Integrative Analysis of Three Novel Competing Endogenous RNA Biomarkers with a Prognostic Value in Lung Adenocarcinoma

SNHG1/miR-21 axis mediates the cardioprotective role of aloin in sepsis through modulating cardiac cell viability and inflammatory responses

BACKGROUND

Aloin has cardioprotective effects, however, its cardioprotective role in sepsis remains unclear. This study aimed to analyze whether aloin could prevent sepsis-related myocardial damage and explore the underlying mechanisms by examining the expression of long-noncoding RNA (lncRNA) SNHG1 and microRNA-21 (miR-21).

METHODS

The interaction of SNHG1 with miR-21 was identified by dual-luciferase reporter assay. The levels of SNHG1 and miR-21 were measured by real-time quantitative PCR. The cardioprotective function of aloin was assessed in a sepsis animal model, which was induced by cecal ligation and puncture, and in a myocardial injury cell model in H9C2 cells stimulated by lipopolysaccharide. Myocardial injury biomarker levels and hemodynamic indicators in mice model were measured to evaluate cardiac function. The viability of H9C2 cells was assessed by cell counting kit-8 assay. Inflammatory cytokine levels were examined by an ELISA method.

RESULTS

Decreased SNHG1 and increased miR-21 were found in sepsis patients with cardiac dysfunction, and they were negatively correlated. Aloin significantly attenuated myocardial damage and inflammatory responses of mice model, and increased the viability and suppressed inflammation in H9C2 cell model. In addition, SNHG1 expression was upregulated and miR-21 expression was downregulated by aloin in both mice and cell models. Moreover, in mice and cell models, SNHG1/miR-21 axis affected sepsis-related myocardial damage, and mediated the cardioprotective effects of aloin.

CONCLUSION

Our findings indicated that aloin exerts protective effects in sepsis-related myocardial damage through regulating cardiac cell viability and inflammatory responses via regulating the SNHG1/miR-21 axis.

Novel pyroptosis-related lncRNAs and ceRNAs predict osteosarcoma prognosis and indicate immune microenvironment signatures

Objective

To study pyroptosis-related biomarkers that are associated with the prognosis and immune microenvironment characteristics of osteosarcoma (OS). The goal is to establish a foundation for the prognosis and treatment of OS.

Methods

We retrieved transcriptome and clinical data from The Cancer Genome Atlas (TCGA) database for 88 OS patients. Using this data, we constructed a prognostic model to identify pyroptosis-related genes (PRGs) associated with OS prognosis. To further explore the biological function of these PRGs, we performed enrichment analysis. To identify pyroptosis-related long non-coding RNAs (PRLncs) associated with the prognosis of OS, we performed co-expression analysis. Subsequently, a risk prognostic model was constructed using these PRLncs to generate a risk score, termed as PRLncs-score, thereby obtaining PRLncs associated with the prognosis of OS. The accuracy of the prognostic model was verified through survival analysis, risk curve, independent prognostic analysis, receiver operating characteristic (ROC) curve, difference analysis between high- and low-risk groups, and clinical correlation analysis. And to determine whether PRLncs-score is independent prognostic factor for OS. In addition, we further conducted external and internal validation for the risk prognosis model. Further analyses of immune cell infiltration and tumor microenvironment were performed. A pyroptosis-related competitive endogenous RNA (PRceRNA) network was constructed to obtain PRceRNAs associated with the prognosis of OS and performed gene set enrichment analysis (GSEA) on PRceRNA genes.

Results

We obtained five PRGs (CHMP4C, BAK1, GSDMA, CASP1, and CASP6) that predicted OS prognosis and seven PRLncs (AC090559.1, AP003119.2, CARD8-AS1, AL390728.4, SATB2-AS1, AL133215.2, and AC009495.3) and one PRceRNA (CARD8-AS1-hsa-miR-21-5p-IL1B) that predicted OS prognosis and indicated characteristics of the OS immune microenvironment. The PRLncs-score, in combination with other clinical features, was established as an independent prognostic factor for OS patients. Subsequent scrutiny of the tumor microenvironment and immune infiltration indicated that patients with low-PRLncs-scores were associated with reduced metastatic risk, improved survival rates, heightened levels of immune cells and stroma, and increased immune activity compared to those with high-PRLncs-scores.

Conclusion

The study's findings offer insight into the prognosis of OS and its immune microenvironment, and hold promise for improving early diagnosis and immunotherapy.

Identification of DDX31 as a Potential Oncogene of Invasive Metastasis and Proliferation in PDAC

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignant tumors worldwide and has poor prognosis. DEAD box proteins31 (DDX31) participate in cellular processes involving RNA secondary structure changes. However, the functions of DDX31 in PDAC remain to be elucidated.

Methods: The key gene DDX31 was identified using a combination of a risk model and weighted gene co-expression network analysis (WGCNA) with R software. The biological functions of DDX31 in PDAC were investigated through bioinformatics analysis and in vitro experiments.

Results: Combining with WGCNA and risk model, DDX31 was identified as a potential factor of the invasive metastasis properties of PDAC, and its expression was closely related to the malignant differentiation of PDAC. The results of gene set enrichment analysis (GSEA) showed that DDX31 was correlated with cell invasive metastasis and proliferation by activating MAPK signaling pathway. The inhibition of DDX31 inhibited the invasion and migration of PDAC cells. Survival analysis showed that DDX31 expression was negatively associated with the poor prognosis in patients with PDAC.

Interpretation:DDX31 may be a potential factor for PDAC. The inhibition of DDX31 may be a potential way to treat PDAC.

Identification of Ferroptosis-Related Genes Signature Predicting the Efficiency of Invasion and Metastasis Ability in Colon Adenocarcinoma

Background: Colon adenocarcinoma (COAD) is one of the most prevalent cancers worldwide and has become a leading cause of cancer death. Although many potential biomarkers of COAD have been screened with the bioinformatics method, it is necessary to explore novel markers for the diagnosis and appropriate individual treatments for COAD patients due to the high heterogeneity of this disease. Epithelial-to-mesenchymal transition (EMT)-mediated tumor metastasis suggests poor prognosis of cancers. Ferroptosis is involved in tumor development. EMT signaling can increase the cellular sensitivity to ferroptosis in tumors. The aim of our study is finding novel prognostic biomarkers to determine COAD patients for predicting efficiency of metastasis status and targeting precise ferroptosis-related therapy.

Methods: A novel gene signature related to metastasis and ferroptosis was identified combing with risk model and WGCNA analysis with R software. The biological functions and predictive ability of the signature in COAD were explored through bioinformatics analysis.

Results: We established a four-gene prognostic signature (MMP7, YAP1, PCOLCE, and HOXC11) based on EMT and ferroptosis related genes and validated the reliability and effectiveness of this model in COAD. This four-gene prognostic signature was closely connected with metastasis and ferroptosis sensitivity of COAD. Moreover, WGCNA analysis further confirmed the correlation between PCOLCE, HOXC11, and liver and lymphatic invasion of COAD.

Conclusion: The four genes may become potential prognostic biomarkers to identify COAD patients with metastasis. Moreover, this four-gene signature may be able to determine the COAD suitable with ferroptosis induction therapy. Finally, PCOLCE2 and HOXC11 were selected individually because of their novelties and precise prediction ability. Overall, this signature provided novel possibilities for better prognostic evaluation of COAD patients and may be of great guiding significance for individualized treatment and clinical decision.

MiR-133b suppresses the proliferation, migration and invasion of lung adenocarcinoma cells by targeting SKA3

Spindle and Kinetochore Associated Complex Subunit 3 (SKA3) is crucial for anaphase mitosis. However, the relationship between SKA3 and lung adenocarcinoma (LUAD) has not been fully clarified. Differentially expressed genes were first identified by analyzing data from TCGA. It was found that miR-133b was significantly lowly expressed in LUAD, while SKA3 was remarkably highly expressed. Cell Counting Kit-8 (CCK8), wound healing assay and Transwell assay uncovered that overexpressing miR-133b could inhibit the proliferation, invasion and migration of LUAD cells. In addition, the targeting relationship between miR-133b and SKA3 was also verified by dual-luciferase analysis. Moreover, it was proved by the rescue assay that the overexpression of miR-133b significantly downregulated SKA3 in LUAD cells. All in all, these findings revealed the role of miR-133b and SKA3 in regulating the proliferation, migration, and invasion of LUAD cells. This study could yield new information about the mechanisms of LUAD.

Overexpression of microRNA-340-5p Ameliorates Inflammatory Response and Intracellular Survival of Mycobacterium Tuberculosis in Alveolar Type II Cells

Background

The importance of microRNAs (miRs) has been documented in infections. This study estimated the role of miR-340-5p in Mycobacterium tuberculosis (Mtb)-infected alveolar type II cells.

Methods

The microarray of GEO database was analyzed to find the differentially expressed miRs caused by Mtb infection, and miR-340-5p was selected as the research object. The effects of Mtb infection on A549 cells were studied by MTT, CFU, EdU, flow cytometry and ELISA assays. miR-340-5p expression was altered in Mtb-infected A549 cells. The downstream target of miR-340-5p was found by bioinformatics analysis and verified by the rescue experiment. The pathways regulated by miR-340-5p and its target gene were further studied.

Results

Mtb infection suppressed the activity of A549 cells and promoted the release of inflammatory factors. Mtb infection inhibited miR-340-5p expression. Overexpression of miR-340-5p enhanced the resistance of A549 cells to Mtb infection. Moreover, miR-340-5p targeted TMED7. Overexpression of TMED7 reversed the protective effect of miR-340-5p on Mtb-infected A549 cells. miR-340-5p inhibited the activation of NF-κB by targeting TMED7.

Conclusion

miR-340-5p inhibits the activation of NF-κB by targeting TMED7, thus alleviating the injury of A549 cells caused by Mtb infection. This study may offer a novel approach to Mtb infection.

Expression and gene regulatory network of SNHG1 in hepatocellular carcinoma

BACKGROUND

Small nucleolar RNA host gene 1 (SNHG1), a long noncoding RNA (lncRNA), is a transcript that negatively regulates tumour suppressor genes, such as p53. Abnormal SNHG1 expression is associated with cell proliferation and cancer. We used sequencing data downloaded from Genomic Data Commons to analyse the expression and interaction networks of SNHG1 in hepatocellular carcinoma (HCC).

METHODS

Expression was examined using the limma package of R and verified by Gene Expression Profiling Interactive Analysis. We also obtained miRNA expression data from StarBase to determine the lncRNA-miRNA-mRNA-related RNA regulatory network in HCC. Kaplan-Meier (KM) analysis was performed using the survival package of R. Gene Ontology annotation of genes was carried out using Metascape.

RESULTS

We found that SNHG1 was overexpressed and often amplified in HCC patients. In addition, SNHG1 upregulation was associated with the promotion of several primary biological functions, including cell proliferation, transcription and protein binding. Moreover, we found similar trends of small nucleolar RNA host gene 1 (SNHG1), E2F8 (E2F transcription factor 8), FANCE (FA complementation group E) and LMNB2 (encodes lamin B2) expression. In the SNHG1-associated network, high expression levels of SNHG1 (log-rank P value = 0.0643), E2F8 (log-rank P value = 0.000048), FANCE (log-rank P value = 0.00125) and LMNB2 (log-rank P value = 0.0392) were significantly associated with poor survival. Single-cell analysis showed that E2F8 may play an important role in tumorigenesis or cancer development.

CONCLUSIONS

Our results highlight the benefit of utilizing multiple datasets to understand the functional potential regulatory networks of SNHG1 and the role of SNHG1 in tumours.