Identification of a competing endogenous RNA axis "SVIL-AS1/miR-103a/ICE1" associated with chemoresistance in lung adenocarcinoma by comprehensive bioinformatics analysis

Emerging role of competing endogenous RNA in lung cancer drug resistance

Lung cancer remains one of the most common malignant cancers worldwide, and its survival rate is extremely low. Chemotherapy, the mainstay of lung cancer treatment, is not as effective as it could be due to the development of cellular resistance. The molecular mechanisms of drug resistance in lung cancer remain to be elucidated. Accumulating evidence suggests that ceRNAs are involved in various carcinogenesis and development. CeRNA is a transcript that regulates each other through competition with miRNA. However, the relationship between ceRNAs and chemoresistance in lung cancer remains unclear. In this narrative review, we provided a summary of treatment approaches that focus on ceRNA networks to overcome drug resistance.

Crosstalk among disulfidptosis-related lncRNAs in lung adenocarcinoma reveals a correlation with immune profile and clinical prognosis

Disulfidptosis refers to a specific programmed cell death process characterized by the accumulation of disulfides. It has recently been reported in several cancers. However, the impact of disulfidptosis-related long non-coding RNAs (lncRNAs) on malignant tumors has remained largely unknown. In the present work, we screened prognostic disulfidptosis-related lncRNAs and studied their effects on lung adenocarcinoma. Relevant clinical data of lung adenocarcinoma cases were retrieved from The Cancer Genome Atlas (TCGA) database. RNA sequencing was used to identify differentially expressed disulfidptosis-related lncRNAs within lung adenocarcinoma. In addition, prognostic disulfidptosis-related lncRNAs were obtained through univariate Cox regression analysis. LASSO-COX was used to construct new disulfidptosis-related lncRNA signatures. Different statistical approaches were used to validate the practicability and accuracy of the disulfidptosis-related lncRNAs signatures. Furthermore, several bioinformatic approaches were used to study relevant heterogeneities in biological processes and pathways of diverse risk groups. Reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was conducted to analyze the expression of disulfidptosis-related lncRNAs. Finally, seven disulfidptosis-related lncRNA signatures were identified in lung adenocarcinoma cells. The prognosis prediction model constructed efficiently predicted patient survival. Subgroup analysis revealed significant differences in immune cell proportion, including T follicular helper cells and M0 macrophages. In addition, in vitro experimental results demonstrated significant differences in disulfidptosis-related lncRNAs. Altogether, the six disulfidptosis-related lncRNA signatures could serve as a potential prognostic biomarker for lung adenocarcinoma. Furthermore, these can be used as a prediction model in individualized immunotherapy for lung adenocarcinoma.

Engineered exosomes transporting the lncRNA, SVIL-AS1, inhibit the progression of lung cancer via targeting miR-21-5p

In this study, we constructed engineered exosomes carrying the long non-coding RNA (lncRNA) SVIL-AS1 (SVIL-AS1 Exos), and explored its role and mechanism in lung cancer. After the construction of SVIL-AS1 Exos, their physicochemical characteristics were identified. Then, their function and effect in three different cell lines, A549, HeLa, and HepG2, were detected using western blot, the quantitative reverse transcriptase polymerase chain reaction, flow cytometry, 5-ethynyl-2'-deoxyuridine, and Cell Counting Kit-8 experiments. Finally, a mouse xenograft model was constructed to analyze tumor growth and explore the in vivo utility of SVIL-AS1 Exos using hematoxylin and eosin staining, immunohistochemistry, and the TdT-mediated dUTP nick end labeling assay. The results demonstrated that SVIL-AS1 Exos preferentially targeted A549 lung cancer cells over HeLa and HepG2 cells. SVIL-AS1 Exos promoted apoptosis and inhibited A549 cell proliferation by elevating expression of the lncRNA, SVIL-AS1. In vivo, SVIL-AS1 Exos effectively inhibited the growth of lung cancer A549 cells. Furthermore, SVIL-AS1 Exos suppressed the expression of miR-21-5p and upregulated the expression of caspase-9, indicating that SVIL-AS1 may regulate the development of lung cancer through the miR-21-5p/caspase-9 pathway. In conclusion, the engineered SVIL-AS1 Exos targeted lung cancer cells to inhibit the expression of miR-21-5p, upregulate the expression of caspase-9, and inhibit the development of lung cancer.

LncRNA-associated competing endogenous RNA network analysis uncovered key lncRNAs involved in temozolomide resistance and tumor recurrence of glioblastoma

Temozolomide (TMZ) is a common alkylating chemotherapeutic agent used to treat brain tumors such as glioblastoma multiforme (GBM) and anaplastic astrocytoma. GBM patients develop resistance to this drug, which has an unclear and complicated molecular mechanism. The competing endogenous RNAs (ceRNAs) play critical roles in tumorigenesis, drug resistance, and tumor recurrence in cancers. This study aims to predict ceRNAs, their possible involvement, and underlying molecular mechanisms in TMZ resistance. Therefore, we analyzed coding and non-coding RNA expression levels in TMZ-resistant GBM samples compared to sensitive GBM samples and performed pathway analysis of mRNAs differentially expressed (DE) in TMZ-resistant samples. We next applied a mathematical model on 950 DE long non-coding RNAs (lncRNAs), 116 microRNAs (miRNAs), and 7977 mRNAs and obtained 10 lncRNA-associated ceRNAs that may be regulating potential target genes involved in cancer-related pathways by sponging 25 miRNAs in TMZ-resistant GBM. Among these, two lncRNAs named ARFRP1 and RUSC2 regulate five target genes (IRS1, FOXG1, GNG2, RUNX2, and CACNA1E) involved in AMPK, AKT, mTOR, and TGF-β signaling pathways that activate or inhibit autophagy causing TMZ resistance. The novel lncRNA-associated ceRNA network predicted in GBM offers a fresh viewpoint on TMZ resistance, which might contribute to treating this malignancy.

Duality of the SVIL expression in bladder cancer and its correlation with immune infiltration

SVIL is a member of the villin/gelsolin superfamily and is responsible for encoding supervillin. It has been reported to be closely related to the occurrence and development of various tumors. However, the mechanism of SVIL in bladder cancer has not been reported yet. In this research, we evaluated the relationship between SVIL expression and bladder cancer in public dataset and examined the expression of SVIL in bladder cancer cell lines, tissue microarrays and patients in our cohort. Our work determined that the expression of SVIL in bladder cancer tissue was significantly lower than that in normal tissue. However, in bladder cancer tissues, the high expression of SVIL is significantly associated with poor prognosis. This kind of duality is very novel and has great research value. The expression level of SVIL can well predict the survival time of bladder cancer patients, and is an independent risk factor of bladder cancer patients. The expression of SVIL is also closely related to the immune tumor microenvironment of bladder cancer. Our research provides a basis for personalized therapeutic targets for bladder cancer.

Integrated analysis to identify the AC005154.6/hsa-miR-29c-3p/CCNL2 axis as a novel prognostic biomarker associated with immune infiltration in prostate cancer

Background

Prostate cancer (PCa) is currently the major malignancy in men. It is becoming increasingly clear that competitive endogenous RNA (ceRNA) regulation networks are important in a wide variety of cancers. Nevertheless, there is still much to learn about the biological functions of the ceRNA network in prostate cancer.

Methods

The ceRNA network was constructed using the "GDCRNATools" package. Based on survival analysis, we obtained AC005154.6/hsa-miR-29c-3p/CCNL2 for further analysis. The prognostic model based on this ceRNA network was constructed by univariate and multivariate Cox regression methods. Furthermore, functional enrichment analysis, mutation landscape analysis, immune infiltration analysis, drug sensitivity analysis, methylation analysis, pan-cancer analysis, and molecular experiments of CCNL2 were carried out to investigate the role of CCNL2 in tumorigenesis.

Results

We identified the AC005154.6/CCNL2 axis as a risk factor that can promote the progression of prostate cancer by bioinformatics analysis and molecular experiments. Immune infiltration analysis suggested that CCNL2 may act as a novel biomarker for treatment decisions. The methylation level of CCNL2 was significantly decreased in tumor samples, possibly contributing to the upregulation of CCNL2 in prostate cancer. Moreover, CCNL2 is differentially expressed in multiple cancers and is tightly correlated with immune infiltration.

Conclusion

The current study constructed a ceRNA network, AC005154.6/hsa-miR-29c-3p/CCNL2. Potentially, this biomarker can be used for early diagnosis and decision-making about prostate cancer treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02779-5.

Weighted Gene Co-Expression Network Analysis and Treatment Strategies of Tumor Recurrence-Associated Hub Genes in Lung Adenocarcinoma

Despite the recent progress of lung adenocarcinoma (LUAD) therapy, tumor recurrence remained to be a challenging factor that impedes the effectiveness of treatment. The objective of the present study was to predict the hub genes affecting LUAD recurrence via weighted gene co-expression network analysis (WGCNA). Microarray samples from LUAD dataset of GSE32863 were analyzed, and the modules with the highest correlation to tumor recurrence were selected. Functional enrichment analysis was conducted, followed by establishment of a protein-protein interaction (PPI) network. Subsequently, hub genes were identified by overall survival analyses and further validated by evaluation of expression in both myeloid populations and tissue samples of LUAD. Gene set enrichment analysis (GSEA) was then carried out, and construction of transcription factors (TF)-hub gene and drug-hub gene interaction network was also achieved. A total of eight hub genes (ACTR3, ARPC5, RAB13, HNRNPK, PA2G4, WDR12, SRSF1, and NOP58) were finally identified to be closely correlated with LUAD recurrence. In addition, TFs that regulate hub genes have been predicted, including MYC, PML, and YY1. Finally, drugs including arsenic trioxide, cisplatin, Jinfukang, and sunitinib were mined for the treatment of the eight hub genes. In conclusion, our study may facilitate the invention of targeted therapeutic drugs and shed light on the understanding of the mechanism for LUAD recurrence.