Biomarkers derived from gene expression profiling data may have a high false-positive rate and must be rigorously validated using independent clinical data sets, which are not always available. Although animal model systems could provide alternative data sets to formulate hypotheses and limit the number of signatures to be tested in clinical samples, the predictive power of such an approach is not yet proven. The present study aims to analyze the molecular signatures of liver cancer in a c-MET-transgenic mouse model and investigate its prognostic relevance to human hepatocellular carcinoma (HCC). Tissue samples were obtained from tumor (TU), adjacent non-tumor (AN) and distant normal (DN) liver in Tet-operator regulated (TRE) human c-MET transgenic mice (n = 21) as well as from a Chinese cohort of 272 HBV- and 9 HCV-associated HCC patients. Whole genome microarray expression profiling was conducted in Affymetrix gene expression chips, and prognostic significances of gene expression signatures were evaluated across the two species. Our data revealed parallels between mouse and human liver tumors, including down-regulation of metabolic pathways and up-regulation of cell cycle processes. The mouse tumors were most similar to a subset of patient samples characterized by activation of the Wnt pathway, but distinctive in the p53 pathway signals. Of potential clinical utility, we identified a set of genes that were down regulated in both mouse tumors and human HCC having significant predictive power on overall and disease-free survival, which were highly enriched for metabolic functions. In conclusions, this study provides evidence that a disease model can serve as a possible platform for generating hypotheses to be tested in human tissues and highlights an efficient method for generating biomarker signatures before extensive clinical trials have been initiated.

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10(-12)), while Dnmt3a KO signature does not (P = 0.017).

Circadian (diurnal) rhythm is an integral part of the physiology of the body; specifically, sleep, feeding behavior and metabolism are tightly linked to the light-dark cycle dictated by earth's rotation.

To dissect common human diseases such as obesity and diabetes, a systematic approach is needed to study how genes interact with one another, and with genetic and environmental factors, to determine clinical end points or disease phenotypes. Bayesian networks provide a convenient framework for extracting relationships from noisy data and are frequently applied to large-scale data to derive causal relationships among variables of interest. Given the complexity of molecular networks underlying common human disease traits, and the fact that biological networks can change depending on environmental conditions and genetic factors, large datasets, generally involving multiple perturbations (experiments), are required to reconstruct and reliably extract information from these networks. With limited resources, the balance of coverage of multiple perturbations and multiple subjects in a single perturbation needs to be considered in the experimental design. Increasing the number of experiments, or the number of subjects in an experiment, is an expensive and time-consuming way to improve network reconstruction. Integrating multiple types of data from existing subjects might be more efficient. For example, it has recently been demonstrated that combining genotypic and gene expression data in a segregating population leads to improved network reconstruction, which in turn may lead to better predictions of the effects of experimental perturbations on any given gene. Here we simulate data based on networks reconstructed from biological data collected in a segregating mouse population and quantify the improvement in network reconstruction achieved using genotypic and gene expression data, compared with reconstruction using gene expression data alone. We demonstrate that networks reconstructed using the combined genotypic and gene expression data achieve a level of reconstruction accuracy that exceeds networks reconstructed from expression data alone, and that fewer subjects may be required to achieve this superior reconstruction accuracy. We conclude that this integrative genomics approach to reconstructing networks not only leads to more predictive network models, but also may save time and money by decreasing the amount of data that must be generated under any given condition of interest to construct predictive network models.

To explore relationships between biological gene expression signatures and pembrolizumab response.

β-thalassemia is one of the most common monogenic diseases in the world. Southeast China is a highly infected area affected by four β-thalassemia mutation types (HBB:c.-78A>G, HBB:c.52A>T, HBB:c.126_129delCTTT, and HBB:c.316-197C>T). Relative haplotype dosage (RHDO), a haplotype-based approach, has shown promise as an application for noninvasive prenatal diagnosis (NIPD); however, additional family members (such as the proband) are required for haplotype construction. The abovementioned circumstances make RHDO-based NIPD cost prohibitive; additionally, the genetic information of the proband is not always available. Thus, it is necessary to find a practical method to solve these problems.

The aim of this study was to investigate the relationship between Hypersensitive C-reactive protein (hs-CRP) and left ventricular hypertrophy (LVH) in elderly community-dwelling patients with hypertension.

Common inflammatome gene signatures as well as disease-specific signatures were identified by analyzing 12 expression profiling data sets derived from 9 different tissues isolated from 11 rodent inflammatory disease models. The inflammatome signature significantly overlaps with known drug targets and co-expressed gene modules linked to metabolic disorders and cancer. A large proportion of genes in this signature are tightly connected in tissue-specific Bayesian networks (BNs) built from multiple independent mouse and human cohorts. Both the inflammatome signature and the corresponding consensus BNs are highly enriched for immune response-related genes supported as causal for adiposity, adipokine, diabetes, aortic lesion, bone, muscle, and cholesterol traits, suggesting the causal nature of the inflammatome for a variety of diseases. Integration of this inflammatome signature with the BNs uncovered 151 key drivers that appeared to be more biologically important than the non-drivers in terms of their impact on disease phenotypes. The identification of this inflammatome signature, its network architecture, and key drivers not only highlights the shared etiology but also pinpoints potential targets for intervention of various common diseases.

Hepatocellular carcinoma (HCC) is one of the most deadly cancers worldwide and has no effective treatment, yet the molecular basis of hepatocarcinogenesis remains largely unknown. Here we report findings from a whole-genome sequencing (WGS) study of 88 matched HCC tumor/normal pairs, 81 of which are Hepatitis B virus (HBV) positive, seeking to identify genetically altered genes and pathways implicated in HBV-associated HCC. We find beta-catenin to be the most frequently mutated oncogene (15.9%) and TP53 the most frequently mutated tumor suppressor (35.2%). The Wnt/beta-catenin and JAK/STAT pathways, altered in 62.5% and 45.5% of cases, respectively, are likely to act as two major oncogenic drivers in HCC. This study also identifies several prevalent and potentially actionable mutations, including activating mutations of Janus kinase 1 (JAK1), in 9.1% of patients and provides a path toward therapeutic intervention of the disease.

Pancreatic polypeptide is released mainly from the pancreas, and is thought to be one of the major endogenous agonists of the neuropeptide Y Y(4) receptor. Pancreatic polypeptide has been shown to stimulate colonic muscle contraction, but whether pancreatic polypeptide has in vivo functional activity with respect to colonic transit is unclear. The present report investigated the effects of pancreatic polypeptide on fecal output as an index of colonic transit as well as intestinal motor activity, using wild-type (WT) and neuropeptide Y Y(4) receptor-deficient (KO) mice. Peripheral administration of pancreatic polypeptide increased fecal weight and caused diarrhea in WT mice in a dose-dependent manner (0.01-3mg/kg s.c.). Pancreatic polypeptide-induced increases in fecal weight and diarrhea completely disappeared in KO mice, while basal fecal weights did not differ between WT and KO mice. In longitudinal and circular muscles of mouse isolated colon, pancreatic polypeptide (0.01-1 microM) increased basal tone and frequency of spontaneous contraction in WT mice, but not in KO mice. Atropine did not affect pancreatic polypeptide-induced fecal output or increase in colonic muscle tone, indicating that the actions of pancreatic polypeptide are not mediated through cholinergic mechanisms. The present findings demonstrate that pancreatic polypeptide enhances colonic contractile activity and fecal output through neuropeptide Y Y(4) receptor, and a neuropeptide Y Y(4) receptor agonist might offer a novel therapeutic approach to ameliorate constipation.

Noninvasive prenatal testing (NIPT) for single gene disorders remains challenging. One approach that allows for accurate detection of the slight increase of the maternally inherited allele is the relative haplotype dosage (RHDO) analysis, which requires the construction of parental haplotypes. Recently, the nanopore sequencing technologies have become available and may be an ideal tool for direct construction of haplotypes. Here, we explored the feasibility of combining nanopore sequencing with the RHDO analysis in NIPT of β-thalassemia. Thirteen families at risk for β-thalassemia were recruited. Targeted region of parental genomic DNA was amplified by long-range PCR of 10 kb and 20 kb amplicons. Parental haplotypes were constructed using nanopore sequencing and next generation sequencing data. Fetal inheritance of parental haplotypes was classified by the RHDO analysis using data from maternal plasma DNA sequencing. Haplotype phasing was achieved in 12 families using data from 10 kb library. While data from the 20 kb library gave a better performance that haplotype phasing was achieved in all 13 families. Fetal status was correctly classified in 12 out of 13 families. Thus, targeted nanopore sequencing combined with the RHDO analysis is feasible to NIPT for β-thalassemia.

Cyclophosphamide is a commonly used anticancer drug, and immunosuppression is one of the most common side effects. How to recover the immunological function is important for cyclophosphamide-treated patients. In the present study, Phellodendri Cortex polysaccharides (CPP) could enhance the proliferation of mouse spleen lymphocytes in vitro. The immunoregulatory function of CPP was then investigated in cyclophosphamide-induced immunosuppressed mice. In CPP-treated groups, mice were orally treated with CPP at doses of 1, 0.5, and 0.25 g/kg bodyweight from 1 to 11 d, respectively. The cyclophosphamide was administrated in CPP and cyclophosphamide groups from 12 to 14 d. In the cyclophosphamide and normal control groups, the mice received equal volume of saline from 1 to 14 d. The results showed that CPP (1 g/kg) could significantly increase the bodyweight of mice, even during cyclophosphamide treatment. The organ coefficients of the spleen and thymus were recovered by CPP treatment. CPP upregulated the contents of cytokines (IL-2, IL-6, IFN-γ, and TNF-α) in serum, which were downregulated by cyclophosphamide. The mRNA levels of these cytokines were also elevated by CPP treatment in the spleen. Cyclophosphamide upregulated the expressions of NF-κB p65, TLR4, and MyD88, suggesting that the NF-κB signaling pathway was activated by cyclophosphamide. After CPP treatment, it was recovered to normal level. These results indicated that CPP alleviated the cyclophosphamide-induced immunosuppression.

Long noncoding RNAs (lncRNAs) are an important subtype of noncoding RNAs (ncRNAs) and microRNA sponges regulate protein-coding gene expression. The lncRNA prostate androgen-regulated transcript 1 (PART1) was implicated in the process of several cancer pathogeneses. However, studies on the regulation of PART1 expression and its mechanism in liver cancer are lacking.

Polygonati Rhizoma is a widely used traditional Chinese medicine (TCM) with complex pre-processing steps. Fermentation is a common method for processing TCM to reduce herb toxicity and enhance their properties and/or produce new effects. Here, in this study, using Bacillus subtilis and Saccharomyces cerevisiae, we aimed to evaluate the potential application of solid fermentation in isolating different functional polysaccharides from Polygonatum cyrtonema Hua. With hot water extraction, ethanol precipitation, DEAE anion exchange chromatography and gel filtration, multiple neutral and acidic polysaccharides were obtained, showing different yields, content, compositions and functional groups after fermentation. Combining in vitro experiments and in vivo aging and immunosuppressed mouse models, we further compared the antioxidant and immunomodulating bioactivities of these polysaccharides and found a prominent role of a natural polysaccharide (BNP) from fermented P. cyrtonema via Bacillus subtilis in regulating intestinal antioxidant defense and immune function, which may be a consequence of the ability of BNP to modulate the homeostasis of gut microbiota. Thus, this work provides evidence for the further development and utilization of P. cyrtonema with fermentation, and reveals the potential values of BNP in the treatment of intestinal disorders.

Tumorigenesis involves multistep genetic alterations. To elucidate the microRNA (miRNA)-gene interaction network in carcinogenesis, we examined their genome-wide expression profiles in 96 pairs of tumor/non-tumor tissues from hepatocellular carcinoma (HCC). Comprehensive analysis of the coordinate expression of miRNAs and mRNAs reveals that miR-122 is under-expressed in HCC and that increased expression of miR-122 seed-matched genes leads to a loss of mitochondrial metabolic function. Furthermore, the miR-122 secondary targets, which decrease in expression, are good prognostic markers for HCC. Transcriptome profiling data from additional 180 HCC and 40 liver cirrhotic patients in the same cohort were used to confirm the anti-correlation of miR-122 primary and secondary target gene sets. The HCC findings can be recapitulated in mouse liver by silencing miR-122 with antagomir treatment followed by gene-expression microarray analysis. In vitro miR-122 data further provided a direct link between induction of miR-122-controlled genes and impairment of mitochondrial metabolism. In conclusion, miR-122 regulates mitochondrial metabolism and its loss may be detrimental to sustaining critical liver function and contribute to morbidity and mortality of liver cancer patients.

The genetics of complex disease produce alterations in the molecular interactions of cellular pathways whose collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer's disease (LOAD), we constructed gene-regulatory networks in 1,647 postmortem brain tissues from LOAD patients and nondemented subjects, and we demonstrate that LOAD reconfigures specific portions of the molecular interaction structure. Through an integrative network-based approach, we rank-ordered these network structures for relevance to LOAD pathology, highlighting an immune- and microglia-specific module that is dominated by genes involved in pathogen phagocytosis, contains TYROBP as a key regulator, and is upregulated in LOAD. Mouse microglia cells overexpressing intact or truncated TYROBP revealed expression changes that significantly overlapped the human brain TYROBP network. Thus the causal network structure is a useful predictor of response to gene perturbations and presents a framework to test models of disease mechanisms underlying LOAD.

A principal task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription and phenotypic information. Here we have validated our method through the characterization of transgenic and knockout mouse models of genes predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being newly confirmed, resulted in significant changes in obesity-related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F(2) intercross studies allows high-confidence prediction of causal genes and identification of pathways and networks involved.

The Copper Metabolism MURR1 Domain (COMMD) family proteins are known to play roles in promoting or inhibiting the proliferation, migration and invasion of tumor cells. However, the role of COMMD3 in hepatocellular carcinoma are still unclear. By investigating the TCGA datasets, we found that the mRNA expression of COMMD3 was significantly upregulated in hepatocellular carcinoma tissue compared with normal liver tissue, which was further supported by Oncomine dataset, Western blot, qRT-PCR, and IHC analysis. Moreover, Kaplan-Meier survival analysis showed that the high expression of COMMD3 was associated with poor overall survival (OS) and disease-free survival (DFS). Consistently, the clinic-pathological analysis found that the overexpression of COMMD3 was correlated with advanced TNM stage, advanced T stage and vascular invasion. By performing multivariate analysis, we found that the expression of COMMD3 was an independent influencing factor on OS and DFS. Furthermore, we knocked down COMMD3 in HCC cells via RNA interference. The results showed that silencing COMMD3 could inhibit the migration, invasion, and angiogenesis of HCC cells. Finally, we established xenograft tumor model in nude mice, and the knockdown of COMMD3 suppressed tumor growth and angiogenesis. In summary, our study showed that the high expression of COMMD3 was correlated with poor prognosis in HCC patients and contributed to migration, invasion and angiogenesis of HCC cells.

Complex diseases result from molecular changes induced by multiple genetic factors and the environment. To derive a systems view of how genetic loci interact in the context of tissue-specific molecular networks, we constructed an F2 intercross comprised of >500 mice from diabetes-resistant (B6) and diabetes-susceptible (BTBR) mouse strains made genetically obese by the Leptin(ob/ob) mutation (Lep(ob)). High-density genotypes, diabetes-related clinical traits, and whole-transcriptome expression profiling in five tissues (white adipose, liver, pancreatic islets, hypothalamus, and gastrocnemius muscle) were determined for all mice. We performed an integrative analysis to investigate the inter-relationship among genetic factors, expression traits, and plasma insulin, a hallmark diabetes trait. Among five tissues under study, there are extensive protein-protein interactions between genes responding to different loci in adipose and pancreatic islets that potentially jointly participated in the regulation of plasma insulin. We developed a novel ranking scheme based on cross-loci protein-protein network topology and gene expression to assess each gene's potential to regulate plasma insulin. Unique candidate genes were identified in adipose tissue and islets. In islets, the Alzheimer's gene App was identified as a top candidate regulator. Islets from 17-week-old, but not 10-week-old, App knockout mice showed increased insulin secretion in response to glucose or a membrane-permeant cAMP analog, in agreement with the predictions of the network model. Our result provides a novel hypothesis on the mechanism for the connection between two aging-related diseases: Alzheimer's disease and type 2 diabetes.

Immune checkpoint blockade (ICB) leads to durable and complete tumour regression in some patients but in others gives temporary, partial or no response. Accordingly, significant efforts are underway to identify tumour-intrinsic mechanisms underlying ICB resistance. Results from a published CRISPR screen in a mouse model suggested that targeting STUB1, an E3 ligase involved in protein homeostasis, may overcome ICB resistance but the molecular basis of this effect remains unclear. Herein, we report an under-appreciated role of STUB1 to dampen the interferon gamma (IFNγ) response. Genetic deletion of STUB1 increased IFNGR1 abundance on the cell surface and thus enhanced the downstream IFNγ response as showed by multiple approaches including Western blotting, flow cytometry, qPCR, phospho-STAT1 assay, immunopeptidomics, proteomics, and gene expression profiling. Human prostate and breast cancer cells with STUB1 deletion were also susceptible to cytokine-induced growth inhibition. Furthermore, blockade of STUB1 protein function recapitulated the STUB1-null phenotypes. Despite these encouraging in vitro data and positive implications from clinical datasets, we did not observe in vivo benefits of inactivating Stub1 in mouse syngeneic tumour models-with or without combination with anti-PD-1 therapy. However, our findings elucidate STUB1 as a barrier to IFNγ sensing, prompting further investigations to assess if broader inactivation of human STUB1 in both tumors and immune cells could overcome ICB resistance.