Abstract Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most common cancers worldwide. Intense efforts have been made to elucidate the molecular pathogenesis, but the molecular mechanisms of PDAC are still not well understood. The purpose of this study is to further explore the molecular mechanism of PDAC through integrated bioinformatics analysis. Methods: To identify the candidate genes in the carcinogenesis and progression of PDAC, next-generation sequencing (NGS) data set [31]GSE133684 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified, and Gene Ontology (GO) and pathway enrichment analyses were performed. The protein-protein interaction network (PPI) was constructed and the module analysis was performed using Integrated Interactions Database (IID) interactome database and Cytoscape. Subsequently, miRNA-DEG regulatory network and TF-DEG regulatory network were constructed using miRNet database, NetworkAnalyst database, and Cytoscape software. The expression levels of hub genes were validated based on Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis. Results: A total of 463 DEGs were identified, consisting of 232 upregulated genes and 233 downregulated genes. The enriched GO terms and pathways of the DEGs include vesicle organization, secretory vesicle, protein dimerization activity, lymphocyte activation, cell surface, transferase activity, transferring phosphorus-containing groups, hemostasis, and adaptive immune system. Four hub genes (namely, cathepsin B [CCNB1], four-and-a-half LIM domains 2 (FHL2), major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1) and tubulin beta 1 class VI (TUBB1)) were obtained via taking interaction of different analysis results. Conclusions: On the whole, the findings of this investigation enhance our understanding of the potential molecular mechanisms of PDAC and provide potential targets for further investigation. Keywords: Pancreatic ductal adenocarcinoma, bioinformatics analysis, biomarker, enrichment analysis, differentially expressed genes, next-generation sequencing Introduction Pancreatic ductal adenocarcinoma (PDAC) is a type of cancer that arises from the cells lining the pancreatic ducts.^ [32]1 Epidemiological studies have identified several risk factors for PDAC, including age, sex, smoking, chronic pancreatitis, obesity, diabetes, family history, and occupational exposure.^ [33]2 In terms of incidence, PDAC is the 12th most common cancer in the world, accounting for about 2% of all cancers. However, it is the seventh leading cause of cancer death, responsible for about 5% of all cancer deaths.^ [34]3 Despite new developments in multimodal therapy, its overall 5-year survival rate remains less than 8%.^ [35]4 Hemostasis is the process that stops bleeding,^ [36]5 and immunity refers to the body’s defense mechanism against foreign substances, including cancer cells.^ [37]6 Pancreatic ductal adenocarcinoma (PDAC) is associated with alterations in both hemostasis and immunity. Pancreatic ductal adenocarcinoma treatment commonly includes surgery, radiation, chemotherapy, and immunotherapy.^ [38]7 However, PDAC remains common and malignant due to recurrence and metastasis, and is ultimately key cause of PDAC-associated death.^ [39]8 Therefore, there is a vital need to advance new diagnostic strategies and therapeutic agents to upgrade the prognosis of patients with PDAC. The molecular mechanisms of PDAC tumorigenesis and development remain imprecise. It is, therefore, key to identify novel genes and pathways that are linked with PDAC tumorigenesis and patient prognosis, which might not only help to illuminate the underlying molecular mechanisms involved but also to disclose novel diagnostic markers and therapeutic targets. Some of the key genetic alterations that have been implicated in PDAC include mutations in the KRAS proto-oncogene, GTPase (KRAS), tumor protein p53 (TP53), cyclin-dependent kinase inhibitor 2A (CDKN2A), SMAD family member 4 (SMAD4) and BRCA2 DNA repair–associated (BRCA2) genes. These mutations can occur in various combinations, and their precise roles in PDAC are still being studied.^ [40]9 Oji et al^ [41]10 demonstrated that the overexpression of WT1 is linked with prognosis in patients with PDAC. A previous investigation reported that phosphoinositide 3-kinase signaling pathway is linked with development of PDAC.^ [42]11 Next-generation sequencing (NGS) can promptly uncover gene expression on a global basis and is especially useful in identifying for differentially expressed genes (DEGs).^ [43]12 A huge amount of data have been generated through the use of NGS and the majority of such data have been deposited and saved in public databases. Previous investigations concerning PDAC gene expression profiling have diagnosed hundreds of DEGs.^ [44]13 Bioinformatics analysis is a beneficial strategy for the broad analysis of large databases, including knotty genetic information. In our investigation, we used sophisticated bioinformatics methods to screen potential biomarkers that might be useful for PDAC. The Gene Expression Omnibus (GEO) ([45]https://www.ncbi.nlm.nih.gov/geo/) database^ [46]14 is an open database that allows researchers to select appropriate NGS data. In our investigation, we obtained NGS data set from the GEO ([47]GSE133684)^ [48]15 and searched for DEGs using limma package of R language. We then performed GO term and pathway enrichment analyses of the identified DEGs using the ToppGene database. Protein-protein interaction networks (PPIs) were constructed using Integrated Interactions Database (IID) interactome database and visualized using Cytoscape. Conduct module analyses of the PPI network were performed using PEWCC1. The associations of hub genes with PDAC were determined using a Kaplan-Meier analysis, expression analysis, stage analysis, mutation analysis, protein expression analysis, immune infiltration analysis, and receiver operating characteristic (ROC) curve analysis. Finally, PDAC-related genes were selected to investigate their potential role in a PDAC diagnostic, prognostic, and therapeutic target. Materials and Methods Next-generation sequencing data source NGS data of human mRNA about PDAC research ([49]GSE133684) were obtained from the GEO database The DEGs were considered by 1 independent PDAC data set, [50]GSE133684^ [51]15 with 284 PDAC and 117 normal control samples. The [52]GSE133684 NGS data were based on the [53]GPL20795 HiSeq X Ten (Homo sapiens) platform.. Identification of DEGs The limma package of R language was used for DEGs between PDAC and normal control samples.^ [54]16 The P value was adjusted by the Benjamini-Hochberg method.^ [55]17 An adjusted P value of <0.05 and |log2 fold change (FC)| > 1 were considered as threshold values for DEGs identification. The ggplot2 package and gplots package of R language were used to generate volcano plot and heat map. A volcano plot displays the logarithm of the P value on the y-axis and the logarithm of the fold-change between the 2 conditions on the x-axis. The P-value represents the statistical significance of the difference in gene expression between the 2 conditions, while the fold-change indicates the magnitude of the difference. Heat maps are particularly useful in gene expression analysis, where they are commonly used to visualize gene expression patterns across different experimental conditions or samples. The identified DEGs were preserved for further bioinformatics analysis. GO analysis and pathway enrichment analysis of DEGs The GO repository ([56]http://geneontology.org/)^ [57]18 consists of a massive set of annotation terms and is generally used for annotating genes and identifying the distinctive biological aspects for NGS data. The REACTOME database ([58]https://reactome.org/)^ [59]19 contains data on known genes and their biochemical functions and is used for identifying functional and metabolic pathways. By performing the GO and REACTOME enrichment analysis at the functional level, we can boost a better understanding of the roles of these DEGs in the induction and in the advancement of PDAC. The ToppGene (ToppFun) ([60]https://toppgene.cchmc.org/enrichment.jsp)^ [61]20 is an online resource that adds tools for functional annotation and bioinformatics analysis. Both GO categories and REACTOME pathway enrichment analysis were implemented using ToppGene to inform the functions of these DEGs. P < 0.05 was considered to indicate a statistically significant difference. PPI network construction and module analysis The online database IID interactome ([62]http://iid.ophid.utoronto.ca//)^ [63]21 was used to construct a PPI network of the proteins encoded by DEGs. Then, Cytoscape software (Version 3.8.1)^ [64]22 was applied to perform protein interaction association network analysis with confidence score > 0.4 and analyze the interaction correlation of the candidate proteins encoded by the DEGs in PDAC. Next, the Network Analyzer Cytoscape plug-in was applied to calculate node degree,^ [65]23 betweenness centrality,^ [66]24 stress centrality,^ [67]25 and closeness centrality.^ [68]26 Finally, the PEWCC1 ([69]http://apps.cytoscape.org/apps/PEWCC1)^ [70]27 module for Cytoscape was used to collect the significant modules in the PPI network complex. Construction of miRNA-DEG regulatory network The miRNet database ([71]https://www.mirnet.ca/)^ [72]28 is a database containing miRNAs involved in various diseases. The miRNAs related to PDAC were searched from miRNet database. Through getting the intersection of the miRNAs and the DEGs, the miRNA-DEG regulatory relationships were selected. Finally, miRNA-DEG regulatory network was built using Cytoscape software. Construction of TF-DEG regulatory network The NetworkAnalyst database ([73]https://www.networkanalyst.ca/)^ [74]29 is a database containing TFs involved in various diseases. The TFs related to PDAC were searched from TF database. Through getting the intersection of the TFs and the DEGs, the TF-DEG regulatory relationships were selected. Finally, TF-DEG regulatory network was built using Cytoscape software. Validation of hub genes After hub genes identified from expression profiling by high-throughput sequencing data set, UALCAN ([75]http://ualcan.path.uab.edu/analysis.html)^ [76]30 was used to validate the selected upregulated and downregulated hub genes. UALCAN is an online tool for gene expression analysis between PDAC and normal data from the Cancer Genome Atlas (TCGA). It adds data such as gene expression, tumor staging, and survival period for PDAC. cBioPortal is an online platform ([77]http://www.cbioportal.org)^ [78]31 for gene alteration of hub genes analysis from TCGA. Human protein atlas is an online database (HPA, [79]www.proteinatlas.org)^ [80]32 for protein expression analysis between PDAC and normal data from TCGA. TIMER is an online platform ([81]https://cistrome.shinyapps.io/timer/)^ [82]33 for immune infiltration analysis from TCGA. To explore diagnostic biomarkers of PDAC, we used the above hub genes as candidates to find their diagnostic value based on generalized linear model (GLM).^ [83]34 The pROC in R was used for receiver operating characteristic (ROC) curve analysis.^ [84]34 In brief, half of the samples (PDAC = 142, controls = 59) were aimlessly distributed as the training set and remaining data were used as the test set, which were used to set up a model. An ROC curve analysis was tested to calculate the specificity and sensitivity of the GLM prediction model. The area under the curve (AUC) was used to determine the diagnostic efficiency of the classifier. Results Identification of DEGs We analyzed the DEGs of [85]GSE133684 by using the limma package. We used P < 0.05 and |logFC| ⩾ 1 as the cutoff criteria. We screened 463 DEGs, including 232 upregulated genes and 231 downregulated genes in PDAC samples compared with normal control samples, which are listed in [86]Table 1. We identified all the DEGs that were shown in the above volcano map according to the value of |logFC| (shown in [87]Figure 1) and then displayed the DEGs on a heatmap (shown in [88]Figure 2). Table 1. The statistical metrics for key differentially expressed genes (DEGs). Gene Symbol logFC p Value adj.P.Val t value Regulation Gene Name DAP 0.729809 3.54E-14 2.59E-11 7.862623 Up death associated protein MTRNR2L2 1.55786 4.87E-14 3.22E-11 7.816552 Up MT-RNR2 like 2 ICA1 1.027176 1.66E-13 9E-11 7.636838 Up islet cell autoantigen 1 KRT8 1.61503 6.94E-13 3.01E-10 7.423576 Up keratin 8 MAP1LC3B2 1.050642 1.03E-11 3.21E-09 7.008711 Up microtubule associated protein 1 light chain 3 beta 2 KRT18 1.317775 1.21E-11 3.67E-09 6.984018 Up keratin 18 DBN1 0.680188 1.71E-11 4.78E-09 6.928904 Up drebrin 1 MAP1B 0.804673 2.02E-11 5.5E-09 6.902127 Up microtubule associated protein 1B IGFBP2 1.26743 2.04E-11 5.5E-09 6.900692 Up insulin like growth factor binding protein 2 KRT19 1.682062 3.2E-11 8.32E-09 6.828975 Up keratin 19 ARNTL2 1.064741 3.25E-11 8.42E-09 6.826429 Up aryl hydrocarbon receptor nuclear translocator like 2 MND1 1.050388 6.48E-11 1.51E-08 6.714983 Up meiotic nuclear divisions 1 LCN2 1.195504 1.23E-10 2.65E-08 6.610378 Up lipocalin 2 HP 1.105468 1.98E-10 4.01E-08 6.531824 Up haptoglobin GOLIM4 0.730931 1.99E-10 4.01E-08 6.531295 Up golgi integral membrane protein 4 FGB 1.281458 2.04E-10 4.09E-08 6.526862 Up fibrinogen beta chain TCEAL3 0.698058 2.11E-10 4.19E-08 6.521292 Up transcription elongation factor A like 3 H3P47 0.806164 3.14E-10 5.88E-08 6.455108 Up H3 histone pseudogene 47 CD27-AS1 1.127104 3.53E-10 6.52E-08 6.435648 Up CD27 antisense RNA 1 LSMEM1 1.300595 3.94E-10 7.16E-08 6.417125 Up leucine rich single-pass membrane protein 1 CD63 0.638758 4.97E-10 8.71E-08 6.378004 Up CD63 molecule MAOB 1.081308 7.82E-10 1.29E-07 6.301015 Up monoamine oxidase B FGG 1.037158 8.4E-10 1.36E-07 6.288927 Up fibrinogen gamma chain LOC105370027 1.046446 1.06E-09 1.66E-07 6.248715 Up uncharacterized LOC105370027 H2BC17 0.973199 1.13E-09 1.75E-07 6.237457 Up H2B clustered histone 17 ZFPM2 1.167509 1.26E-09 1.93E-07 6.218913 Up zinc finger protein, FOG family member 2 UBE2Q2P1 0.75226 2.34E-09 3.3E-07 6.111953 Up ubiquitin conjugating enzyme E2 Q2 pseudogene 1 GTF3C6 0.66658 2.41E-09 3.36E-07 6.107154 Up general transcription factor IIIC subunit 6 FGA 1.058162 2.56E-09 3.52E-07 6.096366 Up fibrinogen alpha chain H4C15 0.646131 3.44E-09 4.5E-07 6.044383 Up H4 clustered histone 15 TAX1BP3 0.761452 3.74E-09 4.85E-07 6.029641 Up Tax1 binding protein 3 RET 0.748469 4.44E-09 5.62E-07 5.999495 Up ret proto-oncogene HTATIP2 0.696367 4.69E-09 5.87E-07 5.989713 Up HIV-1 Tat interactive protein 2 MCEMP1 1.055887 7.5E-09 8.94E-07 5.906144 Up mast cell expressed membrane protein 1 APOB 0.984349 8.66E-09 1.02E-06 5.88037 Up apolipoprotein B TPM2 0.808631 9.37E-09 1.09E-06 5.866037 Up tropomyosin 2 MYL6B 0.735111 9.66E-09 1.12E-06 5.860685 Up myosin light chain 6B PRELID2 1.007003 1.01E-08 1.16E-06 5.851789 Up PRELI domain containing 2 STAC 0.70663 1.08E-08 1.24E-06 5.839882 Up SH3 and cysteine rich domain H4C14 0.640786 1.16E-08 1.32E-06 5.826872 Up H4 clustered histone 14 KLHDC8B 0.931058 1.17E-08 1.32E-06 5.825909 Up kelch domain containing 8B HRG 1.25373 1.49E-08 1.63E-06 5.782449 Up histidine rich glycoprotein DDAH1 0.960624 2.46E-08 2.46E-06 5.689878 Up dimethylargininedimethylaminohydrolase 1 C19orf33 1.048033 2.73E-08 2.69E-06 5.670561 Up chromosome 19 open reading frame 33 FAH 0.995091 3.02E-08 2.92E-06 5.651858 Up fumarylacetoacetate hydrolase DCBLD2 0.939546 3.06E-08 2.96E-06 5.649534 Up discoidin, CUB and LCCL domain containing 2 IFI27L2 0.822377 3.76E-08 3.53E-06 5.611483 Up interferon alpha inducible protein 27 like 2 PTGES3L 0.989667 3.95E-08 3.7E-06 5.602037 Up prostaglandin E synthase 3 like TIMP1 0.829195 4.17E-08 3.89E-06 5.591888 Up TIMP metallopeptidase inhibitor 1 SNURF 0.743535 4.2E-08 3.91E-06 5.590685 Up SNRPN upstream reading frame CMTM2 0.918208 4.76E-08 4.36E-06 5.567227 Up CKLF like MARVEL transmembrane domain containing 2 MDK 0.797135 6.31E-08 5.6E-06 5.513868 Up midkine BCAP31 0.771229 6.77E-08 5.93E-06 5.500637 Up B cell receptor associated protein 31 RAB32 0.725327 7.54E-08 6.49E-06 5.480174 Up RAB32, member RAS oncogene family PCP2 0.848727 7.79E-08 6.64E-06 5.474068 Up Purkinje cell protein 2 AOPEP 0.665257 9.03E-08 7.61E-06 5.445854 Up aminopeptidase O (putative) FKBP1B 1.079675 9.08E-08 7.64E-06 5.444649 Up FKBP prolylisomerase 1B UBE2C 0.919203 9.19E-08 7.7E-06 5.442432 Up ubiquitin conjugating enzyme E2 C CETN2 0.907963 9.64E-08 7.99E-06 5.433373 Up centrin 2 TREML3P 0.736245 1.04E-07 8.51E-06 5.418563 Up triggering receptor expressed on myeloid cells like 3, pseudogene CLMAT3 0.914772 1.09E-07 8.91E-06 5.409301 Up colorectal liver metastasis associated transcript 3 TOM1L1 1.010788 1.25E-07 1E-05 5.382976 Up target of myb1 like 1 membrane trafficking protein RABAC1 0.685861 1.28E-07 1.02E-05 5.378165 Up Rab acceptor 1 PTPRN 0.756419 1.8E-07 1.35E-05 5.312969 Up protein tyrosine phosphatase receptor type N CCDC9B 0.764226 1.89E-07 1.42E-05 5.302684 Up coiled-coil domain containing 9B UNC13B 0.669902 2.49E-07 1.8E-05 5.248667 Up unc-13 homolog B APOH 0.937929 2.62E-07 1.88E-05 5.238638 Up apolipoprotein H MCM10 0.778282 2.66E-07 1.9E-05 5.236183 Up minichromosome maintenance 10 replication initiation factor H2BC11 0.672283 2.8E-07 1.98E-05 5.226015 Up H2B clustered histone 11 EZH2 0.665264 3E-07 2.1E-05 5.211928 Up enhancer of zeste 2 polycomb repressive complex 2 subunit H2AC13 0.672944 3.06E-07 2.14E-05 5.208195 Up H2A clustered histone 13 NCBP2L 0.690397 3.18E-07 2.2E-05 5.200769 Up nuclear cap binding protein subunit 2 like CCNB1 0.69638 3.18E-07 2.2E-05 5.200386 Up cyclin B1 PKD2 0.747713 3.28E-07 2.25E-05 5.194336 Up polycystin 2, transient receptor potential cation channel LOC100130357 0.908199 3.58E-07 2.43E-05 5.176869 Up uncharacterized LOC100130357 ORM1 0.845653 4.18E-07 2.79E-05 5.145905 Up orosomucoid 1 CDR2L 0.75789 4.37E-07 2.89E-05 5.137166 Up cerebellar degeneration related protein 2 like H2AJ 0.700133 4.63E-07 3.02E-05 5.125431 Up H2A.J histone TPM1 0.669813 4.65E-07 3.03E-05 5.124861 Up tropomyosin 1 ACOT7 0.80117 5.34E-07 3.4E-05 5.097055 Up acyl-CoA thioesterase 7 AP1M2 0.962099 5.68E-07 3.57E-05 5.084413 Up adaptor related protein complex 1 subunit mu 2 AVEN 0.668545 6.52E-07 4.05E-05 5.056569 Up apoptosis and caspase activation inhibitor DNAH2 0.732007 6.75E-07 4.17E-05 5.049466 Up dynein axonemal heavy chain 2 TRPC2 0.85544 7.09E-07 4.35E-05 5.039399 Up transient receptor potential cation channel subfamily C member 2 (pseudogene) RND3 0.841233 7.53E-07 4.58E-05 5.027115 Up Rho family GTPase 3 PPP1R14A 0.745833 7.86E-07 4.75E-05 5.018397 Up protein phosphatase 1 regulatory inhibitor subunit 14A TGFB3 0.835809 7.9E-07 4.76E-05 5.01733 Up transforming growth factor beta 3 TPST1 0.819069 8.34E-07 4.99E-05 5.006228 Up tyrosylproteinsulfotransferase 1 VNN1 0.865209 1.1E-06 6.32E-05 4.949468 Up vanin 1 MIR1282 1.063689 1.12E-06 6.41E-05 4.945828 Up microRNA 1282 APOA2 0.724038 1.23E-06 6.93E-05 4.92633 Up apolipoprotein A2 FAM92A 0.677465 1.25E-06 7.03E-05 4.922308 Up family with sequence similarity 92 member A MSANTD3 0.66954 1.29E-06 7.18E-05 4.916615 Up Myb/SANT DNA binding domain containing 3 GRK4 0.900233 1.37E-06 7.55E-05 4.904444 Up G protein-coupled receptor kinase 4 TSPAN15 0.802125 1.4E-06 7.7E-05 4.899117 Up tetraspanin 15 PTGER3 0.731073 1.54E-06 8.36E-05 4.879106 Up prostaglandin E receptor 3 MITF 0.871653 1.63E-06 8.76E-05 4.867297 Up melanocyte inducing transcription factor MMP1 0.771433 1.75E-06 9.33E-05 4.852725 Up matrix metallopeptidase 1 MAL2 0.749667 1.81E-06 9.62E-05 4.845684 Up mal, T cell differentiation protein 2 (gene/pseudogene) CTPS2 0.67219 1.83E-06 9.71E-05 4.843038 Up CTP synthase 2 LOC101929538 0.711706 1.9E-06 9.98E-05 4.835864 Up uncharacterized LOC101929538 OR2B6 0.909758 1.94E-06 0.000102 4.831266 Up olfactory receptor family 2 subfamily B member 6 C20orf96 0.740435 2.13E-06 0.000109 4.811175 Up chromosome 20 open reading frame 96 MPZL3 0.734878 2.16E-06 0.000111 4.808022 Up myelin protein zero like 3 LOC101927420 0.734878 2.29E-06 0.000116 4.79601 Up uncharacterized LOC101927420 EPDR1 0.769808 2.47E-06 0.000125 4.779781 Up ependymin related 1 FHL2 0.853097 2.75E-06 0.000137 4.756748 Up four and a half LIM domains 2 LAPTM4B 0.92193 3.02E-06 0.000148 4.736673 Up lysosomal protein transmembrane 4 beta ARG2 1.000424 3.03E-06 0.000149 4.735971 Up arginase 2 ADAM22 0.710055 3.12E-06 0.000152 4.729888 Up ADAM metallopeptidase domain 22 GPC5 0.6499 3.29E-06 0.000159 4.718778 Up glypican 5 DERA 0.676038 3.31E-06 0.000161 4.716998 Up deoxyribose-phosphate aldolase OXTR 0.917126 3.55E-06 0.00017 4.70246 Up oxytocin receptor PROK2 0.789874 3.77E-06 0.000179 4.689155 Up prokineticin 2 CNN1 0.901951 3.81E-06 0.00018 4.686924 Up calponin 1 KRT7 0.904375 4.03E-06 0.000188 4.674982 Up keratin 7 CENPI 0.730063 4.07E-06 0.00019 4.672762 Up centromere protein I LINC01684 0.731662 4.19E-06 0.000195 4.666397 Up long intergenic non-protein coding RNA 1684 KCNMB1 0.752736 4.56E-06 0.000209 4.647801 Up potassium calcium-activated channel subfamily M regulatory beta subunit 1 LACTB2 0.695963 4.69E-06 0.000215 4.641781 Up lactamase beta 2 BEST3 0.711771 4.73E-06 0.000216 4.640144 Up bestrophin 3 C5orf30 0.731538 5.21E-06 0.000236 4.618767 Up chromosome 5 open reading frame 30 SMPD1 0.834518 5.41E-06 0.000244 4.610568 Up sphingomyelinphosphodiesterase 1 ANO10 0.657575 5.46E-06 0.000246 4.608531 Up anoctamin 10 GINS1 0.706019 5.61E-06 0.000252 4.602785 Up GINS complex subunit 1 TGFB1I1 0.782636 6.07E-06 0.000269 4.585606 Up transforming growth factor beta 1 induced transcript 1 CABLES1 0.659259 6.29E-06 0.000277 4.577514 Up Cdk5 and Abl enzyme substrate 1 ROBO1 0.71818 7.03E-06 0.000304 4.552913 Up roundabout guidance receptor 1 BUB1 0.667318 7.42E-06 0.000319 4.541048 Up BUB1 mitotic checkpoint serine/threonine kinase FUNDC1 0.767386 7.66E-06 0.000328 4.533938 Up FUN14 domain containing 1 CRTC3-AS1 0.751802 7.83E-06 0.000334 4.529039 Up CRTC3 antisense RNA 1 DMC1 0.841001 7.84E-06 0.000334 4.528894 Up DNA meiotic recombinase 1 ZSCAN16-AS1 0.738009 8.09E-06 0.000344 4.521862 Up ZSCAN16 antisense RNA 1 SCARF1 0.676906 8.39E-06 0.000355 4.513776 Up scavenger receptor class F member 1 ACCSL 0.65649 8.65E-06 0.000365 4.50688 Up 1-aminocyclopropane-1-carboxylate synthase homolog (inactive) like CXCL3 0.778559 1.03E-05 0.000421 4.468754 Up C-X-C motif chemokine ligand 3 LINC00892 0.819555 1.05E-05 0.00043 4.462734 Up long intergenic non-protein coding RNA 892 RNF208 0.841349 1.06E-05 0.000433 4.461088 Up ring finger protein 208 EAF2 0.668192 1.15E-05 0.000464 4.443023 Up ELL associated factor 2 LAMB2 0.699363 1.16E-05 0.000468 4.44064 Up laminin subunit beta 2 LOXL3 0.736971 1.19E-05 0.000477 4.435804 Up lysyl oxidase like 3 CEACAM6 0.828845 1.22E-05 0.000489 4.429132 Up CEA cell adhesion molecule 6 HPD 0.801889 1.29E-05 0.00051 4.417691 Up 4-hydroxyphenylpyruvate dioxygenase TMEM67 0.706644 1.3E-05 0.000511 4.415933 Up transmembrane protein 67 LINC00534 0.991484 1.3E-05 0.000511 4.415737 Up long intergenic non-protein coding RNA 534 TYMS 0.660517 1.31E-05 0.000514 4.413975 Up thymidylatesynthetase ZGLP1 0.781496 1.36E-05 0.000529 4.405803 Up zinc finger GATA like protein 1 GNG8 0.74057 1.51E-05 0.000581 4.381524 Up G protein subunit gamma 8 MT1X 0.78313 1.59E-05 0.000609 4.368771 Up metallothionein 1X EVA1B 0.700855 1.71E-05 0.000642 4.352699 Up eva-1 homolog B FRMD3 0.658149 1.91E-05 0.000704 4.326801 Up FERM domain containing 3 ADAMTS1 0.710457 1.94E-05 0.000709 4.324203 Up ADAM metallopeptidase with thrombospondin type 1 motif 1 ACTR3B 0.733415 2.06E-05 0.00075 4.309603 Up actin related protein 3B METTL22 0.69995 2.27E-05 0.00082 4.286931 Up methyltransferase like 22 WASF1 0.742178 2.34E-05 0.000842 4.280128 Up WASP family member 1 LINC00548 0.776323 2.51E-05 0.000886 4.264099 Up long intergenic non-protein coding RNA 548 DTL 0.641962 2.52E-05 0.00089 4.262623 Up denticleless E3 ubiquitin protein ligase homolog NT5DC2 0.692809 2.71E-05 0.000939 4.245871 Up 5'-nucleotidase domain containing 2 VEGFC 0.669813 2.88E-05 0.000989 4.231356 Up vascular endothelial growth factor C MAGI2 0.735314 2.89E-05 0.00099 4.230904 Up membrane associated guanylate kinase, WW and PDZ domain containing 2 LINC00211 0.894161 2.93E-05 0.001001 4.227722 Up long intergenic non-protein coding RNA 211 SPHK1 0.676802 3.04E-05 0.001028 4.219226 Up sphingosine kinase 1 ZNF529-AS1 0.661567 3.35E-05 0.001114 4.196168 Up ZNF529 antisense RNA 1 ADAMTS5 0.660099 3.39E-05 0.001123 4.193506 Up ADAM metallopeptidase with thrombospondin type 1 motif 5 DYNC1I1 0.795012 3.39E-05 0.001124 4.193181 Up dynein cytoplasmic 1 intermediate chain 1 CCDC3 0.674572 3.42E-05 0.001131 4.191397 Up coiled-coil domain containing 3 YIF1B 0.743761 3.43E-05 0.001133 4.190185 Up Yip1 interacting factor homolog B, membrane trafficking protein PRKAR1B 0.701104 3.54E-05 0.001164 4.182731 Up protein kinase cAMP-dependent type I regulatory subunit beta NMNAT3 0.641441 4.03E-05 0.001305 4.151903 Up nicotinamide nucleotide adenylyltransferase 3 TSPAN13 0.656865 4.05E-05 0.00131 4.150707 Up tetraspanin 13 POLR3G 0.862253 4.19E-05 0.001346 4.143028 Up RNA polymerase III subunit G TMEM158 0.832551 4.39E-05 0.0014 4.131626 Up transmembrane protein 158 (gene/pseudogene) CYTOR 0.669042 4.41E-05 0.001403 4.130782 Up cytoskeleton regulator RNA FN3K 0.715739 4.44E-05 0.001411 4.128739 Up fructosamine 3 kinase CENPU 0.685833 4.48E-05 0.001421 4.126825 Up centromere protein U ANXA3 0.642891 4.52E-05 0.001431 4.124872 Up annexin A3 PGLYRP1 0.743358 4.53E-05 0.001432 4.124178 Up peptidoglycan recognition protein 1 LINC00853 0.886342 4.73E-05 0.001482 4.113907 Up long intergenic non-protein coding RNA 853 C21orf58 0.673046 5E-05 0.001552 4.10054 Up chromosome 21 open reading frame 58 PHACTR3 0.768701 5.12E-05 0.001582 4.094798 Up phosphatase and actin regulator 3 CYSTM1 0.639491 6.02E-05 0.001809 4.055347 Up cysteine rich transmembrane module containing 1 E2F1 0.689528 6.28E-05 0.001867 4.045197 Up E2F transcription factor 1 CTNS 0.723506 6.31E-05 0.001876 4.043771 Up cystinosin, lysosomalcystine transporter LUZP6 0.784849 6.33E-05 0.00188 4.043183 Up leucine zipper protein 6 LY6G6F-LY6G6D 0.697512 6.82E-05 0.002 4.024994 Up LY6G6F-LY6G6D readthrough DRC7 0.641026 6.97E-05 0.00203 4.019452 Up dynein regulatory complex subunit 7 SPINT2 0.716213 7.44E-05 0.002142 4.003447 Up serine peptidase inhibitor, Kunitz type 2 TST 0.653129 8.57E-05 0.002428 3.968702 Up thiosulfate sulfurtransferase PBLD 0.728909 9.82E-05 0.002708 3.934854 Up phenazine biosynthesis like protein domain containing COL6A3 0.800552 0.000106 0.002866 3.916014 Up collagen type VI alpha 3 chain SMYD3 0.658545 0.00011 0.002954 3.906774 Up SET and MYND domain containing 3 SEPTIN4 0.678613 0.000113 0.003014 3.900217 Up septin 4 ADAM32 0.660263 0.000114 0.003032 3.898284 Up ADAM metallopeptidase domain 32 ADH1B 0.683312 0.000115 0.003044 3.896241 Up alcohol dehydrogenase 1B (class I), beta polypeptide TTLL7 0.772356 0.000116 0.003081 3.892908 Up tubulin tyrosine ligase like 7 ME1 0.679181 0.000119 0.003134 3.887332 Up malic enzyme 1 PADI4 0.638723 0.000119 0.00315 3.885738 Up peptidyl arginine deiminase 4 CIDECP1 0.65588 0.000123 0.003226 3.877866 Up cell death inducing DFFA like effector c pseudogene 1 CD151 0.680244 0.000133 0.003439 3.859108 Up CD151 molecule (Raph blood group) ETV4 0.762875 0.000137 0.003518 3.851736 Up ETS variant transcription factor 4 MYOM1 0.712787 0.000141 0.003611 3.843573 Up myomesin 1 MSANTD3-TMEFF1 0.694055 0.000161 0.00403 3.810035 Up MSANTD3-TMEFF1 readthrough GLA 0.768164 0.000169 0.004193 3.797347 Up galactosidase alpha TRHDE 0.673175 0.000173 0.004275 3.791127 Up thyrotropin releasing hormone degrading enzyme CCT6P3 0.64622 0.000176 0.00433 3.786849 Up chaperonin containing TCP1 subunit 6 pseudogene 3 DNAH14 0.67538 0.000197 0.004737 3.757991 Up dynein axonemal heavy chain 14 PLEKHA8P1 0.678922 0.000198 0.004758 3.756381 Up pleckstrin homology domain containing A8 pseudogene 1 MIR646HG 0.725938 0.0002 0.004796 3.753511 Up MIR646 host gene TMEFF1 0.71416 0.000213 0.005026 3.73756 Up transmembrane protein with EGF like and two follistatin like domains 1 DPY19L2 0.678632 0.000214 0.005044 3.736377 Up dpy-19 like 2 ERC2 0.640215 0.000232 0.005396 3.715528 Up ELKS/RAB6-interacting/CAST family member 2 PLA2G4A 0.672732 0.000232 0.005396 3.715504 Up phospholipase A2 group IVA ZC3HAV1L 0.67853 0.000241 0.005556 3.705049 Up zinc finger CCCH-type containing, antiviral 1 like AQP10 0.702387 0.000255 0.005825 3.690433 Up aquaporin 10 PRTFDC1 0.732046 0.000266 0.006032 3.67956 Up phosphoribosyltransferase domain containing 1 SERPINE2 0.708281 0.000278 0.006263 3.667198 Up serpin family E member 2 PRR16 0.647548 0.000365 0.007821 3.594668 Up proline rich 16 ACER2 0.714054 0.000441 0.009068 3.543878 Up alkaline ceramidase 2 THEM5 0.68475 0.000632 0.012136 3.44491 Up thioesterase superfamily member 5 MS4A3 0.669703 0.000713 0.013422 3.41125 Up membrane spanning 4-domains A3 CLEC2L 0.667059 0.000745 0.013903 3.398829 Up C-type lectin domain family 2 member L TRPC6 0.669122 0.000816 0.014941 3.373194 Up transient receptor potential cation channel subfamily C member 6 LINC01089 0.641558 0.00098 0.017284 3.320844 Up long intergenic non-protein coding RNA 1089 GRB14 0.73252 0.001457 0.023689 3.205476 Up growth factor receptor bound protein 14 MYEOV 0.66784 0.001553 0.024891 3.186553 Up myeloma overexpressed TNNC2 0.681795 0.001798 0.027848 3.142855 Up troponin C2, fast skeletal type PLAAT1 0.716924 0.001991 0.030092 3.112202 Up phospholipase A and acyltransferase 1 INKA2-AS1 0.64851 0.002272 0.033302 3.072049 Up INKA2 antisense RNA 1 DEFA1 0.710406 0.002482 0.035699 3.044927 Up defensin alpha 1 LYPLAL1-DT 0.653678 0.00251 0.035991 3.041436 Up LYPLAL1 divergent transcript G0S2 0.666254 0.003148 0.04269 2.970966 Up G0/G1 switch 2 LOC105371967 0.715866 0.00336 0.044907 2.950485 Up uncharacterized LOC105371967 FBXO7 -1.02578 4.57E-31 2.47E-26 -12.6471 Down F-box protein 7 CD44 -0.77354 1.37E-24 3.7E-20 -10.9533 Down CD44 molecule (Indian blood group) BNIP3L -1.11652 7.58E-24 1.37E-19 -10.7506 Down BCL2 interacting protein 3 like ITGA4 -0.7155 7.16E-22 6.46E-18 -10.202 Down integrin subunit alpha 4 SRRM2 -0.7545 2.82E-21 1.74E-17 -10.0332 Down serine/arginine repetitive matrix 2 IL7R -0.9167 3.22E-21 1.74E-17 -10.0169 Down interleukin 7 receptor HLA-DRA -0.72512 6.41E-21 2.89E-17 -9.93149 Down major histocompatibility complex, class II, DR alpha AHNAK -1.08285 1.37E-20 5.71E-17 -9.83691 Down AHNAK nucleoprotein SESN3 -0.83384 3.7E-20 1.34E-16 -9.71209 Down sestrin 3 BTG1 -0.67464 8.57E-20 2.9E-16 -9.606 Down BTG anti-proliferation factor 1 TCF7 -1.05537 9.82E-20 3.13E-16 -9.58878 Down transcription factor 7 PTPRC -0.79038 1.95E-19 5.55E-16 -9.50153 Down protein tyrosine phosphatase receptor type C STK17B -0.6627 8.27E-19 1.95E-15 -9.31582 Down serine/threonine kinase 17b IKZF3 -0.84512 4.27E-18 9.64E-15 -9.10211 Down IKAROS family zinc finger 3 OGT -0.85075 8.43E-18 1.83E-14 -9.01274 Down O-linked N-acetylglucosamine (GlcNAc) transferase MALAT1 -1.15502 1.98E-17 4.04E-14 -8.89988 Down metastasis associated lung adenocarcinoma transcript 1 MBNL3 -0.85006 2.01E-17 4.04E-14 -8.89733 Down muscleblind like splicing regulator 3 TXNIP -0.69647 3.04E-17 5.67E-14 -8.8425 Down thioredoxin interacting protein SLC38A1 -0.674 7.23E-17 1.22E-13 -8.72615 Down solute carrier family 38 member 1 NCKAP1L -0.66777 7.45E-17 1.22E-13 -8.72221 Down NCK associated protein 1 like PAX5 -1.15676 2.44E-16 3.67E-13 -8.56139 Down paired box 5 TNRC6B -0.80631 3.35E-16 4.86E-13 -8.51801 Down trinucleotide repeat containing adaptor 6B ATM -0.65967 4.2E-16 5.83E-13 -8.48699 Down ATM serine/threonine kinase HLA-DPA1 -0.67781 1.41E-15 1.82E-12 -8.31961 Down major histocompatibility complex, class II, DP alpha 1 FAM102A -0.76298 1.5E-15 1.89E-12 -8.31093 Down family with sequence similarity 102 member A DYRK2 -0.69741 1.54E-15 1.89E-12 -8.30769 Down dual specificity tyrosine phosphorylation regulated kinase 2 STRADB -0.88854 2.32E-15 2.7E-12 -8.24996 Down STE20 related adaptor beta RNF213 -0.78696 2.36E-15 2.7E-12 -8.2476 Down ring finger protein 213 RPL10 -0.68279 2.4E-15 2.7E-12 -8.24564 Down ribosomal protein L10 EEF1A1 -0.93399 4.56E-15 4.75E-12 -8.15527 Down eukaryotic translation elongation factor 1 alpha 1 RPL23A -0.69095 5.13E-15 5.14E-12 -8.13875 Down ribosomal protein L23a RPL37 -0.68343 6.21E-15 5.9E-12 -8.11176 Down ribosomal protein L37 HBB -1.18457 1.01E-14 9.1E-12 -8.04285 Down hemoglobin subunit beta CAMK4 -1.1638 1.36E-14 1.17E-11 -8.00017 Down calcium/calmodulin dependent protein kinase IV TENT5C -0.78619 1.47E-14 1.24E-11 -7.98892 Down terminal nucleotidyltransferase 5C BACH2 -1.06422 1.5E-14 1.24E-11 -7.98579 Down BTB domain and CNC homolog 2 TBCEL -0.64594 1.51E-14 1.24E-11 -7.98482 Down tubulin folding cofactor E like WDFY4 -0.99635 2.23E-14 1.75E-11 -7.9292 Down WDFY family member 4 RPL27A -0.6388 2.37E-14 1.83E-11 -7.92052 Down ribosomal protein L27a AAK1 -0.65765 4.11E-14 2.89E-11 -7.8413 Down AP2 associated kinase 1 MS4A1 -0.95361 4.31E-14 2.96E-11 -7.8342 Down membrane spanning 4-domains A1 DCAF12 -0.7593 5.05E-14 3.3E-11 -7.81122 Down DDB1 and CUL4 associated factor 12 KMT2D -0.87707 5.94E-14 3.83E-11 -7.78757 Down lysine methyltransferase 2D OPA1 -0.62121 6.75E-14 4.3E-11 -7.76907 Down OPA1 mitochondrial dynamin like GTPase CAMK1D -0.67422 1.2E-13 6.98E-11 -7.68504 Down calcium/calmodulin dependent protein kinase ID FAM117B -0.73486 1.2E-13 6.98E-11 -7.68502 Down family with sequence similarity 117 member B BCL11B -0.71547 1.26E-13 7.28E-11 -7.67723 Down BAF chromatin remodeling complex subunit BCL11B HBA1 -1.28343 1.39E-13 7.86E-11 -7.66283 Down hemoglobin subunit alpha 1 SEC16A -0.63051 2.06E-13 1.07E-10 -7.60474 Down SEC16 homolog A, endoplasmic reticulum export factor NOTCH2 -1.02848 3.2E-13 1.62E-10 -7.53985 Down notch receptor 2 SLC25A37 -0.97321 3.22E-13 1.62E-10 -7.53857 Down solute carrier family 25 member 37 BCL9L -0.7821 3.41E-13 1.67E-10 -7.53032 Down BCL9 like RCAN3 -0.67723 3.62E-13 1.75E-10 -7.52118 Down RCAN family member 3 RALGPS2 -0.81589 4.58E-13 2.08E-10 -7.48622 Down Ral GEF with PH domain and SH3 binding motif 2 SOX6 -1.09995 5.44E-13 2.43E-10 -7.46032 Down SRY-box transcription factor 6 TRANK1 -0.70118 6.86E-13 2.99E-10 -7.4255 Down tetratricopeptide repeat and ankyrin repeat containing 1 IL10RA -0.80857 7.25E-13 3.11E-10 -7.41713 Down interleukin 10 receptor subunit alpha TCP11L2 -0.85596 8.16E-13 3.42E-10 -7.39924 Down t-complex 11 like 2 TMC8 -0.90771 8.95E-13 3.69E-10 -7.38532 Down transmembrane channel like 8 HBA2 -1.1918 1.49E-12 5.84E-10 -7.30802 Down hemoglobin subunit alpha 2 ZBTB20 -0.68652 2.37E-12 8.9E-10 -7.23703 Down zinc finger and BTB domain containing 20 CTSB -0.68749 3.44E-12 1.27E-09 -7.17953 Down cathepsin B NSUN3 -0.97469 3.57E-12 1.3E-09 -7.17397 Down NOP2/Sun RNA methyltransferase 3 MARCHF8 -0.64518 4.02E-12 1.45E-09 -7.15528 Down membrane associated ring-CH-type finger 8 BLK -0.93113 4.45E-12 1.6E-09 -7.13963 Down BLK proto-oncogene, Src family tyrosine kinase LEF1 -0.72094 5.64E-12 1.97E-09 -7.10302 Down lymphoid enhancer binding factor 1 TLCD4 -0.94983 5.98E-12 2.04E-09 -7.09373 Down TLC domain containing 4 CBLB -0.62042 6.13E-12 2.06E-09 -7.08996 Down Cbl proto-oncogene B IFIT1B -1.14286 7.54E-12 2.43E-09 -7.05769 Down interferon induced protein with tetratricopeptide repeats 1B NLRP1 -0.70059 8.94E-12 2.81E-09 -7.03094 Down NLR family pyrin domain containing 1 SORL1 -0.74274 1.46E-11 4.32E-09 -6.95383 Down sortilin related receptor 1 IGF2R -0.81797 1.48E-11 4.34E-09 -6.95175 Down insulin like growth factor 2 receptor PLEC -0.76357 1.63E-11 4.68E-09 -6.93634 Down plectin EEF2 -0.65473 1.63E-11 4.68E-09 -6.93587 Down eukaryotic translation elongation factor 2 AFF3 -0.87612 1.65E-11 4.71E-09 -6.93416 Down AF4/FMR2 family member 3 YOD1 -0.88888 1.72E-11 4.78E-09 -6.92773 Down YOD1 deubiquitinase SFT2D2 -0.63701 2E-11 5.49E-09 -6.90414 Down SFT2 domain containing 2 NIBAN3 -0.99082 2.03E-11 5.5E-09 -6.90116 Down niban apoptosis regulator 3 POU2F2 -0.62862 2.43E-11 6.49E-09 -6.87264 Down POU class 2 homeobox 2 BCL11A -0.69858 3.3E-11 8.52E-09 -6.82374 Down BAF chromatin remodeling complex subunit BCL11A CLEC17A -0.81849 3.72E-11 9.42E-09 -6.80453 Down C-type lectin domain containing 17A ARL4A -0.79887 3.94E-11 9.88E-09 -6.79545 Down ADP ribosylation factor like GTPase 4A TLCD4-RWDD3 -0.96826 4.03E-11 1E-08 -6.79186 Down TLCD4-RWDD3 readthrough SCARNA21B -1.42152 4.37E-11 1.07E-08 -6.77868 Down small Cajal body-specific RNA 21B RANBP10 -0.73457 5.18E-11 1.22E-08 -6.75141 Down RAN binding protein 10 BMF -0.79975 6.24E-11 1.46E-08 -6.72111 Down Bcl2 modifying factor CLEC2D -0.68117 9.34E-11 2.09E-08 -6.65559 Down C-type lectin domain family 2 member D CIITA -0.75359 1.01E-10 2.25E-08 -6.64292 Down class II major histocompatibility complex transactivator TTN -1.14193 1.17E-10 2.57E-08 -6.61882 Down titin SLC4A1 -1.02319 1.56E-10 3.25E-08 -6.57166 Down solute carrier family 4 member 1 (Diego blood group) VSTM2A -0.78114 1.64E-10 3.41E-08 -6.56331 Down V-set and transmembrane domain containing 2A FGL2 -0.65079 1.81E-10 3.71E-08 -6.54693 Down fibrinogen like 2 RORA -0.65858 1.96E-10 3.99E-08 -6.53369 Down RAR related orphan receptor A TNFRSF13C -0.91687 2.97E-10 5.64E-08 -6.46456 Down TNF receptor superfamily member 13C EP400 -0.66759 3.19E-10 5.96E-08 -6.45231 Down E1A binding protein p400 PER1 -0.85447 3.87E-10 7.05E-08 -6.42021 Down period circadian regulator 1 MPEG1 -0.67212 5.39E-10 9.42E-08 -6.3641 Down macrophage expressed 1 MGAT4A -0.65772 5.49E-10 9.55E-08 -6.36127 Down alpha-1,3-mannosyl-glycoprotein 4-beta-N-acetylglucosaminyltransferase A OSBPL10 -0.76921 6.1E-10 1.04E-07 -6.34334 Down oxysterol binding protein like 10 SLC2A1 -1.01788 6.65E-10 1.13E-07 -6.32861 Down solute carrier family 2 member 1 PLAGL2 -0.65128 7.62E-10 1.27E-07 -6.30558 Down PLAG1 like zinc finger 2 WDFY2 -0.69295 7.76E-10 1.29E-07 -6.30233 Down WD repeat and FYVE domain containing 2 SLC14A1 -0.82792 7.81E-10 1.29E-07 -6.30132 Down solute carrier family 14 member 1 (Kidd blood group) VIPR1 -0.76825 8.51E-10 1.37E-07 -6.28656 Down vasoactive intestinal peptide receptor 1 TFRC -0.80086 8.7E-10 1.39E-07 -6.28281 Down transferrin receptor AGPAT4 -0.83329 9.33E-10 1.48E-07 -6.27089 Down 1-acylglycerol-3-phosphate O-acyltransferase 4 COBLL1 -0.72259 1.01E-09 1.59E-07 -6.25677 Down cordon-bleu WH2 repeat protein like 1 SPOCK2 -0.89285 1.11E-09 1.74E-07 -6.24084 Down SPARC (osteonectin), cwcv and kazal like domains proteoglycan 2 FECH -0.79692 1.35E-09 2.03E-07 -6.20743 Down ferrochelatase HLA-DMB -0.71841 1.47E-09 2.19E-07 -6.19232 Down major histocompatibility complex, class II, DM beta MXI1 -0.66288 1.67E-09 2.43E-07 -6.17102 Down MAX interactor 1, dimerization protein TRAK2 -0.99989 1.9E-09 2.73E-07 -6.14798 Down trafficking kinesin protein 2 TSPAN5 -0.68028 3.29E-09 4.34E-07 -6.05219 Down tetraspanin 5 SPTA1 -1.01751 4.06E-09 5.21E-07 -6.01532 Down spectrin alpha, erythrocytic 1 SCARNA10 -1.16787 4.37E-09 5.55E-07 -6.00252 Down small Cajal body-specific RNA 10 CXCR5 -0.91719 5.95E-09 7.25E-07 -5.9476 Down C-X-C motif chemokine receptor 5 KLK1 -0.94232 6.66E-09 8.03E-07 -5.92739 Down kallikrein 1 CTC1 -0.70188 8.37E-09 9.87E-07 -5.88644 Down CST telomere replication complex component 1 ALDH5A1 -0.71117 9.58E-09 1.11E-06 -5.86216 Down aldehyde dehydrogenase 5 family member A1 YIPF4 -0.68858 9.91E-09 1.14E-06 -5.85599 Down Yip1 domain family member 4 SZT2 -0.73017 1.03E-08 1.18E-06 -5.84867 Down SZT2 subunit of KICSTOR complex MIAT -0.63403 1.18E-08 1.33E-06 -5.82457 Down myocardial infarction associated transcript LENG8 -0.63693 1.58E-08 1.72E-06 -5.7713 Down leukocyte receptor cluster member 8 SLC7A6 -0.77445 1.83E-08 1.94E-06 -5.74413 Down solute carrier family 7 member 6 PLBD2 -0.83269 1.94E-08 2.05E-06 -5.73332 Down phospholipase B domain containing 2 RPL13A -0.62991 2.15E-08 2.21E-06 -5.71499 Down ribosomal protein L13a TNFRSF13B -0.94543 2.39E-08 2.41E-06 -5.6953 Down TNF receptor superfamily member 13B CD22 -0.67168 2.5E-08 2.49E-06 -5.68696 Down CD22 molecule SERINC5 -0.73923 2.52E-08 2.5E-06 -5.6859 Down serine incorporator 5 GPRASP1 -0.81967 2.57E-08 2.55E-06 -5.68227 Down G protein-coupled receptor associated sorting protein 1 ADA2 -0.73878 2.61E-08 2.58E-06 -5.67885 Down adenosine deaminase 2 CCR7 -0.82793 2.73E-08 2.68E-06 -5.67111 Down C-C motif chemokine receptor 7 SCARNA6 -0.77803 2.88E-08 2.81E-06 -5.66069 Down small Cajal body-specific RNA 6 CNKSR2 -0.75294 3.18E-08 3.06E-06 -5.64253 Down connector enhancer of kinase suppressor of Ras 2 VCAN -0.73858 3.74E-08 3.52E-06 -5.61242 Down versican SLC24A4 -0.87802 4.35E-08 4.03E-06 -5.58396 Down solute carrier family 24 member 4 LINC00926 -0.87511 4.52E-08 4.17E-06 -5.57692 Down long intergenic non-protein coding RNA 926 ACSL6 -0.82878 4.81E-08 4.39E-06 -5.56537 Down acyl-CoA synthetase long chain family member 6 TTC14 -0.89136 4.84E-08 4.41E-06 -5.5642 Down tetratricopeptide repeat domain 14 FCRL1 -0.86187 5.34E-08 4.82E-06 -5.54543 Down Fc receptor like 1 SLC25A39 -0.68018 5.46E-08 4.91E-06 -5.54135 Down solute carrier family 25 member 39 LY9 -0.76456 5.66E-08 5.08E-06 -5.53456 Down lymphocyte antigen 9 GOLGA8A -0.83441 7.01E-08 6.08E-06 -5.49414 Down golgin A8 family member A ATP2B1 -0.62628 7.37E-08 6.37E-06 -5.48451 Down ATPase plasma membrane Ca2+ transporting 1 PWAR5 -0.75691 8.03E-08 6.79E-06 -5.46817 Down PraderWilli/Angelman region RNA 5 MRC2 -0.81976 9.06E-08 7.63E-06 -5.44524 Down mannose receptor C type 2 SPIB -0.63152 9.37E-08 7.82E-06 -5.43865 Down Spi-B transcription factor GRINA -0.65332 1.01E-07 8.28E-06 -5.42515 Down glutamate ionotropic receptor NMDA type subunit associated protein 1 LRP1 -0.84115 1.01E-07 8.28E-06 -5.42512 Down LDL receptor related protein 1 ADAM28 -0.81306 1.11E-07 9.02E-06 -5.40656 Down ADAM metallopeptidase domain 28 TRABD2A -0.7573 1.16E-07 9.42E-06 -5.39715 Down TraB domain containing 2A PIEZO1 -0.74385 1.17E-07 9.44E-06 -5.39644 Down piezo type mechanosensitive ion channel component 1 ADAM19 -0.68425 1.47E-07 1.15E-05 -5.35189 Down ADAM metallopeptidase domain 19 PARP15 -0.71333 2.02E-07 1.5E-05 -5.29026 Down poly(ADP-ribose) polymerase family member 15 CD27 -0.71993 2.07E-07 1.53E-05 -5.28562 Down CD27 molecule NELL2 -0.67846 2.21E-07 1.62E-05 -5.27231 Down neural EGFL like 2 CD79A -0.74535 2.38E-07 1.73E-05 -5.2578 Down CD79a molecule ANKRD52 -0.63287 2.6E-07 1.87E-05 -5.24037 Down ankyrin repeat domain 52 DNHD1 -0.7211 2.8E-07 1.98E-05 -5.22571 Down dynein heavy chain domain 1 NEURL1 -0.74572 2.93E-07 2.06E-05 -5.21673 Down neuralized E3 ubiquitin protein ligase 1 CRTC1 -0.68306 3.27E-07 2.25E-05 -5.1949 Down CREB regulated transcription coactivator 1 GOLGA8B -0.84973 3.8E-07 2.56E-05 -5.16529 Down golgin A8 family member B ZNF860 -0.72407 3.83E-07 2.58E-05 -5.16356 Down zinc finger protein 860 P2RX5 -0.67155 3.84E-07 2.58E-05 -5.16328 Down purinergic receptor P2X 5 BTLA -0.73832 3.96E-07 2.65E-05 -5.15708 Down B and T lymphocyte associated OBSCN -0.80054 4.42E-07 2.91E-05 -5.13505 Down obscurin, cytoskeletal calmodulin and titin-interacting RhoGEF SEMA7A -0.6976 4.47E-07 2.94E-05 -5.13259 Down semaphorin 7A (John Milton Hagen blood group) IFFO1 -0.65589 4.96E-07 3.2E-05 -5.11184 Down intermediate filament family orphan 1 SLC38A5 -0.75551 5.64E-07 3.56E-05 -5.0858 Down solute carrier family 38 member 5 LINC02273 -0.70556 5.67E-07 3.57E-05 -5.08477 Down long intergenic non-protein coding RNA 2273 DNAH1 -0.7411 6.47E-07 4.02E-05 -5.05819 Down dynein axonemal heavy chain 1 NEU3 -0.70715 7.2E-07 4.4E-05 -5.03638 Down neuraminidase 3 POLM -0.67693 7.44E-07 4.53E-05 -5.02954 Down DNA polymerase mu RPS6KA5 -0.67198 8.28E-07 4.96E-05 -5.00771 Down ribosomal protein S6 kinase A5 PDE3B -0.68318 8.73E-07 5.17E-05 -4.99695 Down phosphodiesterase 3B COL7A1 -0.7674 9.21E-07 5.42E-05 -4.98585 Down collagen type VII alpha 1 chain HEPACAM2 -0.65213 1.02E-06 5.93E-05 -4.96469 Down HEPACAM family member 2 CELSR1 -0.64047 1.12E-06 6.39E-05 -4.94638 Down cadherin EGF LAG seven-pass G-type receptor 1 ZBTB39 -0.67388 1.13E-06 6.46E-05 -4.94372 Down zinc finger and BTB domain containing 39 MOB3B -0.68472 1.25E-06 7.03E-05 -4.92272 Down MOB kinase activator 3B RHAG -0.8349 1.26E-06 7.06E-05 -4.92115 Down Rh associated glycoprotein CR1 -0.65192 1.32E-06 7.32E-05 -4.91176 Down complement C3b/C4b receptor 1 (Knops blood group) DBP -0.65426 1.38E-06 7.62E-05 -4.90202 Down D-box binding PAR bZIP transcription factor TUBGCP6 -0.66735 1.55E-06 8.4E-05 -4.8776 Down tubulin gamma complex associated protein 6 ZNF549 -0.69296 1.59E-06 8.58E-05 -4.87232 Down zinc finger protein 549 CSF1R -0.63553 1.62E-06 8.71E-05 -4.86868 Down colony stimulating factor 1 receptor EPB42 -0.87201 1.73E-06 9.24E-05 -4.85526 Down erythrocyte membrane protein band 4.2 SCARNA7 -0.63099 1.87E-06 9.88E-05 -4.83874 Down small Cajal body-specific RNA 7 GNG7 -0.66304 1.98E-06 0.000104 -4.82656 Down G protein subunit gamma 7 ZNF589 -0.63146 2E-06 0.000105 -4.82428 Down zinc finger protein 589 GCNT2 -0.69581 2.01E-06 0.000105 -4.82357 Down glucosaminyl (N-acetyl) transferase 2 (I blood group) GPR146 -0.72697 2.04E-06 0.000106 -4.82048 Down G protein-coupled receptor 146 QSOX2 -0.66298 2.14E-06 0.000109 -4.8106 Down quiescin sulfhydryl oxidase 2 SNORA53 -0.92118 2.21E-06 0.000113 -4.80308 Down small nucleolar RNA, H/ACA box 53 SCARNA13 -0.77859 2.26E-06 0.000115 -4.79894 Down small Cajal body-specific RNA 13 ITGB2-AS1 -0.62011 3.09E-06 0.000151 -4.73185 Down ITGB2 antisense RNA 1 ESPN -0.78256 3.11E-06 0.000152 -4.73085 Down espin NEAT1 -0.72879 3.35E-06 0.000162 -4.71479 Down nuclear paraspeckle assembly transcript 1 FHDC1 -0.93149 3.52E-06 0.000169 -4.70423 Down FH2 domain containing 1 ZC3H12D -0.64158 3.53E-06 0.000169 -4.70345 Down zinc finger CCCH-type containing 12D ABCD2 -0.6691 3.76E-06 0.000178 -4.6898 Down ATP binding cassette subfamily D member 2 MCOLN1 -0.69108 3.83E-06 0.000181 -4.68576 Down mucolipin 1 NR4A1 -0.64016 4.23E-06 0.000196 -4.66458 Down nuclear receptor subfamily 4 group A member 1 SLC25A42 -0.63249 4.54E-06 0.000209 -4.64904 Down solute carrier family 25 member 42 GYPA -0.73764 5.3E-06 0.000239 -4.61504 Down glycophorin A (MNS blood group) SCARNA2 -0.67524 6.79E-06 0.000297 -4.5607 Down small Cajal body-specific RNA 2 FAM167A -0.65735 7.44E-06 0.000319 -4.54065 Down family with sequence similarity 167 member A ALDH6A1 -0.6308 8.11E-06 0.000345 -4.52128 Down aldehyde dehydrogenase 6 family member A1 CD4 -0.62279 8.14E-06 0.000345 -4.52057 Down CD4 molecule ABCA2 -0.6866 9.04E-06 0.000378 -4.49716 Down ATP binding cassette subfamily A member 2 BEND4 -0.64725 9.32E-06 0.000388 -4.49036 Down BEN domain containing 4 CENPF -0.7335 1.03E-05 0.000422 -4.46818 Down centromere protein F CD6 -0.65075 1.03E-05 0.000423 -4.46737 Down CD6 molecule KLHL3 -0.63143 1.15E-05 0.000465 -4.44229 Down kelch like family member 3 GYPB -0.73759 1.45E-05 0.00056 -4.39099 Down glycophorin B (MNS blood group) ABCC13 -0.70835 1.46E-05 0.000566 -4.38865 Down ATP binding cassette subfamily C member 13 (pseudogene) ATP13A1 -0.61946 1.58E-05 0.000606 -4.3702 Down ATPase 13A1 MYO15B -0.6612 1.65E-05 0.000624 -4.36062 Down myosin XVB CD5 -0.65427 1.89E-05 0.000697 -4.32962 Down CD5 molecule DUSP2 -0.64467 1.91E-05 0.000702 -4.32778 Down dual specificity phosphatase 2 SCML4 -0.63141 1.91E-05 0.000702 -4.32734 Down Scmpolycomb group protein like 4 PIK3IP1 -0.62444 3.82E-05 0.001247 -4.16463 Down phosphoinositide-3-kinase interacting protein 1 ALAS2 -0.66726 5.72E-05 0.001735 -4.06777 Down 5'-aminolevulinate synthase 2 RMRP -0.64882 8.71E-05 0.002461 -3.96458 Down RNA component of mitochondrial RNA processing endoribonuclease RNF182 -0.84789 0.000111 0.00298 -3.90357 Down ring finger protein 182 RNA5-8SN2 -1.28453 0.000116 0.003077 -3.89329 Down RNA, 5.8S ribosomal N2 SELENBP1 -0.63971 0.000122 0.003212 -3.87967 Down selenium binding protein 1 LINC01857 -0.67006 0.000136 0.003506 -3.85285 Down long intergenic non-protein coding RNA 1857 SCARNA5 -0.67276 0.00026 0.005928 -3.68493 Down small Cajal body-specific RNA 5 HBM -0.66252 0.001557 0.024934 -3.18581 Down hemoglobin subunit mu TUBB1 -0.63203 0.002292 0.033535 -3.06938 Down tubulin beta 1 class VI [89]Open in a new tab Figure 1. [90]Figure 1. [91]Open in a new tab Volcano plot of differentially expressed genes. Genes with a significant change of more than 2-fold were selected. Green dot represented upregulated significant genes and red dot represented downregulated significant genes. Figure 2. [92]Figure 2. [93]Open in a new tab Heat map of differentially expressed genes. Legend on the top left indicates log fold change of genes. (A1-A114 = normal control samples; B1-B284 = PDAC samples). PDAC indicates pancreatic ductal adenocarcinoma. GO analysis and pathway enrichment analysis of DEGs To symbolize the function of the DEGs and to identify important candidate pathways, GO functional enrichment analysis and REACTOME pathway enrichment analysis were performed. The results of GO categories analysis, including biological processes (BP), cellular components (CC) and molecular functions (MF), are listed in [94]Table 2. First, the upregulated genes were annotated with the BP category, including vesicle organization and secretion, whereas the downregulated genes were annotated with the GO terms, including lymphocyte activation and regulation of cell death. Second, the upregulated genes were annotated with the GO terms of the CC category, namely, secretory vesicle and whole membrane, whereas the downregulated genes were annotated with the GO terms, including cell surface and intrinsic component of plasma membrane. Third, the upregulated genes were annotated with the GO terms of the MF category such as protein dimerization activity and signaling receptor binding, whereas the downregulated genes were annotated with the GO terms, including transferase activity, transferring phosphorus-containing groups, and drug binding. The REACTOME pathway enrichment analysis showed that the genes upregulated in tumors were enriched in hemostasis and cell cycle, while the downregulated genes were enriched in adaptive immune system and transmembrane transport of small molecules ([95]Table 3). Table 2. The enriched GO terms of the up and down regulated differentially expressed genes. GO ID CATEGORY GO Name P Value FDR B&H FDR B&Y Bonferroni Gene Count Gene Up regulated genes GO:0016050 BP vesicle organization 3.92E-07 8.10E-04 7.19E-03 1.58E-03 40 LAPTM4B,CEACAM6,PTGER3,DEFA1,MAGI2,SERPINE2,GLA,PTPRN,HP,VNN1,SPHK1,FGA ,FGB,HRG,PLA2G4A,LOXL3,FGG,RAB32,WASF1,VEGFC,UNC13B,PGLYRP1,SEPTIN4,ANX A3,GRK4,APOA2,APOB,LCN2,APOH,DERA,SCARF1,TGFB3,ORM1,TIMP1,MS4A3,CYSTM1, CD63,ERC2,CD151,MCEMP1 GO:0046903 BP secretion 5.39E-06 1.17E-03 1.04E-02 2.18E-02 38 MYOM1,MAOB,CEACAM6,MDK,PTGER3,DEFA1,SERPINE2,GLA,PTPRN,HP,VNN1,SPHK1,FG A,FGB,HRG,PLA2G4A,FGG,FKBP1B,VEGFC,UNC13B,PGLYRP1,SEPTIN4,ANXA3,ICA1,AP OA2,LCN2,APOH,DERA,ARG2,TGFB3,ORM1,OXTR,TIMP1,MS4A3,CYSTM1,CD63,ERC2,MC EMP1 GO:0099503 CC secretory vesicle 1.01E-08 4.90E-06 3.31E-05 4.90E-06 32 CEACAM6,DEFA1,SERPINE2,GLA,PTPRN,HP,VNN1,SPHK1,FGA,FGB,HRG,PLA2G4A,FGG, VEGFC,UNC13B,PGLYRP1,SEPTIN4,ANXA3,ICA1,RABAC1,LCN2,APOH,DERA,TGFB3,MAL 2,ORM1,TIMP1,MS4A3,CYSTM1,CD63,SMPD1,MCEMP1 GO:0098805 CC whole membrane 2.77E-03 3.64E-02 2.47E-01 1.00E+00 29 TSPAN15,MAOB,LAPTM4B,CEACAM6,FUNDC1,PTPRN,MAP1LC3B2,VNN1,SPHK1,GOLIM4,H RG,RAB32,WASF1,UNC13B,SEPTIN4,ANXA3,ICA1,TOM1L1,AP1M2,GRB14,APOB,RET,SC ARF1,MAL2,MS4A3,CYSTM1,CD63,CTNS,MCEMP1 GO:0046983 MF protein dimerization activity 4.40E-04 9.54E-02 6.73E-01 2.86E-01 30 TPM1,TPM2,PADI4,MYOM1,MAOB,TRPC6,ACOT7,CEACAM6,ARNTL2,PRTFDC1,TYMS,H2AC 13,H2BC17,GLA,HP,H4C14,MITF,PKD2,FGG,H2BC11,TPST1,SEPTIN4,ICA1,H4C15,GR B14,E2F1,APOA2,LCN2,TGFB3,H2AJ GO:0005102 MF signaling receptor binding 4.71E-03 2.10E-01 1.00E+00 1.00E+00 30 MDK,MTRNR2L2,MAGI2,SERPINE2,GLA,PKD2,FGA,FGB,HRG,FGG,FHL2,FKBP1B,VEGFC, PROK2,PGLYRP1,CMTM2,GRB14,LAMB2,APOA2,APOB,ADAMTS5,CXCL3,ADAM22,CCNB1,T GFB1I1,TGFB3,BCAP31,IGFBP2,TIMP1,CD151 Down regulated genes GO:0046649 BP lymphocyte activation 1.37E-15 5.40E-12 4.78E-11 5.40E-12 40 HLA-DMB,HLA-DPA1,SPTA1,BCL11A,ITGA4,FGL2,CXCR5,FCRL1,PTPRC,ZC3H12D,FBXO 7,CCR7,NOTCH2,TCF7,IKZF3,POLM,CAMK4,POU2F2,BTLA,CR1,CBLB,SLC4A1,TFRC,BC L11B,CD4,CD5,CD6,MS4A1,CD22,CD27,CD44,TNFRSF13C,TNFRSF13B,CD79A,RORA,AT M,LY9,LEF1,IL7R,NCKAP1L GO:0010941 BP regulation of cell death 9.53E-05 6.03E-03 5.34E-02 3.75E-01 40 STK17B,OBSCN,ITGA4,NR4A1,STRADB,BNIP3L,PTPRC,BTG1,TMC8,FBXO7,PLAGL2,CCR 7,NOTCH2,TCF7,IKZF3,OGT,CAMK1D,BMF,NLRP1,GRINA,OPA1,EEF1A1,TXNIP,BCL11B ,IGF2R,CSF1R,CD27,NEURL1,CD44,LRP1,ATM,HBA1,HBA2,HBB,CTSB,LEF1,RPL10,IL 7R,SORL1,NCKAP1L GO:0009986 CC cell surface 2.02E-09 3.10E-07 2.08E-06 9.30E-07 35 ADAM19,HLA-DPA1,HLA-DRA,ITGA4,CXCR5,FCRL1,PTPRC,CIITA,MRC2,CCR7,NOTCH2, SEMA7A,BTLA,CR1,SLC4A1,TFRC,CD4,CD5,IGF2R,CD6,CSF1R,MS4A1,CLEC17A,CD22, CD27,GYPA,VCAN,CD44,CLEC2D,TNFRSF13C,TNFRSF13B,CD79A,LY9,CTSB,IL7R GO:0031226 CC intrinsic component of plasma membrane 5.35E-07 4.11E-05 2.76E-04 2.47E-04 43 HLA-DPA1,HLA-DRA,SPTA1,SLC38A5,ITGA4,SLC38A1,CXCR5,PTPRC,SLC24A4,TMC8,N OTCH2,VIPR1,TRABD2A,SEMA7A,BTLA,SLC7A6,CR1,MCOLN1,SLC2A1,TSPAN5,RHAG,SL C4A1,TFRC,CELSR1,CD4,CD5,IGF2R,CD6,CSF1R,P2RX5,MS4A1,SLC14A1,CD22,CD27, GYPA,GYPB,CD44,CLEC2D,LRP1,TNFRSF13B,ATP2B1,SORL1,NCKAP1L GO:0016772 MF transferase activity, transferring phosphorus-containing groups 9.72E-04 4.32E-02 3.09E-01 6.92E-01 35 ZBTB20,RPS6KA5,STK17B,OBSCN,TENT5C,TTN,PIK3IP1,BLK,STRADB,PTPRC,CIITA,F BXO7,CCR7,DYRK2,OGT,CAMK1D,CTC1,POLM,CAMK4,DUSP2,AAK1,CBLB,SLC4A1,EEF1A 1,RMRP,CD4,IGF2R,CSF1R,NEURL1,CD44,LRP1,ATM,SERINC5,SORL1,NCKAP1L GO:0008144 MF drug binding 1.15E-02 1.55E-01 1.00E+00 1.00E+00 30 ABCA2,RPS6KA5,STK17B,OBSCN,TTN,BLK,STRADB,CIITA,ALAS2,ABCD2,DYRK2,DNHD1 ,ACSL6,CAMK1D,EP400,ATP13A1,CAMK4,AAK1,NLRP1,EEF1A1,DNAH1,CSF1R,P2RX5,A TM,HBA1,HBA2,HBM,HBB,ATP2B1,EPB42 [96]Open in a new tab Biological Process(BP), Cellular Component(CC) and Molecular Functions (MF). Table 3. The enriched pathway terms of the up and down regulated differentially expressed genes. Pathway ID Pathway Name P-value FDR B&H FDR B&Y Bonferroni Gene Count Gene Up regulated genes 1269340 Hemostasis 4.28E-06 7.47E-04 5.11E-03 2.24E-03 22 GNG8,TRPC6,CEACAM6,CABLES1,SERPINE2,FGA,KCNMB1,FGB,HRG,PLA2G4A,MMP1,FGG ,VEGFC,GRB14,APOB,APOH,ZFPM2,TGFB3,ORM1,TIMP1,CD63,PRKAR1B 1269741 Cell Cycle 8.91E-04 2.12E-02 1.45E-01 4.67E-01 17 CETN2,MND1,MCM10,GINS1,TYMS,H2BC17,H4C14,BUB1,H2BC11,UBE2C,H4C15,CENPU, E2F1,CCNB1,DMC1,CENPI,H2AJ 1269507 Signaling by Rho GTPases 1.14E-02 8.42E-02 5.76E-01 1.00E+00 11 PPP1R14A,TAX1BP3,H2BC17,H4C14,BUB1,WASF1,H2BC11,H4C15,CENPU,CENPI,H2AJ 1269203 Innate Immune System 7.89E-02 2.91E-01 1.00E+00 1.00E+00 21 CEACAM6,DEFA1,GLA,HP,VNN1,FGA,FGB,FGG,WASF1,PGLYRP1,APOB,RET,LCN2,POLR3 G,DERA,ORM1,MS4A3,CYSTM1,CD63,PRKAR1B,MCEMP1 1270001 Metabolism of lipids and lipoproteins 1.52E-01 3.82E-01 1.00E+00 1.00E+00 13 ACER2,ACOT7,ME1,GLA,SPHK1,PLA2G4A,FHL2,PLAAT1,G0S2,THEM5,APOA2,APOB,SMP D1 1268677 Metabolism of proteins 3.37E-01 5.01E-01 1.00E+00 1.00E+00 21 GNG8,CETN2,FN3K,H2AC13,H2BC17,VNN1,SPHK1,H4C14,MITF,FGA,MMP1,RAB32,METT L22,DYNC1I1,H2BC11,ADAMTS1,UBE2C,H4C15,ADAMTS5,IGFBP2,AOPEP Down regulated genes 1269171 Adaptive Immune System 1.59E-03 8.64E-02 5.87E-01 7.96E-01 20 HLA-DMB,HLA-DPA1,HLA-DRA,TNRC6B,ITGA4,NR4A1,BLK,KLHL3,PTPRC,MRC2,FBXO7, RNF213,BTLA,CBLB,CD4,CD22,CLEC2D,CD79A,CTSB,RNF182 1269903 Transmembrane transport of small molecules 1.39E-02 1.95E-01 1.00E+00 1.00E+00 15 ABCA2,SLC38A5,SLC38A1,SLC24A4,ABCD2,GNG7,ATP13A1,SLC7A6,MCOLN1,SLC2A1,R HAG,SLC4A1,TFRC,SLC14A1,ATP2B1 1269203 Innate Immune System 8.82E-02 4.76E-01 1.00E+00 1.00E+00 21 RPS6KA5,SPTA1,TNRC6B,NR4A1,ADA2,FGL2,PTPRC,CAMK4,DUSP2,NLRP1,CNKSR2,CR1 ,EEF1A1,TXNIP,EEF2,CD4,IGF2R,CD44,HBB,CTSB,NCKAP1L 1269876 Vesicle-mediated transport 1.54E-01 5.50E-01 1.00E+00 1.00E+00 11 SPTA1,SEC16A,COL7A1,AAK1,TFRC,CD4,IGF2R,LRP1,HBA1,HBA2,HBB 1268854 Disease 3.21E-01 6.43E-01 1.00E+00 1.00E+00 12 RPL23A,RPL27A,RPL37,NR4A1,NOTCH2,CNKSR2,EEF2,CD4,VCAN,NEURL1,RPL13A,RPL 10 1268677 Metabolism of proteins 5.53E-01 7.60E-01 1.00E+00 1.00E+00 19 RPL23A,RPL27A,RPL37,SPTA1,MGAT4A,NEU3,ADA2,TUBB1,YOD1,SEC16A,GNG7,KLK1, COL7A1,OGT,EEF1A1,EEF2,RPL13A,RPL10,SORL1 [97]Open in a new tab Protein-protein interaction (PPI) network construction and module analysis After all the DEGs were uploaded to the online IID interactome database, the PPI network with 6188 nodes and 13 153 edges was constructed using the Cytoscape software ([98]Figure 3A). Hub genes with the node degree, betweenness centrality, stress centrality, and closeness centrality were obtained and are listed in [99]Table 4. Cathepsin B (CCNB1) and four-and-a-half LIM domains 2 (FHL2) were the upregulated genes, while major histocompatibility complex, class II, DP alpha 1 (HLA-DPA1), and tubulin beta 1 class VI (TUBB1) were the downregulated genes. Then, 2 significant modules that fulfilled the cut-off criteria, namely, PEWCC1 scores > 3 and number of nodes > 5, were screened ([100]Figure 3B and [101]C). The fibrinogen beta chain (FGB), fibrinogen alpha chain (FGA), fibrinogen gamma chain (FGG), eukaryotic translation elongation factor 1 alpha 1 (EEF1A1), ribosomal protein L13a (RPL13A), integrin subunit alpha 4 (ITGA4), ribosomal protein L27a (RPL27A), ribosomal protein L23a (RPL23A), and ribosomal protein L10 (RPL10) genes were identified in these modules. GO analysis of these genes showed that they were annotated with vesicle organization, regulation of cell death, and lymphocyte activation. In addition, the REACTOME enrichment analysis suggested that these genes were mainly involved in hemostasis, innate immune system, and disease and adaptive immune system. Figure 3. [102]Figure 3. [103]Open in a new tab PPI network and the most significant modules of DEGs. (A) The PPI network of DEGs was constructed using Cytoscape; (B) the most significant module was obtained from PPI network with 16 nodes and 44 edges for upregulated genes; (C) the most significant module was obtained from PPI network with 6 nodes and 20 edges for upregulated genes. Upregulated genes are marked in green; downregulated genes are marked in red. DEGs indicate differentially expressed genes; PPI, protein-protein interaction network. Table 4. Topology table for up and down regulated genes. Regulation Node Degree Betweenness Stress Closeness Up EZH2 350 0.076224 81130962 0.349924 Up DBN1 256 0.049032 39941040 0.348151 Up CCNB1 158 0.024471 43653864 0.313488 Up FHL2 158 0.031673 16397718 0.336762 Up E2F1 151 0.025971 16601668 0.333208 Up TPM1 134 0.022043 16976362 0.329604 Up KRT18 132 0.018793 17362522 0.338383 Up TPM2 126 0.021531 17717608 0.323503 Up FGB 115 0.021143 15804232 0.298889 Up PTGER3 113 0.019531 25585198 0.284342 Up SPINT2 108 0.023415 14310762 0.303448 Up BUB1 102 0.018982 9083534 0.319527 Up PTPRN 93 0.015139 21217898 0.283912 Up BCAP31 91 0.017733 11925460 0.323825 Up MAP1B 91 0.011535 22589676 0.310858 Up KRT8 79 0.009251 9231600 0.332081 Up TMEM67 76 0.014065 4982016 0.290838 Up RABAC1 74 0.013172 9708740 0.293098 Up APOB 72 0.011818 15182272 0.302587 Up UBE2C 69 0.00877 8892764 0.298716 Up SPHK1 68 0.011494 4951244 0.325666 Up TOM1L1 66 0.00895 6727694 0.305124 Up RET 66 0.009723 10964184 0.305199 Up WASF1 65 0.010329 14175172 0.29873 Up KRT19 64 0.008418 5490710 0.32224 Up CENPU 61 0.011081 3633098 0.296468 Up DTL 61 0.006526 9721978 0.297152 Up CETN2 60 0.009249 16418248 0.269586 Up MCM10 59 0.007694 9107150 0.300602 Up DYNC1I1 58 0.007347 6841812 0.299279 Up PLA2G4A 57 0.006497 7102868 0.307673 Up TYMS 55 0.008254 2898568 0.306378 Up MDK 54 0.007633 2641060 0.307322 Up GOLIM4 45 0.009056 6535396 0.299091 Up TGFB1I1 43 0.00576 2542056 0.317363 Up PKD2 42 0.006903 2134988 0.290538 Up FGA 41 0.004439 1801264 0.293153 Up PRKAR1B 41 0.004763 4851900 0.299424 Up ACOT7 39 0.00511 6777086 0.287968 Up FGG 37 0.002736 1188570 0.282125 Up AP1M2 37 0.007088 9431672 0.281894 Up MITF 36 0.006067 5049390 0.308118 Up SMYD3 35 0.006122 1971838 0.303776 Up ACTR3B 35 0.002767 5762182 0.273907 Up CTPS2 34 0.004516 1656234 0.297352 Up HP 33 0.004002 2476788 0.299743 Up MYL6B 33 0.001721 1494552 0.303835 Up LAMB2 33 0.003266 3787290 0.283015 Up ME1 32 0.00497 5458746 0.266142 Up FKBP1B 31 0.002492 3149134 0.263535 Up EAF2 31 0.003666 3614748 0.273181 Up CD63 30 0.002963 1542292 0.278807 Up TMEFF1 29 0.004306 1459454 0.277382 Up PHACTR3 29 0.003235 6793662 0.273205 Up MMP1 28 0.004131 1062610 0.285972 Up RAB32 28 0.004125 3089688 0.273326 Up NT5DC2 27 0.003149 4016356 0.290497 Up LAPTM4B 26 0.003861 1308630 0.280985 Up LCN2 26 0.003047 3293226 0.261121 Up GRB14 26 0.001737 2102726 0.272171 Up PRTFDC1 26 0.003559 2778424 0.248364 Up SERPINE2 25 0.003606 2767974 0.266199 Up APOA2 24 0.003639 1777538 0.282035 Up CNN1 24 0.002696 1398988 0.281984 Up MAGI2 24 0.003636 4072986 0.273277 Up PADI4 24 0.001853 2786250 0.285457 Up ARNTL2 23 0.004537 2736046 0.276156 Up MAL2 23 0.004035 3057928 0.266555 Up TAX1BP3 22 0.00296 2483404 0.27773 Up APOH 22 0.002261 1011952 0.294759 Up GLA 22 0.002185 2812520 0.25131 Up KRT7 22 0.002247 3354252 0.283132 Up ROBO1 22 0.002997 2829202 0.285181 Up ADAMTS1 21 0.003523 2991386 0.249044 Up OXTR 21 0.003005 1885024 0.254274 Up ADAM32 21 0.002751 2226220 0.244362 Up TSPAN15 20 0.002903 1636154 0.248684 Up DMC1 20 0.001518 1667540 0.255218 Up EPDR1 20 0.00263 955076 0.289735 Up LACTB2 20 0.003285 3861294 0.241888 Up UNC13B 19 0.003409 6715552 0.228252 Up ERC2 19 0.002956 2368572 0.246592 Up HRG 19 0.002437 1023636 0.273991 Up SMPD1 19 0.00236 2063048 0.275125 Up ZFPM2 19 0.001198 1822000 0.266153 Up METTL22 19 0.001598 2257038 0.269023 Up ORM1 18 0.001349 1072266 0.255461 Up ZC3HAV1 L 18 0.001054 1624786 0.281202 Up STAC 18 0.001798 2388538 0.275578 Up POLR3G 17 0.003237 9664174 0.229055 Up DDAH1 17 0.003704 1699018 0.290824 Up TIMP1 17 0.002047 1211820 0.264888 Up DERA 17 0.001512 1709944 0.240983 Up TGFB3 16 0.001732 1135010 0.26056 Up ANXA3 16 0.002306 3218636 0.263928 Up ETV4 16 0.00158 1430402 0.286767 Up RND3 16 0.001618 1798784 0.267963 Up FUNDC1 16 0.001881 5031262 0.246033 Up PPP1R14A 16 0.001348 1468196 0.269398 Up ADAM22 16 9.66E-04 1467492 0.278092 Up TRHDE 16 0.002417 2718244 0.265571 Up AOPEP 15 5.09E-04 455628 0.281778 Up LOXL3 15 0.002245 2647672 0.272735 Up TST 15 0.002644 2760934 0.24058 Up CENPI 15 6.90E-04 213372 0.26143 Up TRPC6 15 0.002982 3195972 0.236597 Up MSANTD3 14 0.001423 599870 0.282602 Up DCBLD2 14 0.001863 1414006 0.280806 Up ICA1 14 0.001837 1818980 0.253566 Up CABLES1 14 4.42E-04 448806 0.275222 Up GTF3C6 13 0.001446 393772 0.300413 Up AVEN 13 7.46E-04 364352 0.294788 Up PBLD 13 0.001491 1062854 0.235839 Up CD151 13 0.001883 1879220 0.264662 Up YIF1B 13 0.001267 1419634 0.263917 Up C5orf30 13 0.001783 1452154 0.265582 Up FRMD3 11 8.55E-04 686546 0.235579 Up FAH 11 0.001509 1294972 0.259587 Up HTATIP2 11 0.00148 1272602 0.261231 Up CYSTM1 11 0.002293 1438306 0.2152 Up MAP1LC3B2 10 0.001139 1052378 0.240608 Up MYEOV 2 5.45E-05 24642 0.227079 Up DNAH14 1 0 0 0.212349 Up MYOM1 1 0 0 0.247539 Down HEPACAM2 496 0.004088 4614336 0.259565 Down HLA-DPA1 443 0.021345 6656236 0.294395 Down DCAF12 359 0.002195 1838728 0.28738 Down POLM 259 6.45E-05 60748 0.246809 Down TUBB1 231 0.017014 13445244 0.31686 Down KMT2D 211 0.004121 6143304 0.276119 Down TNFRSF13B 208 0.004558 7473486 0.25441 Down SEC16A 199 0.024345 23456762 0.332778 Down AHNAK 158 0.012868 12992410 0.339572 Down OGT 151 0.02538 23785672 0.321486 Down TRAK2 148 0.005447 1889278 0.291359 Down PER1 143 0.007889 3343992 0.297667 Down TXNIP 142 0.005831 3723272 0.3011 Down GPRASP1 140 0.011046 5269570 0.284316 Down CTSB 139 0.011516 5746824 0.316973 Down ITGA4 132 0.110358 99169576 0.373747 Down CBLB 131 0.011859 9651222 0.31117 Down LEF1 111 0.008924 3863000 0.305275 Down PLEC 110 0.025923 21209448 0.346999 Down BNIP3L 110 0.005843 2394548 0.292184 Down CAMK1D 109 0.007993 5854240 0.294255 Down NR4A1 99 0.024611 10885038 0.333639 Down OPA1 94 0.007387 5152054 0.317804 Down EEF2 83 0.037887 47075150 0.354698 Down SEMA7A 82 0.00308 4153990 0.271146 Down RPS6KA5 78 0.010004 5767566 0.321653 Down STK17B 78 0.00446 1356036 0.284918 Down P2RX5 75 0.003754 3579124 0.255008 Down SLC2A1 68 0.003791 2359116 0.318622 Down GYPB 66 0.007619 6671358 0.262863 Down HBB 65 0.01032 10858208 0.304059 Down CD22 64 0.001809 1124092 0.279752 Down CD4 64 0.018753 14195846 0.322845 Down CD44 63 0.031474 16859342 0.344469 Down TFRC 63 0.019104 17774714 0.337221 Down PTPRC 62 0.012352 6796924 0.316681 Down CD5 62 0.00189 1129318 0.283456 Down HLA-DRA 61 0.009348 4428892 0.287995 Down HLA-DMB 60 0.002503 1238774 0.277344 Down CELSR1 60 0.003079 1745004 0.272928 Down MS4A1 58 0.0017 1236694 0.276378 Down SPTA1 55 0.007158 4511084 0.30275 Down IL7R 54 0.027811 45141856 0.327043 Down GYPA 53 8.14E-04 390278 0.260045 Down SLC4A1 53 0.002142 1341058 0.273169 Down EPB42 52 0.002323 1787000 0.260879 Down RHAG 49 0 0 0.214566 Down CD79A 49 0.008789 4491848 0.293056 Down CD6 48 0 0 0.220862 Down CSF1R 48 0.002723 5503564 0.281868 Down IKZF3 48 0.021447 15624140 0.316487 Down POU2F2 46 0.002814 4242740 0.262773 Down IGF2R 45 0.005336 8354606 0.300049 Down NSUN3 45 0 0 0.226647 Down BLK 44 0.009001 4827382 0.309644 Down VCAN 44 0.00605 2854094 0.288546 Down ADAM28 41 0 0 0.272076 Down RPL27A 41 0.009338 13186584 0.337921 Down RPL23A 39 0.022449 25286012 0.35326 Down EEF1A1 37 0.098882 1.23E + 08 0.370457 Down RPL13A 37 0.009659 13645424 0.339386 Down RPL10 35 0.066934 69760500 0.352275 Down NOTCH2 35 0.009449 4095454 0.307291 Down ATP2B1 35 0.00508 5650696 0.303835 Down SLC38A1 35 0.008346 5880382 0.292709 Down QSOX2 35 0.00527 3561792 0.291167 Down SORL1 34 0.01017 6644994 0.299569 Down LRP1 34 0.030447 29146796 0.321269 Down SRRM2 34 0.044661 52105132 0.347662 Down ABCC13 34 0 0 0.250182 Down ATM 33 0.040568 31808618 0.330997 Down FECH 33 0.007383 3340210 0.299511 Down CD27 32 0.004882 2960412 0.278142 Down VIPR1 32 0.004948 5472644 0.278694 Down AGPAT4 32 1.70E-05 28760 0.230987 Down CIITA 32 0.003427 3117716 0.289328 Down EP400 31 0.007237 9601258 0.288196 Down RORA 31 0.004548 1396286 0.302558 Down SOX6 31 0.001788 1768940 0.255661 Down CENPF 30 0.008068 6644598 0.297681 Down FAM167A 29 0.008587 3540932 0.276168 Down MXI1 28 0.001985 3293278 0.269504 Down ALDH5A1 27 0.003494 4468018 0.270813 Down RPL37 27 0.001913 3460916 0.29617 Down TSPAN5 26 0.01221 9998796 0.2873 Down PIEZO1 26 0 0 0.223188 Down BTG1 25 0.002334 3106952 0.271777 Down SPIB 25 0.001073 679476 0.280679 Down ALDH6A1 25 0.00345 3839804 0.246053 Down COL7A1 25 0.003621 3830672 0.277705 Down PAX5 25 0.008408 15230588 0.288317 Down DUSP2 24 0.003694 4774362 0.262573 Down IFFO1 24 0.004108 2648480 0.262006 Down COBLL1 24 0.00318 3800612 0.267373 Down DBP 24 0.00207 2593884 0.258708 Down SELENBP1 24 0.011965 15173332 0.275259 Down DYRK2 23 0.00992 5736550 0.313918 Down PDE3B 23 0.005858 5188848 0.268242 Down ABCA2 22 0.002246 1887488 0.270647 Down TTN 22 0.022803 22179002 0.328956 Down AAK1 22 0.001768 1776702 0.306636 Down CAMK4 21 0.001804 1122842 0.282382 Down ANKRD52 21 0.004706 3610412 0.290251 Down OBSCN 21 0.002307 1424536 0.295125 Down YOD1 21 0.003727 4452540 0.278581 Down RNF213 21 0.003281 4225796 0.28073 Down HBM 21 0.003971 2893622 0.211891 Down FAM117B 20 0.002939 3060242 0.274465 Down RANBP10 20 0.010162 16110914 0.263344 Down RALGPS2 20 0.008034 10752578 0.280386 Down CNKSR2 19 0.003716 4283878 0.253753 Down MYO15B 19 0.001548 1850770 0.253763 Down BMF 18 0.002348 3575424 0.266842 Down WDFY2 18 0.004928 3808614 0.241237 Down LENG8 18 0.006353 9944066 0.270896 Down TUBGCP6 18 0.00405 3821222 0.278155 Down NELL2 17 0.005907 5985122 0.250435 Down YIPF4 17 0.002754 3249620 0.263928 Down OSBPL10 17 0.002471 663904 0.287727 Down BACH2 16 0.002632 2910574 0.257534 Down NLRP1 16 0.003929 3755972 0.280691 Down BCL11B 2 0.001184 2467486 0.258362 Down STRADB 2 0.001267 1783952 0.276898 Down BCL11A 1 0.004017 6158386 0.273664 Down RCAN3 1 0 0 0.233006 Down KLHL3 1 0.003155 2811806 0.280551 Down CLEC2D 1 0.015351 13153684 0.270766 Down TNRC6B 1 0.010638 19725384 0.302365 Down FBXO7 1 0.011435 14645282 0.298528 Down MOB3B 1 0 0 0.202401 Down ZNF549 1 0 0 0.230523 Down VSTM2A 1 0 0 0.220343 Down CTC1 1 0 0 0.200285 Down MRC2 1 0.002911 3908206 0.26787 Down TTC14 1 0 0 0.257985 Down ADA2 1 0 0 0.257985 [104]Open in a new tab Construction of miRNA-DEG regulatory network The regulatory network of miRNA-DEG and predicted targets is presented in [105]Figure 4A. Microtubule-associated protein 1B (MAP1B) was modulated by 202 miRNAs (eg, hsa-mir-4461), CCNB1 that was modulated by 94 miRNAs (eg, hsa-mir-3928-3p), AHNAK nucleoprotein (AHNAK) that was modulated by 256 miRNAs (eg, hsa-mir-2682-5p), and lysine methyltransferase 2D (KMT2D) that was modulated by 209 miRNAs (ex: hsa-mir-1202) are listed in [106]Table 5. As a group, a total of 257 of the 463 DEGs were contained in the miRNA-DEG regulatory network. Figure 4. [107]Figure 4. [108]Open in a new tab (A) Target gene—miRNA regulatory network between target genes and miRNAs (B) Target gene—TF regulatory network between target genes and TFs. Upregulated genes are marked in green; downregulated genes are marked in red; the blue color diamond nodes represent the key miRNAs; the gray color triangle nodes represent the key TFs. Table 5. miRNA—target gene and TF—target gene interaction. Regulation Target genes Degree MicroRNA Regulation Target genes Degree TF Up COL1A1 178 hsa-mir-4492 Up IRF4 10 NFATC2 Up IRF4 140 hsa-mir-4319 Up LCK 10 YY1 Up MYBL2 83 hsa-mir-637 Up RET 10 NR2 C2 Up PRKCB 81 hsa-mir-1261 Up MAP1LC3 C 10 MAX Up IL2RB 54 hsa-mir-4300 Up IL2RB 8 PDX1 Up CCR5 50 hsa-mir-5193 Up GRAP2 8 ELK1 Up GRAP2 41 hsa-mir-3681-5p Up MYBPC2 7 RELA Up MDFI 41 hsa-mir-4441 Up MDFI 6 TFAP2A Up RET 17 hsa-mir-129-2-3p Up MYBL2 6 GATA2 Up IKZF1 16 hsa-mir-3607-3p Up CD247 5 SREBF1 Up BTK 13 hsa-mir-4667-3p Up COL1A1 5 NFYA Up LCK 6 hsa-mir-210-3p Up PRKCB 4 IRF2 Up MYBPC2 6 hsa-mir-214-3p Up IKZF1 4 E2 F6 Up CD247 4 hsa-mir-346 Up BTK 2 SOX5 Up MAP1LC3 C 2 hsa-mir-27a-3p Up CCR5 1 EGR1 Down JUN 144 hsa-mir-3943 Down ATF3 19 TP53 Down EGR1 132 hsa-mir-548e-3p Down EGR1 16 ARID3A Down ZFP36 130 hsa-mir-6077 Down JUNB 15 SRF Down FOS 105 hsa-mir-5586-5p Down FOS 13 CREB1 Down DUSP1 97 hsa-mir-4458 Down PTPRO 12 NR3 C1 Down JUNB 85 hsa-mir-3065-5p Down NR0B2 11 USF1 Down MME 54 hsa-mir-922 Down MME 9 BRCA1 Down NR4A2 50 hsa-mir-29b-2-5p Down JUN 9 SP1 Down ATF3 48 hsa-mir-5000-5p Down DUSP1 9 STAT3 Down NR4A1 43 hsa-mir-107 Down NR4A1 9 HINFP Down PCK1 38 hsa-mir-1185-1-3p Down NR4A2 7 NR2E3 Down PTPRO 18 hsa-mir-203a-3p Down PCK1 6 NR2 F1 Down APOB 17 hsa-mir-548p Down ZFP36 5 TFAP2 C Down ALB 10 hsa-mir-492 Down APOB 4 FOXA1 Down NR0B2 5 hsa-mir-141-3p Down ALB 4 STAT1 [109]Open in a new tab Construction of TF-DEG regulatory network The regulatory network of TF-DEG and predicted targets is presented in [110]Figure 4B. Enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) that was modulated by 45 TFs (eg, SRY-box transcription factor 2 [SOX2]), tropomyosin 1 (TPM1) that was modulated by 40 TFs (eg, MYC proto-oncogene, bHLH transcription factor [MYC]), AHNAK that was modulated by 58 TFs (eg, KLF4), and thioredoxin interacting protein (TXNIP) that was modulated by 51 TFs (eg, tumor protein p63 [TP63]) are listed in [111]Table 5. As a group, a total of 259 of the 463 DEGs were contained in the TF-DEG regulatory network. Validation of hub genes All of the hub genes were validated in TCGA data. Hub genes contributed to the survival period in patients with PDAC, and we analyzed the overall survival (OS) for each hub gene by UALCAN ([112]Figure 5). The results showed that the high expression of CCNB1 and FHL2 mRNA level was associated with the worse OS in patients with PDAC, while low expression of HLA-DPA1 and TUBB1 mRNA level was associated with the worse OS in patients with PDAC. As shown in [113]Figure 6, the expression of the upregulated hub genes CCNB1 and FHL2 in PDAC was significantly elevated compared with normal, while expression of the downregulated hub genes HLA-DPA1 and TUBB1 in PDAC was significantly decreased compared with normal. The expression of each hub gene in PDAC patients was analyzed according to the individual cancer stage. As shown in [114]Figure 7, the expression of CCNB1 and FHL2 were higher in patients with all individual cancer stages than that in normal, which revealed that these upregulated hub genes might be associated with tumor progression positively, whereas the expression of HLA-DPA1 and TUBB1 were lower in patients with all individual cancer stages than that in normal, which revealed that these downregulated hub genes might be associated with tumor progression positively. We used cBioportal tool to explore the specific mutation of hub genes in PDAC data set with 184 samples. From the OncoPrint, percentages of alterations in CCNB1, FHL2, HLA-DPA1, and TUBB1 genes among lung cancer ranged from 0% to 2.3% in individual genes (CCNB1, 0%; FHL2, 0.6%; HLA-DPA1, 2.3%; TUBB1, 2.3%) and are shown in [115]Figure 8. In addition, we used the “HPA” to examine the protein expression levels of CCNB1 and FHL2, and found that the protein expression levels of the these hub genes were noticeably upregulated in PDAC compared with normal tissues, whereas protein expression levels of HLA-DPA1 and TUBB1 were noticeably downregulated in PDAC compared with normal tissues ([116]Figure 9). The association of CCNB1, FHL2, HLA-DPA1, and TUBB1 expression level with immune infiltration abundance in PDAC was evaluated using TIMER database. CCNB1 and FHL2 expression were negatively correlated with infiltration degree of B cells, CD8+ T cells, macrophage, neutrophil, and dendritic cells, whereas HLA-DPA1 and TUBB1 were positively correlated with infiltration degree of B cells, CD8+ T cells, macrophage, neutrophil, and dendritic cells and are shown in [117]Figure 10. As these 4 genes are prominently expressed in PDAC, we performed an ROC curve analysis to evaluate their sensitivity and specificity for the diagnosis of PDAC. As shown in [118]Figure 11, CCNB1, FHL2, HLA-DPA1, and TUBB1 achieved an AUC value of >0.70, demonstrating that these genes have high sensitivity and specificity for PDAC diagnosis. The results suggested that CCNB1, FHL2, HLA-DPA1, and TUBB1 can be used as biomarkers for the diagnosis of PDAC. Figure 5. [119]Figure 5. [120]Open in a new tab Overall survival analysis of hub genes. Overall survival analyses were performed using the UALCAN online platform. Red line denotes high expression; Blue line denotes low expression. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, (D) TUBB1. Figure 6. [121]Figure 6. [122]Open in a new tab Box plots (expression analysis) hub genes were produced using the UALCAN platform. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, (D) TUBB1. Figure 7. [123]Figure 7. [124]Open in a new tab Box plots (clinical stage analysis) hub genes were produced using the UALCAN platform. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, (D) TUBB1. Figure 8. [125]Figure 8. [126]Open in a new tab Mutation analyses of hub genes were produced using the CbioPortal online platform. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, (D) TUBB1. Figure 9. [127]Figure 9. [128]Open in a new tab Immunohistochemical (IHC) analyses of hub genes were produced using the human protein atlas (HPA) online platform. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, (D) TUBB1. PDAC indicates pancreatic ductal adenocarcinoma. Figure 10. [129]Figure 10. [130]Open in a new tab Scatter plot for immune infiltration for hub genes. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, (D) TUBB1. Figure 11. [131]Figure 11. [132]Open in a new tab ROC curve validated the sensitivity and specificity of hub genes as a predictive biomarker for PDAC prognosis. (A) CCNB1, (B) FHL2, (C) HLA-DPA1, and (D) TUBB1. PDAC indicates pancreatic ductal adenocarcinoma; ROC, receiver operating characteristic. Discussion Due to the high heterogeneity of PDAC, it was still a disease with high rates of pervasiveness and fatality. With surgery as the main treatment, the other treatments including radiotherapy, chemotherapy, targeted therapy, and gene therapy as a additive to the finite treatment measures of PDAC, the 5-year survival rate was still less than 8%.^ [133]35 Therefore, the early diagnosis and effective treatment of PDAC are crucially required, which might be achieved via the identification of the DEGs between PDAC and normal control, and by considering the underlying molecular mechanism. NGS data analysis can screen a massive number of genes in the human genome for further functional analysis, and can be extensively used to screen biomarkers for early diagnosis and unique therapeutic targets. Therefore, they might help the diagnosis and prognosis of PDAC in the early stages and help in advancement of targeted treatment. The current investigation systematically applied integrated bioinformatics methods to identify novel biomarkers that serve roles in the advancement of PDAC. The data extracted from the GEO data set contained 284 PDAC and 117 normal control samples. A total of 232 upregulated and 231 downregulated genes in PDAC, when compared with normal control samples, were identified using bioinformatics analysis, indicating the incidence and advancement of PDAC. The results of the DEGs might provide potential biomarkers for the diagnosis of PDAC. DAP (death associated protein),^ [134]36 keratin 8 (KRT8),^ [135]37 insulin-like growth factor binding protein 2 (IGFBP2),^ [136]38 keratin 19 (KRT19),^ [137]39 CD44 molecule (Indian blood group) (CD44),^ [138]40 AHNAK,^ [139]41 and BTG anti-proliferation factor 1 (BTG1)^ [140]42 were the potential gene targets of the drugs for treating PDAC. KIF2C^ [141]43 induces proliferation, migration, and invasion in gastric cancer patients through the MAPK signaling pathway. Drebrin 1 (DBN1)^ [142]44 has been reported to be expressed in breast cancer. MAP1B^ [143]45 has been reported to be associated with lung cancer progression. BCL2 interacting protein 3 like (BNIP3L)^ [144]46 is involved in the progression of breast and ovarian cancer. Integrin subunit alpha 4 (ITGA4)^ [145]47 was found to promote oral cancer. Serine/arginine repetitive matrix 2 (SRRM2)^ [146]48 plays an important role in regulating thyroid carcinoma. Interleukin 7 receptor (IL7R)^ [147]49 plays important roles in the progression of esophageal squamous cell carcinoma. Major histocompatibility complex, class II, and DR alpha (HLA-DRA)^ [148]50 have been reported to encourage the development of colorectal cancer. Sestrin 3 (SESN3)^ [149]51 is important in the development of hepatocellular carcinoma. These genes served as biomarkers for cancer diagnosis and prognosis. Then, GO and REACTOME pathway analyses were used to investigate the interactions of these DEGs. Lysosomal protein transmembrane 4 beta (LAPTM4B),^ [150]52 CEA cell adhesion molecule 6 (CEACAM6),^ [151]53 serpin family E member 2 (SERPINE2),^ [152]54 vanin 1 (VNN1),^ [153]55 sphingosine kinase 1 (SPHK1),^ [154]56 histidine rich glycoprotein (HRG),^ [155]57 vascular endothelial growth factor C (VEGFC),^ [156]58 annexin A3 (ANXA3),^ [157]59 apolipoprotein A2 (APOA2),^ [158]60 lipocalin 2 (LCN2),^ [159]61 TIMP metallopeptidase inhibitor 1 (TIMP1),^[160]62 CD63 molecule (CD63),^ [161]63 CD151 molecule (Raph blood group) (CD151),^ [162]64 mal, T-cell differentiation protein 2 (MAL2),^ [163]65 aryl hydrocarbon receptor nuclear translocator-like 2 (ARNTL2),^ [164]66 polycystin 2, transient receptor potential cation channel (PKD2),^ [165]67 E2F transcription factor 1 (E2F1),^ [166]68 matrix metallopeptidase 1 (MMP1),^ [167]69 C-C motif chemokine receptor 7 (CCR7),^ [168]70 notch receptor 2 (NOTCH2),^ [169]71 B and T lymphocyte associated (BTLA),^ [170]72 transferrin receptor (TFRC),^ [171]73 CD4 molecule (CD4),^ [172]74 ATM serine/threonine kinase (ATM),^[173]75 lymphoid enhancer binding factor 1 (LEF1),^ [174]76 colony stimulating factor 1 receptor (CSF1R),^ [175]77 cathepsin B (CTSB),^ [176]78 dual specificity phosphatase 2 (DUSP2),^ [177]79 and nuclear receptor subfamily 4 group A member 1 (NR4A1)^ [178]80 are pathogenic genes for PDAC. Prostaglandin E receptor 3 (PTGER3)^ [179]81 and membrane associated guanylate kinase, WW and PDZ domain containing 2 (MAGI2)^ [180]82 have been reported to encourage the development of angiogenesis, chemoresistance, cell proliferation, and migration in ovary cancer. Recent studies have proposed that the haptoglobin (HP)^ [181]83 is associated with progression of lung cancer. FGA^ [182]84 is a gene which plays a role in diagnosis of lung cancer. FGB^ [183]85 has been known to be involved in gastric carcinoma. Phospholipase A2 group IVA (PLA2G4A),^ [184]86 FGG,^ [185]87 thymidylatesynthetase (TYMS),^ [186]88 RAB32,^ [187]89 SEPTIN4,^ [188]90 TPM2,^ [189]91 acyl-CoA thioesterase 7 ACOT7,^ [190]92 phosphoribosyl transferase domain containing 1 (PRTFDC1),^ [191]93 Cdk5 and Abl enzyme substrate 1 (CABLES1),^ [192]94 major histocompatibility complex, class II, DM beta (HLA-DMB),^ [193]95 protein tyrosine phosphatase receptor type C (PTPRC),^ [194]96 CD5 molecule (CD5),^ [195]97 CD6 molecule (CD6),^ [196]97 membrane spanning 4-domains A1 (MS4A1),^ [197]98 CD22 molecule (CD22),^ [198]99 CD27 molecule (CD27),^ [199]100 mannose receptor C type 2 (MRC2),^ [200]101 C-type lectin domain family 2 member D (CLEC2D),^ [201]102 EEF1A1,^ [202]103 and apolipoprotein B (APOB)^ [203]104 have a significant prognostic potential in various types of cancer. Sphingomyelin phosphodiesterase 1 (SMPD1)^ [204]105 expression in colorectal cancer results in drug resistance. Peptidyl arginine deiminase 4 (PADI4),^ [205]106 monoamine oxidase B (MAOB),^ [206]107 transient receptor potential cation channel subfamily C member 6 (TRPC6),^ [207]108 BCL11 transcription factor A (BCL11A),^ [208]109 C-X-C motif chemokine receptor 5 (CXCR5),^ [209]110 transcription factor 7 (TCF7),^ [210]111 POU class 2 homeobox 2 (POU2F2),^ [211]112 solute carrier family 4 member 1 (Diego blood group) (SLC4A1),^ [212]113 serine/threonine kinase 17b (STK17B),^ [213]114 and LDL receptor-related protein 1 (LRP1)^ [214]115 play crucial role in cancer cell invasion. Growth factor receptor bound protein 14 (GRB14),^ [215]116 transient receptor potential cation channel subfamily C member 6 (TRPC6),^ [216]117 zinc finger protein, FOG family member 2 (ZFPM2),^ [217]118 TNF receptor superfamily member 13B (TNFRSF13B),^ [218]119 ADAM metallopeptidase domain 19 (ADAM19),^ [219]120 and phosphoinositide-3-kinase interacting protein 1 (PIK3IP1)^ [220]121 are associated with cancer cell proliferation. HLA-DPA1,^ [221]122 fibrinogen like 2 (FGL2),^ [222]123 Cbl proto-oncogene B (CBLB),^ [223]124 NCK associated protein 1 like (NCKAP1L),^ [224]125 dual specificity tyrosine phosphorylation regulated kinase 2 (DYRK2),^ [225]126 O-linked N-acetylglucosamine (GlcNAc) transferase (OGT),^ [226]127 calcium-/calmodulin-dependent protein kinase ID (CAMK1D),^ [227]128 and ring finger protein 213 (RNF213)^ [228]129 are molecular markers for the diagnosis and prognosis of various types of cancer. Recent reports have revealed that RAR-related orphan receptor A (RORA),^[229]130 insulin-like growth factor 2 receptor (IGF2R),^ [230]131 and zinc finger and BTB domain containing 20 (ZBTB20)^ [231]132 acted as polymorphic genes in various types of cancer. Versican (VCAN)^ [232]133 induces immune cell infiltration in cancer. Therefore, these enriched GO and pathways are most likely to be essential in the development of PDAC. In the future investigation, we might combine gene expression levels of these enriched genes and cell biological behavior analysis to further explore the pathogenesis of PDAC. To explore the molecular mechanism of PDAC, we constructed the PDAC-related PPI network. CCNB1^ [233]134 plays a crucial role in proliferation of cancer cells. Recent reports have revealed that FHL2^ [234]135 and RPL10^ [235]136 acted as genetic factors in PDAC. FGB,^ [236]85 FGA,^ [237]84 FGG,^ [238]87 eukaryotic translation elongation factor 1 alpha 1 (EEF1A1),^ [239]103 and integrin subunit alpha 4 (ITGA4)^ [240]47 might be diagnostic markers of cancer and could be used as therapeutic targets. HLA-DPA1, TUBB1, RPL13A, RPL27A, and RPL23A were the novel potential gene targets of the drugs for treating PDAC in this investigation. Importantly, study on ribosomal proteins might be a significant novel direction for the diagnosis, prognosis, and treatment of PDAC. The miRNA-DEG regulatory network and TF-DEG regulatory network were constructed to explore the molecular mechanism of PDAC. Researchers have shown that AHNAK^ [241]41 , E2F transcription factor 1 (E2F1),^ [242]68 cathepsin B (CTSB),^ [243]78 O-linked N-acetylglucosamine (GlcNAc) transferase (OGT),^ [244]127 FHL2,^ [245]135 EZH2,^ [246]137 KMT2D,^ [247]138 TXNIP,^ [248]139 TP63,^ [249]140 SOX2,^ [250]141 MYC,^ [251]142 and KLF4^ [252]143 promoted PDAC. MAP1B,^ [253]45 CCNB1,^ [254]134 TPM1,^ [255]144 and hsa-mir-1202^ [256]145 might be novel prognostic markers of cancer. We identified SEC16 homolog A, endoplasmic reticulum export factor (SEC16A), keratin 18 (KRT18), period circadian regulator 1 (PER1), hsa-mir-4461, hsa-mir-3928-3p, and hsa-mir-2682-5p might serve as potential novel biomarkers for PDAC. Therefore, these biomarkers might be used as potential effective candidates for early diagnosis or prognosis of PDAC. Bioinformatics analysis has been performed and NGS data analysis has been carried out in these present investigations, but limitations exist. Lack of experimental validation of the hub genes is a limitation of the investigation. Corresponding experiments will be performed to verify hub genes in our future work, thus conversely testifying in bioinformatics analysis. In conclusion, using NGS data set and integrated bioinformatics analysis, PDAC-associated hub genes were identified. The expression of the hub genes was revealed to be altered in PDAC. Experimental evidence is warranted to investigate the functional roles of the identified hub genes in PDAC. Collectively, it is our sincere hope that the present investigations will contribute to the discovery of new diagnostic and prognostic biomarkers as well as therapeutic targets for PDAC. Acknowledgments