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Abstract：
UNASSIGNED: Pancreatic adenocarcinoma (PAAD) is a lethal disease with a poor prognosis. Genes involved in acute pancreatitis (AP) or chronic pancreatitis (CP) might be important for PAAD development. This study sought to identify potential PAAD diagnosis markers and to establish a PAAD prognosis prediction model based on AP- and CP-related genes.
UNASSIGNED: The significantly differentially expressed genes in both AP or CP and PAAD were obtained by a bioinformatics analysis. A risk-score model for predicting survival was constructed based on The Cancer Genome Atlas (TCGA) data and validated using an International Cancer Genome Consortium (ICGC) cohort. Protein expression and the effects of the genes in the risk models were validated by immunohistochemistry, or Cell Counting Kit-8 (CCK-8) and transwell assays. The study sample data included six AP tissue samples and five normal pancreatic tissue samples, six CP tissue samples and six normal pancreatic tissue samples from the Gene Expression Omnibus (GEO) expression profiling microarrays GSE109227 and GSE41418 data sets, respectively, and fragments per kilobase per million mapped fragments (FPKM) data from four normal controls and 150 PAAD cases from TCGA database, and 182 cancer patient samples with complete survival prognostic data from the ICGC database.
UNASSIGNED: In total, 508 significantly differentially expressed genes were found in both AP or CP and PAAD. Trefoil factor 2 (TFF2), tubulointerstitial nephritis antigen (TINAG), trefoil factor 1 (TFF1), aquaporin 5 (AQP5), SAM pointed domain containing ETS transcription factor (SPDEF), anterior gradient protein 2 (AGR2), apolipoprotein B messenger RNA editing enzyme catalytic subunit 1 (APOBEC1), kallikrein-related peptidase 6 (KLK6), dopa decarboxylase (DDC), mucin 13 (MUC13), claudin 18 (CLDN18), annexin A10 (ANXA10), and tetraspanin 1 (TSPAN1) were found to be present in PAAD and had the largest fold change. A risk-score model, comprising 19 genes, was constructed for prognostic prediction. A high-risk score indicated a poor prognosis. TINAG, DDC, SPDEF, and APOBEC1 proteins were increased in PAAD, while TINAG and DDC were correlated with the pathologic grade. Decreased TINAG, APOBEC1, transmembrane protein 94 (TMEM94), and kelch like family member 36 (KLHL36) expression inhibited PAAD cell proliferation, while decreased SPDEF, TMEM94, and KLHL36 expression significantly inhibited PAAD cell migration.
UNASSIGNED: The AP and CP co-related genes were significantly correlated with PAAD. TINAG, DDC, SPDEF, and APOBEC1 could serve as new PAAD predictors. The risk model developed in this study could be used to predict the prognosis of PAAD patients.
UNASSIGNED: The significantly differentially expressed genes in both AP or CP and PAAD were obtained by a bioinformatics analysis. A risk-score model for predicting survival was constructed based on The Cancer Genome Atlas (TCGA) data and validated using an International Cancer Genome Consortium (ICGC) cohort. Protein expression and the effects of the genes in the risk models were validated by immunohistochemistry, or Cell Counting Kit-8 (CCK-8) and transwell assays. The study sample data included six AP tissue samples and five normal pancreatic tissue samples, six CP tissue samples and six normal pancreatic tissue samples from the Gene Expression Omnibus (GEO) expression profiling microarrays GSE109227 and GSE41418 data sets, respectively, and fragments per kilobase per million mapped fragments (FPKM) data from four normal controls and 150 PAAD cases from TCGA database, and 182 cancer patient samples with complete survival prognostic data from the ICGC database.
UNASSIGNED: In total, 508 significantly differentially expressed genes were found in both AP or CP and PAAD. Trefoil factor 2 (TFF2), tubulointerstitial nephritis antigen (TINAG), trefoil factor 1 (TFF1), aquaporin 5 (AQP5), SAM pointed domain containing ETS transcription factor (SPDEF), anterior gradient protein 2 (AGR2), apolipoprotein B messenger RNA editing enzyme catalytic subunit 1 (APOBEC1), kallikrein-related peptidase 6 (KLK6), dopa decarboxylase (DDC), mucin 13 (MUC13), claudin 18 (CLDN18), annexin A10 (ANXA10), and tetraspanin 1 (TSPAN1) were found to be present in PAAD and had the largest fold change. A risk-score model, comprising 19 genes, was constructed for prognostic prediction. A high-risk score indicated a poor prognosis. TINAG, DDC, SPDEF, and APOBEC1 proteins were increased in PAAD, while TINAG and DDC were correlated with the pathologic grade. Decreased TINAG, APOBEC1, transmembrane protein 94 (TMEM94), and kelch like family member 36 (KLHL36) expression inhibited PAAD cell proliferation, while decreased SPDEF, TMEM94, and KLHL36 expression significantly inhibited PAAD cell migration.
UNASSIGNED: The AP and CP co-related genes were significantly correlated with PAAD. TINAG, DDC, SPDEF, and APOBEC1 could serve as new PAAD predictors. The risk model developed in this study could be used to predict the prognosis of PAAD patients.
摘要：
■胰腺腺癌(PAAD)是一种预后不良的致命疾病。参与急性胰腺炎（AP）或慢性胰腺炎（CP）的基因可能对PAAD的发展很重要。本研究旨在确定潜在的PAAD诊断标志物，并基于AP和CP相关基因建立PAAD预后预测模型。
■通过生物信息学分析获得了AP或CP和PAAD中的显着差异表达基因。基于癌症基因组图谱（TCGA）数据构建了预测生存的风险评分模型，并使用国际癌症基因组联盟（ICGC）队列进行了验证。通过免疫组织化学验证了蛋白质表达和基因在风险模型中的作用，或细胞计数试剂盒-8(CCK-8)和transwell测定。研究样本数据包括6个AP组织样本和5个正常胰腺组织样本,来自基因表达综合（GEO）表达谱微阵列GSE109227和GSE41418数据集的六个CP组织样本和六个正常胰腺组织样本，分别,以及来自四个正常对照的每百万映射片段的每千碱基片段（FPKM）数据和来自TCGA数据库的150个PAAD病例，和182例癌症患者样本，其完整的生存预后数据来自ICGC数据库。
■总共，在AP或CP和PAAD中均发现508个显著差异表达的基因。三叶因子2（TFF2），肾小管间质性肾炎抗原（TINAG），三叶因子1（TFF1），水通道蛋白5（AQP5），SAM指出域含有ETS转录因子(SPDEF),前梯度蛋白2（AGR2），载脂蛋白B信使RNA编辑酶催化亚基1（APOBEC1），激肽释放酶相关肽酶6（KLK6），多巴脱羧酶（DDC），粘蛋白13（MUC13），claudin18(CLDN18),附件A10(ANXA10),发现四跨膜蛋白1（TSPAN1）存在于PAAD中，并且具有最大的倍数变化。风险评分模型，包含19个基因，构建用于预后预测。高风险评分表明预后不良。TINAG,DDC,SPDEF,APOBEC1蛋白在PAAD中增加，而TINAG和DDC与病理分级相关。减少了TINAG,APOBEC1,跨膜蛋白94(TMEM94),Kelch样家族成员36(KLHL36)表达抑制PAAD细胞增殖,虽然减少了SPDEF，TMEM94和KLHL36的表达显著抑制PAAD细胞的迁移。
■AP和CP共同相关基因与PAAD显著相关。TINAG,DDC,SPDEF,APOBEC1可以作为新的PAAD预测因子。本研究建立的风险模型可用于预测PAAD患者的预后。
■通过生物信息学分析获得了AP或CP和PAAD中的显着差异表达基因。基于癌症基因组图谱（TCGA）数据构建了预测生存的风险评分模型，并使用国际癌症基因组联盟（ICGC）队列进行了验证。通过免疫组织化学验证了蛋白质表达和基因在风险模型中的作用，或细胞计数试剂盒-8(CCK-8)和transwell测定。研究样本数据包括6个AP组织样本和5个正常胰腺组织样本,来自基因表达综合（GEO）表达谱微阵列GSE109227和GSE41418数据集的六个CP组织样本和六个正常胰腺组织样本，分别,以及来自四个正常对照的每百万映射片段的每千碱基片段（FPKM）数据和来自TCGA数据库的150个PAAD病例，和182例癌症患者样本，其完整的生存预后数据来自ICGC数据库。
■总共，在AP或CP和PAAD中均发现508个显著差异表达的基因。三叶因子2（TFF2），肾小管间质性肾炎抗原（TINAG），三叶因子1（TFF1），水通道蛋白5（AQP5），SAM指出域含有ETS转录因子(SPDEF),前梯度蛋白2（AGR2），载脂蛋白B信使RNA编辑酶催化亚基1（APOBEC1），激肽释放酶相关肽酶6（KLK6），多巴脱羧酶（DDC），粘蛋白13（MUC13），claudin18(CLDN18),附件A10(ANXA10),发现四跨膜蛋白1（TSPAN1）存在于PAAD中，并且具有最大的倍数变化。风险评分模型，包含19个基因，构建用于预后预测。高风险评分表明预后不良。TINAG,DDC,SPDEF,APOBEC1蛋白在PAAD中增加，而TINAG和DDC与病理分级相关。减少了TINAG,APOBEC1,跨膜蛋白94(TMEM94),Kelch样家族成员36(KLHL36)表达抑制PAAD细胞增殖,虽然减少了SPDEF，TMEM94和KLHL36的表达显著抑制PAAD细胞的迁移。
■AP和CP共同相关基因与PAAD显著相关。TINAG,DDC,SPDEF,APOBEC1可以作为新的PAAD预测因子。本研究建立的风险模型可用于预测PAAD患者的预后。
