Gene expression profiles of glucose toxicity-exposed islet microvascular endothelial cells.

OBJECTIVE: Islet microcirculation is mainly composed by IMECs. The aim of the study was to investigate the differences in gene expression profiles of IMECs upon glucose toxicity exposure and insulin treatment. METHODS: IMECs were treated with 5.6 mmol L-1 glucose, 35 mmol L-1 glucose, and 35 mmol L-1 glucose plus 10-8  mol L-1 insulin, respectively. Gene expression profiles were determined by microarray and verified by qPCR. GO terms and KEGG analysis were performed to assess the potential roles of differentially expressed genes. The interaction and expression tendency of differentially expressed genes were analyzed by Path-Net algorithm. RESULTS: Compared with glucose toxicity-exposed IMECs, 1574 mRNAs in control group and 2870 mRNAs in insulin-treated IMECs were identified with differential expression, respectively. GO and KEGG pathway analysis revealed that these genes conferred roles in regulation of apoptosis, proliferation, migration, adhesion, and metabolic process etc. Additionally, MAPK signaling pathway and apoptosis were the dominant nodes in Path-Net. IMECs survival and function pathways were significantly changed, and the expression tendency of genes from euglycemia and glucose toxicity exposure to insulin treatment was revealed and enriched in 7 patterns. CONCLUSIONS: Our study provides a microcirculatory framework for gene expression profiles of glucose toxicity-exposed IMECs.

The Landscape of Genetic Alterations Stratified Prognosis in Oriental Pancreatic Cancer Patients.

BACKGROUND: Pancreatic cancer is a life-threatening malignant disease with significant diversity among geographic regions and races leading to distinct carcinogenesis and prognosis. Previous studies mainly focused on Western patients, while the genomic landscape of Oriental patients, especially Chinese, remained less investigated. METHODS: A total of 408 pancreatic cancer patients were enrolled. A panel containing 436 cancer-related genes was used to detect genetic alterations in tumor samples. RESULTS: We profiled the genomic alteration landscape of pancreatic duct adenocarcinoma (PDAC), intraductal papillary mucinous neoplasm (IPMN), periampullary carcinoma (PVC), and solid-pseudopapillary tumor (SPT). Comparison with a public database revealed specific gene mutations in Oriental PDAC patients including higher mutation rates of DNA damage repair-related genes. Analysis of mutational signatures showed potential heterogenous carcinogenic factors caused by diabetes mellitus. KRAS mutation, especially KRAS G12D mutation, was associated with poor survival, while patients not harboring the 17 significant copy number variations (CNVs) had a better prognosis. We further identified multiple correlations between clinicopathologic variables and genetic mutations, as well as CNVs. Finally, by network-based stratification, three classes of PDAC patients were robustly clustered. Among these, class 1 (characterized by the Fanconi anemia pathway) achieved the best outcome, while class 2 (involved in the platinum drug resistance pathway) suffered from the worst prognosis. CONCLUSIONS: In this study, we reported for the first time the genetic alteration landscape of Oriental PDAC patients identifying many Oriental-specific alterations. The relationship between genetic alterations and clinicopathological factors as well as prognosis demonstrated important genomic impact on tumor biology. This study will help to optimize clinical treatment of Oriental PDAC patients and improve their survival.

Genetic Profiling of Breast Cancer with and Without Preexisting Metabolic Disease.

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death among women. Various mechanisms are involved in the initiation and progression of breast cancer. Metabolic dysregulation has been associated with increasing breast cancer incidence and mortality. However, little is known about how metabolic disease regulates the development and progression of breast cancer at the molecular level. Here, using a hybridization capture-based panel including 124 cancer-associated genes, we performed targeted next-generation sequencing of tumor tissues and matched blood samples from 20 postmenopausal patients with primary breast cancer, in which 6 cases suffered from preexisting metabolic disorders including hypertension, type 2 diabetes, and coronary heart disease. We took only the protein-altering variants and identified 170 somatic mutations of 59 genes. Among these, 40 mutated genes were found in the metabolic disease group, and 33 mutated genes were found in the non-metabolic disease group. Importantly, nonsynonymous mutations of 26 genes (MSH3, BRAF, MLH3, MTOR, DDR2, ALK, etc.) were uniquely present in the metabolic disease group. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed to investigate biological functions and key pathways of somatic mutations. TP53, PIK3CA, and PTEN were the top three commonly mutated genes at a higher frequency compared with the Cancer Genome Atlas (TCGA) data, and several novel but infrequent mutations in other genes were also found. Although further studies are required to validate these variants, our results are the first to suggest a specific molecular profile of breast cancer with preexisting metabolic disease.