Dysregulation of Circadian Clock Genes as Significant Clinic Factor in the Tumorigenesis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the leading cause of cancer-related mortality worldwide due to its asymptomatic onset and poor survival rate. This highlights the urgent need for developing novel diagnostic markers for early HCC detection. The circadian clock is important for maintaining cellular homeostasis and is tightly associated with key tumorigenesis-associated molecular events, suggesting the so-called chronotherapy. An analysis of these core circadian genes may lead to the discovery of biological markers signaling the onset of the disease. In this study, the possible functions of 13 core circadian clock genes (CCGs) in HCC were systematically analyzed with the aim of identifying ideal biomarkers and therapeutic targets. Profiles of HCC patients with clinical and gene expression data were downloaded from The Cancer Genome Atlas and International Cancer Genome Consortium. Various bioinformatics methods were used to investigate the roles of circadian clock genes in HCC tumorigenesis. We found that patients with high TIMELESS expression or low CRY2, PER1, and RORA expressions have poor survival. Besides, a prediction model consisting of these four CCGs, the tumor-node-metastasis (TNM) stage, and sex was constructed, demonstrating higher predictive accuracy than the traditional TNM-based model. In addition, pathway analysis showed that these four CCGs are involved in the cell cycle, PI3K/AKT pathway, and fatty acid metabolism. Furthermore, the network of these four CCGs-related coexpressed genes and immune infiltration was analyzed, which revealed the close association with B cells and nTreg cells. Notably, TIMELESS exhibited contrasting effects against CRY2, PER1, and RORA in most situations. In sum, our works revealed that these circadian clock genes TIMELESS, CRY2, PER1, and RORA can serve as potential diagnostic and prognostic biomarkers, as well as therapeutic targets, for HCC patients, which may promote HCC chronotherapy by rhythmically regulating drug sensitivity and key cellular signaling pathways.

Network-Based Analysis of Fatal Comorbidities of COVID-19 and Potential Therapeutics.

COVID-19 is a highly contagious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The case-fatality rate is significantly higher in older patients and those with diabetes, cancer or cardiovascular disorders. The human proteins, angiotensin-converting enzyme 2 (ACE2), transmembrane protease serine 2 (TMPRSS2) and basigin (BSG), are involved in high-confidence host-pathogen interactions with SARS-CoV-2 proteins. We considered these three proteins as seed nodes and applied the random walk with restart method on the human interactome to construct a protein-protein interaction sub-network, which captures the effects of viral invasion. We found that 'Insulin resistance', 'AGE-RAGE signaling in diabetic complications' and 'adipocytokine signaling' were the common pathways associated with diabetes, cancer and cardiovascular disorders. The association of these critical pathways with aging and its related diseases explains the molecular basis of COVID-19 fatality. We further identified drugs that have effects on these proteins/pathways based on gene expression studies. We particularly focused on drugs that significantly downregulate ACE2 along with other critical proteins identified by the network-based approach. Among them, COL-3 had earlier shown activity against acute lung injury and acute respiratory distress, while entinostat and mocetinostat have been investigated for non-small-cell lung cancer. We propose that these drugs can be repurposed for COVID-19.

Predicting protein targets for drug-like compounds using transcriptomics.

An expanded chemical space is essential for improved identification of small molecules for emerging therapeutic targets. However, the identification of targets for novel compounds is biased towards the synthesis of known scaffolds that bind familiar protein families, limiting the exploration of chemical space. To change this paradigm, we validated a new pipeline that identifies small molecule-protein interactions and works even for compounds lacking similarity to known drugs. Based on differential mRNA profiles in multiple cell types exposed to drugs and in which gene knockdowns (KD) were conducted, we showed that drugs induce gene regulatory networks that correlate with those produced after silencing protein-coding genes. Next, we applied supervised machine learning to exploit drug-KD signature correlations and enriched our predictions using an orthogonal structure-based screen. As a proof-of-principle for this regimen, top-10/top-100 target prediction accuracies of 26% and 41%, respectively, were achieved on a validation of set 152 FDA-approved drugs and 3104 potential targets. We then predicted targets for 1680 compounds and validated chemical interactors with four targets that have proven difficult to chemically modulate, including non-covalent inhibitors of HRAS and KRAS. Importantly, drug-target interactions manifest as gene expression correlations between drug treatment and both target gene KD and KD of genes that act up- or down-stream of the target, even for relatively weak binders. These correlations provide new insights on the cellular response of disrupting protein interactions and highlight the complex genetic phenotypes of drug treatment. With further refinement, our pipeline may accelerate the identification and development of novel chemical classes by screening compound-target interactions.

Initial Trends in the Use of the 21-Gene Recurrence Score Assay for Patients With Breast Cancer in the Medicare Population, 2005-2009.

IMPORTANCE: In 2006, the Centers for Medicare & Medicaid Services approved coverage for the use of the 21-gene recurrence score (RS) assay in women with early-stage, estrogen receptor-positive, node-negative breast cancers to help guide recommendations for adjuvant chemotherapy. Use of the assay in community settings has not been previously examined in a nationally representative sample of patients. OBJECTIVE: To examine trends in the use of the RS assay in routine clinical practice in a nationally representative sample of women with breast cancer. DESIGN, SETTING, AND PARTICIPANTS: Retrospective observational study of Medicare beneficiaries diagnosed with incident breast cancer between 2005 and 2009, as recorded in a Surveillance, Epidemiology, and End Results data set with linked Medicare claims through 2010. MAIN OUTCOMES AND MEASURES: Demographic and clinical variables associated with the use of the assay. RESULTS: A total of 70,802 patients met the study criteria. Use of the RS assay increased from 1.1% in 2005 to 10.1% in 2009 (P < .001). The majority of tests (60.9%) occurred in patients with National Comprehensive Cancer Network-defined intermediate-risk disease (ie, estrogen receptor-positive, node-negative tumors >1 cm). Most patients with other than intermediate-risk disease had borderline indications for testing, including T1b (47.5%) or N1 (26.8%) disease. Testing was associated with younger age, fewer comorbid conditions, higher-grade disease, and being married. Among patients younger than 70 years with intermediate-risk disease, testing rates increased from 7.7% in 2005 to 38.8% in 2009 (P < .001). In multivariable analysis, testing was modestly higher in Northeast than in Western registries (odds ratio, 1.83; 95% CI, 1.49-2.26) but was otherwise not associated with region, local census tract demographic characteristics, black race, location in an urban area, or tumor histologic characteristics. CONCLUSIONS AND RELEVANCE: The RS assay was adopted quickly in clinical practice after the Medicare coverage decision in 2006, and use appears to be consistent with guidelines and equitable across geographic and racial groups. Factors influencing adoption of the assay and its impact on adjuvant chemotherapy use in clinical practice remain important areas of study.

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: myocardial and infectious adverse reactions as application cases.

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure-activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation.

The yin and yang of yeast transcription: elements of a global feedback system between metabolism and chromatin.

When grown in continuous culture, budding yeast cells tend to synchronize their respiratory activity to form a stable oscillation that percolates throughout cellular physiology and involves the majority of the protein-coding transcriptome. Oscillations in batch culture and at single cell level support the idea that these dynamics constitute a general growth principle. The precise molecular mechanisms and biological functions of the oscillation remain elusive. Fourier analysis of transcriptome time series datasets from two different oscillation periods (0.7 h and 5 h) reveals seven distinct co-expression clusters common to both systems (34% of all yeast ORF), which consolidate into two superclusters when correlated with a compilation of 1,327 unrelated transcriptome datasets. These superclusters encode for cell growth and anabolism during the phase of high, and mitochondrial growth, catabolism and stress response during the phase of low oxygen uptake. The promoters of each cluster are characterized by different nucleotide contents, promoter nucleosome configurations, and dependence on ATP-dependent nucleosome remodeling complexes. We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling. We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries. Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions.

Association of feature gene expression with structural fingerprints of chemical compounds.

Exploring the relationship between a chemical structure and its biological function is of great importance for drug discovery. For understanding the mechanisms of drug action, researchers traditionally focused on the molecular structures in the context of interactions with targets. The newly emerged high-throughput "omics" technology opened a new dimension to study the structure-function relationship of chemicals. Previous studies made attempts to introduce transcriptomics data into chemical function investigation. But little effort has been made to link structural fingerprints of compounds with defined intracellular functions, i.e. expression of particular genes and altered pathways. By integrating the chemical structural information with the gene expression profiles of chemical-treated cells, we developed a novel method to associate the structural difference between compounds with the expression of a definite set of genes, which were called feature genes. A subtraction protocol was designed to extract a minimum gene set related to chemical structural features, which can be utilized in practice as markers for drug screening. Case studies demonstrated that our approach is capable of finding feature genes associated with chemical structural fingerprints.

Differential gene expression of blood-derived cell lines in familial combined hyperlipidemia.

OBJECTIVES: The genetic background of familial combined hyperlipidemia (FCHL) is currently unclear. We propose transcriptional profiling as a complementary tool for its understanding. Two hypotheses were tested: the existence of a disease-specific modification of gene expression in FCHL and the detectability of such a transcriptional profile in blood derived cell lines. METHODS AND RESULTS: We established lymphoblastic cell lines from FCHL patients and controls. The cells were cultured in fixed conditions and their basal expression profile was compared using microarrays; 166 genes were differentially expressed in FCHL-derived cell lines compared with controls, with enrichment in metabolism-related genes. Of note was the upregulation of EGR-1, previously found to be upregulated in the adipose tissue of FCHL patients, the upregulation of DCHR-7, the downregulation of LYPLA2, and the differential expression of several genes previously unrelated to FCHL. A cluster of potential EGR-1-regulated transcripts was also differentially expressed in FCHL cells. CONCLUSIONS: Our data indicate that in FCHL, a disease-specific transcription profile is detectable in immortalized cell lines easily obtained from peripheral blood and provide complementary information to classical genetic approaches to FCHL and/or the metabolic syndrome.

Neural system-enriched gene expression: relationship to biological pathways and neurological diseases.

To understand the commitment of the genome to nervous system differentiation and function, we sought to compare nervous system gene expression to that of a wide variety of other tissues by gene expression database construction and mining. Gene expression profiles of 10 different adult nervous tissues were compared with that of 72 other tissues. Using ANOVA, we identified 1,361 genes whose expression was higher in the nervous system than other organs and, separately, 600 genes whose expression was at least threefold higher in one or more regions of the nervous system compared with their median expression across all organs. Of the 600 genes, 381 overlapped with the 1,361-gene list. Limited in situ gene expression analysis confirmed that identified genes did represent nervous system-enriched gene expression, and we therefore sought to evaluate the validity and significance of these top-ranked nervous system genes using known gene literature and gene ontology categorization criteria. Diverse functional categories were present in the 381 genes, including genes involved in intracellular signaling, cytoskeleton structure and function, enzymes, RNA metabolism and transcription, membrane proteins, as well as cell differentiation, death, proliferation, and division. We searched existing public sites and identified 110 known genes related to mental retardation, neurological disease, and neurodegeneration. Twenty-one of the 381 genes were within the 110-gene list, compared with a random expectation of 5. This suggests that the 381 genes provide a candidate set for further analyses in neurological and psychiatric disease studies and that as a field, we are as yet, far from a large-scale understanding of the genes that are critical for nervous system structure and function. Together, our data indicate the power of profiling an individual biologic system in a multisystem context to gain insight into the genomic basis of its structure and function.

Regional variations in ABC transporter expression along the mouse intestinal tract.

The ATP-binding cassette (ABC) family of proteins comprise a group of membrane transporters involved in the transport of a wide variety of compounds, such as xenobiotics, vitamins, lipids, amino acids, and carbohydrates. Determining their regional expression patterns along the intestinal tract will further characterize their transport functions in the gut. The mRNA expression levels of murine ABC transporters in the duodenum, jejunum, ileum, and colon were examined using the Affymetrix MuU74v2 GeneChip set. Eight ABC transporters (Abcb2, Abcb3, Abcb9, Abcc3, Abcc6, Abcd1, Abcg5, and Abcg8) displayed significant differential gene expression along the intestinal tract, as determined by two statistical models (a global error assessment model and a classic ANOVA, both with a P < 0.01). Concordance with semiquantitative real-time PCR was high. Analyzing the promoters of the differentially expressed ABC transporters did not identify common transcriptional motifs between family members or with other genes; however, the expression profile for Abcb9 was highly correlated with fibulin-1, and both genes share a common complex promoter model involving the NFkappaB, zinc binding protein factor (ZBPF), GC-box factors SP1/GC (SP1F), and early growth response factor (EGRF) transcription binding motifs. The cellular location of another of the differentially expressed ABC transporters, Abcc3, was examined by immunohistochemistry. Staining revealed that the protein is consistently expressed in the basolateral compartment of enterocytes along the anterior-posterior axis of the intestine. Furthermore, the intensity of the staining pattern is concordant with the expression profile. This agrees with previous findings in which the mRNA, protein, and transport function of Abcc3 were increased in the rat distal intestine. These data reveal regional differences in gene expression profiles along the intestinal tract and demonstrate that a complete understanding of intestinal ABC transporter function can only be achieved by examining the physiologically distinct regions of the gut.

Cytoprotection against thermal injury: evaluation of herbimycin A by cell viability and cDNA arrays.

Herbimycin A (HA), a known inducer of the heat shock response, was investigated for its ability to increase survival of a human cell line following thermal injury. Its effect on transcriptional activity was also assessed with cDNA arrays to provide new targets for cytoprotection. Pretreatment with at least 0.75 microg/ml HA significantly increased the fraction of cells surviving thermal injury by up to 50% (based on 8s exposure) compared to untreated controls. HA also significantly induced transcription of mRNA for HSP90 and HSP70, and protein production for HSP40 and HSP70. Gene expression profiling demonstrated that the most highly elevated genes included growth factors and transcription factors, while prominently suppressed genes included transcription factors and kinases. These results suggest that cytoprotection may be due to the contribution of the products of a significant number of genes in addition to the classic stress response genes, suggesting that modulation of these genes might induce thermotolerance and amelioration of thermal injury.

Identification of rat enamel organ RNA transcripts using differential-display.

Enamel formation is a complex process which involves the expression of a number of genes, the most obvious being those related to the mineralized extracellular matrix. In this study the differential-display technique, first described by Liang and Pardee, has been used to identify genes specifically expressed in enamel organ cells. By comparing results obtained from RNA derived from rat enamel organ with RNA derived from other cellular sources, a number of differentially expressed transcripts have been identified. The nucleotide sequences of two of these have been analyzed and shown to have no homology with any previously published sequences. Further analysis will provide information on the type of protein that they may encode, their tissue distribution and their potential role in enamel formation.