Construction of a prognostic prediction system for pancreatic ductal adenocarcinoma to investigate the key prognostic genes

Association of a Novel DOCK2 Mutation-Related Gene Signature With Immune in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a malignant tumor with high morbidity and mortality worldwide. Many studies have shown that dedicator of cytokinesis 2 (DOCK2) has a crucial role as a prognostic factor in various cancers. However, the potentiality of DOCK2 in the diagnosis of HCC has not been fully elucidated. In this work, we aimed to investigate the prognostic role of DOCK2 mutation in HCC. The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) cohorts were utilized to identify the mutation frequency of DOCK2. Then, univariate Cox proportional hazard regression analysis, random forest (RF), and multivariate Cox regression analysis were performed to develop the risk score that was significantly related to DOCK2 mutation. Moreover, Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and immune correlation analysis were conducted for an in-depth study of the biological process of DOCK2 mutation involved in HCC. The results revealed that the mutation frequency of DOCK2 was relatively higher than that in non-cancer control subjects, and patients with DOCK2 mutations had a low survival rate and a poor prognosis compared with the DOCK2-wild group. In addition, the secretin receptor (SCTR), tetratricopeptide repeat, ankyrin repeat and coiled-coil domain-containing 1 (TANC1), Alkb homolog 7 (ALKBH7), FRAS1-related extracellular matrix 2 (FREM2), and G protein subunit gamma 4 (GNG4) were found to be the most relevant prognostic genes of DOCK2 mutation, and the risk score based on the five genes played an excellent role in predicting the status of survival, tumor mutation burden (TMB), and microsatellite instability (MSI) in DOCK2 mutant patients. In addition, DOCK2 mutation and the risk score were closely related to immune responses. In conclusion, the present study identifies a novel prognostic signature in light of DOCK2 mutation-related genes that shows great prognostic value in HCC patients; and this gene mutation might promote tumor progression by influencing immune responses. These data may provide valuable insights for future investigations into personalized forecasting methods and also shed light on stratified precision oncology treatment.

RPL38 knockdown inhibits the inflammation and apoptosis in chondrocytes through regulating METTL3-mediated SOCS2 m6A modification in osteoarthritis

BACKGROUND

Ribosomal protein L38 (RPL38) was found upregulated in osteoarthritic peripheral blood mononuclear cells, however, its role in progression of osteoarthritis has not been characterized.

METHODS

The protein levels of RPL38 and SOCS2 in cartilage tissues from OA patients and controls were detected with Western blotting. IL-1β was used to stimulate primary chondrocytes to establish an OA cell model, and RPL38 siRNA (si-RPL38) was transfected into chondrocytes to investigate the effect of RPL38 knockdown on cell viability, apoptosis, inflammatory factor secretion and extracellular matrix degradation. Then, the mechanism that RPL38 regulate the SOCS2 expression and SOCS2-induced chondrocyte dysfunction was explored. The methyltransferase-like 3 (METTL3)-mediated m6A modification of SOCS2 mRNA was confirmed, and the interaction of RPL38 and METTL3 was verified. Moreover, the effects of SOCS2 overexpression on IL-1β-induced chondrocyte dysfunction and SOCS2 knockdown on the restoration of chondrocyte function by siRPL38 were investigated. Finally, RPL38 was knocked down in vivo and its role in OA progression was validated.

RESULTS

RPL38 was upregulated and SOCS2 was downregulated in OA cartilages. RPL38 knockdown or SOCS2 overexpression either attenuated IL-1β-induced chondrocyte apoptosis, inflammatory cytokine secretion, and ECM degradation. RPL38 directly interacted with METTL3 and it inhibited SOCS2 expression through METTL3-mediated m6A modification. SOCS2 knockdown activated the JAK2/STAT3 proinflammatory pathway and reversed the effects of RPL38 knockdown on IL-1β-induced chondrocyte apoptosis, inflammation and ECM degradation. RPL38 knockdown alleviated cartilage tissue damage and ECM degradation in OA mice.

CONCLUSION

RPL38 knockdown inhibited osteoarthritic chondrocyte dysfunction and alleviated OA progression through promoting METTL3-m6A-mediated SOCS2 expression.

Development and Validation of a Novel Metabolic-Related Signature Predicting Overall Survival for Pancreatic Cancer

Recently, growing evidence has revealed the significant effect of reprogrammed metabolism on pancreatic cancer in relation to carcinogenesis, progression, and treatment. However, the prognostic value of metabolism-related genes in pancreatic cancer has not been fully revealed. We identified 379 differentially expressed metabolic-related genes (DEMRGs) by comparing 178 pancreatic cancer tissues with 171 normal pancreatic tissues in The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx) databases. Then, we used univariate Cox regression analysis together with Lasso regression for constructing a prognostic model consisting of 15 metabolic genes. The unified risk score formula and cutoff value were taken into account to divide patients into two groups: high risk and low risk, with the former exhibiting a worse prognosis compared with the latter. The external validation results of the International Cancer Genome Consortium (IGCC) cohort and the Gene Expression Omnibus (GEO) cohort further confirm the effectiveness of this prognostic model. As shown in the receiver operating characteristic (ROC) curve, the area under curve (AUC) values of the risk score for overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were 0.871, 0.885, and 0.886, respectively. Based on the Gene Set Enrichment Analysis (GSEA), the 15-gene signature can affect some important biological processes and pathways of pancreatic cancer. In addition, the prognostic model was significantly correlated with the tumor immune microenvironment (immune cell infiltration, and immune checkpoint expression, etc.) and clinicopathological features (pathological stage, lymph node, and metastasis, etc.). We also built a nomogram based on three independent prognostic predictors (including individual neoplasm status, lymph node metastasis, and risk score) for the prediction of 1-, 3-, and 5-year OS of pancreatic cancer, which may help to further improve the treatment strategy of pancreatic cancer.

Identification of Critical Pathways and Potential Key Genes in Poorly Differentiated Pancreatic Adenocarcinoma

Introduction

The poorly differentiated pancreatic adenocarcinoma (PDAC) is an extremely lethal neoplasm without effective biomarkers for early detection and prognosis prediction, which is characteristically unresponsive to chemotherapeutic regimens. This study aims at searching for key genes which could be applied as novel prognostic biomarkers and therapeutic targets in PDAC.

Methods

Clinical samples were collected and a comprehensive differential analysis of seven PDAC samples by integrating RNA-seq data of tumor tissues and matched normal tissues from both our cohort and gene expression profiling interactive analysis (GEPIA) were performed to discover potential prognostic genes in PDAC. Pathway enrichment analysis was carried out to determine the biological function of PDAC differentially expressed genes (DEGs), and protein-protein interaction (PPI) network was constructed for functional modules analysis. Real-time PCR was performed to validate expression of hub genes.

Results

A total of 126 PDAC-specific expressed genes identified from seven PDAC samples were predominantly enriched in cell adhesion, integral component of membrane, signal transduction and chemical carcinogenesis, IL-17 signaling pathway, indicating that obtained genes might play a unique role in PDAC tumorigenesis. Furthermore, survival analysis revealed that five genes (CEACAM5, KRT6A, KRT6B, KRT7, KRT17) which exhibited high expression levels in tumor tissues were obviously correlated with the prognosis of PDAC patients and KRT7 was positively correlated with KRT6A, KRT6B, KRT17 expression. In addition, real-time PCR demonstrated that the expression level of the hub genes was consistent with RNA-seq analysis.

Discussion

The current study suggested that CEACAM5, KRT6A, KRT6B, KRT7, and KRT17 may represent novel prognostic biomarkers as well as novel therapeutic targets for poorly differentiated PDAC.

Integrated transcriptome meta-analysis of pancreatic ductal adenocarcinoma and matched adjacent pancreatic tissues

A comprehensive meta-analysis of publicly available gene expression microarray data obtained from human-derived pancreatic ductal adenocarcinoma (PDAC) tissues and their histologically matched adjacent tissue samples was performed to provide diagnostic and prognostic biomarkers, and molecular targets for PDAC. An integrative meta-analysis of four submissions (GSE62452, GSE15471, GSE62165, and GSE56560) containing 105 eligible tumor-adjacent tissue pairs revealed 344 differentially over-expressed and 168 repressed genes in PDAC compared to the adjacent-to-tumor samples. The validation analysis using TCGA combined GTEx data confirmed 98.24% of the identified up-regulated and 73.88% of the down-regulated protein-coding genes in PDAC. Pathway enrichment analysis showed that “ECM-receptor interaction”, “PI3K-Akt signaling pathway”, and “focal adhesion” are the most enriched KEGG pathways in PDAC. Protein-protein interaction analysis identified FN1, TIMP1, and MSLN as the most highly ranked hub genes among the DEGs. Transcription factor enrichment analysis revealed that TCF7, CTNNB1, SMAD3, and JUN are significantly activated in PDAC, while SMAD7 is inhibited. The prognostic significance of the identified and validated differentially expressed genes in PDAC was evaluated via survival analysis of TCGA Pan-Cancer pancreatic ductal adenocarcinoma data. The identified candidate prognostic biomarkers were then validated in four external validation datasets (GSE21501, GSE50827, GSE57495, and GSE71729) to further improve reliability. A total of 28 up-regulated genes were found to be significantly correlated with worse overall survival in patients with PDAC. Twenty-one of the identified prognostic genes (ITGB6, LAMC2, KRT7, SERPINB5, IGF2BP3, IL1RN, MPZL2, SFTA2, MET, LAMA3, ARNTL2, SLC2A1, LAMB3, COL17A1, EPSTI1, IL1RAP, AK4, ANXA2, S100A16, KRT19, and GPRC5A) were also found to be significantly correlated with the pathological stages of the disease. The results of this study provided promising prognostic biomarkers that have the potential to differentiate PDAC from both healthy and adjacent-to-tumor pancreatic tissues. Several novel dysregulated genes merit further study as potentially promising candidates for the development of more effective treatment strategies for PDAC.

RPL38 Regulates the Proliferation and Apoptosis of Gastric Cancer via miR-374b-5p/VEGF Signal Pathway

Aim

To explore the role of RPL38 on proliferation and apoptosis of gastric cancer cells by regulating miR-374b-5p/VEGF signal pathway.

Methods

qRT-PCR was used to measure the expression of RPL38. CCK8 assay, Matrigel invasion assay, and flow cytometry were used to detect the role of RPL38in MKN-45 cells. Western blot was used to measure the protein expression of VEGF, p-ERK, ERK, p-AKT, AKT in cells. Dual-luciferase assay was performed to verify the relationship between miR-374b-5p and RPL38, miR-374b-5p and VEGF.

Results

In our research, we found that RPL38 was upregulation in gastric cancer, loss function of RPL38 could inhibit MKN-45 cell proliferation and invasion, accompany with increasing apoptosis. Then, we verified that RPL38 could interact with miR-374b-5p by performed luciferase assay, there was a negative correlation between RPL38 and miR-374b-5p. Furthermore, we observed that VEGF is a potential target of miR-374b-5p, miR-374b-5p negatively regulated the expression of VEGF, and effected ERK/AKT signal pathways. Next, we found that miR-374b-5p inhibitor or overexpression of VEGF could prevent the anti-tumor function of si-RPL38.

Conclusion

Knockdown of RPL38 inhibits the proliferation and apoptosis of gastric cancer via miR-374b-5p/VEGF signal pathway.

Identification of breast cancer risk modules via an integrated strategy

Breast cancer is one of the most common malignant cancers among females worldwide. This complex disease is not caused by a single gene, but resulted from multi-gene interactions, which could be represented by biological networks. Network modules are composed of genes with significant similarities in terms of expression, function and disease association. Therefore, the identification of disease risk modules could contribute to understanding the molecular mechanisms underlying breast cancer. In this paper, an integrated disease risk module identification strategy was proposed according to a multi-objective programming model for two similarity criteria as well as significance of permutation tests in Markov random field module score, function consistency score and Pearson correlation coefficient difference score. Three breast cancer risk modules were identified from a breast cancer-related interaction network. Genes in these risk modules were confirmed to play critical roles in breast cancer by literature review. These risk modules were enriched in breast cancer-related pathways or functions and could distinguish between breast tumor and normal samples with high accuracy for not only the microarray dataset used for breast cancer risk module identification, but also another two independent datasets. Our integrated strategy could be extended to other complex diseases to identify their risk modules and reveal their pathogenesis.

The clinicopathological significance of decreased miR-125b-5p in hepatocellular carcinoma: evidence based on RT-qPCR, microRNA-microarray, and microRNA-sequencing

The aim of the study was to comprehensively evaluate the clinical value of miR-125b-5p in hepatocellular carcinoma (HCC) and its potential molecular mechanisms. MiR-125b-5p expression was remarkably lower as examined by real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) in 95 paired HCC and nonmalignant liver tissues in house (P<0.001), which was in accord with the results from miRNA-sequencing data with 371 cases of HCC. miRNA-chips from Gene Expression Omnibus (GEO) and ArrayExpress were screened. Among the seven included miRNA-chips, the relative expression of miR-125b-5p expression levels showed decreasing trends in HCC tissue samples compared with non-cancerous liver tissue samples. Altogether, A total of 655 cases of HCC tissues and 334 non-HCC liver tissues were included in the final meta-analysis. We observed that the expression of miR-125b-5p indeed decreased markedly in HCC tissues compared with the non-HCC tissues (SMD: -1.414, 95% CI: -1.894 to -0.935, P<0.001). The area under the SROC curve of lower expression of miR-125b-5p was 0.91 (95% CI: 0.89 to 0.94). A Kaplan-Meier survival analysis indicated that the lower expression or the absence of miR-125b-5p may be a risk factor for the poor outcome of HCC patients. Furthermore, the potential target genes of miR-125b-5p from 11 miRNA target prediction databases were intersected with 1,486 differentially expressed genes (DEGs) as calculated by RNA-sequencing data. Finally, a total of 330 GEGs were collected and enriched in the pathways of lysosome, focal adhesion, and pathways in cancer. In conclusion, this study utilizes a variety of research methods to confirm the lower level of miR-125b-5p in HCC tissues. This lower expression level of miR-125b-5p is closely related to increased disease progression in HCC patients.