Construction of an RNA-Binding Protein-Related Prognostic Model for Pancreatic Adenocarcinoma Based on TCGA and GTEx Databases

PABPC1 silencing inhibits pancreatic cancer cell proliferation and EMT, and induces apoptosis via PI3K/AKT pathway

Pancreatic cancer is difficult to manage owing to the challenges involved in its treatment and nursing. This study aimed to clarify the roles and mechanisms of action of Poly (A)-binding protein cytoplasmic 1 (PABPC1) on pancreatic cancer. The expression of PABPC1 in pancreatic cancer tissues and cell lines was detected using RT-qPCR and western blotting. The effects of PABPC1 on proliferation, apoptosis, epithelial-mesenchymal transition (EMT), and the PI3K/AKT signaling pathway in pancreatic cancer cells were further investigated using MTT assays, flow cytometry, and western blotting. The expression of PABPC1 was significantly upregulated in pancreatic cancer tissues and cells, whereas PABPC1 downregulation inhibited pancreatic cancer cell proliferation, induced apoptosis, decreased the expression of EMT-associated proteins, and exerted a regulatory effect by inhibiting the PI3K/AKT signaling pathway. In addition, the findings indicated that PABPC1 over-expression significantly promoted pancreatic cancer cell proliferation, inhibited apoptosis, decreased the expression of E-cadherin, enhanced N-cadherin expression, and activating the PI3K/AKT signaling pathway. PABPC1 silencing significantly inhibited proliferation and EMT and induced apoptosis in pancreatic cancer cells. These findings provide novel insights into the role of PABPC1 in the development of pancreatic cancer.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10616-024-00626-1.

Identification of a basement membrane-related genes signature with immune correlation in bladder urothelial carcinoma and verification in vitro

BACKGROUND

Bladder urothelial carcinoma (BLCA) is the most common genitourinary cancer and the prognosis of patients is often poor. However, studies of basement membrane-related genes (BM-related genes) in BLCA are less reported. Therefore, we established a BM-related genes signature to explore their functional and prognostic value in BLCA.

METHODS

In this study, a BM-related genes signature was constructed by LASSO-Cox regression analysis, and then a series of bioinformatics methods was used to assess the accuracy and validity of the signature. We constructed a nomogram for clinical application and also screened for possible therapeutic drugs. To investigate the functions and pathways affected by BM-related genes in BLCA, we performed functional enrichment analyses. In addition, we analyzed the immune cell infiltration landscape and immune checkpoint-related genes in the high and low-risk groups. Finally, we confirmed the prognostic value of BM-related genes in BLCA in vitro.

RESULTS

Combining multiple bioinformatics approaches, we identified a seven-gene signature. The accuracy and validity of this signature in predicting BLCA patients were confirmed by the test cohort. In addition, the risk score was strongly correlated with prognosis, immune checkpoint genes, drug sensitivity, and immune cell infiltration landscape. The risk score is an independent prognostic factor for BLCA patients. Further experiments revealed that all seven signature genes were differentially expressed between BLCA cell lines and normal bladder cells. Finally, overexpression of LAMA2 inhibited the migration and invasion ability of BLCA cell lines.

CONCLUSIONS

In summary, the BM-related genes signature was able to predict the prognosis of BLCA patients accurately, indicating that the BM-related genes possess great clinical value in the diagnosis and treatment of BLCA. Moreover, LAMA2 could be a potential therapeutic target, which provides new insights into the application of the BM-related genes in BLCA patients.

A prospective prognostic signature for pancreatic adenocarcinoma based on ubiquitination-related mRNA-lncRNA with experimental validation in vitro and vivo

Ubiquitination-related genes (URGs) exerted a crucial part in a variety of human disease disorders; however, their association with pancreatic adenocarcinoma (PAAD) had yet to be clearly described. We aimed to comprehensively characterize the contributions of URGs in PAAD through in silico analysis and experimental validation, and then identified a robust mRNA-lncRNA-based molecular prognostic panel for patients with PAAD using bulk RNA-sequencing and single-cell RNA-sequencing data. Initially, we collected the multi-omics data from TCGA platform to depict a comprehensive landscape of URGs in pan-cancer. Furthermore, we were accurate to PAAD for in-depth analysis. Significant differences of the activation of ubiquitination pathways and the expression of URGs were detected between normal and malignant cells. Unsupervised hierarchical clustering determined two PAAD subtypes with distinct clinical outcomes, ubiquitination pathway activities, immune microenvironment, and functional annotation characteristics. The expression profiles of ubiquitination-associated mRNAs and lncRNAs in the training and validation datasets were utilized to develop and verify a novel ubiquitination-related mRNA-lncRNA prognostic panel, which had a satisfied prediction efficiency. Our ubiquitination-associated model could function as an effective prognostic index and outperformed four other recognized panels in evaluating PAAD patients' survival status. Tumor immune microenvironment, mutation burden, and chemotherapy response were intensively explored to demonstrate the underlying mechanism of prognostic difference according to our panel. Our findings also revealed that FTI-277, a farnesyltransferase inhibitor, had a better curative effect in high-risk patients, while MK-2206, an Akt allosteric inhibitor, had a superior therapeutic effect in low-risk patients. The real-time PCR results uncovered the RNA expression of AC005062.1 in all the three PAAD cell lines was elevated several thousandfold. In conclusion, our URGs-based classification panel could be triumphantly served as a prediction tool for survival evaluation in patients with PAAD, and the genes in this panel could be developed as a potential target in PAAD therapy.

PABPC1 promotes cell proliferation and metastasis in pancreatic adenocarcinoma by regulating COL12A1 expression

BACKGROUND

The expression of cytoplasmic poly (A) binding protein-1 (PABPC1) has been reported in multiple cancer types. This protein is known to modulate cancer progression. However, the effects of PABPC1 expression in pancreatic adenocarcinoma (PAAD) have not been investigated. Here, we investigate the regulatory targets and molecular mechanisms of PABPC1 in PAAD.

METHODS

PABPC1 and collagen type XII α1 chain (COL12A1) expression in PAAD and their role in tumor prognosis and tumor stage were investigated using The Cancer Genome Atlas database analysis. After silencing PABPC1, messenger RNA sequencing and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. The expression of differentially expressed genes (DEGs), cell viability, apoptosis, and cell migration and invasion were explored using reverse transcription-quantitative polymerase chain reaction, Cell Counting Kit-8 assay, flow cytometry assay, and transwell assay, respectively. The relationship between PABPC1 and COL12A1 expression was assessed by Pearson's correlation analysis. The regulatory function of COL12A1 in PABPC1-affected BXPC3 cell behavior was studied after COL12A1 was overexpressed.

RESULTS

PABPC1 and COL12A1 expression was upregulated in patients with PAAD and was linked to poor prognosis. Four hundred and seventy-four DEGs were observed in BXPC3 cells after PABPC1 silencing. GO and KEGG analyses revealed that the top 10 DEGs were enriched in cell adhesion pathways. Additionally, PABPC1 silencing inhibited cell viability, migration, and invasion and accelerated apoptosis in BXPC3 cells. PABPC1 silencing increased AZGP1 and ARHGAP30 expression and decreased CAV1 and COL12A1 expression in BXPC3 cells. PABPC1 positively mediated COL12A1 expression, whereas PABPC1 knockdown induced the inhibition of BXPC3 cell proliferation, migration, and invasion.

CONCLUSION

The results of this study indicate that PABPC1 may function as a tumor promoter in PAAD, accelerating BXPC3 cell proliferation and metastasis by regulating COL12A1 expression.

The RNA-Binding Proteins OAS1, ZFP36L2, and DHX58 Are Involved in the Regulation of CD44 mRNA Splicing in Colorectal Cancer Cells

Regulation of alternative splicing is carried out by RNA-binding proteins. Each alternative splicing event is controlled by several RNA-binding proteins, which in combination create the distribution of alternative splicing products in a given cell type. Transmembrane protein CD44 plays an important role at various stages of the metastatic cascade and is considered as a promising molecule for the therapy of tumor diseases and the construction of prognostic classifiers. However, the functions of specific isoforms of this protein may differ significantly. In this work, we performed a bioinformatic search of RNA-binding proteins that can determine the expression of clinically significant isoforms 3 and 4 of CD44 protein. The analysis revealed five RNA-binding proteins, three of which (OAS1, ZFP36L2, and DHX58) are shown for the first time as potential regulators of the studied process.

The diagnostic significance of the ZNF gene family in pancreatic cancer: a bioinformatics and experimental study

Background: Pancreatic adenocarcinoma (PAAD) is among the most devastating of all cancers with a poor survival rate. Therefore, we established a zinc finger (ZNF) protein-based prognostic prediction model for PAAD patients. Methods: The RNA-seq data for PAAD were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Differentially expressed ZNF protein genes (DE-ZNFs) in PAAD and normal control tissues were screened using the "lemma" package in R. An optimal risk model and an independent prognostic value were established by univariate and multivariate Cox regression analyses. Survival analyses were performed to assess the prognostic ability of the model. Results: We constructed a ZNF family genes-related risk score model that is based on the 10 DE-ZNFs (ZNF185, PRKCI, RTP4, SERTAD2, DEF8, ZMAT1, SP110, U2AF1L4, CXXC1, and RMND5B). The risk score was found to be a significant independent prognostic factor for PAAD patients. Seven significantly differentially expressed immune cells were identified between the high- and low-risk patients. Then, based on the prognostic genes, we constructed a ceRNA regulatory network that includes 5 prognostic genes, 7 miRNAs and 35 lncRNAs. Expression analysis showed ZNF185, PRKCI and RTP4 were significantly upregulated, while ZMAT1 and CXXC1 were significantly downregulated in the PAAD samples in all TCGA - PAAD, GSE28735 and GSE15471 datasets. Moreover, the upregulation of RTP4, SERTAD2, and SP110 were verified by the cell experiments. Conclusion: We established and validated a novel, Zinc finger protein family - related prognostic risk model for patients with PAAD, that has the potential to inform patient management.

Endo-Lysosomal Two-Pore Channels and Their Protein Partners

Two-pore channels are ion channels expressed on acidic organelles such as the various vesicles that constitute the endo-lysosomal system. They are permeable to Ca2+ and Na+ and activated by the second messenger NAADP as well as the phosphoinositide, PI(3,5)P2 and/or voltage. Here, we review the proteins that interact with these channels including recently identified NAADP receptors.

ITGB5 promotes innate radiation resistance in pancreatic adenocarcinoma by promoting DNA damage repair and the MEK/ERK signaling pathway

Pancreatic adenocarcinoma (PAAD) is one of the most aggressive digestive system tumors in the world, with a low early diagnosis rate and a high mortality. Integrin beta 5 (ITGB5) is demonstrated to be a potent tumor promoter in several carcinomas. However, it is unknown whether ITGB5 participates in the occurrence and development of PAAD. In this study, we confirmed a high expression of ITGB5 in PAAD and its role in promoting invasiveness and transitivity in PAAD. Besides, the knockdown of ITGB5 increased cell sensitivity to radiation by promoting DNA damage repair and the MEK/ERK signaling pathway. Collectively, these results show that ITGB5 plays an essential role in pancreatic cancer growth and survival.

Single Cell RNA-Seq Identifies Immune-Related Prognostic Model and Key Signature-SPP1 in Pancreatic Ductal Adenocarcinoma

There are no reliable biomarkers for early diagnosis or prognosis evaluation in pancreatic ductal adenocarcinoma (PDAC). Multiple scRNA-seq datasets for PDAC were retrieved from online databases and combined with scRNA-seq results from our previous study. The malignant ductal cells were identified through calculating copy number variation (CNV) scores. The robust markers of malignant ductal cells in PDAC were found. Five immune-related signatures, including SPP1, LINC00683, SNHG10, LINC00237, and CASC19, were used to develop a risk score formula to predict the overall survival of PDAC patients. We also constructed an easy-to-use nomogram, combining risk score, N stage, and margin status. The expression level of SPP1 was related to the prognosis and immune regulators. We found that SPP1 was mainly expressed in ductal cells and macrophages in PDAC. In conclusion, we constructed a promising prognostic model based on immune-related signatures for PDAC using scRNA-seq and TCGA_PAAD datasets.

Values of OAS gene family in the expression signature, immune cell infiltration and prognosis of human bladder cancer

Background

Bladder cancer (BLCA) is one of the most common genitourinary malignancies in the world, but its pathogenic genes have not been fully identified and the treatment outcomes are still unsatisfactory. Although the members of 2', 5'-oligoadenylate synthetase (OAS) gene family are known involved in some tumorous biological processes, the roles of the OAS gene family in BLCA are still undetermined.

Methods

By combining vast bioinformatic datasets analyses of BLCA and the experimental verification on clinical BLCA specimen, we identified the expressions and biological functions of OAS gene family members in BLCA with comparison to normal bladder tissues.

Results

The expression levels of OAS gene family members were higher in BLCA than in normal bladder tissues. The expression levels of most OAS genes had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells in the microenvironment of BLCA. In addition, high expressions of OAS1, OAS2, OAS3, and OASL predicted better overall survival in BLCA patients.

Conclusions

The highly expressed OAS genes in BLCA can reflect immune cells infiltration in the tumor microenvironment and predict the better overall survival of BLCA, and thus may be considered as a signature of BLCA. The study provides new insights into the diagnosis, treatment, and prognosis of BLCA.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10102-8.

Development and validation of prognostic and diagnostic model for pancreatic ductal adenocarcinoma based on scRNA-seq and bulk-seq datasets

The 5-year overall survival (OS) of pancreatic ductal adenocarcinoma (PDAC) is only 10%, partly owing to the lack of reliable diagnostic and prognostic biomarkers. The raw gene-cell matrix for single-cell RNA-seq (scRNA-seq) analysis was downloaded from the GSA database. We drew cell atlas for PDAC and normal pancreatic tissues. The inferCNV analysis was used to distinguish tumor cells from normal ductal cells. We identified differential expression genes (DEGs) by comparing tumor cells and normal ductal cells. The common DEGs were used to conduct prognostic and diagnostic model using univariate and multivariate Cox or logistic regression analysis. Four genes, MET, KLK10, PSMB9 and ITGB6, were utilized to create risk score formula to predict OS and to establish diagnostic model for PDAC. Finally, we drew an easy-to-use nomogram to predict 2-year and 3-year OSs. In conclusion, we developed and validated the prognostic and diagnostic model for PDAC based on scRNA-seq and bulk-seq datasets.

LAMC1 is a Novel Prognostic Factor and a Potential Therapeutic Target in Gastric Cancer

Purpose

To investigate the role of LAMC1 in gastric cancer (GC), if it is of great importance to identify tumour driver genes with prognostic value.

Patients and Methods

GC-related gene expression profile data were downloaded from TCGA. R-limma package and univariate Cox regression were used to identify the differentially expressed genes (DEGs) and survival-genes, respectively. Then, the ClusterProfiler package was used to analyse the Gene Ontology and pathway enrichment of DEGs. Cytoscape was used to build a protein interaction network (PPI) and identify key genes. The GEPIA2 and TIMER databases were used to validate the differential expression of LAMC1. The relationship between LAMC1 and the prognosis of GC was analysed by the KM. GSEA and GSVA were used to analyse the major activated and mutated pathways, respectively. Real-time fluorescence quantitative PCR (RT-qPCR) was used to reidentify the expression of LAMC1 in GES-1 and 5 GC cell lines. Finally, we explored the relationship between LAMC1 and FGFR1.

Results

A total of 266 DEGs were be selected, which were mainly enriched in extracellular structure organization. LAMC1 was identified as one of the hub genes. The expression of LAMC1 was significantly higher in GC tissue than in paracancerous tissues, and the prognosis of the GC patient with high expression of LAMC1 was relatively poor. Univariate and multivariate Cox analysis indicated that LAMC1 could be used as an independent prognostic indicator. The results of GSEA and GSVA showed that LAMC1 was mainly enriched in pathways such as MYOGENESIS and UV_RESPONSE_DN. The RT-qPCR results showed that the expression level in AGS cells was significantly higher than that in gastric epithelial cells. LAMC1 may play a role in the development of gastric cancer by influencing FGFR1.

Conclusion

LAMC1 may mediate the occurrence and development of GC and has potential as a biomarker for the prognosis and treatment of GC.

Identification of Key Deregulated RNA-Binding Proteins in Pancreatic Cancer by Meta-Analysis and Prediction of Their Role as Modulators of Oncogenesis

RNA-binding proteins (RBPs) play a significant role in multiple cellular processes with their deregulations strongly associated with cancer. However, there are not adequate evidences regarding global alteration and functions of RBPs in pancreatic cancer, interrogated in a systematic manner. In this study, we have prepared an exhaustive list of RBPs from multiple sources, downloaded gene expression microarray data from a total of 241 pancreatic tumors and 124 normal pancreatic tissues, performed a meta-analysis, and obtained differentially expressed RBPs (DE-RBPs) using the Limma package of R Bioconductor. The results were validated in microarray datasets and the Cancer Genome Atlas (TCGA) RNA sequencing dataset for pancreatic adenocarcinoma (PAAD). Pathway enrichment analysis was performed using DE-RBPs, and we also constructed the protein-protein interaction (PPI) network to detect key modules and hub-RBPs. Coding and noncoding targets for top altered and hub RBPs were identified, and altered pathways modulated by these targets were also investigated. Our meta-analysis identified 45 upregulated and 15 downregulated RBPs as differentially expressed in pancreatic cancer, and pathway enrichment analysis demonstrated their important contribution in tumor development. As a result of PPI network analysis, 26 hub RBPs were detected and coding and noncoding targets for all these RBPs were categorized. Functional exploration characterized the pathways related to epithelial-to-mesenchymal transition (EMT), cell migration, and metastasis to emerge as major pathways interfered by the targets of these RBPs. Our study identified a unique meta-signature of 26 hub-RBPs to primarily modulate pancreatic tumor cell migration and metastasis in pancreatic cancer. IGF2BP3, ISG20, NIP7, PRDX1, RCC2, RUVBL1, SNRPD1, PAIP2B, and SIDT2 were found to play the most prominent role in the regulation of EMT in the process. The findings not only contribute to understand the biology of RBPs in pancreatic cancer but also to evaluate their candidature as possible therapeutic targets.

Construction of a five-gene prognostic model based on immune-related genes for the prediction of survival in pancreatic cancer

Purpose: To identify differentially expressed immune-related genes (DEIRGs) and construct a model with survival-related DEIRGs for evaluating the prognosis of patients with pancreatic cancer (PC).

Methods: Six microarray gene expression datasets of PC from the Gene Expression Omnibus (GEO) and Immunology Database and Analysis Portal (ImmPort) were used to identify DEIRGs. RNA sequencing and clinical data from The Cancer Genome Atlas Program-Pancreatic Adenocarcinoma (TCGA-PAAD) database were used to establish the prognostic model. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to determine the final variables of the prognostic model. The median risk score was used as the cut-off value to classify samples into low- and high-risk groups. The prognostic model was further validated using an internal validation set of TCGA and an external validation set of GSE62452.

Results: In total, 142 DEIRGs were identified from six GEO datasets, 47 were survival-related DEIRGs. A prognostic model comprising five genes (i.e., ERAP2, CXCL9, AREG, DKK1, and IL20RB) was established. High-risk patients had poor survival compared with low-risk patients. The 1-, 2-, 3-year area under the receiver operating characteristic (ROC) curve of the model reached 0.85, 0.87, and 0.93, respectively. Additionally, the prognostic model reflected the infiltration of neutrophils and dendritic cells. The expression of most characteristic immune checkpoints was significantly higher in the high-risk group versus the low-risk group.

Conclusions: The five-gene prognostic model showed reliably predictive accuracy. This model may provide useful information for immunotherapy and facilitate personalized monitoring for patients with PC.