Competing endogenous RNA (ceRNA) pathways play pivotal roles in the formation and progression of gastric cancer (GC). Employing multi-omics analysis, we sought to identify a ceRNA network associated with GC progression. We analyzed3Gene Expression Omnibus datasets as well as data from The Cancer Genome Atlas to identify genes that were differentially expressed in GC tissues. A total of 84 upregulated genes and 106 downregulated genes were found. Enrichment analysis indicated that some pathways were strongly linked with tumor formation and progression. We also screened hub genes to establish a lncRNA-miRNA-mRNA network. We ultimately identified 8 hub genes, 6 key miRNAs and 4 key lncRNAs that interact within a common ceRNA network. Correlation analysis and in vitro experiments were conducted to verify the regulatory effect of the ceRNA network in GC. A knockdown assay confirmed that the DLGAP1-AS1/miR-203a-3p/THBS2 axis is a ceRNA network involved in GC progression. In this study, we elucidated the role of the DLGAP1-AS1/miR-203a-3p/THBS2 ceRNA network in the progression of GC. These molecules maybe evaluated as therapeutic targets and prognostic biomarkers for GC.

Background It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression. Methods We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC. Results A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC. Conclusion Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with invasive and metastatic characteristics and poor prognosis. Intracellular protein homeostasis is associated with invasion and metastasis of pancreatic cancer, but the specific molecular mechanism remains unclear. Our previous studies have revealed that DNAJB11, a key protein in protein homeostasis, is secreted by exosomes in the supernatant of dissociated pancreatic cancer cells with high metastasis. The results from transcriptome sequencing and co-immunoprecipitation (Co-IP)-based liquid chromatography with tandem mass spectrometry (LC–MS/MS) showed that depletion of DNAJB11 levels could increase HSPA5 expression and induce endoplasmic reticulum stress through the PRKR-like endoplasmic reticulum kinase signaling pathway in pancreatic cancer cells. Furthermore, exosomal DNAJB11 promoted cell development of PC cells in vitro and in vivo. In addition, exosomal DNAJB11 could regulate the expression of EGFR and activate the downstream MAPK signaling pathway. Clinical blood samples were collected to evaluate the potential of exosome DNAJB11 as a diagnostic biomarker and therapeutic target for the treatment of pancreatic cancer. This study could provide a new theoretical basis and potential molecular targets for the treatment of pancreatic cancer.

Outcomes for patients with pancreatic cancer (PC) are poor; therefore, there is an urgent need to identify novel therapeutic targets involved in the progression of PC. We previously identified 161 differentially expressed proteins (DEPs) in PC. Syntenin (SDCBP) was identified as a survival-related protein through integrated, survival, and Cox analyses. High expression of SDCBP was associated with a poor prognosis in PC tissue and promoted the proliferation, migration, and invasion of PC cells, and induced epithelial–mesenchymal transition (EMT) via the PI3K/AKT pathway. Additionally, we elucidated the regulatory mechanism underlying these roles of SDCBP at the post-transcriptional level. microRNAs (miRNAs) of SDCBP were predicted using bioinformatics. Low levels of miR-216b expression were confirmed in PC tissues and were negatively correlated with SDCBP expression. miR-216b was found to directly regulate SDCBP expression through luciferase reporter assays. Furthermore, agomiR-216b restrained PC proliferation, migration, invasion, and EMT via the PI3K/AKT pathway, whereas antagomiR-216b facilitated this process. Notably, the knockout of SDCBP counteracted the effect of antagomiR-216b in PC, which suggested that miR-216b and SDCBP represent molecular targets underlying PC progression and EMT. Finally, the results were validated in in vivo studies. These findings indicated that low expression of miR-216b and the oncogene SDCBP contributes to PC migration, invasion, and EMT, and that they have potential as future therapeutic targets for patients with PC.

Background: It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression.Methods: We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC.Results: A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b-/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC.Conclusion: Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b-/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

Background MicroRNAs (miRNAs) play pivotal roles in the development and progression of breast cancer (BC). In this study, we attempted to identify miRNAs associated with BC prognosis and progression via integrated analysis. Methods We first screened 83 differentially expressed miRNAs (DEMs) in 1249 BC samples and 151 normal samples. We then validated their roles in expression and prognosis of BC, identified two survival-related DEMs, and established a risk model. The prediction efficiency was assessed in both the training and validation groups. Tissue and cell experiments were conducted to verify the regulatory effects of miR-127 in BC. Results The ROC curve indicated good prediction ability with 1-, 3-, and 5-year survival rates of 0.73, 0.72, and 0.72, respectively. Moreover, hsa-miR-127 was found to be an independent prognostic factor of BC. Functional analyses revealed that it is involved in various cancer pathways such as the PI3K-Akt and p53 pathways. miR-127 expression was down-regulated in both BC tissues and cell lines. The knockdown of miR-127 substantially increased, whereas overexpression decreased BC cell proliferation, invasion, and migration. This effect of miR-127 was consistent with its tumorigenic ability and tumor volume in nude mice. Conclusions These findings indicate that low expression of miR-127 contributes to BC migration, invasion, and tumorigenesis and that it can be a therapeutic target and prognostic biomarker for BC.

BackgroundEnergy metabolism has been considered as one of the novel features of neoplasms. This study aimed to establish the prognostic signature for pancreatic cancer (PC) based on metabolism-related genes (MRGs).MethodsWe obtained MRGs from the Molecular Signatures Database (MSigDB) and gene sequence data in the Cancer Genome Atlas (TCGA) databases. Then, differentially expressed MRGs (DE-MRGs) were identified utilizing the R software. We built the prognostic model via multivariate Cox regression. Moreover, external validation of the prognostic signature was also performed. Nomogram was created to predict the overall survival (OS). Next, this study analyzed the prognostic value, clinical relationship, and metabolism-related signaling pathways of the prognostic signature. The role in tumor infiltration was further evaluated. Eventually, the expression level of the three MRGs along with the function of NT5E was validated.ResultsTwenty-two MRGs were chosen, eight of which were identified to be most significantly correlated with the prognosis of PC. Meanwhile, a 3-MRG prognostic signature was established, and we verified this prognostic model in two separate external cohorts. What is more, the nomogram was used to predict 1-/2-/3-year OS of PC patients. In addition, the immune cell infiltration and expression of immune checkpoint were significantly influenced by the risk score. Finally, three MRGs were highly expressed in PC cell lines, and NT5E was associated with the proliferation and migration ability of PC.ConclusionTo sum up, the study established and validated a 3-MRG prognostic signature for PC, and the signature could be utilized to predict the prognosis and assist the individualized clinical management of patients with PC.

Background: It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression.Methods: We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC.Results: A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b-/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC.Conclusion: Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b-/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.