C2ORF40 suppresses breast cancer cell proliferation and invasion through modulating expression of M phase cell cycle genes

Recently, it has been suggested that C2ORF40 is a candidate tumor suppressor gene in breast cancer. However, the mechanism for reduced expression of C2ORF40 and its functional role in breast cancers remain unclear. Here we show that C2ORF40 is frequently silenced in human primary breast cancers and cell lines through promoter hypermethylation. C2ORF40 mRNA level is significantly associated with patient disease-free survival and distant cancer metastasis. Overexpression of C2ORF40 inhibits breast cancer cell proliferation, migration and invasion. By contrast, silencing C2ORF40 expression promotes these biological phenotypes. Bioinformatics and FACS analysis reveal C2ORF40 functions at G2/M phase by downregulation of mitotic genes expression, including UBE2C. Our results suggest that C2ORF40 acts as a tumor suppressor gene in breast cancer pathogenesis and progression and is a candidate prognostic marker for this disease.     

Perturbation Biology: Inferring Signaling Networks in Cellular Systems

We present a powerful experimental-computational technology for inferring network models that predict the response of cells to perturbations, and that may be useful in the design of combinatorial therapy against cancer. The experiments are systematic series of perturbations of cancer cell lines by targeted drugs, singly or in combination. The response to perturbation is quantified in terms of relative changes in the measured levels of proteins, phospho-proteins and cellular phenotypes such as viability. Computational network models are derived de novo, i.e., without prior knowledge of signaling pathways, and are based on simple non-linear differential equations. The prohibitively large solution space of all possible network models is explored efficiently using a probabilistic algorithm, Belief Propagation (BP), which is three orders of magnitude faster than standard Monte Carlo methods. Explicit executable models are derived for a set of perturbation experiments in SKMEL-133 melanoma cell lines, which are resistant to the therapeutically important inhibitor of RAF kinase. The resulting network models reproduce and extend known pathway biology. They empower potential discoveries of new molecular interactions and predict efficacious novel drug perturbations, such as the inhibition of PLK1, which is verified experimentally. This technology is suitable for application to larger systems in diverse areas of molecular biology.     

Prediction of Drug-Target Interactions for Drug Repositioning Only Based on Genomic Expression Similarity

Small drug molecules usually bind to multiple protein targets or even unintended off-targets. Such drug promiscuity has often led to unwanted or unexplained drug reactions, resulting in side effects or drug repositioning opportunities. So it is always an important issue in pharmacology to identify potential drug-target interactions (DTI). However, DTI discovery by experiment remains a challenging task, due to high expense of time and resources. Many computational methods are therefore developed to predict DTI with high throughput biological and clinical data. Here, we initiatively demonstrate that the on-target and off-target effects could be characterized by drug-induced in vitro genomic expression changes, e.g. the data in Connectivity Map (CMap). Thus, unknown ligands of a certain target can be found from the compounds showing high gene-expression similarity to the known ligands. Then to clarify the detailed practice of CMap based DTI prediction, we objectively evaluate how well each target is characterized by CMap. The results suggest that (1) some targets are better characterized than others, so the prediction models specific to these well characterized targets would be more accurate and reliable; (2) in some cases, a family of ligands for the same target tend to interact with common off-targets, which may help increase the efficiency of DTI discovery and explain the mechanisms of complicated drug actions. In the present study, CMap expression similarity is proposed as a novel indicator of drug-target interactions. The detailed strategies of improving data quality by decreasing the batch effect and building prediction models are also effectively established. We believe the success in CMap can be further translated into other public and commercial data of genomic expression, thus increasing research productivity towards valid drug repositioning and minimal side effects.     

Hepatitis C virus inhibits AKT-tuberous sclerosis complex (TSC), the mechanistic target of rapamycin (MTOR) pathway,through endoplasmic reticulum stress to induce autophagy

Hepatitis C virus (HCV) is able to induce autophagy via endoplasmic reticulum (ER) stress, but the exact molecular signaling pathway is not well understood. We found that the activity of the mechanistic target of rapamycin complex 1 (MTORC1) was inhibited in Huh7 cells either harboring HCV-N (genotype 1b) full-genomic replicon or infected with JFH1 (genotype 2a) virus, which led to the activation of UNC-51-like kinase 1 (ULK1) and thus to autophagy. We then analyzed activity upstream of MTORC1, and found that both protein kinase, AMP-activated, α (PRKAA, including PRKAA1 and PRKAA2, also known as AMP-activated protein kinase, AMPKα) and AKT (refers to pan AKT, including three isoforms of AKT1-3, also known as protein kinase B, PKB) were inhibited by HCV infection. The inhibition of the AKT-TSC-MTORC1 pathway contributed to upregulating autophagy, but inhibition of PRKAA downregulated autophagy. The net effect on autophagy was from AKT, which overrode the inhibition effect from PRKAA. It was further found that HCV-induced ER stress was responsible for the inhibition of the AKT pathway. Metformin, a PRKAA agonist, inhibited HCV replication not only by activating PRKAA as previously reported, but also by activating AKT independently of the autophagy pathway. Taken together, our data suggested HCV inhibited the AKT-TSC-MTORC1 pathway via ER stress, resulting in autophagy, which may contribute to the establishment of the HCV-induced autophagy.     

The molecular basis for the inhibition of phosphodiesterase-4D by three natural resveratrol analogs. Isolation,molecular docking,molecular dynamics simulations,binding free energy,and bioassay

The phosphodiesterase-4 (PDE4) enzyme is a promising therapeutic target for several diseases. Our previous studies found resveratrol and moracin M to be natural PDE4 inhibitors. In the present study, three natural resveratrol analogs [pterostilbene, (E)-2′,3,5′,5-tetrahydroxystilbene (THSB), and oxyresveratrol] are structurally related to resveratrol and moracin M, but their inhibition and mechanism against PDE4 are still unclear. A combined method consisting of molecular docking, molecular dynamics (MD) simulations, binding free energy, and bioassay was performed to better understand their inhibitory mechanism. The binding pattern of pterostilbene demonstrates that it involves hydrophobic/aromatic interactions with Phe340 and Phe372, and forms hydrogen bond(s) with His160 and Gln369 in the active site pocket. The present work also reveals that oxyresveratrol and THSB can bind to PDE4D and exhibits less negative predicted binding free energies than pterostilbene, which was qualitatively validated by bioassay (IC₅₀ = 96.6, 36.1, and 27.0 μM, respectively). Additionally, a linear correlation (R² = 0.953) is achieved for five PDE4D/ligand complexes between the predicted binding free energies and the experimental counterparts approximately estimated from their IC₅₀ values (≈RT ln IC₅₀). Our results imply that hydrophobic/aromatic forces are the primary factors in explaining the mechanism of inhibition by the three products. Results of the study help to understand the inhibitory mechanism of the three natural products, and thus help the discovery of novel PDE4 inhibitors from resveratrol, moracin M, and other natural products.     

Developmental expression of P2X5 receptors in the mouse prenatal central and peripheral nervous systems

The functions of P2X purinoceptors (P2X1-7) in the nervous system of adults have been widely studied. However, little is known about their roles during embryonic development. Our previous work has reported an extensive expression of P2X5 receptors in the adult mouse central nervous system. In the present study, we have examined the expression pattern of P2X5 receptor mRNA and protein during prenatal development of the mouse nervous system (from embryonic day E8 to E17). P2X5 receptors appeared in the neural tube as early as E8 and were gradually confined to new-born neurons in the cortical plate and ventral horn of the spinal cord. Heavy signals for P2X5 receptors were also found in dorsal root ganglia (DRG), retina, olfactory epithelium, and nerve fibers in skeletal muscles. In conclusion, P2X5 receptors were strongly represented in the developing mouse nervous system. The transient high expression pattern of P2X5 receptors in epithelium-like structures suggests a role during early neurogenesis.     

Block of P2X7 receptors could partly reverse the delayed neuronal death in area CA1 of the hippocampus after transient global cerebral ischemia

Transient global ischemia (which closely resembles clinical situations such as cardiac arrest, near drowning or severe systemic hypotension during surgical procedures), often induces delayed neuronal death in the brain, especially in the hippocampal CA1 region. The mechanism of ischemia/reperfusion (I/R) injury is not fully understood. In this study, we have shown that the P2X7 receptor antagonist, BBG, reduced delayed neuronal death in the hippocampal CA1 region after I/R injury; P2X7 receptor expression levels increased before delayed neuronal death after I/R injury; inhibition of the P2X7 receptor reduced I/R-induced microglial microvesicle-like components, IL-1β expression, P38 phosphorylation, and glial activation in hippocampal CA1 region after I/R injury. These results indicate that antagonism of the P2X7 receptor and signaling pathways of microglial MV shedding, such as src-protein tyrosine kinase, P38 MAP kinase and A-SMase, might be a promising therapeutic strategy for clinical treatment of transient global cerebral I/R injury.     

Unusual lipids and acylglucosylsterols from the roots of Livistona chinensis

A 70% ethanol extract from the roots of Livistona chinensis has been investigated, led to the isolation of 18 compounds, including two new 6′-O-acyl-β-d-glucosyl-β-sitosterols, 6′-O-(2″-hydroxyheptadecanoyl)-β-d-glucosyl-β-sitosterol (1) and 6′-O-(icosa-9″Z,12″Z-dienoyl)-β-d-glucosyl-β-sitosterol (2), two new keto esters, ethyl 16-(dodeca-4″′Z,7″′Z-dienyl)-29-oxo-15-(tetradeca-5″Z,8″Z,11″Z-trienyl) triacontanoate (7), and 16-hydroxy-8-oxohexadecyl tetradecanoate (9), a new unsaturated fatty acid, tetracosa-(11Z,14Z,18Z)-trienoic acid (8), as well as a new fatty alcohol, 10-decylnonadecane-1,19-diol (10). The structures of new compounds were elucidated, based on spectroscopic and chemical methods. The antiproliferative activity against four human tumor cell lines (K562, HL-60, HepG2, and CNE-1) was evaluated. Four compounds (1–3, 5) showed potent antiproliferative effects with the IC₅₀ of 10–100 μM. To our knowledge, this is the first report of the occurrence of 6′-O-acyl-β-d-glucosyl-β-sitosterol and 3-O-acyl-β-sitosterol in the genus Livistona. Keto fatty acids and their esters are also rare in higher plant.     

Temperature Response of Soil Respiration in a Chinese Pine Plantation: Hysteresis and Seasonal vs. Diel Q 10

Although the temperature response of soil respiration (R_s) has been studied extensively, several issues remain unresolved, including hysteresis in the R_s–temperature relationship and differences in the long- vs. short-term R_s sensitivity to temperature. Progress on these issues will contribute to reduced uncertainties in carbon cycle modeling. We monitored soil CO₂ efflux with an automated chamber system in a Pinus tabulaeformis plantation near Beijing throughout 2011. Soil temperature at 10-cm depth (T_s) exerted a strong control over R_s, with the annual temperature sensitivity (Q ₁₀) and basal rate at 10°C (R_{s 10}) being 2.76 and 1.40 µmol m⁻² s⁻¹, respectively. Both R_s and short-term (i.e., daily) estimates of R_{s 10} showed pronounced seasonal hysteresis with respect to T_s, with the efflux in the second half of the year being larger than that early in the season for a given temperature. The hysteresis may be associated with the confounding effects of microbial population dynamics and/or litter input. As a result, all of the applied regression models failed to yield unbiased estimates of R_s over the entire annual cycle. Lags between R_s and T_s were observed at the diel scale in the early and late growing season, but not in summer. The seasonality in these lags may be due to the use of a single T_s measurement depth, which failed to represent seasonal changes in the depth of CO₂ production. Daily estimates of Q ₁₀ averaged 2.04, smaller than the value obtained from the seasonal relationship. In addition, daily Q ₁₀ decreased with increasing T_s, which may contribute feedback to the climate system under global warming scenarios. The use of a fixed, universal Q ₁₀ is considered adequate when modeling annual carbon budgets across large spatial extents. In contrast, a seasonally-varying, environmentally-controlled Q ₁₀ should be used when short-term accuracy is required.