Gly-tRF enhances LCSC-like properties and promotes HCC cells migration by targeting NDFIP2.

BACKGROUND: Accumulating evidence demonstrates that tRFs (tRNA-derived small RNA fragments) and tiRNAs (tRNA-derived stress-induced RNA), an emerging category of regulatory RNA molecules derived from transfer RNAs (tRNAs), are dysregulated in in various human cancer types and play crucial roles. However, their roles and mechanisms in hepatocellular carcinoma (HCC) and liver cancer stem cells (LCSCs) are still unknown. METHODS: The expression of glycine tRNA-derived fragment (Gly-tRF) was measured by qRT-PCR. Flow cytometric analysis and sphere formation assays were used to determine the properties of LCSCs. Transwell assays and scratch wound assays were performed to detect HCC cell migration. Western blotting was conducted to evaluate the abundance change of Epithelial-mesenchymal transition (EMT)-related proteins. Dual luciferase reporter assays and signalling pathway analysis were performed to explore the underlying mechanism of Gly-tRF functions. RESULTS: Gly-tRF was highly expressed in HCC cell lines and tumour tissues. Gly-tRF mimic increased the LCSC subpopulation proportion and LCSC-like cell properties. Gly-tRF mimic promoted HCC cell migration and EMT. Loss of Gly-tRF inhibited HCC cell migration and EMT. Mechanistically, Gly-tRF decreased the level of NDFIP2 mRNA by binding to the NDFIP2 mRNA 3' UTR. Importantly, overexpression of NDFIP2 weakened the promotive effects of Gly-tRF on LCSC-like cell sphere formation and HCC cell migration. Signalling pathway analysis showed that Gly-tRF increased the abundance of phosphorylated AKT. CONCLUSIONS: Gly-tRF enhances LCSC-like cell properties and promotes EMT by targeting NDFIP2 and activating the AKT signalling pathway. Gly-tRF plays tumor-promoting role in HCC and may lead to a potential therapeutic target for HCC.

Loss of neuropilin1 inhibits liver cancer stem cells population and blocks metastasis in hepatocellular carcinoma via epithelial-mesenchymal transition.

It is generally believed that the existence of cancer stem cells (CSCs) is related to tumor recurrence and metastasis of hepatocellular carcinoma (HCC). Neuropilin1 (NRP1) is involved in numerous pathophysiological processes of tumor progression, however, whether NRP1 is involved in the regulation of liver CSCs and metastasis of HCC is still unknown. In the present study, we examined the effect of NRP1 on the population of liver CSCs and the metastasis mechanism of HCC. In NRP1 small hairpin RNA (shRNA)-transduced HCC cells, liver CSCs surface markers (CD133+/ EpCAM+/CD13+/CD44+) expressing cells, which imply the CSCs population, were decreased. Transwell assay and nude mouse liver orthotopic transplantation model confirmed that NRP1 knockdown inhibited HCC cells' migration and lung metastasis. Our data showed that the expression of NRP1 was upregulated in 5 independent cohorts of HCC patients, consequently, high levels of NRP1 correlated with recurrence and poor prognosis in HCC. Mechanism research showed that NRP1 promotes cell spreading through the epithelial-mesenchymal transition (EMT) signaling pathway. In summary, NRP1 enhanced the population of liver CSCs and migration of HCC via EMT, indicating that NRP1 might be a novel target for HCC treatments.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets.

PURPOSE: Esophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC. METHODS: After comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1-C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed. RESULTS: The ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1's susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC. CONCLUSION: The identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

Identification of prognostic biomarkers associated with tumor microenvironment in ceRNA network for esophageal squamous cell carcinoma: a bioinformatics study based on TCGA database.

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is the most common histological type of esophageal cancer in the world with high incidence rate and poor prognosis. Infiltrated immune and stromal cells are vital components of tumor microenvironment (TME) and have a significant impact on the progression of ESCC. The competitive endogenous RNA (ceRNA) hypothesis has been proved important in the molecular biological mechanisms of tumor development. However, there are few studies on the relationship between ceRNA and ESCC TME. METHODS: The proportion of tumor-infiltrating immune cells and the amount of stromal and immune cells in ESCC cases were calculated from The Cancer Genome Atlas database using the CIBERSORT and ESTIMATE calculation methods. After stratified identification of differentially expressed genes, WGCNA and miRNA prediction system were applied to construct ceRNA network. Finally, PPI network and survival analysis were selected to discriminate prognostic signature. And the results were verified in two independent groups from Gene Expression Omnibus and Lanzhou, China. RESULTS: We found that high Stromal and ESTIMATE scores were significantly associated with poor overall survival. Three TME-related key prognostic genes were screened, namely, LCP2, CD86, SLA. And the expression of them was significantly correlated with infiltrated immunocytes. It is also found that ESTIMATE Score and the expression of CD86 were both related to TNM system of ESCC. CONCLUSIONS: We identified three novel TME-related prognostic markers and their lncRNA-miRNA-mRNA pathway in ESCC patients, which may provide new strategies for the targeted therapy.

Identification of biomarkers associated with diagnosis and prognosis of gastroesophageal junction adenocarcinoma-a study based on integrated bioinformatics analysis in GEO and TCGA database.

ABSTRACT: Gastroesophageal junction adenocarcinoma (GEJAC) is a malignant tumor with high mortality. Its incidence has increased sharply all over the world in recent years. The study aims to search for potential biomarkers for the diagnosis and prognosis of GEJAC based on the Gene Expression Omnibus database (GEO) database and The Cancer Genome Atlas (TCGA) database.Microarray dataset (GSE96668 and GSE74553) of GEJAC was downloaded from the GEO. After screening overlapping differentially expressed genes (DEGs) by GEO2R and Wayne map, functional enrichment analysis of the DEGs was performed by the DAVID database. Then, a protein-protein interaction (PPI) network was constructed, and the hub gene was identified by using STRING and Cytoscape, as well as the diagnostic value of hub genes was evaluated by the receiver operating characteristic (ROC) curves. Finally, the gene transcriptome profiles of gastric cancer named TCGA-STAD were downloaded from TCGA database to screen the potential prognostic genes and construct the prognostic risk model using Cox proportional hazards regression. Meanwhile, the Kaplan-Meier curve and time-dependent ROC curve were adopted to test the prognostic value of the prognostic gene signature.In this study, we identified 10 hub genes that might have high diagnostic value for GEJAC, and inferred that they might be involved in the occurrence and development of GEJAC. Moreover, we conducted a survival prediction model consisting of 6 genes and proved that they have value to some extent in predicting prognosis for GEJAC patients.

Identification of immunophenotypes in esophageal squamous cell carcinoma based on immune gene sets

PurposeEsophageal squamous cell carcinoma (ESCC) is a malignant tumor with high heterogeneity. Research on molecular mechanisms involved in the process of tumor origination and progression is extremely limited to investigating mechanisms of molecular typing for ESCC.MethodsAfter comprehensively analyzing the gene expression profiles in The Cancer Genome Atlas and Gene Expression Omnibus databases, we identified four immunotypes of ESCC (referred to as C1–C4) based on the gene sets of 28 immune cell subpopulations. The discrepancies in prognostic value, clinical features, drug sensitivity, and tumor components between the immunotypes were individually analyzed.ResultsThe ranking of immune infiltration is C1 > C4 > C3 > C2. These subtypes are characterized by high and low expression of immune checkpoint proteins, enrichment and insufficiency of immune-related pathways, and differential distribution of immune cell subgroups. Poorer survival was observed in the C1 subtype, which we hypothesized could be caused by an immunosuppressive cell population. Fortunately, C1’s susceptibility to anti-PD-1 therapy offers hope for patients with poor prognosis in advanced stages. On the other hand, C4 is sensitive to docetaxel, which may offer novel treatment strategies for ESCC in the future. It is worth noting that immunophenotyping is tightly bound to the abundance of stromal components and stem cells, which could explain the tumor immune escape to some extent. Ultimately, determination of hub genes based on the C1 subtypes provides a reference for the discovery of immunotarget drugs against ESCC.ConclusionThe identification of immunophenotypes in our study provides new therapeutic strategies for patients with ESCC.

MicroRNA-146a promotes IgE class switch in B cells via upregulating 14-3-3σ expression.

B cells play a critical role in immune responses both in physiological and pathological conditions, and microRNAs have been shown to play important roles in regulating B cell proliferation and function. MiR-146a has been shown to modulate T cell immunity, but its function in regulating B cell response remains partially understood. Our previous studies indicated that germinal center (GC) B cells are significantly expanded in miR-146a-overexpressing (TG) mice. In this study, we further characterized the roles of miR-146a in regulating humoral immune responses to specific antigens. We found that the production of IgE antibody were significantly elevated in TG mice, while the antibody affinity maturation of IgM and IgG were similar between TG mice and the normal controls. We further found higher IgE antibody levels in TG B cell culture supernatant than that in normal controls. A global protein expression comparison of B cells from TG mice and the normal controls through TMT proteomic assay showed that 14-3-3σ, a key factor of immunoglobulin class switch DNA recombination (CSR) in B cells, was highly up-regulated in B cells with overexpression of miR-146a, while Smad4, the target of miR-146a, was decreased. Using an asthma model induced by OVA immunization, we further confirmed the increased level of OVA specific IgE antibodies in TG mice. These results demonstrate that miR-146a enhances class switch and secretion of IgE in B cells by upregulating 14-3-3σ expression, and suggest that miR-146a may be a potential target for asthma therapy.