Characterization of a non-coding RNA-associated ceRNA network in metastatic lung adenocarcinoma

GPR37-centered ceRNA network contributes to metastatic potential in lung adenocarcinoma: Evidence from high-throughput sequencing

The competing endogenous RNA (ceRNA)-based profiling has been extensively studied in carcinogenesis of lung adenocarcinoma (LUAD), while it has seldomly been applied to investigate the metastatic potential of LUAD. This study aims to examine the function and in-depth mechanism of GPR37-centered ceRNA network in LUAD. Cancer tissues and adjacent normal tissues from three LUAD patients were collected for high-throughput sequencing to screen for differentially expressed genes. A PPI network was constructed to screen the key gene GPR37, followed by analysis for the functions and pathways. Clinical data from LUAD patients were integrated with gene expression data in TCGA-LUAD dataset for survival analysis. Based on the miRNAs targeting_GPR37 and lncRNAs targeting_miRNAs, a lncRNA-miRNA-mRNA ceRNA network was established. GPR37 was up-regulated in LUAD tissue samples, and it may be a key gene involved in LUAD progression. GPR37 in LUAD was mainly enriched in the mitosis-related pathways. High GPR37 expression corresponded to poor prognosis in LUAD patients. Meanwhile, GPR37 could be used as an independent factor to predict the prognosis in LUAD patients. LncRNA DLEU1, up-regulated in LUAD tissue samples, may competitively bind to miR-4458 to up-regulate the expression of the miR-4458 downstream target GPR37. DLEU1 was associated with poor prognosis and tumor metastasis in LUAD patients. Altogether, our findings reveal a novel ceRNA network of DLEU1/miR-4458/GPR37 in LUAD growth and metastasis.

Regulation Networks of Non-Coding RNA-Associated ceRNAs in Cisplatin-Induced Acute Kidney Injury

Cisplatin is widely used as a chemotherapeutic drug to treat various solid tumors. However, it often induces severe side effects, including nephrotoxicity, which limits its application in clinical settings. Furthermore, the underlying mechanisms of action are unclear. Here, we applied whole-transcriptome RNA sequencing to a cisplatin-induced acute kidney injury (CP-AKI) mouse model to evaluate competing endogenous RNA (ceRNA) networks. We found 4460 mRNAs, 1851 long non-coding RNAs, 101 circular RNAs, and 102 microRNAs significantly differentially expressed between CP-AKI and control mice. We performed gene set enrichment analysis to reveal the biological functions of the mRNAs and constructed non-coding RNA-associated ceRNA networks in CP-AKI mice. Two ceRNA regulatory pathways, Lhx1os-203/mmu-miR-21a-3p/Slc7a13 and circular RNA_3907/mmu-miR-185-3p/Ptprn, were validated using quantitative real-time PCR. The protein–protein interaction network indicated that Il6, Cxcl1, Cxcl2, and Plk1 serve as hub genes and are highly connected with the inflammatory response or DNA damage. Transcription factors, such as Stat3, Cebpb, and Foxm1, regulate gene expression levels in CP-AKI. Our study provides insight into non-coding RNA-associated ceRNA networks and mRNAs in CP-AKI and identifies potential treatment targets.

Immune-Related Nine-MicroRNA Signature for Predicting the Prognosis of Gastric Cancer

Recent findings have demonstrated the superiority and utility of microRNAs (miRNAs) as new biomarkers for cancer diagnosis, therapy, and prognosis. In this study, to explore the prognostic value of immune-related miRNAs in gastric cancer (GC), we analyzed the miRNA-expression profiles of 389 patients with GC, using data deposited in The Cancer Genome Atlas database. Using a forward- and backward-variable selection and multivariate Cox regression analyses model, we identified a nine-miRNA signature (the “ImmiRSig,” consisting of miR-125b-5p, miR-99a-3p, miR-145-3p, miR-328-3p, miR-133a-5p, miR-1292-5p, miR-675-3p, miR-92b-5p, and miR-942-3p) in the training cohort that enabled the division of patients into high- and low-risk groups with significantly different survival rates. The ImmiRSig was successfully validated with an independent test cohort of 193 GC patients. Univariate and multivariate Cox regression analyses indicated that the ImmiRSig would serve as an independent prognostic factor after adjusting for other clinical covariates. Pending further prospective validation, the identified ImmiRSig appears to have significant clinical importance in terms of improving outcome predictions and guiding personalized treatment for patients with GC. Finally, significant associations between the ImmiRSig and the half-maximal inhibitory concentrations of chemotherapeutic agents were observed, suggesting that ImmiRSig may predict the clinical efficacy of chemotherapy.

ALDH3A1 driving tumor metastasis is mediated by p53/BAG1 in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a lethal malignancy with metastasis, a major tumor feature that predominantly correlated with progression, but the molecules that mediated tumor metastasis remain elusive. To declare the critical regulatory genes, RNA sequencing data in LUAD patients was acquired from The Cancer Genome Atlas (TCGA) and found that ALDH3A1 was distinctly highly expressed in LUAD patients with metastasis (M1) compared with those without metastasis (M0), linked to the property of cancer stem cell and epithelial-mesenchymal transition (EMT). Besides, high ALDH3A1 expression predicted a poor prognosis. Knockdown of ALDH3A1 showed decreased proliferation, migration, and invasion in A549 cell line. Furthermore, BAG1 was regulated by ALDH3A1 through p53, enhanced cell proliferation, and predicted clinical prognosis. Our findings collectively uncovered a novel mechanism that orchestrates tumor cells' metastasis, and decreasing ALDH3A1 represented a potential therapeutic target for reprogramming metastasis.

A Seven-Long Non-coding RNA Signature Improves Prognosis Prediction of Lung Adenocarcinoma: An Integrated Competing Endogenous RNA Network Analysis

Early and precise prediction is an important way to reduce the poor prognosis of lung adenocarcinoma (LUAD) patients. Nevertheless, the widely used tumor, node, and metastasis (TNM) staging system based on anatomical information only often could not achieve adequate performance on foreseeing the prognosis of LUAD patients. This study thus aimed to examine whether the long non-coding RNAs (lncRNAs), known highly involved in the tumorigenesis of LUAD through the competing endogenous RNAs (ceRNAs) mechanism, could provide additional information to improve prognosis prediction of LUAD patients. To prove the hypothesis, a dataset consisting of both RNA sequencing data and clinical pathological data, obtained from The Cancer Genome Atlas (TCGA) database, was analyzed. Then, differentially expressed RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) were identified and a lncRNA-miRNA-mRNA ceRNA network was constructed based on those differentially expressed RNAs. Functional enrichment analysis revealed that this ceRNA network was highly enriched in some cancer-associated signaling pathways. Next, lasso-Cox model was run 1,000 times to recognize the potential survival-related combinations of the candidate lncRNAs in the ceRNA network, followed by the "best subset selection" to further optimize these lncRNA-based combinations, and a seven-lncRNA prognostic signature with the best performance was determined. Based on the median risk score, LUAD patients could be well distinguished into high-/low-risk subgroups. The Kaplan-Meier survival curve showed that LUAD patients in the high-risk group had significantly shorter overall survival than those in the low-risk group (log-rank test P = 4.52 × 10^-9). The ROC curve indicated that the clinical genomic model including both the TNM staging system and the signature had a superior performance in predicting the patients' overall survival compared to the clinical model with the TNM staging system only. Further stratification analysis suggested that the signature could work well in the different strata of the stage, gender, or age, rendering it to be a wide application. Finally, a ceRNA subnetwork related to the signature was extracted, demonstrating its high involvement in the tumorigenesis mechanism of LUAD. In conclusion, the present study established a lncRNA-based molecular signature, which can significantly improve prognosis prediction for LUAD patients.

Characterization of a non-coding RNA-associated ceRNA network in metastatic lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a highly malignant cancer. Although competing endogenous RNA (ceRNA)-based profiling has been investigated in patients with LUAD, it has not been specifically used to study metastasis in LUAD. We found 130 differentially expressed (DE) lncRNAs, 32 DE miRNAs and 981 DE mRNAs from patients with LUAD in The Cancer Genome Atlas (TCGA) database. We analysed the functions and pathways of 981 DE mRNAs using the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Based on the target DE mRNAs and DE lncRNAs of DE miRNAs, we established an lncRNA-miRNA-mRNA ceRNA network, comprising 37 DE lncRNAs, 22 DE miRNAs and 212 DE mRNAs. Subsequently, we constructed a protein-protein interaction network of DE mRNAs in the ceRNA network. Among all, DE RNAs, 5 DE lncRNAs, 5 DE miRNAs and 45 DE mRNAs were confirmed found to be associated with clinical prognosis. Moreover, 3 DE lncRNAs, 4 DE miRNAs and 9 DE mRNAs in the ceRNA network were associated with clinical prognosis. We further screened 3 DE lncRNAs, 3 DE miRNAs and 3 DE mRNAs using clinical samples. These DE lncRNAs, DE miRNAs and DE mRNAs in ceRNA network may serve as independent biomarkers of LUAD metastasis.