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Watanabe H, Fujishima F, Unno M, Sasano H, Suzuki T. Immunohistochemical and in situ hybridization analyses of glucose transporter 2 in pancreatic neuroendocrine tumors: Possible glucose transporter 2 association with neoplastic insulin production. Pathol Res Pract 2024; 253:154966. [PMID: 38043192 DOI: 10.1016/j.prp.2023.154966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/18/2023] [Accepted: 11/21/2023] [Indexed: 12/05/2023]
Abstract
BACKGROUND Pancreatic neuroendocrine tumors (PanNETs) are rare neoplasms. Additionally, glucose transporter 2 (GLUT2) is associated with insulin production and is essential for glucose transport to normal pancreatic β-cells. Neoplastic cell GLUT2 expression may also influence insulin production by using this transporter. GLUT2 expression and its clinical significance remain unclear in PanNETs. This study aimed to provide GLUT2 expression profiles and evidence of correlation with insulin in PanNETs. METHODS Clinical data were retrieved from 113 surgically resected paraffin-embedded PanNET tissue samples fixed with 10% formalin. PanNETs are categorized as insulinoma, non-functional (NF)-PanNET, or PanNET-not otherwise specified (NOS). A GLUT2 score was used to evaluate cytoplasmic GLUT2 immunoreactivity. The immunoreactive score (IRS) was used to determine membranous GLUT2, cytoplasmic insulin, and proinsulin immunoreactivities. A commercially available in situ hybridization (ISH) kit detected human SLC2A2 (GLUT2) mRNA on tissues in all seven positive- and 20 negative-GLUT2 IRS cases. RESULTS GLUT2 and IRSs significantly differed among insulinoma, NF-PanNET, and PanNET-NOS. Insulinomas exhibited significantly higher GLUT2 scores and IRSs than did NF-PanNETs. GLUT2 IRS positive cases demonstrated significantly higher insulin and proinsulin IRSs than did negative cases. Additionally, GLUT2 ISH-positive cases demonstrated positive GLUT2 scores and IRSs, with significantly higher GLUT2 IRSs than did negative cases. PanNET histological grade categories did not significantly affect GLUT2 scores and IRSs. CONCLUSION The first evidence of a correlation between GLUT2 expressions and insulin in PanNETs is shown in this study.
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Affiliation(s)
- Hirofumi Watanabe
- Department of Pathology, Tohoku University Hospital, Sendai, Miyagi, Japan
| | | | - Michiaki Unno
- Department of Surgery, Tohoku University, Graduate School of Medicine, Sendai, Miyagi, Japan
| | - Hironobu Sasano
- Department of Pathology, Tohoku University Hospital, Sendai, Miyagi, Japan
| | - Takashi Suzuki
- Department of Pathology, Tohoku University Hospital, Sendai, Miyagi, Japan
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Duan YY, Chen XF, Zhu RJ, Jia YY, Huang XT, Zhang M, Yang N, Dong SS, Zeng M, Feng Z, Zhu DL, Wu H, Jiang F, Shi W, Hu WX, Ke X, Chen H, Liu Y, Jing RH, Guo Y, Li M, Yang TL. High-throughput functional dissection of noncoding SNPs with biased allelic enhancer activity for insulin resistance-relevant phenotypes. Am J Hum Genet 2023; 110:1266-1288. [PMID: 37506691 PMCID: PMC10432149 DOI: 10.1016/j.ajhg.2023.07.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/04/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023] Open
Abstract
Most of the single-nucleotide polymorphisms (SNPs) associated with insulin resistance (IR)-relevant phenotypes by genome-wide association studies (GWASs) are located in noncoding regions, complicating their functional interpretation. Here, we utilized an adapted STARR-seq to evaluate the regulatory activities of 5,987 noncoding SNPs associated with IR-relevant phenotypes. We identified 876 SNPs with biased allelic enhancer activity effects (baaSNPs) across 133 loci in three IR-relevant cell lines (HepG2, preadipocyte, and A673), which showed pervasive cell specificity and significant enrichment for cell-specific open chromatin regions or enhancer-indicative markers (H3K4me1, H3K27ac). Further functional characterization suggested several transcription factors (TFs) with preferential allelic binding to baaSNPs. We also incorporated multi-omics data to prioritize 102 candidate regulatory target genes for baaSNPs and revealed prevalent long-range regulatory effects and cell-specific IR-relevant biological functional enrichment on them. Specifically, we experimentally verified the distal regulatory mechanism at IRS1 locus, in which rs952227-A reinforces IRS1 expression by long-range chromatin interaction and preferential binding to the transcription factor HOXC6 to augment the enhancer activity. Finally, based on our STARR-seq screening data, we predicted the enhancer activity of 227,343 noncoding SNPs associated with IR-relevant phenotypes (fasting insulin adjusted for BMI, HDL cholesterol, and triglycerides) from the largest available GWAS summary statistics. We further provided an open resource (http://www.bigc.online/fnSNP-IR) for better understanding genetic regulatory mechanisms of IR-relevant phenotypes.
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Affiliation(s)
- Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Xiao-Feng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Ren-Jie Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Ying-Ying Jia
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Xiao-Ting Huang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Meng Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Ning Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Mengqi Zeng
- Frontier Institute of Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Zhihui Feng
- Frontier Institute of Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Dong-Li Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Hao Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Feng Jiang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Wei-Xin Hu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Xin Ke
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Hao Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, School of Medicine, Indiana University, Indianapolis, IN 46202, USA
| | - Rui-Hua Jing
- Department of Ophthalmology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710000, China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China; Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi 710061, China.
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Stern C, Schwarz S, Moser G, Cvitic S, Jantscher-Krenn E, Gauster M, Hiden U. Placental Endocrine Activity: Adaptation and Disruption of Maternal Glucose Metabolism in Pregnancy and the Influence of Fetal Sex. Int J Mol Sci 2021; 22:ijms222312722. [PMID: 34884524 PMCID: PMC8657775 DOI: 10.3390/ijms222312722] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 11/16/2021] [Accepted: 11/17/2021] [Indexed: 02/07/2023] Open
Abstract
The placenta is an endocrine fetal organ, which secretes a plethora of steroid- and proteo-hormones, metabolic proteins, growth factors, and cytokines in order to adapt maternal physiology to pregnancy. Central to the growth of the fetus is the supply with nutrients, foremost with glucose. Therefore, during pregnancy, maternal insulin resistance arises, which elevates maternal blood glucose levels, and consequently ensures an adequate glucose supply for the developing fetus. At the same time, maternal β-cell mass and function increase to compensate for the higher insulin demand. These adaptations are also regulated by the endocrine function of the placenta. Excessive insulin resistance or the inability to increase insulin production accordingly disrupts physiological modulation of pregnancy mediated glucose metabolism and may cause maternal gestational diabetes (GDM). A growing body of evidence suggests that this adaptation of maternal glucose metabolism differs between pregnancies carrying a girl vs. pregnancies carrying a boy. Moreover, the risk of developing GDM differs depending on the sex of the fetus. Sex differences in placenta derived hormones and bioactive proteins, which adapt and modulate maternal glucose metabolism, are likely to contribute to this sexual dimorphism. This review provides an overview on the adaptation and maladaptation of maternal glucose metabolism by placenta-derived factors, and highlights sex differences in this regulatory network.
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Affiliation(s)
- Christina Stern
- Department of Obstetrics and Gynecology, Medical University of Graz, 8036 Graz, Austria; (C.S.); (S.S.); (E.J.-K.)
| | - Sarah Schwarz
- Department of Obstetrics and Gynecology, Medical University of Graz, 8036 Graz, Austria; (C.S.); (S.S.); (E.J.-K.)
| | - Gerit Moser
- Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, 8010 Graz, Austria;
| | - Silvija Cvitic
- Research Unit of Analytical Mass Spectrometry, Cell Biology and Biochemistry of Inborn Errors of Metabolism, Department of Pediatrics and Adolescent Medicine, Medical University of Graz, 8036 Graz, Austria;
| | - Evelyn Jantscher-Krenn
- Department of Obstetrics and Gynecology, Medical University of Graz, 8036 Graz, Austria; (C.S.); (S.S.); (E.J.-K.)
| | - Martin Gauster
- Division of Cell Biology, Histology and Embryology, Gottfried Schatz Research Center, Medical University of Graz, 8010 Graz, Austria;
- Correspondence: (M.G.); (U.H.); Tel.: +43-316385-71896 (M.G.); +43-136385-17837 (U.H.)
| | - Ursula Hiden
- Department of Obstetrics and Gynecology, Medical University of Graz, 8036 Graz, Austria; (C.S.); (S.S.); (E.J.-K.)
- Correspondence: (M.G.); (U.H.); Tel.: +43-316385-71896 (M.G.); +43-136385-17837 (U.H.)
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