| BackgroundPancreatic cancer is a malignant tumor in the gastrointestinal system with a very low survival rate.Although surgery is used as a radical treatment for pancreatic cancer patients,most patients often have distant metastases at the time of diagnosis and lose the opportunity for surgery.Chemotherapy is an effective treatment method for both early and advanced pancreatic cancer patients,but the patients are often resistant to chemotherapy,resulting in poor treatment effects.Therefore,how to overcome the chemoresistance of pancreatic cancer is a scientific problem that needs to be solved urgently,and it is also a hot issue focused on the majority of pancreatic cancer researchers.In the previous study,we used the patient-derived tumor xenograft(PDX)model of pancreatic cancer to conduct a gemcitabine pharmacodynamic experiment and screened out the PDX models that were sensitive and resistant to gemcitabine chemotherapy.Through the high-throughput RNAsequencing,a gemcitabine-resistance-related molecular regulatory network was constructed,from which we found that the Inhibitor of Bruton’s tyrosine kinase(IBTK)was significantly overexpressed in the gemcitabine-resistant group.Previous studies have shown that IBTK was a carcinogenic gene and is closely related to biological effects such as tumor cell proliferation,apoptosis,and chemosensitivity.Therefore,we chose IBTK as a research target to further explore the molecular mechanism of its mediating gemcitabine chemoresistance in pancreatic cancer,expecting to provide new hope for the treatment of pancreatic cancer in the future.ObjectiveDetect the expression and clinical significance of IBTK in pancreatic cancer tissues;clarify the effects of IBTK on the biological behaviors of pancreatic cancer cells,such as proliferation,apoptosis,and chemosensitivity;explore the specific mechanism of gemcitabine induce over-expression of IBTK;exploration of whether autophagy and ubiquitinated proteasomal degradation pathways affect the chemoresistance in pancreatic cancer.MethodsUsing the bioinformatics analysis,the heat map of differential genes between gemcitabine chemotherapy-sensitive and chemotherapy-resistant PDX models was drawn,and IBTK was overexpression in gemcitabine-resistant PDX was screened out as the research target.The mRNA and protein expressions of IBTK in chemoresistant PDX model tissues and gemcitabine-resistant pancreatic cancer cell lines were detected by qRT-PCR and Western Blot.Then,immunohistochemical staining was performed on pancreatic cancer tissue to detect the expression level of IBTK.Kaplan-Meier(K-M)survival analysis and Log-rank test were used to test differences in the survival time between patients with high or low expression of IBTK.Univariate and multivariate Cox regression analysis was used to screen independent risk factors affecting the prognosis of pancreatic cancer patients,and to evaluate the clinical application value of IBTK predicting prognosis in pancreatic cancer patients.In the upstream regulatory mechanism of IBTK,qRT-PCR was used to detect the mRNA expression of IBTK in pancreatic cancer with the increase of gemcitabine drug concentration and medication time gradient.The KEGG enriched signaling pathway between the previous and later gemcitabine treatment was analyzed,and Western Blot was used to verify the specific mechanism of gemcitabine-induced endoplasmic reticulum stress regulating IBTK expression.In addition,in the exploration of the specific function of IBTK in pancreatic cancer,we up-regulated or down-regulated the expression level of IBTK in pancreatic cancer cell lines,and used the CCK8 method,flow cytometry detection,and clone formation assay to detect the effect of IBTK on pancreatic cancer cell proliferation,apoptosis and the chemosensitivity of gemcitabine;then,the effect of IBTK on gemcitabine chemoresistance was clarified in vivo by subcutaneous xenografts of nude mice.In the downstream regulation mechanism of IBTK,the specific molecular mechanism of IBTK regulation was speculated by transcriptome sequencing and proteome mass spectrometry analysis of IBTK knockout pancreatic cancer cell lines.Then,we used Western Blot,GFP/mRFP-LC3B double fluorescence staining protein,electron microscopy,Lyso-Tracker probe,and other methods to clarify the regulation of IBTK on autophagy in pancreatic cancer.Finally,we used CO-IP,CHX,and MG132 drugs to explore the effect of IBTK on autophagy by regulating ubiquitylation degradation of ARID2.ResultsThe expression level of IBTK is up-regulated in gemcitabine-resistant PDX model and gemcitabine-resistant cell lines,and its expression level is significantly higher in pancreatic cancer tissue than in normal pancreatic tissue;the level of IBTK expression is an independent risk for prognosis evaluation of pancreatic cancer patients.In the results of functional experiments,the increased expression of IBTK in pancreatic cancer can promote the proliferation,improve the resistance to gemcitabine chemotherapy and inhibit the apoptosis in pancreatic cancer cells;in addition,inhibiting the expression of IBTK can inhibit proliferation,enhance sensitivity to gemcitabine chemotherapy and promote the apoptosis in pancreatic cancer cells.In vivo,we used the subcutaneous xenograft model to confirm that overexpression of IBTK can induce the gemcitabine chemoresistance of pancreatic cancer.Next,in the upstream regulation mechanism of IBTK,we found that with the increase of gemcitabine drug concentration and the medication time,the mRNA expression of IBTK became higher and higher,and gemcitabine could trigger endoplasmic reticulum stress in pancreatic cancer cells.In addition,in the downstream regulatory mechanism of IBTK,we found that overexpression of IBTK in pancreatic cancer cells can enhance lysosomal function and enhance autophagosome degradation leading to the decreased number of autophagosomes to promote the autophagic flux.In a more in-depth study of the downstream mechanism of IBTK,we found that IBTK can bind to the tumor suppressor protein ARID2,and affected the ubiquitination level of ARID2 which is hydrolyzed by the proteasome.Finally,IBTK could regulate the function of lysosomes and change the autophagy inducing the gemcitabine chemoresistance in pancreatic cancer.ConclusionsThe expression of IBTK is up-regulated in pancreatic cancer patients,and its expression level can be used as an independent risk factor for evaluating the prognosis of pancreatic cancer patients.Mechanistically,the stimulation of gemcitabine can mediate the increase of IBTK expression by the PERK/CHOP pathway in endoplasmic reticulum stress,and then IBTK can promote the proteasome hydrolysis of the tumor suppressor protein ARID2 by affecting its ubiquitylation level,thereby affecting the autophagy status leads to chemoresistance in pancreatic cancer.IBTK may serve as a prognostic marker and potential therapeutic target for pancreatic cancer patients,providing new thought for related research in the future.BackgroundAmong gastrointestinal tumors,pancreatic cancer is a highly malignant tumor with an extremely poor prognosis.The overall five-year survival rate of patients with pancreatic cancer is approximately 10%.Most patients have been diagnosed with local progression or distant metastases.Therefore,the early screening of pancreatic cancer patients and the in-depth exploration of the pathogenesis of pancreatic cancer are of great clinical significance for improving the prognosis of patients.In clinical work,the importance of individualized systemic treatment for different patients has become increasingly prominent.The problems need to be solved urgently that how to use the existing technology to effectively evaluate patient prognosis,and in-depth disclosure of the malignant biological mechanism of pancreatic cancer patients at the molecular level,which will assist doctors to provide individualized clinical decision-making.With the development and a large number of applications of various omics tests in tumors,based on genomic and transcriptomic data,the usage of hub genes to establish specific prognostic evaluation models can be beneficial for early diagnosis,evaluation of prognosis,and therapeutic effect of cancer patients.In recent years,studies have found that long non-coding RNAs(lncRNAs)and autophagy play an important role in the occurrence and development of pancreatic cancer.At the same time,there is no report for constructing a prognostic risk model with autophagy-related lncRNA in pancreatic cancer.Therefore,the rational use of existing public databases and the identification of prognostic autophagy-related lncRNAs in pancreatic cancer through bioinformatics analysis can help to establish a more accurate evaluation system for the prognosis of pancreatic cancer patients which can provide effective strategies in the future.ObjectiveUsing the transcriptome sequencing data in the tumor public database combined with the corresponding clinical data,we screened the prognostic autophagy-related lncRNAs in pancreatic cancer,and the lncRNA-mRNA co-expression regulatory network was constructed to reveal the important roles of autophagy and lncRNAs in pancreatic cancer.A multi-gene prediction model with the screened key lncRNAs was established to reasonably and effectively evaluate the prognosis of patients with pancreatic cancer,and provide guidance for clinical decision-making in the individualized treatment of patients.MethodsFirst,the transcriptome sequencing data of pancreatic cancer tissues were downloaded from The Cancer Genome Atlas(TCGA)and International Cancer Genome Consortium(ICGC).All reported autophagy-related genes were extracted from Human Autophagy Database(HADb).Next,all the obtained genes were annotated with Ensemble ID in the GENCODE database and got all the lncRNA of pancreatic cancer in the TCGA database.Pearson correlation analysis was performed to screen autophagy-related lncRNAs from TCGA and HADb databases.Cox regression and survival analysis were used to identify autophagy-related lncRNAs significantly associated with prognosis,and the selected genes were used to construct a risk score model.The patients with pancreatic cancer were divided into the high-risk group and low-risk group by calculating the risk score of each patient and taking the median risk score as the cut-off value.Principal component(PCA)analysis was used to clarify that there were significant differences between the high-risk group and the low-risk group,which proved that the two groups had different distributions.Kaplan-Meier(K-M)survival analysis and Log-rank test were used to test whether the survival time of pancreatic cancer patients was statistically different between high-and low-risk groups.We used the external independent validation cohort in the ICGC database to confirm the stability of the constructed risk score model.Univariate Cox regression and multivariate Cox regression analysis were utilized to screen the factors significantly associated with prognosis.The time-dependent receiver operating characteristic curve(ROC)was plotted,and the area under the ROC curve(AUC)was calculated to predict the 3-year survival time of pancreatic cancer patients.By comparing the AUC values of the risk scoring model and different clinical factors,the predictive performance of each index was clarified.Next,we used Cytoscape software and Sankey diagram to visualize the lncRNA-mRNA network and used GO and KEGG pathway enrichment analysis to predict the molecular biological functions and possible biological processes of the selected genes.In addition,we also used gene set enrichment analysis(GSEA)to further explore the potential molecular biological mechanisms associated with poor prognosis in pancreatic cancer between high-and low-risk groups.Finally,we used qRT-PCR to verify the expression of each autophagy-related lncRNA in normal pancreatic ductal epithelial cells HPNE and pancreatic cancer cells PANC-1.ResultsA total of 14,142 lncRNAs were extracted from the pancreatic cancer transcriptome sequencing data of the TCGA database.Then,1234 lncRNAs with a high correlation with autophagy were identified.According to the results of univariate and multivariate Cox regression analysis,7 autophagy lncRNAs related to prognosis were finally screened,including 2 risk genes:AC245041.2 and LINC02257(HR>1),and 5 protective genes:AC006504.8,AC012306.2,AC125494.2,FLVCR1-DT and AC005332.6(HR<1).Based on the above 7 genes,a risk score model was constructed in which pancreatic cancer patients were divided into the high-risk group and the lowrisk group.At the same time,both in the TCGA training set and the ICGC validation set,the survival time of patients in the high-risk group was shorter than that of the patients in the low-risk group.PCA analysis showed that there were significant differences between the high-and low-risk groups.Through univariate and multivariate Cox regression analysis,it was found that the risk score system can be used as an independent prognostic factor for evaluating the prognosis of pancreatic cancer.In addition,by comparing the AUC values of predicting the 3-year survival time of the risk score model with different clinical factors in the patients with pancreatic cancer,it was confirmed that the predictive performance of the risk score model was significantly better than other traditional clinical factors.Next,we visualized the lncRNA-mRNA regulatory network and performed GO and KEGG analysis,and found that autophagy,ubiquitinated protein regulation,PI3K-Akt,and FoxO signaling pathways were significantly enriched.Then,using GSEA to analyze the differences in molecular signaling pathways between high-risk and low-risk groups,it was found that the molecular mechanisms of pancreatic cancer in the low-risk group were significantly related to autophagy and metabolic signaling pathways.Finally,experiments verified that the expression levels of risk lncRNAs(AC245041.2 and LINC0225)in pancreatic cancer were significantly higher in PANC-1 than in HPNE,while protective lncRNAs(AC005332.6,AC012306.2,AC125494.2)were low-expressed in PANC-1 compared with HPNE.ConclusionsCollectively,the seven autophagy-related lncRNAs identified by the analysis are closely related to the progression and prognosis of pancreatic cancer and may be novel potential therapeutic targets for the treatment of pancreatic cancer.Meanwhile,the autophagy-related lncRNA-mRNA regulatory network further explained the molecular mechanism of malignant behavior of pancreatic cancer.In addition,the construction of a risk score model based on autophagy-related lncRNA has better clinical prognosis prediction performance than traditional clinical factors.Furthermore,the risk score model has been verified by an external independent data set and has a certain stability,which is beneficial for guiding clinical decision-making in the future. |
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