New Insights into the Role of ENPP1 in Insulin Resistance

Human antibodies targeting ENPP1 as candidate therapeutics for cancers

Ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) is a type II transmembrane glycoprotein expressed in many tissues. High expression levels of ENPP1 have been observed in many cancer types such as lung cancer, ovarian cancer, and breast cancer. Such overexpression has been associated with poor prognosis in these diseases. Hence, ENPP1 is a potential target for immunotherapy across multiple cancers. Here, we isolated and characterized two high-affinity and specific anti-ENPP1 Fab antibody candidates, 17 and 3G12, from large phage-displayed human Fab libraries. After conversion to IgG1, the binding of both antibodies increased significantly due to avidity effects. Based on these antibodies, we generated antibody-drug conjugates (ADCs), IgG-based bispecific T-cell engagers (IbTEs), and CAR T-cells which all exhibited potent killing of ENPP1-expressing cells. Thus, these various antibody-derived modalities are promising therapeutic candidates for cancers expressing human ENPP1.

Generation and characterization of CRISPR/Cas9-mediated MEN1 knockout BON1 cells: a human pancreatic neuroendocrine cell line

Among patients with the rare diagnosis of pancreatic neuroendocrine tumor (P-NET), a substantial proportion suffer from the inherited cancer syndrome multiple endocrine neoplasia type 1 (MEN1), which is caused by germline mutations of the MEN1 suppressor gene. Somatic mutations and loss of the MEN1 protein (menin) are frequently also found in sporadic P-NETs. Thus, a human neuroendocrine pancreatic cell line with biallelic inactivation of MEN1 might be of value for studying tumorigenesis. We used the polyclonal human P-NET cell line BON1, which expresses menin, serotonin, chromogranin A and neurotensin, to generate a monoclonal stable MEN1 knockout BON1 cell line (MEN1-KO-BON1) by CRISPR/Cas9 editing. Changes in morphology, hormone secretion, and proliferation were analyzed, and proteomics were assessed using nanoLC-MS/MS and Ingenuity Pathway Analysis (IPA). The menin-lacking MEN1-KO-BON1 cells had increased chromogranin A production and were smaller, more homogenous, rounder and grew faster than their control counterparts. Proteomic analysis revealed 457 significantly altered proteins, and IPA identified biological functions related to cancer, e.g., posttranslational modification and cell death/survival. Among 39 proteins with at least a two-fold difference in expression, twelve are relevant in glucose homeostasis and insulin resistance. The stable monoclonal MEN1-KO-BON1 cell line was found to have preserved neuroendocrine differentiation, increased proliferation, and an altered protein profile.

E4orf1 Enhances Glucose Uptake Independent of Proximal Insulin Signaling

Impaired proximal insulin signaling is often present in diabetes. Hence, approaches to enhance glucose disposal independent of proximal insulin signaling are desirable. Evidence indicates that Adenovirus-derived E4orf1 protein may offer such an approach. This study determined if E4orf1 improves insulin sensitivity and downregulates proximal insulin signaling in vivo and enhances cellular glucose uptake independent of proximal insulin signaling in vitro. High fat fed mice were injected with a retrovirus plasmid expressing E4orf1, or a null vector. E4orf1 significantly improved insulin sensitivity in response to a glucose load. Yet, their proximal insulin signaling in fat depots was impaired, as indicated by reduced tyrosine phosphorylation of insulin receptor (IR), and significantly increased abundance of ectonucleotide pyrophosphatase/phosphodiesterase-1 (ENPP1). In 3T3-L1 pre-adipocytes E4orf1 expression impaired proximal insulin signaling. Whereas, treatment with rosiglitazone reduced ENPP1 abundance. Unaffected by IR-KD (insulin receptor knockdown) with siRNA, E4orf1 significantly up-regulated distal insulin signaling pathway and enhanced cellular glucose uptake. In vivo, E4orf1 impairs proximal insulin signaling in fat depots yet improves glycemic control. This is probably explained by the ability of E4orf1 to promote cellular glucose uptake independent of proximal insulin signaling. E4orf1 may provide a therapeutic template to enhance glucose disposal in the presence of impaired proximal insulin signaling.

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity

Background

Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach.

Methods

Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data.

Results

Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B.

Conclusions

To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0229-0) contains supplementary material, which is available to authorized users.