62.3% and 61.8% of the risk variation were explained by the Model with CRFs and fracture GRF and by the Model with CRFs and FN-BMD GRF, respectively, as compared to 65.5% in the Model with CRFs only. The net reclassification improvement (NRI) index in the reclassification analysis is 0.56% (P = 0.57) and 1.13% (P = 0.29), respectively. There is no significant difference either between the performance of the model with CRFs and that of the model with both CRFs and GRF for BMD prediction. We concluded that, in the current study, GRF of fracture identified in people of European descent does not contributes to improve the fracture prediction in Chinese; and GRF of BMD from people of European descent cannot help improve the accuracy of the fracture prediction in Chinese perhaps partially because GRF of BMD from people of European descent may not contribute to BMD prediction in Chinese. This study highlights the limited utility of the current genetics studies largely focused on people of European descent for disease or risk factor prediction in other ethnic groups, and calls for more and larger scale studies focused on other ethnic groups.

Identification of Pre-symptomatic Gene Signatures That Predict Resilience to Cognitive Decline in the Genetically Diverse AD-BXD Model.

Across the population, individuals exhibit a wide variation of susceptibility or resilience to developing Alzheimer's disease (AD). Identifying specific factors that promote resilience would provide insight into disease mechanisms and nominate potential targets for therapeutic intervention. Here, we use transcriptome profiling to identify gene networks present in the pre-symptomatic AD mouse brain relating to neuroinflammation, brain vasculature, extracellular matrix organization, and synaptic signaling that predict cognitive performance at an advanced age. We highlight putative drivers of these observed relationships, including Itgb2, Fcgr2b, Slc6a14, and Gper1, which represent prime targets through which to promote resilience prior to overt symptom onset. In addition, we identify a genomic region on chromosome 2 containing variants that directly modulate resilience network expression. Overall, work here highlights new potential drivers of resilience to AD and contributes significantly to our understanding of early, potentially causal, disease mechanisms.

RhoC/ROCK2 promotes vasculogenic mimicry formation primarily through ERK/MMPs in hepatocellular carcinoma.

Vasculogenic mimicry (VM) results in the formation of an alternative circulatory system that can improve the blood supply to multiple malignant tumors, including hepatocellular carcinoma (HCC). However, the potential mechanisms of RhoC/ROCK in VM have not yet been investigated in HCC. Here, RhoC expression was upregulated in HCC tissues, especially the VM-positive (VM+) group, compared to noncancerous tissues (P < 0.01), and patients with high expression of RhoC had shorter survival times (P < 0.001). The knockdown of RhoC via short hairpin RNA (shRNA) in SK-Hep-1 cells significantly decreased VM formation and cell motility. In contrast, cell motility and VM formation were remarkably enhanced when RhoC was overexpressed in HepG2 cells. To further assess the potential role of ROCK1 and ROCK2 on VM, we stably knocked down ROCK1 or ROCK2 in MHCC97H cells. Compared to ROCK1 shRNA, ROCK2 shRNA could largely affect VM formation, cell motility and the key VM factors, as well as the epithelial-mesenchymal transition (EMT) markers in vitro and in vivo. Moreover, p-ERK, p-MEK, p-FAK, p-paxillin, MT1-MMP and MMP2 levels were clearly altered following the overexpression of RhoC, but ROCK2 shRNA had little effect on the expression of p-FAK, which indicated that RhoC regulates FAK/paxillin signaling, but not through ROCK2. In conclusion, our results show that RhoC/ROCK2 may have a major effect on VM in HCC via ERK/MMPs signaling and might be a potential therapeutic target for the treatment of HCC.

Identify gene expression pattern change at transcriptional and post-transcriptional levels.

Gene transcription is regulated with distinct sets of regulatory factors at multiple levels. Transcriptional and post-transcriptional regulation constitute two major regulation modes of gene expression to either activate or repress the initiation of transcription and thereby control the number of proteins synthesized during translation. Disruptions of the proper regulation patterns at transcriptional and post-transcriptional levels are increasingly recognized as causes of human diseases. Consequently, identifying the differential gene expression at transcriptional and post-transcriptional levels respectively is vital to identify potential disease-associated and/or causal genes and understand their roles in the disease development. Here, we proposed a novel method with a linear mixed model that can identify a set of differentially expressed genes at transcriptional and post-transcriptional levels. The simulation and real data analysis showed our method could provide an accurate way to identify genes subject to aberrant transcriptional and post-transcriptional regulation and reveal the potential causal genes that contributed to the diseases.

Metabolomic profiles associated with bone mineral density in US Caucasian women.

BACKGROUND: Individuals' peak bone mineral density (BMD) achieved and maintained at ages 20-40 years is the most powerful predictor of low bone mass and osteoporotic fractures later in life. The aim of this study was to identify metabolomic factors associated with peak BMD variation in US Caucasian women. METHODS: A total of 136 women aged 20-40 years, including 65 subjects with low and 71 with high hip BMD, were enrolled. The serum metabolites were assessed using a liquid chromatography-mass spectrometry (LC-MS) method. The partial least-squares discriminant analysis (PLS-DA) method and logistic regression models were used, respectively, to examine the associations of metabolomic profiles and individual metabolites with BMD. RESULTS: The low and high BMD groups could be differentiated by the detected serum metabolites using PLS-DA (Ppermutation = 0.008). A total of 14 metabolites, including seven amino acids and amino acid derivatives, five lipids (including three bile acids), and two organic acids, were significantly associated with the risk for low BMD. Most of these metabolites are novel in that they have never been linked with BMD in humans earlier. The prediction model including the newly identified metabolites significantly improved the classification of the groups with low and high BMD. The area under the receiver operating characteristic curve without and with metabolites were 0.88 (95% CI: 0.83-0.94) and 0.97 (95% CI: 0.94-0.99), respectively (P for the difference = 0.0004). CONCLUSION: Metabolomic profiling may improve the risk prediction of osteoporosis among Caucasian women. Our findings also suggest the potential importance of the metabolism of amino acids and bile acids in bone health.

Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power. To identify potential pleiotropic genes for these three disorders, we performed a systematic analysis by incorporating GWAS (genome-wide associated study) datasets of six correlated traits related to type 2 diabetes, obesity and dyslipidemia using Meta-CCA (meta-analysis using canonical correlation analysis). Meta-CCA is an emerging method to systematically identify potential pleiotropic genes using GWAS summary statistics of multiple correlated traits. 2,720 genes were identified as significant genes after multiple testing (Bonferroni corrected p value < 0.05). Further, to refine the identified genes, we tested their relationship to the six correlated traits using VEGAS-2 (versatile gene-based association study-2). Only the genes significantly associated (Bonferroni corrected p value < 0.05) with more than one trait were kept. Finally, 25 genes (including two confirmed pleiotropic genes and eleven novel pleiotropic genes) were identified as potential pleiotropic genes. They were enriched in 5 pathways including the statin pathway and the PPAR (peroxisome proliferator-activated receptor) Alpha pathway. In summary, our study identified potential pleiotropic genes and pathways of type 2 diabetes, obesity and dyslipidemia, which may shed light on the common biological etiology and pathogenesis of these three disorders and provide promising insights for new therapies.

Immunomodulatory interventions in myocardial infarction and heart failure: a systematic review of clinical trials and meta-analysis of IL-1 inhibition.

Following a myocardial infarction (MI), the immune system helps to repair ischaemic damage and restore tissue integrity, but excessive inflammation has been implicated in adverse cardiac remodelling and development towards heart failure (HF). Pre-clinical studies suggest that timely resolution of inflammation may help prevent HF development and progression. Therapeutic attempts to prevent excessive post-MI inflammation in patients have included pharmacological interventions ranging from broad immunosuppression to immunomodulatory approaches targeting specific cell types or factors with the aim to maintain beneficial aspects of the early post-MI immune response. These include the blockade of early initiators of inflammation including reactive oxygen species and complement, inhibition of mast cell degranulation and leucocyte infiltration, blockade of inflammatory cytokines, and inhibition of adaptive B and T-lymphocytes. Herein, we provide a systematic review on post-MI immunomodulation trials and a meta-analysis of studies targeting the inflammatory cytokine Interleukin-1. Despite an enormous effort into a significant number of clinical trials on a variety of targets, a striking heterogeneity in study population, timing and type of treatment, and highly variable endpoints limits the possibility for meaningful meta-analyses. To conclude, we highlight critical considerations for future studies including (i) the therapeutic window of opportunity, (ii) immunological effects of routine post-MI medication, (iii) stratification of the highly diverse post-MI patient population, (iv) the potential benefits of combining immunomodulatory with regenerative therapies, and at last (v) the potential side effects of immunotherapies.

Joint Detection of Associations between DNA Methylation and Gene Expression from Multiple Cancers.

DNA methylation plays an important role in the development of various cancers mainly through the regulation on gene expression. Hence, the study on the relation between DNA methylation and gene expression is of particular interest to understand cancers. Recently, an increasing number of datasets are available from multiple cancers, which makes it possible to study both the similarity and difference of genomic alterations across multiple tumor types. However, most of the existing pan-cancer analysis methods perform simple aggregations, which may overlook the heterogeneity of the interactions. In this paper, we propose a novel method to jointly detect complex associations between DNA methylation and gene expression levels from multiple cancers. The main idea is to apply joint sparse canonical correlation analysis to detect a small set of methylated sites, which are associated with another set of genes either shared across cancers or specific to a particular group (group-specific) of cancers. These methylated sites and genes form a complex module with strong multivariate correlations. We further introduced a joint sparse precision matrix estimation method to identify driver methylation-gene pairs in the module. These pairs are characterized by significant partial correlations, which may imply high functional impacts and contribute to complementary information to the main step. We apply our method to The Cancer Genome Atlas(TCGA) datasets with 1166 samples from four cancers. The results reveal significant shared and groupspecific interactions between DNA methylation and gene expression levels. To promote reproducible research, the Matlab code is available at https://sites.google.com/site/jianfang86/jointTCGA.

Potential Nexus of Non-alcoholic Fatty Liver Disease and Type 2 Diabetes Mellitus: Insulin Resistance Between Hepatic and Peripheral Tissues.

The liver is the central metabolic organ and plays a pivotal role in regulating homeostasis of glucose and lipid metabolism. Aberrant liver metabolism promotes insulin resistance, which is reported to be a common characteristic of metabolic diseases such as non-alcoholic fatty liver disease (NAFLD) and type 2 diabetes mellitus (T2DM). There is a complex and bidirectional relationship between NAFLD and T2DM. NAFLD patients with hepatic insulin resistance generally share a high risk of impaired fasting glucose associated with early diabetes; most patients with T2DM experience non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), and other more severe liver complications such as cirrhosis and hepatocellular carcinoma (HCC). Additionally, hepatic insulin resistance, which is caused by diacylglycerol-mediated activation of protein kinase C epsilon (PKC𝜀), may be the critical pathological link between NAFLD and T2DM. Therefore, this review aims to illuminate current insights regarding the complex and strong association between NAFLD and T2DM and summarize novel and emerging targets for the treatment of hepatic insulin resistance based on established mechanistic knowledge.