Expression profiling of cell cycle genes in human pancreatic islets with and without type 2 diabetes

Senescence of human pancreatic beta cells enhances functional maturation through chromatin reorganization and promotes interferon responsiveness

Senescent cells can influence the function of tissues in which they reside, and their propensity for disease. A portion of adult human pancreatic beta cells express the senescence marker p16, yet it is unclear whether they are in a senescent state, and how this affects insulin secretion. We analyzed single-cell transcriptome datasets of adult human beta cells, and found that p16-positive cells express senescence gene signatures, as well as elevated levels of beta-cell maturation genes, consistent with enhanced functionality. Senescent human beta-like cells in culture undergo chromatin reorganization that leads to activation of enhancers regulating functional maturation genes and acquisition of glucose-stimulated insulin secretion capacity. Strikingly, Interferon-stimulated genes are elevated in senescent human beta cells, but genes encoding senescence-associated secretory phenotype (SASP) cytokines are not. Senescent beta cells in culture and in human tissue show elevated levels of cytoplasmic DNA, contributing to their increased interferon responsiveness. Human beta-cell senescence thus involves chromatin-driven upregulation of a functional-maturation program, and increased responsiveness of interferon-stimulated genes, changes that could increase both insulin secretion and immune reactivity.

Identification of HDAC9 and ARRDC4 as potential biomarkers and targets for treatment of type 2 diabetes

We aimed to identify the key potential insulin resistance (IR)-related genes and investigate their correlation with immune cell infiltration in type 2 diabetes (T2D). The GSE78721 dataset (68 diabetic patients and 62 controls) was downloaded from the Gene Expression Omnibus database and utilized for single-sample gene set enrichment analysis. IR-related genes were obtained from the Comparative Toxicology Genetics Database, and the final IR-differentially expressed genes (DEGs) were screened by intersecting with the DEGs obtained from the GSE78721 datasets. Functional enrichment analysis was performed, and the networks of the target gene with microRNA, transcription factor, and drug were constructed. Hub genes were identified based on a protein-protein interaction network. Least absolute shrinkage and selection operator regression and Random Forest and Boruta analysis were combined to screen diagnostic biomarkers in T2D, which were validated using the GSE76894 (19 diabetic patients and 84 controls) and GSE9006 (12 diabetic patients and 24 controls) datasets. Quantitative real-time polymerase chain reaction was performed to validate the biomarker expression in IR mice and control mice. In addition, infiltration of immune cells in T2D and their correlation with the identified markers were computed using CIBERSORT. We identified differential immune gene set regulatory T-cells in the GSE78721 dataset, and T2D samples were assigned into three clusters based on immune infiltration. A total of 2094 IR-DEGs were primarily enriched in response to endoplasmic reticulum stress. Importantly, HDAC9 and ARRDC4 were identified as markers of T2D and associated with different levels of immune cell infiltration. HDAC9 mRNA level were higher in the IR mice than in control mice, while ARRDC4 showed the opposite trend. In summary, we discovered potential vital biomarkers that contribute to immune cell infiltration associated with IR, which offers a new sight of immunotherapy for T2D.

Validating Fractalkine receptor as a target and identifying candidates for drug discovery against type 2 diabetes

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases employing abnormal levels of insulin. Enhancing the insulin production is greatly aided by the regulatory mechanisms of the Fractalkine receptor (CX3CR1) system in islet β-cell function. However, elements including a high-fat diet, obesity, and ageing negatively impact the expression of CX3CR1 in islets. CX3CL1/CX3CR1 receptor-ligand complex is now recognized as a novel therapeutic target. It suggests that T2DM-related β-cell dysfunction may result from lower amount of these proteins. We analyzed the differential expression of CX3CR1 gene samples taken from persons with T2DM using data obtained from the Gene Expression Omnibus database. Homology modeling enabled us to generate the three-dimensional structure of CX3CR1 and a possible binding pocket. The optimized CX3CR1 structure was subjected to rigorous screening against a massive library of 693 million drug-like molecules from the ZINC15 database. This screening process led to the identification of three compounds with strong binding affinity at the identified binding pocket of CX3CR1. To further evaluate the potential of these compounds, molecular dynamics simulations were conducted over a 50 ns time scale to assess the stability of the protein-ligand complexes. These simulations revealed that ZINC000032506419 emerged as the most promising drug-like compound among the three potent molecules. The discovery of ZINC000032506419 holds exciting promise as a potential therapeutic agent for T2D and other related metabolic disorders. These findings pave the way for the development of effective medications to address the complexities of T2DM and its associated metabolic diseases.

Circulating MiRNAs Are Associated With Low-grade Systemic Inflammation and Leptin Levels in Older Adults

Inflammaging refers to the low-grade systemic inflammation that occurs with aging present in chronic non-communicable diseases. MicroRNAs (miRNAs) are potential biomarkers for these diseases in older adults. This study aimed to assess the expression of 21 circulating miRNAs and their associations with inflammatory biomarkers in older adults. This cross-sectional study was performed with 200 individuals participating in ISA-Nutrition. The systemic low-grade inflammation score (SIS) was calculated from the plasma concentration of 10 inflammatory biomarkers. Circulating miRNA expression was assessed using the Fluidigm method. Wilcoxon-Mann-Whitney test was employed to determine differences in SIS among groups distributed according to sex and presence of MetS. Spearman's correlation was used to estimate correlations among SIS, leptin levels, miRNA expression, and variables of interest. Analyses were performed using software R version 4.2.3, with a significance level of 0.05. The final sample consisted of 193 individuals with a mean age of 69.1 (SE = 0.5) years, being 64.7% individuals with metabolic syndrome (MetS). Positive correlations were observed between leptin concentration and metabolic risk factors, and leptin concentration was higher in individuals with MetS compared to those without MetS. The expression of 15 circulating miRNAs was negatively correlated with leptin concentration. GLMs showed negative associations between miRNAs (miR-15a, miR-16, miR-223, miR-363, miR-532), leptin, and/or SIS values; and only miR-21 showed positive association with SIS values. The results suggest the presence of peripheral leptin resistance associated with low-grade inflammation and plasma expression of miRNAs in older adults. These findings suggest the potential role of miRNAs as biomarkers for cardiometabolic risk.

A data integration approach unveils a transcriptional signature of type 2 diabetes progression in rat and human islets

Pancreatic islet failure is a key characteristic of type 2 diabetes besides insulin resistance. To get molecular insights into the pathology of islets in type 2 diabetes, we developed a computational approach to integrating expression profiles of Goto-Kakizaki and Wistar rat islets from a designed experiment with those of the human islets from an observational study. A principal gene-eigenvector in the expression profiles characterized by up-regulated angiogenesis and down-regulated oxidative phosphorylation was identified conserved across the two species. In the case of Goto-Kakizaki versus Wistar islets, such alteration in gene expression can be verified directly by the treatment-control tests over time, and corresponds to the alteration of α/β-cell distribution obtained by quantifying the islet micrographs. Furthermore, the correspondence between the dual sample- and gene-eigenvectors unveils more delicate structures. In the case of rats, the up- and down-trend of insulin mRNA levels before and after week 8 correspond respectively to the top two principal eigenvectors. In the case of human, the top two principal eigenvectors correspond respectively to the late and early stages of diabetes. According to the aggregated expression signature, a large portion of genes involved in the hypoxia-inducible factor signaling pathway, which activates transcription of angiogenesis, were significantly up-regulated. Furthermore, top-ranked anti-angiogenic genes THBS1 and PEDF indicate the existence of a counteractive mechanism that is in line with thickened and fragmented capillaries found in the deteriorated islets. Overall, the integrative analysis unravels the principal transcriptional alterations underlying the islet deterioration of morphology and insulin secretion along type 2 diabetes progression.

Search for polymorphic variants of candidate genes contributing to individual radiosensitivity

Background. Cytogenetic damage (СD) in lymphocytes induced by low doses (up to 0.1 Sv) of ionizing radiation (IR) is the main cytogenetic sign of individual radiosensitivity of the human body. In addition to DNA repair and cell death, which affect the formation of СD and its elimination, IR effects on the cell can be manifested through changes in proliferation of cells with unrepaired DNA damage. The system of cyclins and cyclin-dependent kinases (CDK), which provide coordination of mitotic events during passage of a cell through the cell cycle, plays a crucial role in regulation of cell proliferation.

Aim. To evaluate the relationship of single-nucleotide polymorphisms (SNPs) of cell cycle genes with an increased frequency of СD in workers of a nuclear power plant affected by chronic occupational radiation exposure in the dose range of 100–500 mSv.

Materials and methods. The object of the study was blood of 55 conditionally healthy workers of Siberian Chemical Plant (SCP) who were affected by chronic occupational radiation exposure (gamma radiation) in the dose range of 100–500 mSv. A standard cytogenetic analysis of blood lymphocytes was performed for all examined individuals. Genomic DNA was isolated from the blood of the workers using the QIAamp DNA Blood Mini Kit (QIAGEN, Germany). DNA was genotyped using 257 SNPs of cyclin genes and neighboring intergenic regions using DNA microarrays from the high-density CytoScan HD Array (Affymetrix, USA).

Results. Taking into account the Bonferroni correction, only statistically significant associations of SNPs with the frequency of dicentric chromosomes were found; all other types of chromosomal aberrations did not show statistical significance. The rs803054 CCNI2 was associated with an increased frequency of dicentric chromosomes arising under the influence of chronic occupational radiation exposure.

Conclusion. The discovered SNP (rs803054), whose recessive genotype is associated with an increased frequency of dicentric chromosomes in workers of SCP exposed to radiation at doses of 100–500 mSv over a long time, can be considered as a potential marker of individual radiosensitivity. To confirm the identified associations, further validation studies are needed on an expanded sample of people affected by chronic occupational radiation exposure.

CDK8/19 inhibition plays an important role in pancreatic β-cell induction from human iPSCs

BACKGROUND

Transplantation of differentiated cells from human-induced pluripotent stem cells (hiPSCs) holds great promise for clinical treatments. Eliminating the risk factor of malignant cell transformation is essential for ensuring the safety of such cells. This study was aimed at assessing and mitigating mutagenicity that may arise during the cell culture process in the protocol of pancreatic islet cell (iPIC) differentiation from hiPSCs.

METHODS

We evaluated the mutagenicity of differentiation factors used for hiPSC-derived pancreatic islet-like cells (iPICs). We employed Ames mutagenicity assay, flow cytometry analysis, immunostaining, time-resolved fluorescence resonance energy transfer-based (TR-FRET) cell-free dose-response assays, single-cell RNA-sequencing and in vivo efficacy study.

RESULTS

We observed a mutagenic effect of activin receptor-like kinase 5 inhibitor II (ALK5iII). ALK5iII is a widely used β-cell inducer but no other tested ALK5 inhibitors induced β-cells. We obtained kinase inhibition profiles and found that only ALK5iII inhibited cyclin-dependent kinases 8 and 19 (CDK8/19) among all ALK5 inhibitors tested. Consistently, CDK8/19 inhibitors efficiently induced β-cells in the absence of ALK5iII. A combination treatment with non-mutagenic ALK5 inhibitor SB431542 and CDK8/19 inhibitor senexin B afforded generation of iPICs with in vitro cellular composition and in vivo efficacy comparable to those observed with ALK5iII.

CONCLUSION

Our findings suggest a new risk mitigation approach for cell therapy and advance our understanding of the β-cell differentiation mechanism.

T3 and glucose increase expression of phosphoenolpyruvate carboxykinase (PCK1) leading to increased β-cell proliferation

OBJECTIVES

Thyroid hormone (T3) and high glucose concentrations are critical components of β-cell maturation and function. In the present study, we asked whether T3 and glucose signaling pathways coordinately regulate transcription of genes important for β-cell function and proliferation.

METHODS

RNA-seq analysis was performed on cadaveric human islets from five different donors in response to low and high glucose concentrations and in the presence or absence of T3. Gene expression was also studies in sorted human β-cells, mouse islets and Ins-1 cells by RT-qPCR. Silencing of the thyroid hormone receptors (THR) was conducted using lentiviruses. Proliferation was assessed by ki67 immunostaining in primary human/mouse islets. Chromatin immunoprecipitation and proximity ligation assay were preformed to validate interactions of ChREBP and THR.

RESULTS

We found glucose-mediated expression of carbohydrate response element binding protein alpha and beta (ChREBPα and ChREBPβ) mRNAs and their target genes are highly dependent on T3 concentrations in rodent and human β-cells. In β-cells, T3 and glucose coordinately regulate the expression of ChREBPβ and PCK1 (phosphoenolpyruvate carboxykinase-1) among other important genes for β-cell maturation. Additionally, we show the thyroid hormone receptor (THR) and ChREBP interact, and their relative response elements are located near to each other on mutually responsive genes. In FACS-sorted adult human β-cells, we found that high concentrations of glucose and T3 induced the expression of PCK1. Next, we show that overexpression of Pck1 together with dimethyl malate (DMM), a substrate precursor, significantly increased β-cell proliferation in human islets. Finally, using a Cre-Lox approach, we demonstrated that ChREBPβ contributes to Pck1-dependent β-cell proliferation in mouse β-cells.

CONCLUSIONS

We conclude that T3 and glucose act together to regulate ChREBPβ, leading to increased expression and activity of Pck1, and ultimately increased β-cell proliferation.

A suggested shared aetiology of dementia - a colocalization study

Identification of shared causal genes between dementia and its related clinical outcomes can help understand shared aetiology and multimorbidity surrounding dementia. We performed the HyPrColoc colocalization analysis to detect possible shared causal genes between dementia or Alzheimer's disease (AD) and 5 selected traits: stroke, diabetes, atherosclerosis, cholesterol level, and alcohol consumption within 601 dementia or AD associated genetic regions using summary results of the UK Biobank genome-wide association studies. Functional analysis was performed on the candidate causal genes to explore potential biological pathways. Rs150562240 in the LPIN3 gene was identified as a candidate shared causal variant across dementia, AD and atherosclerosis. Evidence for pairwise colocalization between dementia and stroke, dementia (or AD) and atherosclerosis, and dementia (or AD) and diabetes was found in 2, 6 and 2 genetic regions respectively. Colocalization signals between diabetes and the other 3 non-dementia/AD traits were detected in 5 regions. The colocalization evidence shown in our study suggested shared aetiology between dementia and related diseases such as stroke, atherosclerosis, and diabetes.

Retinal Transcriptome and Cellular Landscape in Relation to the Progression of Diabetic Retinopathy

Purpose

Previous studies that identify putative genes associated with diabetic retinopathy are only focusing on specific clinical stages, thus resulting genes are not necessarily reflective of disease progression.

This study identified genes associated with the severity level of diabetic retinopathy using the likelihood-ratio test (LRT) and ordinal logistic regression (OLR) model, as well as to profile immune and retinal cell landscape in progressive diabetic retinopathy using a machine learning deconvolution approach.

Methods

This study used a published transcriptomic dataset (GSE160306) from macular regions of donors with different degrees of diabetic retinopathy (10 healthy controls, 10 cases of diabetes, 9 cases of nonproliferative diabetic retinopathy, and 10 cases of proliferative diabetic retinopathy or combined with diabetic macular edema). LRT and OLR models were applied to identify severity-associated genes. In addition, CIBERSORTx was used to estimate proportional changes of immune and retinal cells in progressive diabetic retinopathy.

Results

By controlling for gender and age using LRT and OLR, 50 genes were identified to be significantly increased in expression with the severity of diabetic retinopathy. Functional enrichment analyses suggested these severity-associated genes are related to inflammation and immune responses. CCND1 and FCGR2B are further identified as key regulators to interact with many other severity-associated genes and are crucial to inflammation. Deconvolution analyses demonstrated that the proportions of memory B cells, M2 macrophages, and Müller glia were significantly increased with the progression of diabetic retinopathy.

Conclusions

These findings demonstrate that deep analyses of transcriptomic data can advance our understanding of progressive ocular diseases, such as diabetic retinopathy, by applying LRT and OLR models as well as bulk gene expression deconvolution.

Overview of Transcriptomic Research on Type 2 Diabetes: Challenges and Perspectives

Type 2 diabetes (T2D) is a common chronic disease whose etiology is known to have a strong genetic component. Standard genetic approaches, although allowing for the detection of a number of gene variants associated with the disease as well as differentially expressed genes, cannot fully explain the hereditary factor in T2D. The explosive growth in the genomic sequencing technologies over the last decades provided an exceptional impetus for transcriptomic studies and new approaches to gene expression measurement, such as RNA-sequencing (RNA-seq) and single-cell technologies. The transcriptomic analysis has the potential to find new biomarkers to identify risk groups for developing T2D and its microvascular and macrovascular complications, which will significantly affect the strategies for early diagnosis, treatment, and preventing the development of complications. In this article, we focused on transcriptomic studies conducted using expression arrays, RNA-seq, and single-cell sequencing to highlight recent findings related to T2D and challenges associated with transcriptome experiments.

Establishment and Verification of a Gene Signature for Diagnosing Type 2 Diabetics by WGCNA, LASSO Analysis, and In Vitro Experiments

Objective

The incidence and prevalence of type 2 diabetes are increasing with age. Nevertheless, there is lack of sensitive diagnostic tools and effective therapeutic regimens. We aimed to establish and verify a practical and valid diagnostic tool for this disease.

Methods

WGCNA was presented on the expression profiling of type 2 diabetic and normal islets in combined GSE25724 and GSE38642 datasets. By LASSO Cox regression analyses, a gene signature was constructed based on the genes in diabetes-related modules. ROC curves were plotted for assessing the diagnostic efficacy. Correlations between the genes and immune cell infiltration and pathways were analyzed. BST2 and BTBD1 expression was verified in glucotoxicity-induced and normal islet β cells. The influence of BST2 on β cell dysfunction was investigated under si-BST2 transfection.

Results

Totally, 14 coexpression modules were constructed, and red and cyan modules displayed the correlations to diabetes. The LASSO gene signature (BST2, BTBD1, IFIT1, IFIT3, and RTP4) was developed. The AUCs in the combined datasets and GSE20966 dataset were separately 0.914 and 0.910, confirming the excellent performance in diagnosing type 2 diabetes. Each gene in the model was distinctly correlated to immune cell infiltration and key signaling pathways (TGF-β and P53, etc.). The abnormal expression of BST2 and BTBD1 was confirmed in glucotoxicity-induced β cells. BST2 knockdown ameliorated β cell dysfunction and altered the activation of TGF-β and P53 pathways.

Conclusion

Our findings propose a gene signature with high efficacy to diagnose type 2 diabetes, which could assist and improve early diagnosis and therapy.

Gene-environment interaction identification via penalized robust divergence

In high-throughput cancer studies, gene-environment interactions associated with outcomes have important implications. Some commonly adopted identification methods do not respect the "main effect, interaction" hierarchical structure. In addition, they can be challenged by data contamination and/or long-tailed distributions, which are not uncommon. In this article, robust methods based on γ$\gamma$ -divergence and density power divergence are proposed to accommodate contaminated data/long-tailed distributions. A hierarchical sparse group penalty is adopted for regularized estimation and selection and can identify important gene-environment interactions and respect the "main effect, interaction" hierarchical structure. The proposed methods are implemented using an effective group coordinate descent algorithm. Simulation shows that when contamination occurs, the proposed methods can significantly outperform the existing alternatives with more accurate identification. The proposed approach is applied to the analysis of The Cancer Genome Atlas (TCGA) triple-negative breast cancer data and Gene Environment Association Studies (GENEVA) Type 2 Diabetes data.

Mutations in key driver genes of pancreatic cancer: molecularly targeted therapies and other clinical implications

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, with a minimal difference between its incidence rate and mortality rate. Advances in oncology over the past several decades have dramatically improved the overall survival of patients with multiple cancers due to the implementation of new techniques in early diagnosis, therapeutic drugs, and personalized therapy. However, pancreatic cancers remain recalcitrant, with a 5-year relative survival rate of <9%. The lack of measures for early diagnosis, strong resistance to chemotherapy, ineffective adjuvant chemotherapy and the unavailability of molecularly targeted therapy are responsible for the high mortality rate of this notorious disease. Genetically, PDAC progresses as a complex result of the activation of oncogenes and inactivation of tumor suppressors. Although next-generation sequencing has identified numerous new genetic alterations, their clinical implications remain unknown. Classically, oncogenic mutations in genes such as KRAS and loss-of-function mutations in tumor suppressors, such as TP53, CDNK2A, DPC4/SMAD4, and BRCA2, are frequently observed in PDAC. Currently, research on these key driver genes is still the main focus. Therefore, studies assessing the functions of these genes and their potential clinical implications are of paramount importance. In this review, we summarize the biological function of key driver genes and pharmaceutical targets in PDAC. In addition, we conclude the results of molecularly targeted therapies in clinical trials and discuss how to utilize these genetic alterations in further clinical practice.

MicroRNA‑532‑5p regulates oxidative stress and insulin secretion damage in high glucose‑induced pancreatic β cells by downregulating the expression levels of CCND1

Diabetes mellitus is a metabolic disorder caused by insufficient insulin secretion. The expression of microRNA (miR)-532-5P is downregulated in diabetes, but its specific role in diabetes has not yet been elucidated. The present study aimed to investigate the specific mechanism underlying the effects of miR-532-5p on diabetes. Cell viability was determined using an MTT assay. The expression levels of miR-532-5P, cyclin D1 (CCND1), Insulin1 and Insulin2 were detected using reverse transcription-quantitative PCR. The expression of miR-532-5p and CCND1 were overexpressed in cells by cell transfection. ELISA was used to detect insulin secretion. 2′,7′-dichlorodihydrofluorescein diacetate was used to quantify reactive oxygen species levels in cells. Apoptosis was detected using a TUNEL assay. Western blotting was performed to detect the expression of apoptosis-related proteins, CCND1 and p53. A dual-luciferase reporter assay was conducted, and verified the targeted binding of miR-532-5p and CCND1. The expression of miR-532-5p was downregulated in high glucose (HG)-induced MIN6 cells. Overexpression of miR-532-5p could improve the HG-induced decline in insulin secretion and inhibit HG-induced oxidative stress and apoptosis in cells. miR-532-5p can target and regulate the expression of CCND1. Overexpression of miR-532-5p downregulated HG-induced cell insulin secretion, oxidative stress and apoptosis by downregulating CCND1, which is involved in regulating the expression of p53. To conclude, miR-532-5p regulated oxidative stress and insulin secretion damage in HG-induced pancreatic β cells by downregulating the expression of CCND1, which is involved in the upregulation of the expression of p53.

Cisplatin's potential for type 2 diabetes repositioning by inhibiting CDKN1A, FAS, and SESN1

Cisplatin is a DNA-damaging chemotherapeutic agent used for treating cancer. Based on cDNA dataset analysis, we investigated how cisplatin modified gene expression and observed cisplatin-induced dysregulation and system-level variations relating to insulin resistance and type 2 diabetes mellitus (T2DM). T2DM is a multifactorial disease affecting 462 million people in the world, and drug-induced T2DM is a serious issue. To understand this etiology, we designed an integrative, system-level study to identify associations between cisplatin-induced differentially expressed genes (DEGs) and T2DM. From a list of differential expressed genes, cisplatin downregulated the cyclin-dependent kinase inhibitor 1 (CDKN1A), tumor necrosis factor (FAS), and sestrin-1 (SESN1) genes responsible for modifying signaling pathways, including the p53, JAK-STAT, FOXO, MAPK, mTOR, P13-AKT, Toll-like receptor (TLR), adipocytokine, and insulin signaling pathways. These enriched pathways were expressively associated with the disease. We observed significant gene signatures, including SMAD3, IRS, PDK1, PRKAA1, AKT, SOS, RAS, GRB2, MEK1/2, and ERK, interacting with source genes. This study revealed the value of system genetics for identifying the cisplatin-induced genetic variants responsible for the progression of T2DM. Also, by cross-validating gene expression data for T2DM islets, we found that downregulating IRS and PRK families is critical in insulin and T2DM signaling pathways. Cisplatin, by inhibiting CDKN1A, FAS, and SESN1, promotes IRS and PRK activity in a similar way to rosiglitazone (a popular drug used for T2DM treatment). Our integrative, network-based approach can help in understanding the drug-induced pathophysiological mechanisms of diabetes.

Redox Homeostasis in Pancreatic β-Cells: From Development to Failure

Redox status is a key determinant in the fate of β-cell. These cells are not primarily detoxifying and thus do not possess extensive antioxidant defense machinery. However, they show a wide range of redox regulating proteins, such as peroxiredoxins, thioredoxins or thioredoxin reductases, etc., being functionally compartmentalized within the cells. They keep fragile redox homeostasis and serve as messengers and amplifiers of redox signaling. β-cells require proper redox signaling already in cell ontogenesis during the development of mature β-cells from their progenitors. We bring details about redox-regulated signaling pathways and transcription factors being essential for proper differentiation and maturation of functional β-cells and their proliferation and insulin expression/maturation. We briefly highlight the targets of redox signaling in the insulin secretory pathway and focus more on possible targets of extracellular redox signaling through secreted thioredoxin1 and thioredoxin reductase1. Tuned redox homeostasis can switch upon chronic pathological insults towards the dysfunction of β-cells and to glucose intolerance. These are characteristics of type 2 diabetes, which is often linked to chronic nutritional overload being nowadays a pandemic feature of lifestyle. Overcharged β-cell metabolism causes pressure on proteostasis in the endoplasmic reticulum, mainly due to increased demand on insulin synthesis, which establishes unfolded protein response and insulin misfolding along with excessive hydrogen peroxide production. This together with redox dysbalance in cytoplasm and mitochondria due to enhanced nutritional pressure impact β-cell redox homeostasis and establish prooxidative metabolism. This can further affect β-cell communication in pancreatic islets through gap junctions. In parallel, peripheral tissues losing insulin sensitivity and overall impairment of glucose tolerance and gut microbiota establish local proinflammatory signaling and later systemic metainflammation, i.e., low chronic inflammation prooxidative properties, which target β-cells leading to their dedifferentiation, dysfunction and eventually cell death.

CCNI2 plays a promoting role in the progression of colorectal cancer

Colorectal cancer (CRC) is one of the most common malignancies and most of the patients diagnosed with advanced CRC have unsatisfactory treatment effect and poor prognosis. The purpose of this study was to investigate the effect of CCNI2 on the development of CRC. In this sutdy, immunohistochemical staining was used to detect CCNI2 expression levels in clinical samples, meanwhile, the Kaplan‐Meier survival analysis was conducted. Celigo cell counting assay was used for screening shCCNI2s. QPCR and WB were performed to verify knockdown efficiency of CCNI2. Cell proliferation, colony formation, cell cycle, apoptosis, and mechanism investigation of CCNI2 knockdown were investigated by MTT assay, colony formation assay, fluorescence‐activated cell sorting, and human apoptosis antibody array, respectively. Otherwise, the mouse model of CCNI2 knockdown was also constructed. The results of immunohistochemical staining and qPCR indicated that CCNI2 had a high expression level in the CRC tissues and cell lines. Kaplan‐Meier survival analysis manifested that the high expression of CCNI2 suggested poor prognosis. The expression of CCNI2 was significantly reduced by CCNI2‐siRNAs, and the downregulated expression level of CCNI2 inhibited CRC cell proliferation and colony formation, arrested cell cycle in G2 phase, as well as promoted cell apoptosis. The various indexes of solid tumor in mice models indicated that CCNI2 knockdown could suppress the growth of CRC tumor. Based on the comprehensive analysis of the above results, CCNI2 was contributed to the progression of CRC and could serve as a prognostic marker for CRC.

Integrative transcriptomic analysis of pancreatic islets from patients with prediabetes/type 2 diabetes

AIM

To identify new transcriptomic alterations in pancreatic islets associated with metabolic dysfunctions in people with prediabetes (PD)/type 2 diabetes (T2D).

MATERIALS AND METHODS

We collected information from public data repositories T2D related microarray datasets from pancreatic islets. We identified Differential Expressed Genes (DEGs) in non-diabetic (ND) vs people with T2D in each study. To identify relevant DEGs in T2D, we selected those that varied consistently in the different studies for further meta-analysis and functional enrichment analysis. DEGs were also evaluated at the PD stage.

RESULTS

A total of seven microarray datasets were collected and analysed to find the DEGs in each study and meta-analysis was performed with 245 ND and 96 T2D cases. We identified 55 transcriptional alterations potentially associated with specific metabolic dysfunctions in T2D. Meta-analysis showed that 87% of transcripts identified as DEGs (48 out of 55) were confirmed as having statistically significant up- or down-modulation in T2D compared to ND. Notably, nine of these DEGs have not been previously reported as dysregulated in pancreatic islets from people with T2D. Consistently, the most significantly enriched pathways were related to the metabolism and/or development/maintenance of β-cells. Eighteen of the 48 selected DEGs (38%) showed an altered expression in islets from people with PD.

CONCLUSIONS

These results provide new evidence to interpret the pathogenesis of T2D and the transition from PD to T2D. Further studies are necessary to validate its potential use for the development/implementation of efficient new strategies for the prevention, diagnosis/prognosis and treatment of T2D.

Angel or Devil ? - CDK8 as the new drug target

Cyclin-dependent kinase 8 (CDK8) plays an momentous role in transcription regulation by forming kinase module or transcription factor phosphorylation. A large number of evidences have identified CDK8 as an important factor in cancer occurrence and development. In addition, CDK8 also participates in the regulation of cancer cell stress response to radiotherapy and chemotherapy, assists tumor cell invasion, metastasis, and drug resistance. Therefore, CDK8 is regarded as a promising target for cancer therapy. Most studies in recent years supported the role of CDK8 as a carcinogen, however, under certain conditions, CDK8 exists as a tumor suppressor. The functional diversity of CDK8 and its exceptional role in different types of cancer have aroused great interest from scientists but even more controversy during the discovery of CDK8 inhibitors. In addition, CDK8 appears to be an effective target for inflammation diseases and immune system disorders. Therefore, we summarized the research results of CDK8, involving physiological/pathogenic mechanisms and the development status of compounds targeting CDK8, provide a reference for the feasibility evaluation of CDK8 as a therapeutic target, and guidance for researchers who are involved in this field for the first time.

A set of miRNAs predicts T2DM remission in patients with coronary heart disease: from the CORDIOPREV study

MicroRNAs (miRNAs) regulate the expression of genes associated with the development of diseases, including type 2 diabetes mellitus (T2DM). However, the use of miRNAs to predict T2DM remission has been poorly studied. Therefore, we aimed to investigate whether circulating miRNAs could be used to predict the probability of T2DM remission in patients with coronary heart disease. We included the newly diagnosed T2DM (n = 190) of the 1,002 patients from the CORDIOPREV study. Seventy-three patients reverted from T2DM after 5 years of dietary intervention with a low-fat or Mediterranean diet. Plasma levels of 56 miRNAs were measured by OpenArray. Generalized linear model, receiver operating characteristic (ROC), Cox regression, and pathway analyses were performed. ROC analysis based on clinical variables showed an area under the curve (AUC) of 0.66. After a linear regression analysis, seven miRNAs were identified as the most important variables in the group’s differentiation. The addition of these miRNAs to clinical variables showed an AUC of 0.79. Cox regression analysis using a T2DM remission score including miRNAs showed that high-score patients have a higher probability of T2DM remission (hazard ratio [HR]_{low versus high}, 4.44). Finally, 26 genes involved in 10 pathways were related to the miRNAs. We have identified miRNAs (hsa-let-7b, hsa-miR-101, hsa-miR-130b-3p, hsa-miR-27a, hsa-miR-30a-5p, hsa-miR-375, and hsa-miR-486) that contribute to the prediction of T2DM remission in patients with coronary heart disease.

CDK8 Regulates Insulin Secretion and Mediates Postnatal and Stress-Induced Expression of Neuropeptides in Pancreatic β Cells

Cyclin-dependent kinases (CDKs) contribute to vital cellular processes including cell cycle regulation. Loss of CDKs is associated with impaired insulin secretion and β cell survival; however, the function of CDK8 in β cells remains elusive. Here, we report that genetic ablation of Cdk8 improves glucose tolerance by increasing insulin secretion. We identify OSBPL3 as a CDK8-dependent phosphoprotein, which acts as a negative regulator of insulin secretion in response to glucose. We also show that embryonic gene silencing of neuropeptide Y in β cells is compromised in Cdk8-null mice, leading to continued expression into adulthood. Cdk8 ablation in β cells aggravates apoptosis and induces de novo expression of neuropeptides upon oxidative stress. Moreover, pancreatic islets exposed to stress display augmented apoptosis in the presence of these same neuropeptides. Our results reveal critical roles for CDK8 in β cell function and survival during metabolic stress that are in part mediated through de novo expression of neuropeptides.

Mitochondrial Proton Leak Regulated by Cyclophilin D Elevates Insulin Secretion in Islets at Nonstimulatory Glucose Levels

Fasting hyperinsulinemia precedes the development of type 2 diabetes. However, it is unclear whether fasting insulin hypersecretion is a primary driver of insulin resistance or a consequence of the progressive increase in fasting glycemia induced by insulin resistance in the prediabetic state. Herein, we have discovered a mechanism that specifically regulates non-glucose-stimulated insulin secretion (NGSIS) in pancreatic islets that is activated by nonesterified free fatty acids, the major fuel used by β-cells during fasting. We show that the mitochondrial permeability transition pore regulator cyclophilin D (CypD) promotes NGSIS, but not glucose-stimulated insulin secretion, by increasing mitochondrial proton leak. Islets from prediabetic obese mice show significantly higher CypD-dependent proton leak and NGSIS compared with lean mice. Proton leak-mediated NGSIS is conserved in human islets and is stimulated by exposure to nonesterified free fatty acids at concentrations observed in obese subjects. Mechanistically, proton leak activates islet NGSIS independently of mitochondrial ATP synthesis but ultimately requires closure of the KATP channel. In summary, we have described a novel nonesterified free fatty acid-stimulated pathway that selectively drives pancreatic islet NGSIS, which may be therapeutically exploited as an alternative way to halt fasting hyperinsulinemia and the progression of type 2 diabetes.

Identification of Hub Genes in Type 2 Diabetes Mellitus Using Bioinformatics Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases in the world with complicated pathogenesis. This study aimed to identify differentially expressed genes (DEGs) and molecular pathways in T2DM using bioinformatics analysis.

MATERIALS AND METHODS

To explore potential therapeutic targets for T2DM, we analyzed three microarray datasets (GSE50397, GSE38642, and GSE44035) acquired from the Gene Expression Omnibus (GEO) database. DEGs between T2DM islet and normal islet were picked out by the GEO2R tool and Venn diagram software. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) to identify the pathways and functional annotation of DEGs. Then, protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes/Proteins (STRING).

RESULTS

In total, we identified 36 DEGs in the three datasets, including 32 up-regulated genes and four down-regulated genes. The improved functions and pathways of the DEGs enriched in cytokine-cytokine receptor interaction, pathways in cancer, PI3K-Akt signaling pathway, and Rheumatoid arthritis. Among them, ten hub genes with a high degree of connectivity were selected. Furthermore, via the re-analysis of DAVID, four genes (IL6, MMP3, MMP1, and IL11) were significantly enriched in the Rheumatoid arthritis pathway.

CONCLUSION

Our study, based on the GEO database, identified four significant up-regulated DEGs and provided novel targets for diagnosis and treatment of T2DM.

Elucidation of the Mechanisms and Molecular Targets of Sanhuang Xiexin Decoction for Type 2 Diabetes Mellitus Based on Network Pharmacology

Sanhuang Xiexin Decoction (SXD) is commonly used to treat type 2 diabetes mellitus (T2DM) in clinical practice of traditional Chinese medicine (TCM). In order to elucidate the specific analysis mechanisms of SXD for T2DM, the method of network pharmacology was applied to this article. First, the effective ingredients of SXD were obtained and their targets were identified based on the TCMSP database. The T2DM-related targets screened from the GEO database were also collected by comparing the differential expressed genes between T2DM patients and healthy individuals. Then, the common targets in SXD-treated T2DM were obtained by intersecting the putative targets of SXD and the differential expressed genes of T2DM. And the protein-protein interaction (PPI) network was established using the above common targets to screen key genes through protein interactions. Meanwhile, these common targets were used for GO and KEGG analyses to further elucidate how they exert antidiabetic effects. Finally, a gene pathway network was established to capture the core one in common targets enriched in the major pathways to further illustrate the role of specific genes. Based on the data obtained, a total of 67 active compounds and 906 targets of SXD were identified. Four thousand one hundred and seventy-six differentially expressed genes with a P value < 0.005 and ∣log2(fold change) | >0.5 were determined between T2DM patients and control groups. After further screening, thirty-seven common targets related to T2DM in SXD were finally identified. Through protein interactions, the top 5 genes (YWHAZ, HNRNPA1, HSPA8, HSP90AA1, and HSPA5) were identified. It was found that the functional annotations of target genes were associated with oxygen levels, protein kinase regulator, mitochondria, and so on. The top 20 pathways including the PI3K-Akt signaling pathway, cancers, HIF-1 signaling pathway, and JAK-STAT signaling pathway were significantly enriched. CDKN1A was shown to be the core gene in the gene-pathway network, and other several genes such as CCND1, ERBB2, RAF1, EGF, and VEGFA were the key genes for SXD against T2DM. Based on the network pharmacology approach, we identified key genes and pathways related to the prognosis and pathogenesis of T2DM and also provided a feasible method for further studying the chemical basis and pharmacology of SXD.

NIH Initiative to Improve Understanding of the Pancreas, Islet, and Autoimmunity in Type 1 Diabetes: The Human Pancreas Analysis Program (HPAP)

Type 1 diabetes risk can reliably be predicted by markers of autoimmunity, but approaches to prevent or modify the underlying disease process are needed. We posit this void fundamentally results from a limited understanding of immune-islet cell interactions within the pancreas and relevant immune organs, contributions of β-cells to their own demise, and epigenetic predispositions affecting both immune and islet cells. Because biopsy of the human pancreas and pancreatic lymph nodes carries risk and the pancreas begins to autodigest soon after death, detailed cellular and molecular phenotyping of the human type 1 diabetes pancreas is lacking, limiting our understanding of the mechanisms of β-cell loss. To address these challenges, the National Institutes of Health/National Institute of Diabetes and Digestive and Kidney Diseases established the Human Pancreas Analysis Program (HPAP) to procure human type 1 diabetes pancreata for an extensive array of tissue-based, cellular, and epigenetic assays aimed at critical knowledge gaps in our understanding of the local immune attack and loss of β-cells. In this Methodology Review, we describe how HPAP is performing detailed islet and immune cell phenotyping and creating publicly available data sets with the goals of an improved understanding of type 1 diabetes and the development of more effective treatments to prevent or reverse the disease.

Molecular mechanisms linking peri-implantitis and type 2 diabetes mellitus revealed by transcriptomic analysis

Aims

To explore molecular mechanisms that link peri-implantitis and type 2 diabetes mellitus (T2DM) by bioinformatic analysis of publicly available experimental transcriptomic data.

Materials and methods

Gene expression data from peri-implantitis were downloaded from the Gene Expression Omnibus database, integrated and differentially expressed genes (DEGs) in peri-implantitis were identified. Next, experimentally validated and computationally predicted genes related to T2DM were downloaded from the DisGeNET database. Protein–protein interaction network (PPI) pairs of DEGs related to peri-implantitis and T2DM related genes were constructed, “hub” genes and overlapping DEG were determined. Functional enrichment analysis was used to identify significant shared biological processes and signaling pathways. The PPI networks were subjected to cluster and specific class analysis for identifying “leader” genes. Module network analysis of the merged PPI network identified common or cross-talk genes connecting the two networks.

Results

A total of 92 DEGs overlapped between peri-implantitis and T2DM datasets. Three hub genes (IL-6, NFKB1, and PIK3CG) had the highest degree in PPI networks of both peri-implantitis and T2DM. Three leader genes (PSMD10, SOS1, WASF3), eight cross-talk genes (PSMD10, PSMD6, EIF2S1, GSTP1, DNAJC3, SEC61A1, MAPT, and NME1), and one signaling pathway (IL-17 signaling) emerged as peri-implantitis and T2DM linkage mechanisms.

Conclusions

Exploration of available transcriptomic datasets revealed IL-6, NFKB1, and PIK3CG expression along with the IL-17 signaling pathway as top candidate molecular linkage mechanisms between peri-implantitis and T2DM.

Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes

In order to better understand the etiology of obese type 2 diabetes (T2D) at the molecular level, the present study investigated the gene expression and DNA methylation profiles associated with T2D via systemic analysis. Gene expression (GSE64998) and DNA methylation profiles (GSE65057) from liver tissues of healthy controls and obese patients with T2D were downloaded from the Gene Expression Omnibus database. Differentially-expressed genes (DEGs) and differentially-methylated genes (DMGs) were identified using the Limma package, and their overlapping genes were additionally determined. Enrichment analysis was performed using the BioCloud platform on the DEGs and the overlapping genes. Using Cytoscape software, protein-protein interaction (PPI), transcription factor target networks and microRNA (miRNA) target networks were then constructed in order to determine associated hub genes. In addition, a further GSE15653 dataset was utilized in order to validate the DEGs identified in the GSE64998 dataset analyses. A total of 251 DEGs, including 124 upregulated and 127 downregulated genes, were detected, and a total of 9,698 genes were demonstrated to be differentially methylated in obese patients with T2D compared with non-obese healthy controls. A total of 103 overlapping genes between the two datasets were revealed, including 47 upregulated genes and 56 downregulated genes. The identified overlapping genes were revealed to be strongly associated with fatty acid and glucose metabolic pathways, in addition to oxidation/reduction. The overlapping genes cyclin D1 (CCND1), PPARG coactivator α (PPARGC1A), fatty acid synthase (FASN), glucokinase (GCK), steraroyl-coA desaturase (SCD) and tyrosine aminotransferase (TAT) had higher degrees in the PPI, transcription target networks and miRNA target networks. In addition, among the 251 DEGs, a total of 35 DEGs were validated to be being shared genes between the datasets, which included a number of key genes in the PPI network, including CCND1, FASN and TAT. Abnormal gene expression and DNA methylation patterns that were implicated in fatty acid and glucose metabolic pathways and oxidation/reduction reactions were detected in obese patients with T2D. Furthermore, the CCND1, PPARGC1A, FANS, GCK, SCD and TAT genes may serve a role in the development of obesity-associated T2D.

Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes

AIMS/HYPOTHESIS

Pancreatic islet beta cell failure causes type 2 diabetes in humans. To identify transcriptomic changes in type 2 diabetic islets, the Innovative Medicines Initiative for Diabetes: Improving beta-cell function and identification of diagnostic biomarkers for treatment monitoring in Diabetes (IMIDIA) consortium ( www.imidia.org ) established a comprehensive, unique multicentre biobank of human islets and pancreas tissues from organ donors and metabolically phenotyped pancreatectomised patients (PPP).

METHODS

Affymetrix microarrays were used to assess the islet transcriptome of islets isolated either by enzymatic digestion from 103 organ donors (OD), including 84 non-diabetic and 19 type 2 diabetic individuals, or by laser capture microdissection (LCM) from surgical specimens of 103 PPP, including 32 non-diabetic, 36 with type 2 diabetes, 15 with impaired glucose tolerance (IGT) and 20 with recent-onset diabetes (<1 year), conceivably secondary to the pancreatic disorder leading to surgery (type 3c diabetes). Bioinformatics tools were used to (1) compare the islet transcriptome of type 2 diabetic vs non-diabetic OD and PPP as well as vs IGT and type 3c diabetes within the PPP group; and (2) identify transcription factors driving gene co-expression modules correlated with insulin secretion ex vivo and glucose tolerance in vivo. Selected genes of interest were validated for their expression and function in beta cells.

RESULTS

Comparative transcriptomic analysis identified 19 genes differentially expressed (false discovery rate ≤0.05, fold change ≥1.5) in type 2 diabetic vs non-diabetic islets from OD and PPP. Nine out of these 19 dysregulated genes were not previously reported to be dysregulated in type 2 diabetic islets. Signature genes included TMEM37, which inhibited Ca²⁺-influx and insulin secretion in beta cells, and ARG2 and PPP1R1A, which promoted insulin secretion. Systems biology approaches identified HNF1A, PDX1 and REST as drivers of gene co-expression modules correlated with impaired insulin secretion or glucose tolerance, and 14 out of 19 differentially expressed type 2 diabetic islet signature genes were enriched in these modules. None of these signature genes was significantly dysregulated in islets of PPP with impaired glucose tolerance or type 3c diabetes.

CONCLUSIONS/INTERPRETATION

These studies enabled the stringent definition of a novel transcriptomic signature of type 2 diabetic islets, regardless of islet source and isolation procedure. Lack of this signature in islets from PPP with IGT or type 3c diabetes indicates differences possibly due to peculiarities of these hyperglycaemic conditions and/or a role for duration and severity of hyperglycaemia. Alternatively, these transcriptomic changes capture, but may not precede, beta cell failure.

Effective litmus gene test for monitoring the quality of blood samples: Application to Alzheimer's disease diagnostics

Gene expression profiles reflect the biologically diverse activities of cells under specific cell environments. Using the transcriptional response of cultured cells to blood composition, we developed a litmus gene assay to discriminate blood samples reflecting different sample qualities or disease conditions. This cell-based litmus gene assay identified six genes (CCL20, CEMIP, IL1B, IL8, PRG2, PTGS2) as potential biomarkers of plasma quality control and the SPC25 gene as a diagnostic biomarker of Alzheimer’s disease (AD). In addition, the SPC25 gene expression level was significantly increased in the cell-based assay using serum samples from patients with mild cognitive impairment (MCI). In conclusion, we demonstrated the effectiveness and potential of a litmus gene assay to detect the orchestrated effects of circulating systemic factors, leading to the successful diagnosis of AD and MCI. This method is broadly applicable to the diagnosis of disease subtypes or patho-physiological stages of complex diseases and tumors.

CDK1 promotes nascent DNA synthesis and induces resistance of cancer cells to DNA-damaging therapeutic agents

Cyclin dependent kinase 1 (CDK1) is essential for cell viability and plays a vital role in many biological events including cell cycle control, DNA damage repair, and checkpoint activation. Here, we identify an unanticipated role for CDK1 in promoting nascent DNA synthesis during S-phase. We report that a short duration of CDK1 inhibition, which does not perturb cell cycle progression, triggers a replication-associated DNA damage response (DDR). This DDR is associated with a disruption of replication fork progression and leads to genome instability. Moreover, we show that compromised CDK1 activity dramatically increases the efficacy of chemotherapeutic agents that kill cancer cells through perturbing DNA replication, including Olaparib, an FDA approved PARP inhibitor. Our study has revealed an important role for CDK1 in the DNA replication program, and suggests that the therapeutic targeting CDK1 may be a novel approach for combination chemotherapy.

Up-regulation of CDK16 by multiple mechanisms in hepatocellular carcinoma promotes tumor progression

Background

Hepatocellular carcinoma (HCC) remains difficult to cure due to lack of effective treatment and the molecular mechanisms are complex and not completely understood. In this study, We investigated the role of CDK16 in tumor progression of HCC.

Methods

We interrogated the expression level of CDK16 by polymerase chain reaction and immunohistochemistry(IHC) and studied its clinical significance. The functional role of CDK16 on HCC was studied via gain and loss of function in vitro and in vivo. Luciferase reporter assay and Chromatin immunoprecipitation(ChIP) assay were performed to investigate the transcriptional and post-transcriptional mechanisms involved in the regulation of CDK16.

Results

CDK16 expression was significantly up-regulated in HCC and higher expression of CDK16 was positively correlated with aggressive clinicopathological phenotype and poorer survival rates. Functionally, knockdown of CDK16 suppressed proliferation in vitro and in vivo. Inactivation of CDK16 also induced apoptosis and cell cycle arrest. Most importantly, CDK16 promoted epithelial mesenchymal transition and tumor invasion by activating β-catenin signaling. In addition, We identified E2F1 as a positive transcriptional regulator of CDK16. Moreover, down regulation of miR-125b-5p enhanced CDK16 expression at post-transcriptional level.

Conclusion

We provided the first evidence that CDK16 is an bona fide oncogene in HCC, and multiple activating mechanisms at transcriptional and posttranscriptional levels together contributes to CDK16 up-regulation in HCC.

Electronic supplementary material

The online version of this article (doi:10.1186/s13046-017-0569-2) contains supplementary material, which is available to authorized users.

RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes

Pancreatic islet cells are critical for maintaining normal blood glucose levels, and their malfunction underlies diabetes development and progression. We used single-cell RNA sequencing to determine the transcriptomes of 1,492 human pancreatic α, β, δ, and PP cells from non-diabetic and type 2 diabetes organ donors. We identified cell-type-specific genes and pathways as well as 245 genes with disturbed expression in type 2 diabetes. Importantly, 92% of the genes have not previously been associated with islet cell function or growth. Comparison of gene profiles in mouse and human α and β cells revealed species-specific expression. All data are available for online browsing and download and will hopefully serve as a resource for the islet research community.

Islet biology, the CDKN2A/B locus and type 2 diabetes risk

Type 2 diabetes, fuelled by the obesity epidemic, is an escalating worldwide cause of personal hardship and public cost. Diabetes incidence increases with age, and many studies link the classic senescence and ageing protein p16(INK4A) to diabetes pathophysiology via pancreatic islet biology. Genome-wide association studies (GWASs) have unequivocally linked the CDKN2A/B locus, which encodes p16 inhibitor of cyclin-dependent kinase (p16(INK4A)) and three other gene products, p14 alternate reading frame (p14(ARF)), p15(INK4B) and antisense non-coding RNA in the INK4 locus (ANRIL), with human diabetes risk. However, the mechanism by which the CDKN2A/B locus influences diabetes risk remains uncertain. Here, we weigh the evidence that CDKN2A/B polymorphisms impact metabolic health via islet biology vs effects in other tissues. Structured in a bedside-to-bench-to-bedside approach, we begin with a summary of the evidence that the CDKN2A/B locus impacts diabetes risk and a brief review of the basic biology of CDKN2A/B gene products. The main emphasis of this work is an in-depth look at the nuanced roles that CDKN2A/B gene products and related proteins play in the regulation of beta cell mass, proliferation and insulin secretory function, as well as roles in other metabolic tissues. We finish with a synthesis of basic biology and clinical observations, incorporating human physiology data. We conclude that it is likely that the CDKN2A/B locus influences diabetes risk through both islet and non-islet mechanisms.

Type 2 diabetes: genetic data sharing to advance complex disease research

As with other complex diseases, unbiased association studies followed by physiological and experimental characterization have for years formed a paradigm for identifying genes or processes of relevance to type 2 diabetes mellitus (T2D). Recent large-scale common and rare variant genome-wide association studies (GWAS) suggest that substantially larger association studies are needed to identify most T2D loci in the population. To hasten clinical translation of genetic discoveries, new paradigms are also required to aid specialized investigation of nascent hypotheses. We argue for an integrated T2D knowledgebase, designed for a worldwide community to access aggregated large-scale genetic data sets, as one paradigm to catalyse convergence of these efforts.

Definition of a Skp2-c-Myc Pathway to Expand Human Beta-cells

Type 2 diabetes (T2D) is characterized by insulin resistance and reduced functional β-cell mass. Developmental differences, failure of adaptive expansion and loss of β-cells via β-cell death or de-differentiation have emerged as the possible causes of this reduced β-cell mass. We hypothesized that the proliferative response to mitogens of human β-cells from T2D donors is reduced, and that this might contribute to the development and progression of T2D. Here, we demonstrate that the proliferative response of human β-cells from T2D donors in response to cdk6 and cyclin D3 is indeed dramatically impaired. We show that this is accompanied by increased nuclear abundance of the cell cycle inhibitor, p27^kip1. Increasing nuclear abundance of p27^kip1 by adenoviral delivery decreases the proliferative response of β-cells from non-diabetic donors, mimicking T2D β-cells. However, while both p27^kip1 gene silencing and downregulation by Skp2 overexpression increased similarly the proliferative response of human β-cells, only Skp2 was capable of inducing a significant human β-cell expansion. Skp2 was also able to double the proliferative response of T2D β-cells. These studies define c-Myc as a central Skp2 target for the induction of cell cycle entry, expansion and regeneration of human T2D β-cells.

Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein-Protein Interaction Data

Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention data integration across omics-es. In the present study, transcriptomics data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with protein-protein interaction data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active protein-protein interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.

Differential expression network analysis for diabetes mellitus type 2 based on expressed level of islet cells

OBJECTIVE

Diabetes mellitus type 2 (T2DM) is a metabolic disease that has become a pressing issue, with potential adverse impact on mental health. We aimed to explore the potential molecular mechanism of T2DM.

MATERIAL AND METHODS

GSE38642 microarray data downloaded from gene expression omnibus was used to identify the differentially expressed genes (DEGs). Profiling of complex functionality (ProfCom) was used to analyze the complex function and mine T2DM signature genes. Finally, the differential expression network (DEN) was constructed.

RESULTS

We identified 147 DEGs including 59 up- and 88 down-regulated genes. With increasing of degree, the specificity of functional description of DEGs was higher. GO term of "integral to membrane and immune response (not receptor activity) not regulation of immune response" in degree 4 was enriched by 6 DEGs, while the GO term of "immune response" in degree 1 was enriched by 12 DEGs. Two complex functions of integral to membrane an immune response and response to glucose stimulus were enriched by 11 T2DM signature genes including ARG2, GLP1R, PFKFB2, PTPRN, ACSL5, CCR7, IL2RA, IL7R, IL1R2, IL1RL1 and CHST4. Finally, DEN including 11 signature genes and 491 edges was obtained.

CONCLUSION

The identified DEGs especially 11 signature genes such as PTPRN, GLP1R, CCR7 and IL2RA may play important roles in the pathogenesis of T2DM.

Targeting cell cycle regulators in hematologic malignancies

Hematologic malignancies represent the fourth most frequently diagnosed cancer in economically developed countries. In hematologic malignancies normal hematopoiesis is interrupted by uncontrolled growth of a genetically altered stem or progenitor cell (HSPC) that maintains its ability of self-renewal. Cyclin-dependent kinases (CDKs) not only regulate the mammalian cell cycle, but also influence other vital cellular processes, such as stem cell renewal, differentiation, transcription, epigenetic regulation, apoptosis, and DNA repair. Chromosomal translocations, amplification, overexpression and altered CDK activities have been described in different types of human cancer, which have made them attractive targets for pharmacological inhibition. Mouse models deficient for one or more CDKs have significantly contributed to our current understanding of the physiological functions of CDKs, as well as their roles in human cancer. The present review focuses on selected cell cycle kinases with recent emerging key functions in hematopoiesis and in hematopoietic malignancies, such as CDK6 and its role in MLL-rearranged leukemia and acute lymphocytic leukemia, CDK1 and its regulator WEE-1 in acute myeloid leukemia (AML), and cyclin C/CDK8/CDK19 complexes in T-cell acute lymphocytic leukemia. The knowledge gained from gene knockout experiments in mice of these kinases is also summarized. An overview of compounds targeting these kinases, which are currently in clinical development in various solid tumors and hematopoietic malignances, is presented. These include the CDK4/CDK6 inhibitors (palbociclib, LEE011, LY2835219), pan-CDK inhibitors that target CDK1 (dinaciclib, flavopiridol, AT7519, TG02, P276-00, terampeprocol and RGB 286638) as well as the WEE-1 kinase inhibitor, MK-1775. The advantage of combination therapy of cell cycle inhibitors with conventional chemotherapeutic agents used in the treatment of AML, such as cytarabine, is discussed.

Genetics of type 2 diabetes-pitfalls and possibilities

Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult.

Rb and p107 are required for alpha cell survival, beta cell cycle control and glucagon-like peptide-1 action

AIMS/HYPOTHESIS

Diabetes mellitus is characterised by beta cell loss and alpha cell expansion. Analogues of glucagon-like peptide-1 (GLP-1) are used therapeutically to antagonise these processes; thus, we hypothesised that the related cell cycle regulators retinoblastoma protein (Rb) and p107 were involved in GLP-1 action.

METHODS

We used small interfering RNA and adenoviruses to manipulate Rb and p107 expression in insulinoma and alpha-TC cell lines. In vivo we examined pancreas-specific Rb knockout, whole-body p107 knockout and Rb/p107 double-knockout mice.

RESULTS

Rb, but not p107, was downregulated in response to the GLP-1 analogue, exendin-4, in both alpha and beta cells. Intriguingly, this resulted in opposite outcomes of cell cycle arrest in alpha cells but proliferation in beta cells. Overexpression of Rb in alpha and beta cells abolished or attenuated the effects of exendin-4 supporting the important role of Rb in GLP-1 modulation of cell cycling. Similarly, in vivo, Rb, but not p107, deficiency was required for the beta cell proliferative response to exendin-4. Consistent with this finding, Rb, but not p107, was suppressed in islets from humans with diabetes, suggesting the importance of Rb regulation for the compensatory proliferation that occurs under insulin resistant conditions. Finally, while p107 alone did not have an essential role in islet homeostasis, when combined with Rb deletion, its absence potentiated apoptosis of both alpha and beta cells resulting in glucose intolerance and diminished islet mass with ageing.

CONCLUSIONS/INTERPRETATION

We found a central role of Rb in the dual effects of GLP-1 in alpha and beta cells. Our findings highlight unique contributions of individual Rb family members to islet cell proliferation and survival.