BACKGROUND Pancreatic cancer is a highly invasive malignant tumor. Expression levels of the autophagy-related protein microtubule-associated protein 1 A/1 B-light chain 3(LC3) and perineural invasion(PNI) are closely ...BACKGROUND Pancreatic cancer is a highly invasive malignant tumor. Expression levels of the autophagy-related protein microtubule-associated protein 1 A/1 B-light chain 3(LC3) and perineural invasion(PNI) are closely related to its occurrence and development. Our previous results showed that the high expression of LC3 was positively correlated with PNI in the patients with pancreatic cancer. In this study, we further searched for differential genes involved in autophagy of pancreatic cancer by gene expression profiling and analyzed their biological functions in pancreatic cancer, which provides a theoretical basis for elucidating the pathophysiological mechanism of autophagy in pancreatic cancer and PNI.AIM To identify differentially expressed genes involved in pancreatic cancer autophagy and explore the pathogenesis at the molecular level.METHODS Two sets of gene expression profiles of pancreatic cancer/normal tissue(GSE16515 and GSE15471) were collected from the Gene Expression Omnibus.Significance analysis of microarrays algorithm was used to screen differentially expressed genes related to pancreatic cancer. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were used to analyze the functional enrichment of the differentially expressed genes. Protein interaction data containing only differentially expressed genes was downloaded from String database and screened. Module mining was carried out by Cytoscape software and ClusterOne plug-in. The interaction relationship between the modules was analyzed and the pivot nodes between the functional modules were determined according to the information of the functional modules and the data of reliable protein interaction network.RESULTS Based on the above two data sets of pancreatic tissue total gene expression, 6098 and 12928 differentially expressed genes were obtained by analysis of genes with higher phenotypic correlation. After extracting the intersection of the two differential gene sets, 4870 genes were determined. GO analysis showed that 14 significant functional items including negative regulation of protein ubiquitination were closely related to autophagy. A total of 986 differentially expressed genes were enriched in these functional items. After eliminating the autophagy related genes of human cancer cells which had been defined, 347 differentially expressed genes were obtained. KEGG pathway analysis showed that the pathways hsa04144 and hsa04020 were related to autophagy. In addition,65 clustering modules were screened after the protein interaction network was constructed based on String database, and module 32 contains the LC3 gene,which interacts with multiple autophagy-related genes. Moreover, ubiquitin C acts as a pivot node in functional modules to connect multiple modules related to pancreatic cancer and autophagy.CONCLUSION Three hundred and forty-seven genes associated with autophagy in human pancreatic cancer were concentrated, and a key gene ubiquitin C which is closely related to the occurrence of PNI was determined, suggesting that LC3 may influence the PNI and prognosis of pancreatic cancer through ubiquitin C.展开更多
目的探究维持性血液透析(maintenance hemodialysis,MHD)患者血清Beclin1和微管相关蛋白1轻链3-Ⅱ(microtubule associated protein 1 light chain 3-Ⅱ,LC3-Ⅱ)表达水平与血管钙化(vascular calcification,VC)的相关性。方法选取2017年...目的探究维持性血液透析(maintenance hemodialysis,MHD)患者血清Beclin1和微管相关蛋白1轻链3-Ⅱ(microtubule associated protein 1 light chain 3-Ⅱ,LC3-Ⅱ)表达水平与血管钙化(vascular calcification,VC)的相关性。方法选取2017年4月~2020年9月三河市燕郊人民医院收治的MHD患者145例作为研究对象,根据是否发生VC,将患者分为MHD未并发VC组(n=75)和MHD并发VC组(n=70)。根据VC评估结果将MHD并发VC患者分为轻度VC组(n=36)、中度VC组(n=24)、重度VC组(n=10);另选取同期在该院进行体检的健康人80例作为对照组。收集受试者一般资料,酶联免疫吸附法(enzyme-linked immunosorbent assay,ELISA)检测受试者血清Beclin1和LC3-Ⅱ的水平,Pearson法分析MHD患者血清Beclin1和LC3-Ⅱ水平与VC相关指标的相关性,二元logistic回归分析MHD患者发生VC的影响因素。结果与对照组相比,MHD未并发VC组和MHD并发VC组血清肌酐(serum creatinine,SCr)(72.48±18.26μmol/L vs 685.30±192.42μmol/L,733.98±206.35μmol/L)、血磷(1.28±0.42mmol/L vs 2.08±0.71mmol/L。2.86±0.87mmol/L)、血钙(1.54±0.45mmol/L vs 2.46±0.62mmol/L,2.98±0.77mmol/L)、全段甲状旁腺激素(intact parathyroid hormone,iPTH)(58.10±17.36pg/ml vs 634.58±172.44pg/ml,769.48±195.02pg/ml)水平升高,差异有统计学意义(F=100.197~500.960,均P<0.05);血清血红蛋白(hemoglobin,Hb)(134.82±35.16g/L vs 112.78±32.85g/L,103.66±27.91g/L),Beclin1(8.09±2.16μg/L vs 5.65±1.43μg/L,2.56±0.73μg/L)和LC3-Ⅱ(45.16±5.15μg/L vs 36.31±3.42μg/L,27.47±2.76μg/L)水平降低,差异有统计学意义(F=18.748~372.522,均P<0.05);与MHD未并发VC组相比,MHD并发VC组血磷、血钙及iPTH水平升高(t=7.136~9.723,均P<0.05),血清Beclin1和LC3-Ⅱ水平降低(t=16.605,18.982,均P<0.05)。轻度VC组、中度VC组和重度VC组血清Beclin1(4.35±0.71μg/L,3.49±0.57μg/L和1.91±0.26μg/L)和LC3-Ⅱ(31.12±3.32μg/L,25.65±2.62μg/L vs 20.47±1.76μg/L)水平依次降低,差异均有统计学意义(F=366.298,296.025,均P<0.05)。MHD患者血清Beclin1水平与血磷、血钙及iPTH均呈负相关(r=-0.674,-0.682,-0.597,均P<0.05);血清LC3-Ⅱ水平与血磷、血钙及i PTH也呈负相关(r=-0.648,-0.703,-0.674,均P<0.05)。二元logistic回归分析发现,Beclin1和LC3-Ⅱ水平偏低是MHD患者发生VC的危险因素(P<0.05)。结论MHD并发VC患者血清Beclin1和LC3-Ⅱ水平降低,与VC严重程度有关,是MHD患者发生VC的危险因素,可作为预测MHD患者发生VC的潜在生物学标志物。展开更多
基金Supported by the National Natural Science Foundation of China,No.U1504815 and No.U1504808
文摘BACKGROUND Pancreatic cancer is a highly invasive malignant tumor. Expression levels of the autophagy-related protein microtubule-associated protein 1 A/1 B-light chain 3(LC3) and perineural invasion(PNI) are closely related to its occurrence and development. Our previous results showed that the high expression of LC3 was positively correlated with PNI in the patients with pancreatic cancer. In this study, we further searched for differential genes involved in autophagy of pancreatic cancer by gene expression profiling and analyzed their biological functions in pancreatic cancer, which provides a theoretical basis for elucidating the pathophysiological mechanism of autophagy in pancreatic cancer and PNI.AIM To identify differentially expressed genes involved in pancreatic cancer autophagy and explore the pathogenesis at the molecular level.METHODS Two sets of gene expression profiles of pancreatic cancer/normal tissue(GSE16515 and GSE15471) were collected from the Gene Expression Omnibus.Significance analysis of microarrays algorithm was used to screen differentially expressed genes related to pancreatic cancer. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were used to analyze the functional enrichment of the differentially expressed genes. Protein interaction data containing only differentially expressed genes was downloaded from String database and screened. Module mining was carried out by Cytoscape software and ClusterOne plug-in. The interaction relationship between the modules was analyzed and the pivot nodes between the functional modules were determined according to the information of the functional modules and the data of reliable protein interaction network.RESULTS Based on the above two data sets of pancreatic tissue total gene expression, 6098 and 12928 differentially expressed genes were obtained by analysis of genes with higher phenotypic correlation. After extracting the intersection of the two differential gene sets, 4870 genes were determined. GO analysis showed that 14 significant functional items including negative regulation of protein ubiquitination were closely related to autophagy. A total of 986 differentially expressed genes were enriched in these functional items. After eliminating the autophagy related genes of human cancer cells which had been defined, 347 differentially expressed genes were obtained. KEGG pathway analysis showed that the pathways hsa04144 and hsa04020 were related to autophagy. In addition,65 clustering modules were screened after the protein interaction network was constructed based on String database, and module 32 contains the LC3 gene,which interacts with multiple autophagy-related genes. Moreover, ubiquitin C acts as a pivot node in functional modules to connect multiple modules related to pancreatic cancer and autophagy.CONCLUSION Three hundred and forty-seven genes associated with autophagy in human pancreatic cancer were concentrated, and a key gene ubiquitin C which is closely related to the occurrence of PNI was determined, suggesting that LC3 may influence the PNI and prognosis of pancreatic cancer through ubiquitin C.
文摘目的探究维持性血液透析(maintenance hemodialysis,MHD)患者血清Beclin1和微管相关蛋白1轻链3-Ⅱ(microtubule associated protein 1 light chain 3-Ⅱ,LC3-Ⅱ)表达水平与血管钙化(vascular calcification,VC)的相关性。方法选取2017年4月~2020年9月三河市燕郊人民医院收治的MHD患者145例作为研究对象,根据是否发生VC,将患者分为MHD未并发VC组(n=75)和MHD并发VC组(n=70)。根据VC评估结果将MHD并发VC患者分为轻度VC组(n=36)、中度VC组(n=24)、重度VC组(n=10);另选取同期在该院进行体检的健康人80例作为对照组。收集受试者一般资料,酶联免疫吸附法(enzyme-linked immunosorbent assay,ELISA)检测受试者血清Beclin1和LC3-Ⅱ的水平,Pearson法分析MHD患者血清Beclin1和LC3-Ⅱ水平与VC相关指标的相关性,二元logistic回归分析MHD患者发生VC的影响因素。结果与对照组相比,MHD未并发VC组和MHD并发VC组血清肌酐(serum creatinine,SCr)(72.48±18.26μmol/L vs 685.30±192.42μmol/L,733.98±206.35μmol/L)、血磷(1.28±0.42mmol/L vs 2.08±0.71mmol/L。2.86±0.87mmol/L)、血钙(1.54±0.45mmol/L vs 2.46±0.62mmol/L,2.98±0.77mmol/L)、全段甲状旁腺激素(intact parathyroid hormone,iPTH)(58.10±17.36pg/ml vs 634.58±172.44pg/ml,769.48±195.02pg/ml)水平升高,差异有统计学意义(F=100.197~500.960,均P<0.05);血清血红蛋白(hemoglobin,Hb)(134.82±35.16g/L vs 112.78±32.85g/L,103.66±27.91g/L),Beclin1(8.09±2.16μg/L vs 5.65±1.43μg/L,2.56±0.73μg/L)和LC3-Ⅱ(45.16±5.15μg/L vs 36.31±3.42μg/L,27.47±2.76μg/L)水平降低,差异有统计学意义(F=18.748~372.522,均P<0.05);与MHD未并发VC组相比,MHD并发VC组血磷、血钙及iPTH水平升高(t=7.136~9.723,均P<0.05),血清Beclin1和LC3-Ⅱ水平降低(t=16.605,18.982,均P<0.05)。轻度VC组、中度VC组和重度VC组血清Beclin1(4.35±0.71μg/L,3.49±0.57μg/L和1.91±0.26μg/L)和LC3-Ⅱ(31.12±3.32μg/L,25.65±2.62μg/L vs 20.47±1.76μg/L)水平依次降低,差异均有统计学意义(F=366.298,296.025,均P<0.05)。MHD患者血清Beclin1水平与血磷、血钙及iPTH均呈负相关(r=-0.674,-0.682,-0.597,均P<0.05);血清LC3-Ⅱ水平与血磷、血钙及i PTH也呈负相关(r=-0.648,-0.703,-0.674,均P<0.05)。二元logistic回归分析发现,Beclin1和LC3-Ⅱ水平偏低是MHD患者发生VC的危险因素(P<0.05)。结论MHD并发VC患者血清Beclin1和LC3-Ⅱ水平降低,与VC严重程度有关,是MHD患者发生VC的危险因素,可作为预测MHD患者发生VC的潜在生物学标志物。
