Adipocyte-specific tribbles pseudokinase 1 regulates plasma adiponectin and plasma lipids in mice.

OBJECTIVE: Multiple genome-wide association studies (GWAS) have identified SNPs in the 8q24 locus near TRIB1 that are significantly associated with plasma lipids and other markers of cardiometabolic health, and prior studies have revealed the roles of hepatic and myeloid Trib1 in plasma lipid regulation and atherosclerosis. The same 8q24 SNPs are additionally associated with plasma adiponectin levels in humans, implicating TRIB1 in adipocyte biology. Here, we hypothesize that TRIB1 in adipose tissue regulates plasma adiponectin, lipids, and metabolic health. METHODS: We investigate the metabolic phenotype of adipocyte-specific Trib1 knockout mice (Trib1_ASKO) fed on chow and high-fat diet (HFD). Through secretomics of adipose tissue explants and RNA-seq of adipocytes and livers from these mice, we further investigate the mechanism of TRIB1 in adipose tissue. RESULTS: Trib1_ASKO mice have an improved metabolic phenotype with increased plasma adiponectin levels, improved glucose tolerance, and decreased plasma lipids. Trib1_ASKO adipocytes have increased adiponectin production and secretion independent of the known TRIB1 function of regulating proteasomal degradation. RNA-seq analysis of adipocytes and livers from Trib1_ASKO mice indicates that alterations in adipocyte function underlie the observed plasma lipid changes. Adipose tissue explant secretomics further reveals that Trib1_ASKO adipose tissue has decreased ANGPTL4 production, and we demonstrate an accompanying increase in the lipoprotein lipase (LPL) activity that likely underlies the triglyceride phenotype. CONCLUSIONS: This study shows that adipocyte Trib1 regulates multiple aspects of metabolic health, confirming previously observed genetic associations in humans and shedding light on the further mechanisms by which TRIB1 regulates plasma lipids and metabolic health.

Competing tissue-specific functions for the Tribbles-1 plasma lipid associated locus.

PURPOSE OF REVIEW: The pseudokinase Tribbles-1 (TRIB1) remains the focus of intense research since genome-wide association studies (GWAS) associated it with multiple cardiometabolic traits in humans, including plasma lipids and atherosclerosis. This review highlights recent advances in understanding the function of TRIB1 and what outstanding questions remain. RECENT FINDINGS: Studies performed in a myeloid-specific Trib1 mouse model show that Trib1 contributes to foam cell formation, underscoring the importance of continued research into tissue-specific functions of TRIB1. Investigations of TRIB1 function in a 3D hepatic organoid model demonstrate that hepatic TRIB1 functions elucidated in mouse models are recapitulated in these organoid systems. Lastly, a recent study showed berberine, an existing lipid-lowering drug, to be acting via a TRIB1-dependent mechanism, highlighting both a novel regulator of TRIB1 expression and the potential of studying TRIB1 through existing therapeutics. SUMMARY: TRIB1 remains one of the more fascinating loci to arise from cardiometabolic GWAS, given the constellation of traits it associates with. As genetic studies continue to link TRIB1 to metabolic phenotypes, more functional research on tissue-specific TRIB1, regulation of TRIB1 and its function in current therapies, as well as the reproduction of results from mice in human contexts are all necessary to increase our understanding of TRIB1 and its relevance.

Simultaneous Identification of Cell of Origin, Translocations, and Hotspot Mutations in Diffuse Large B-Cell Lymphoma Using a Single RNA-Sequencing Assay.

OBJECTIVES: Diffuse large B-cell lymphoma (DLBCL) is an aggressive non-Hodgkin lymphoma with a heterogenous genetic landscape that can require multiple assays to characterize. We reviewed a 1-step RNA-based assay to determine cell of origin (COO), detect translocations, and identify mutations and to assess the role of the assay in diagnosis. METHODS: Using a single custom Archer FusionPlex Lymphoma panel, we performed anchored multiplex polymerase chain reaction-based RNA sequencing on 41 cases of de novo DLBCL. Each case was subclassified by COO, and gene fusions and hotspot mutations were identified. The findings were then compared with COO classification by the Hans immunohistochemical algorithm and NanoString technology, cytogenetics, and fluorescence in situ hybridization results. RESULTS: Concordant COO classification by the FusionPlex panel and NanoString was observed in 35 of 41 cases (85.3%), with NanoString and Hans concordant in 33 of 41 cases (80.5%) and FusionPlex and Hans concordant in 33 of 41 cases (80.5%). The FusionPlex assay also detected 6 of 11 BCL6 translocations (4 cryptic), 2 of 3 BCL2 translocations, and 2 of 4 MYC translocations. Mutations were detected in lymphoma-related genes in 24 of 41 cases. CONCLUSION: This FusionPlex assay offers a single method for COO classification, mutation detection, and identification of important translocations in DLBCL. Although not replacing traditional testing, it could offer useful data when limited tissue is available.

Clinical Validation of a Cell-Free DNA Gene Panel.

The use of liquid biopsies to identify driver mutations in patients with solid tumors holds great promise for performing targeted therapy selection, monitoring disease progression, and detecting treatment resistance mechanisms. We describe herein the development and clinical validation of a 28-gene cell-free DNA panel that targets the most common genetic alterations in solid tumors. Bioinformatic and variant filtering solutions were developed to improve test sensitivity and specificity. The panel and these tools were used to analyze commercially available controls, allowing establishment of a limit of detection allele fraction cutoff of 0.25%, with 100% (95% CI, 81.5%-100%) specificity and 89.8% (95% CI, 81.0%-94.9%) sensitivity. In addition, we analyzed a total of 163 blood samples from patients with metastatic cancer (n = 123) and demonstrated a >90% sensitivity for detecting previously identified expected mutations. Longitudinal monitoring of patients revealed a strong correlation of variant allele frequency changes and clinical outcome. Additional clinically relevant information included identification of resistance mutations in patients receiving targeted treatment and detection of complex patterns of mutational heterogeneity. Achieving lower limits of detection will require additional improvements to molecular barcoding; however, these data strongly support clinical implementation of cell-free DNA panels in advanced cancer patients.