Analysis of global gene expression profiles suggests a role of acute inflammation in type 3C diabetes mellitus caused by pancreatic ductal adenocarcinoma

Gao, Wenchao; Zhou, Yu; Li, Qingyan; Zhou, Quanbo; Tan, Langping; Song, Yadong; Zhao, Xiaohui; Yu, Min; Zheng, Shusen; Ye, Huilin; Zeng, Bing; Q, Lin; Zhou, Jiajia; Liu, Yimin; Huang, Huaiqiu; Zhang, Hui; Hu, Xuchu; Li, Zhihua; Dai, Xianhua; Chen, Rufu

doi:10.1007/s00125-014-3481-8

Cited by 6 publications

(5 citation statements)

References 24 publications

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“…All patients who donated their tissue samples for biomedical research, which were approved by the ethics committee of Guangdong Provincial People's Hospital, have signed informed consent forms. To detect the mRNA expression of LBP, quantitative reverse transcriptase-polymerase chain reaction (PCR) was performed as described previously (25). To achieve robust single-base specificity, a novel PCR-based method, named quantitative analysis of single-base methylation (QASM), was used to detect cg08351331 status in HCC samples (26).…”

Section: Validation Of Lbp and Cg08351331 In Hcc Samplesmentioning

confidence: 99%

Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival

et al. 2020

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This study aimed to identify aberrantly methylated differentially methylated CpG sites (DMCs) and investigate their prognostic value in hepatocellular carcinoma (HCC). A total of 2,404 DMCs were selected from Gene Expression Omnibus (GEO) and validated by The Cancer Genome Atlas (TCGA). The TCGA cohort was divided into a training cohort and a validating cohort. First, the prognostic model based on six DMCs, including cg08351331, cg02910574, cg09947274, cg17589341, cg24652919, and cg26545968, was constructed based on the least absolute shrinkage and selection operator (LASSO) regression Cox analysis. The area under the curve (AUC) of the DMC-based model was 0.765 in the training cohort and 0.734 in the validating cohort. The accuracy of a model combining the DMC signature and American Joint Committee on Cancer (AJCC) stage, with an AUC of 0.795, was better than that of the DMCs or AJCC stage alone. Second, further analysis revealed that the methylation rate of cg08351331 was negatively associated with the expression of its relative gene, lipopolysaccharide-binding protein (LBP). Besides, the gene expression of LBP was significantly associated with poor overall survival in patients with hepatitis B virus (HBV) infection. Finally, these findings were confirmed by GSE57956 data and our own cohort. In conclusion, we established an accurate DMC-based prognostic model that could be combined with AJCC stage to improve the accuracy of prognostic prediction in HCC. Moreover, our preliminary data indicate that LBP may be a new key factor in HBV-induced HCC initiation through the regulation of its methylation.

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Section: Validation Of Lbp and Cg08351331 In Hcc Samplesmentioning

confidence: 99%

Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival

et al. 2020

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“…Notably, PC harbors a chronic inflammatory microenvironment (16), and chronic inflammation is a crucial mediator of insulin resistance (17). Analysis of gene ontology also showed that secretory genes differentially expressed in tumors of patients with PCDM are related mainly to inflammation (18). Therefore, we hypothesized that insulin resistance and PCDM are induced by overexpression of specific inflammatory mediators in PC, and blood levels of those mediators may facilitate differentiation between PCDM and type 2 diabetes.…”

mentioning

confidence: 97%

Galectin-3 and S100A9: Novel Diabetogenic Factors Mediating Pancreatic Cancer–Associated Diabetes

Liao

Huang

et al. 2019

Diabetes Care

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Pancreatic cancer-associated diabetes (PCDM) is a paraneoplastic phenomenon accounting for 1% of new-onset diabetes. We aimed to identify the mediators of PCDM and evaluate their usefulness in distinguishing PCDM from type 2 diabetes. RESEARCH DESIGN AND METHODS Secreted proteins of MIA PaCa-2 cells were identified by proteomics, and those with ‡10-fold overexpression in transcriptome analysis were assessed by bioinformatics and glucose uptake assay to identify candidate factors. Expression of factors was compared between tumors with and without PCDM by immunohistochemistry. Serum levels were measured in a training set including PC with and without PCDM, type 2 diabetes, pancreatitis, other pancreatic/peripancreatic tumors, and control subjects (n = 50 each). Cutoff values for differentiation between PCDM and type 2 diabetes from the training set were validated in a test set (n = 41 each). RESULTS Galectin-3 and S100A9 were overexpressed in tumors with PCDM and dosedependently suppressed insulin-stimulated glucose uptake in C2C12 myotubes. In the training set, serum galectin-3 and S100A9 levels were exclusively increased in patients with PCDM and distinguished PCDM from type 2 diabetes (area under the curve [AUC] galectin-3: 0.73 [95% CI 0.64-0.83]; S100A9: 0.79 [95% CI 0.70-0.87]). Similar results were observed in the test set (AUC galectin-3: 0.83 [95% CI 0.74-0.92]; S100A9: 0.77 [95% CI 0.67-0.87]), with sensitivity and specificity 72.1% and 86.1%, respectively, for galectin-3 and 69.8% and 58.1% for S100A9 in differentiating between PCDM and type 2 diabetes. CONCLUSIONS Galectin-3 and S100A9 are overexpressed in PCDM tumors and mediate insulin resistance. Galectin-3 and S100A9 distinguish PCDM from type 2 diabetes in subjects with new-onset diabetes. Approximately 1% of new-onset diabetes is attributed to pancreatic cancerassociated diabetes (PCDM), which occurs in ;50% of pancreatic adenocarcinoma patients within 24 months before the diagnosis of cancer (1-4). Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the U.S. and is projected to become the second leading cause of cancer deaths by 2030 (5). Surgical resection of tumor is

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“…Gao et al reported that the TNFSF13 level in serum was significantly associated with the diabetic status of patients with pancreatic ductal adenocarcinoma-associated diabetes [25]. …”

Section: Discussionmentioning

confidence: 99%

Integrating Genome-Wide Association and eQTLs Studies Identifies the Genes and Gene Sets Associated with Diabetes

Liang

Wang

et al. 2017

BioMed Research International

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Aim To identify novel candidate genes and gene sets for diabetes. Methods We performed an integrative analysis of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTLs) data for diabetes. Summary data was driven from a large-scale GWAS of diabetes, totally involving 58,070 individuals. eQTLs dataset included 923,021 cis-eQTL for 14,329 genes and 4,732 trans-eQTL for 2,612 genes. Integrative analysis of GWAS and eQTLs data was conducted by summary data-based Mendelian randomization (SMR). To identify the gene sets associated with diabetes, the SMR single gene analysis results were further subjected to gene set enrichment analysis (GSEA). A total of 13,311 annotated gene sets were analyzed in this study. Results SMR analysis identified 6 genes significantly associated with fasting glucose, such as C11ORF10 (p value = 6.04 × 10−8), MRPL33 (p value = 1.24 × 10−7), and FADS1 (p value = 2.39 × 10−7). Gene set analysis identified HUANG_FOXA2_TARGETS_UP (false discovery rate = 0.047) associated with fasting glucose. Conclusion Our study provides novel clues for clarifying the genetic mechanism of diabetes. This study also illustrated the good performance of SMR approach and extended it to gene set association analysis for complex diseases.

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Analysis of global gene expression profiles suggests a role of acute inflammation in type 3C diabetes mellitus caused by pancreatic ductal adenocarcinoma

Cited by 6 publications

References 24 publications

Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival

Identification of Aberrantly Methylated Differentially CpG Sites in Hepatocellular Carcinoma and Their Association With Patient Survival

Galectin-3 and S100A9: Novel Diabetogenic Factors Mediating Pancreatic Cancer–Associated Diabetes

Integrating Genome-Wide Association and eQTLs Studies Identifies the Genes and Gene Sets Associated with Diabetes

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