Overexpression of heat shock protein 47 is associated with increased proliferation and metastasis in gastric cancer.

Here, we investigated that the heat shock protein 47 (HSP47) plays a crucial role in the progression of gastric cancer (GC). We analyzed HSP47 gene expression in GC cell lines and patient tissues. The HSP47 mRNA and protein expression levels were significantly higher in GC cell lines and tumor tissues compared to normal gastric mucosa. Using siRNA to silence the expression of HSP47 in GC cells resulted in a significant reduction in their proliferation, wound healing, migration, and invasion capacities. Additionally, we also showed that the mRNA expression of matrix metallopeptidase-7 (MMP-7), a metastasis-promoting gene, was significantly reduced in HSP47 siRNA-transfected GC cells. We confirmed that the HSP47 promoter region was methylated in the SNU-216 GC cell line expressing low levels of HSP47 and in most non-cancerous gastric tissues. It means that the expression of HSP47 is regulated by epigenetic regulatory mechanisms. These findings suggest that targeting HSP47, potentially through its promoter methylation, could be a useful new therapeutic strategy for treating GC.

vSPACE: Exploring Virtual Spatial Representation of Articular Chondrocytes at the Single-Cell Level.

Single cell RNA sequencing technology has been dramatically changing how gene expression studies are performed. However, its use has been limited to identifying subtypes of cells by comparing cells' gene expression levels in an unbiased manner to produce a 2D plot (e.g., UMAP/tSNE). We developed a new method of placing cells in 2D space. This system, called vSPACE, shows a virtual spatial representation of scRNAseq data obtained from human articular cartilage by emulating the concept of spatial transcriptomics technology, but virtually. This virtual 2D plot presentation of human articular cartage cells generates several zonal distribution patterns, in one or multiple genes at a time, reveling patterns that scientists can appreciate as imputed spatial distribution patterns along the zonal axis. The discovered patterns are explainable and remarkably consistent across all six healthy doners despite their respectively different clinical variables (age and sex), suggesting the confidence of the discovered patterns.

CGCom: a framework for inferring Cell-cell Communication based on Graph Neural Network.

Cell-cell communication is crucial in maintaining cellular homeostasis, cell survival and various regulatory relationships among interacting cells. Thanks to recent advances of spatial transcriptomics technologies, we can now explore if and how cells' proximal information available from spatial transcriptomics datasets can be used to infer cell-cell communication. Here we present a cell-cell communication inference framework, called CGCom, which uses a graph neural network (GNN) to learn communication patterns among interacting cells by combining single-cell spatial transcriptomic datasets with publicly available ligand-receptor information and the molecular regulatory information down-stream of the ligand-receptor signaling. To evaluate the performance of CGCom, we applied it to mouse embryo seqFISH datasets. Our results demonstrate that CGCom can not only accurately infer cell communication between individual cell pairs but also generalize its learning to predict communication between different cell types. We compared the performance of CGCom with two existing methods, CellChat and CellPhoneDB, and our comparative study revealed both common and unique communication patterns from the three approaches. Commonly found communication patterns include three sets of ligand-receptor communication relationships, one between surface ectoderm cells and spinal cord cells, one between gut tube cells and endothelium, and one between neural crest and endothelium, all of which have already been reported in the literature thus offering credibility of all three methods. However, we hypothesize that CGCom is superior in reducing false positives thanks to its use of cell proximal information and its learning between specific cell pairs rather than between cell types. CGCom is a GNN-based solution that can take advantage of spatially resolved single-cell transcriptomic data in predicting cell-cell communication with a higher accuracy.

Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes.

We present a multi-sensor data fusion model based on a reconfigurable module (RM) with three fusion layers. In the data layer, raw data are refined with respect to the sensor characteristics and then converted into logical values. In the feature layer, a fusion tree is configured, and the values of the intermediate nodes are calculated by applying predefined logical operations, which are adjustable. In the decision layer, a final decision is made by computing the value of the root according to predetermined equations. In this way, with given threshold values or sensor characteristics for data refinement and logic expressions for feature extraction and decision making, we reconstruct an RM that performs multi-sensor fusion and is adaptable for a dedicated application. We attempted to verify its feasibility by applying the proposed RM to an actual application. Considering the spread of the COVID-19 pandemic, an unmanned storage box was selected as our application target. Four types of sensors were used to determine the state of the door and the status of the existence of an item inside it. We implemented a prototype system that monitored the unmanned storage boxes by configuring the RM according to the proposed method. It was confirmed that a system built with only low-cost sensors can identify the states more reliably through multi-sensor data fusion.

Predicting the targets of IRF8 and NFATc1 during osteoclast differentiation using the machine learning method framework cTAP.

BACKGROUND: Interferon regulatory factor-8 (IRF8) and nuclear factor-activated T cells c1 (NFATc1) are two transcription factors that have an important role in osteoclast differentiation. Thanks to ChIP-seq technology, scientists can now estimate potential genome-wide target genes of IRF8 and NFATc1. However, finding target genes that are consistently up-regulated or down-regulated across different studies is hard because it requires analysis of a large number of high-throughput expression studies from a comparable context. METHOD: We have developed a machine learning based method, called, Cohort-based TF target prediction system (cTAP) to overcome this problem. This method assumes that the pathway involving the transcription factors of interest is featured with multiple "functional groups" of marker genes pertaining to the concerned biological process. It uses two notions, Gene-Present Sufficiently (GP) and Gene-Absent Insufficiently (GA), in addition to log2 fold changes of differentially expressed genes for the prediction. Target prediction is made by applying multiple machine-learning models, which learn the patterns of GP and GA from log2 fold changes and four types of Z scores from the normalized cohort's gene expression data. The learned patterns are then associated with the putative transcription factor targets to identify genes that consistently exhibit Up/Down gene regulation patterns within the cohort. We applied this method to 11 publicly available GEO data sets related to osteoclastgenesis. RESULT: Our experiment identified a small number of Up/Down IRF8 and NFATc1 target genes as relevant to osteoclast differentiation. The machine learning models using GP and GA produced NFATc1 and IRF8 target genes different than simply using a log2 fold change alone. Our literature survey revealed that all predicted target genes have known roles in bone remodeling, specifically related to the immune system and osteoclast formation and functions, suggesting confidence and validity in our method. CONCLUSION: cTAP was motivated by recognizing that biologists tend to use Z score values present in data sets for the analysis. However, using cTAP effectively presupposes assembling a sizable cohort of gene expression data sets within a comparable context. As public gene expression data repositories grow, the need to use cohort-based analysis method like cTAP will become increasingly important.

rPAC: Route based pathway analysis for cohorts of gene expression data sets.

Pathway analysis is a popular method aiming to derive biological interpretation from high-throughput gene expression studies. However, existing methods focus mostly on identifying which pathway or pathways could have been perturbed, given differential gene expression patterns. In this paper, we present a novel pathway analysis framework, namely rPAC, which decomposes each signaling pathway route into two parts, the upstream portion of a transcription factor (TF) block and the downstream portion from the TF block and generates a pathway route perturbation analysis scheme examining disturbance scores assigned to both parts together. This rPAC scoring is further applied to a cohort of gene expression data sets which produces two summary metrics, "Proportion of Significance" (PS) and "Average Route Score" (ARS), as quantitative measures discerning perturbed pathway routes within and/or between cohorts. To demonstrate rPAC's scoring competency, we first used a large amount of simulated data and compared the method's performance against those by conventional methods in terms of power curve. Next, we performed a case study involving three epithelial cancer data sets from The Cancer Genome Atlas (TCGA). The rPAC method revealed specific pathway routes as potential cancer type signatures. A deeper pathway analysis of sub-groups (i.e., age groups in COAD or cancer sub-types in BRCA) resulted in pathway routes that are known to be associated with the sub-groups. In addition, multiple previously uncharacterized pathways routes were identified, potentially suggesting that rPAC is better in deciphering etiology of a disease than conventional methods particularly in isolating routes and sections of perturbed pathways in a finer granularity.

Tumour-derived Dilp8/INSL3 induces cancer anorexia by regulating feeding neuropeptides via Lgr3/8 in the brain.

In patients with advanced-stage cancer, cancer-associated anorexia affects treatment success and patient survival. However, the underlying mechanism is poorly understood. Here, we show that Dilp8, a Drosophila homologue of mammalian insulin-like 3 peptide (INSL3), is secreted from tumour tissues and induces anorexia through the Lgr3 receptor in the brain. Activated Dilp8-Lgr3 signalling upregulated anorexigenic nucleobinding 1 (NUCB1) and downregulated orexigenic short neuropeptide F (sNPF) and NPF expression in the brain. In the cancer condition, the protein expression of Lgr3 and NUCB1 was significantly upregulated in neurons expressing sNPF and NPF. INSL3 levels were increased in tumour-implanted mice and INSL3-treated mouse hypothalamic cells showed Nucb2 upregulation and Npy downregulation. Food consumption was significantly reduced in intracerebrospinal INSL3-injected mice. In patients with pancreatic cancer, higher serum INSL3 levels increased anorexia. These results indicate that tumour-derived Dilp8/INSL3 induces cancer anorexia by regulating feeding hormones through the Lgr3/Lgr8 receptor in Drosophila and mammals.

Skeletal screening IMPC/KOMP using µCT and computer automated cryohistology: Application to the Efna4 KO mouse line.

The IMPC/KOMP program provides the opportunity to screen mice harboring well defined gene-inactivation mutations in a uniform genetic background. The program performs a global tissue phenotyping survey that includes skeletal x-rays and bone density measurements. Because of the relative insensitivity of the two screening tests for detecting variance in bone architecture, we initiated a secondary screen based on µCT and a cryohistolomorphological workflow that was performed on the femur and vertebral compartments on 220 randomly selected knockouts (KOs) and 36 control bone samples over a 2 1/2 year collection period provided by one of the production/phenotyping centers. The performance of the screening protocol was designed to balance throughput and cost versus sensitivity and informativeness such that the output would be of value to the skeletal biology community. Here we report the reliability of this screening protocol to establish criteria for control skeletal variance at the architectural, dynamic and cellular histomorphometric level. Unexpected properties of the control population include unusually high variance in BV/TV in male femurs and greater bone formation and bone turnover rates in the female femur and vertebral trabeculae bone compartments. However, the manner for maintaining bone formation differed between these two bone sites. The vertebral compartment relies on maintaining a greater number of bone forming surfaces while the femoral compartment utilized more matrix production per cell. The comparison of the architectural properties obtained by µCT and histomorphology revealed significant differences in values for BV/TV, Tb.Th and Tb.N which is attributable to sampling density of the two methods. However, as a screening tool, expressing the ratio of KO to the control line as obtained by either method was remarkably similar. It identified KOs with significant variance which led to a more detailed histological analysis. Our findings are exemplified by the Efna4 KO, in which a high BV/TV was identified by µCT and confirmed by histomorphometry in the femur but not in the vertebral compartment. Dynamic labeling showed a marked increase in BFR which was attributable to increased labeling surfaces. Cellular analysis confirmed partitioning of osteoblast to labeling surfaces and a marked decrease in osteoclastic activity on both labeling and quiescent surfaces. This pattern of increased bone modeling would not be expected based on prior studies of the Ephrin-Ephrin receptor signaling pathways between osteoblasts and osteoclasts. Overall, our findings underscore why unbiased screening is needed because it can reveal unknown or unanticipated genes that impact skeletal variation.

Cryptotanshinone chemosensitivity potentiation by TW-37 in human oral cancer cell lines by targeting STAT3-Mcl-1 signaling.

BACKGROUND: Despite being one of the leading cancer types in the world, the diagnosis of oral cancer and its suitable therapeutic options remain limited. This study aims to investigate the single and chemosensitizing effects of TW-37, a BH3 mimetic in oral cancer, on human oral cancer cell lines. METHODS: We assessed the single and chemosensitizing effects of TW-37 in vitro using trypan blue exclusion assay, Western blotting, DAPI staining, Annexin V-FITC/PI double staining, and quantitative real-time PCR. Mcl-1 overexpression models were established by transforming vector and transient transfection was performed to test for apoptosis. RESULTS: TW-37 enhanced the cytotoxicity of human oral cancer cell lines by inducing caspase-dependent apoptosis, which correlates with the reduction of the myeloid cell leukemia-1 (Mcl-1) expression via transcriptional and post-translational regulation. The ectopic expression of Mcl-1 partially attenuated the apoptosis-inducing capacity of TW-37 in human oral cancer cell lines. Besides, TW-37 decreased the phosphorylation of signal transducer and activator of transcription 3 (STAT3) at Tyr705 and nuclear translocation in human oral cancer cell lines at the early time points. Furthermore, TW-37 potentiated chemosusceptibility of cryptotanshinone in human oral cancer cell lines by suppressing STAT3-Mcl-1 signaling compared with either TW-37 or cryptotanshinone alone, resulting in potent apoptosis. CONCLUSIONS: This study not only unravels the single and chemosensitizing effects of TW-37 for treatment of human oral cancer but also highlights the likelihood of TW-37 as a good therapeutic strategy to enhance the prognosis of patients with oral cancer in the future.

Astaxanthin attenuates the increase in mitochondrial respiration during the activation of hepatic stellate cells.

Upon liver injury, quiescent hepatic stellate cells (qHSCs) transdifferentiate to myofibroblast-like activated HSCs (aHSCs), which are primarily responsible for the accumulation of extracellular matrix proteins during the development of liver fibrosis. Therefore, aHSCs may exhibit different energy metabolism from that of qHSCs to meet their high energy demand. We previously demonstrated that astaxanthin (ASTX), a xanthophyll carotenoid, prevents the activation of HSCs. The objective of this study was to determine if ASTX can exert its antifibrogenic effect by attenuating any changes in energy metabolism during HSC activation. To characterize the energy metabolism of qHSCs and aHSCs, mouse primary HSCs were cultured on uncoated plastic dishes for 7 days for spontaneous activation in the presence or absence of 25 µM ASTX. qHSCs (1 day after isolation) and aHSCs treated with or without ASTX for 7 days were used to determine parameters related to mitochondrial respiration using a Seahorse XFe24 Extracellular Flux analyzer. aHSCs had significantly higher basal respiration, maximal respiration, ATP production, spare respiratory capacity and proton leak than those of qHSCs. However, ASTX prevented most of the changes occurring during HSC activation and improved mitochondrial cristae structure with decreased cristae junction width, lumen width and the area in primary mouse aHSCs. Furthermore, qHSCs isolated from ASTX-fed mice had lower mitochondrial respiration and glycolysis than control qHSCs. Our findings suggest that ASTX may exert its antifibrogenic effect by attenuating the changes in energy metabolism during HSC activation.

BioTarget: A Computational Framework Identifying Cancer Type Specific Transcriptional Targets of Immune Response Pathways.

Transcriptome data can provide information on signaling pathways active in cancers, but new computational tools are needed to more accurately quantify pathway activity and identify tissue-specific pathway features. We developed a computational method called "BioTarget" that incorporates ChIP-seq data into cellular pathway analysis. This tool relates the expression of transcription factor TF target genes (based on ChIP-seq data) with the status of upstream signaling components for an accurate quantification of pathway activity. This analysis also reveals TF targets expressed in specific contexts/tissues. We applied BioTarget to assess the activity of TBX21 and GATA3 pathways in cancers. TBX21 and GATA3 are TF regulators that control the differentiation of T cells into Th1 and Th2 helper cells that mediate cell-based and humoral immune responses, respectively. Since tumor immune responses can impact cancer progression, the significance of our pathway scores should be revealed by effective patient stratification. We found that low Th1/Th2 activity ratios were associated with a significantly poorer survival of stomach and breast cancer patients, whereas an unbalanced Th1/Th2 response was correlated with poorer survival of colon cancer patients. Lung adenocarcinoma and lung squamous cell carcinoma patients had the lowest survival rates when both Th1 and Th2 responses were high. Our method also identified context-specific target genes for TBX21 and GATA3. Applying the BioTarget tool to BCL6, a TF associated with germinal center lymphocytes, we observed that patients with an active BCL6 pathway had significantly improved survival for breast, colon, and stomach cancer. Our findings support the effectiveness of the BioTarget tool for transcriptome analysis and point to interesting associations between some immune-response pathways and cancer progression.

Synthesis of Metal Boride Nanoparticles Using Triple Thermal Plasma Jet System.

Titanium, nickel, and tungsten boride nanoparticles were synthesized in the triple thermal plasma jet system. The coalesced high-enthalpy thermal plasma jet not only generates extensive high temperature regions but also allows the starting materials to penetrate into the center of high temperature regions effectively. The synthesis process of metal boride was investigated according to the nucleation temperature of three metals and boron. In the case of titanium and nickel borides synthesis, metals nucleation temperatures are lower than boron. The crystallinity of synthesized titanium boride nanoparticles was higher than nickel boride nanoparticles, since not only the nucleation temperature of titanium is higher than nickel but also the Gibbs free energy of all titanium boride was lower than whole nickel boride. However, the nucleation temperature of tungsten is higher than boron where nanoparticle synthesis process differed from former synthesis processes. It had influence on the crystal growth time in the high temperature regions where tungsten boride crystal structure was strongly prepared than nickel boride nanoparticles.

Synthesis of Tungsten Carbide Nanomaterials in Triple DC Thermal Plasma Jet System.

The tungsten carbide nanomaterials were synthesized in the triple DC thermal plasma jet system using refractory tungsten, and carbon sources such as multi wall carbon nanotube (MWCNT), amorphous carbon and methane. The starting materials were evaporated in the high temperature region of triple plasma jet, then condensed particles were prepared in nanoscale under 100 nm. The effect of carbon sources was investigated on a view of crystal phase structure and morphology. W2C crystal nanoparticles were mainly synthesized and WC and WC1-x phase nanoparticles were observed additionally with all carbon sources. From MWCNT starting material, tungsten carbide attached MWCNT composite were produced with spherical tungsten carbide nanoparticles. In case of amorphous carbon, spherical and rod-shaped tungsten carbide was synthesized. Only spherical tungsten carbide nanoparticles were synthesized by methane. In addition, it was revealed that the main crystal structure was changed from W2C to WC1-x by increasing W/CH4 composition ratio.

Neuropeptide Y mitigates ER stress-induced neuronal cell death by activating the PI3K-XBP1 pathway.

The unfolded protein response (UPR) is an evolutionarily conserved adaptive reaction that increases cell survival under endoplasmic reticulum (ER) stress conditions. ER stress-associated neuronal cell death pathways play roles in the pathogenesis of neurodegenerative diseases, including Alzheimer's, Parkinson's, and Huntington's disease. Neuropeptide Y (NPY) has an important role in neuroprotection against neurodegenerative diseases. In this study, we investigated whether NPY has a protective role in ER stress-induced neuronal cell death in SK-N-SH human neuroblastoma cells. An ER stress-inducing chemical, tunicamycin, increased the activities of caspase-3 and -4, whereas pretreatment with NPY decreased caspase-3 and -4 activities during the ER stress response. In addition, NPY suppressed the activation of three major ER stress sensors during the tunicamycin-induced ER stress response. NPY-mediated activation of PI3K increased nuclear translocation of XBP1s, which in turn induced expression of Grp78/BiP. Taken together, our data indicated that NPY plays a protective role in ER stress-induced neuronal cell death through activation of the PI3K-XBP1 pathway, and that NPY signaling can serve as therapeutic target for ER stress-mediated neurodegenerative diseases.

Screening Gene Knockout Mice for Variation in Bone Mass: Analysis by µCT and Histomorphometry.

PURPOSE OF REVIEW: The international mouse phenotyping consortium (IMPC) is producing defined gene knockout mouse lines. Here, a phenotyping program is presented that is based on micro-computed tomography (µCT) assessment of distal femur and vertebra. Lines with significant variation undergo a computer-based bone histomorphometric analysis. RECENT FINDINGS: Of the 220 lines examined to date, approximately 15% have a significant variation (high or low) by µCT, most of which are not identified by the IMPC screen. Significant dimorphism between the sexes and bone compartments adds to the complexity of the skeletal findings. The µCT information that is posted at www.bonebase.org can group KOMP lines with similar morphological features. The histological data is presented in a graphic form that associates the cellular features with a specific anatomic group. The web portal presents a bone-centric view appropriate for the skeletal biologist/clinician to organize and understand the large number of genes that can influence skeletal health. Cataloging the relative severity of each variant is the first step towards compiling the dataset necessary to appreciate the full polygenic basis of degenerative bone disease.

A route-based pathway analysis framework integrating mutation information and gene expression data.

We propose a new way of analyzing biological pathways in which the analysis combines both transcriptome data and mutation information and uses the outcome to identify "routes" of aberrant pathways potentially responsible for the etiology of disease. Each pathway route is encoded as a Bayesian Network which is initialized with a sequence of conditional probabilities which are designed to encode directionality of regulatory relationships encoded in the pathways, i.e. activation and inhibition relationships. First, we demonstrate the effectiveness of our model through simulation in which the model was able to easily separate Test samples from Control samples using fictitiously perturbed pathway routes. Second, we apply our model to analyze the Breast Cancer data set, available from TCGA, against many cancer pathways available from KEGG and rank the significance of identified pathways. The outcome is consistent with what have already been reported in the literature. Third, survival analysis has been carried out on the same data set by using pathway routes as features. Overall, we envision that our model of using pathway routes for analysis can further refine the conventional ways of subtyping cancer patients as it can discover additional characteristics specific to individual's tumor.

Oncogenic function and clinical implications of SLC3A2-NRG1 fusion in invasive mucinous adenocarcinoma of the lung.

The neuregulin 1 (NRG1) fusion is a recently identified novel driver oncogene in invasive mucinous adenocarcinoma of the lung (IMA). After identification of a case of SLC3A2-NRG1 in a patient with IMA, we verified this fusion gene in a cohort of 59 patients with IMA. Targeted cancer panel sequencing and RT-PCR identified the possible coexistence of other driver oncogenes. Among 59 IMAs, we found 16 NRG1 fusions (13 SLC3A2-NRG1 and 3 CD74-NRG1). Of 16 patients with NRG1 fusions, concurrent KRAS codon 12 mutations were found in 10 cases. We also found concurrent NRAS Q61L mutation and EML4-ALK fusion in additional two cases with NRG1 fusions. When comparing overall survival (OS) according to the presence of NRG1 fusions showed that patients harboring NRG1 fusions had significantly inferior OS than those without NRG1 fusions (hazard ratio = 0.286; 95% confidence interval, .094 to .865). Ectopic expression of the SLC3A2-NRG1 fusion in lung cancer cells increased cell migration, proliferation and tumor growth in vitro and in xenograft models, suggesting oncogenic function for the fusion protein. We found that the SLC3A2-NRG1 fusion promoted ERBB2-ERBB3 phosphorylation and heteroduplex formation and activated the downstream PI3K/AKT/mTOR pathway through paracrine signaling. These findings suggested that the SLC3A2-NRG1 fusion was a driver in IMA with an important prognostic impact. SLC3A2-NRG1 should be considered a therapeutic target for patients with IMA.

High-Throughput, Multi-Image Cryohistology of Mineralized Tissues.

There is an increasing need for efficient phenotyping and histopathology of a variety of tissues. This phenotyping need is evident with the ambitious projects to disrupt every gene in the mouse genome. The research community needs rapid and inexpensive means to phenotype tissues via histology. Histological analyses of skeletal tissues are often time consuming and semi-quantitative at best, regularly requiring subjective interpretation of slides from trained individuals. Here, we present a cryohistological paradigm for efficient and inexpensive phenotyping of mineralized tissues. First, we present a novel method of tape-stabilized cryosectioning that preserves the morphology of mineralized tissues. These sections are then adhered rigidly to glass slides and imaged repeatedly over several rounds of staining. The resultant images are then aligned either manually or via computer software to yield composite stacks of several layered images. The protocol allows for co-localization of numerous molecular signals to specific cells within a given section. In addition, these fluorescent signals can be quantified objectively via computer software. This protocol overcomes many of the shortcomings associated with histology of mineralized tissues and can serve as a platform for high-throughput, high-content phenotyping of musculoskeletal tissues moving forward.

nc886, a non-coding RNA and suppressor of PKR, exerts an oncogenic function in thyroid cancer.

nc886 is a recently identified cellular non-coding RNA and its depletion leads to acute cell death via PKR (Protein Kinase RNA-activated) activation. nc886 expression is increased in some malignancies, but silenced in others. However, the precise role of nc886/PKR is controversial: is it a tumor suppressor or an oncogene? In this study, we have clarified the role of nc886 in thyroid cancer by sequentially generating PKR knockout (KO) and PKR/nc886 double KO cell lines from Nthy-ori 3-1, a partially transformed thyroid cell line. Compared to the wildtype, PKR KO alone does not exhibit any significant phenotypic changes. However, nc886 KO cells are less proliferative, migratory, and invasive than their parental PKR KO cells. Importantly, the requirement of nc886 in tumor phenotypes is totally independent of PKR. In our microarray data, nc886 KO suppresses some genes whose elevated expression is associated with poor survival confirmed by data from total of 505 thyroid cancer patients in the Caner Genome Atlas project. Also, the nc886 expression level tends to be elevated and in more aggressively metastatic tumor specimens from thyroid cancer patients. In summary, we have discovered nc886's tumor-promoting role in thyroid cancer which has been concealed by the PKR-mediated acute cell death.

High fat diet-induced TGF-ß/Gbb signaling provokes insulin resistance through the tribbles expression.

Hyperglycemia, hyperlipidemia, and insulin resistance are hallmarks of obesity-induced type 2 diabetes, which is often caused by a high-fat diet (HFD). However, the molecular mechanisms underlying HFD-induced insulin resistance have not been elucidated in detail. In this study, we established a Drosophila model to investigate the molecular mechanisms of HFD-induced diabetes. HFD model flies recapitulate mammalian diabetic phenotypes including elevated triglyceride and circulating glucose levels, as well as insulin resistance. Expression of glass bottom boat (gbb), a Drosophila homolog of mammalian transforming growth factor-ß (TGF-ß), is elevated under HFD conditions. Furthermore, overexpression of gbb in the fat body produced obese and insulin-resistant phenotypes similar to those of HFD-fed flies, whereas inhibition of Gbb signaling significantly ameliorated HFD-induced metabolic phenotypes. We also discovered that tribbles, a negative regulator of AKT, is a target gene of Gbb signaling in the fat body. Overexpression of tribbles in flies in the fat body phenocopied the metabolic defects associated with HFD conditions or Gbb overexpression, whereas tribbles knockdown rescued these metabolic phenotypes. These results indicate that HFD-induced TGF-ß/Gbb signaling provokes insulin resistance by increasing tribbles expression.