Construction and validation of an autophagy-related long non-coding RNA signature to predict the prognosis of kidney renal papillary cell carcinoma

C2orf48 promotes the progression of nasopharyngeal carcinoma by regulating high mobility group AT-hook 2

Recurrence and metastasis are the major factors affecting the survival of nasopharyngeal carcinoma (NPC), and the mechanism remains unclear. Long non-coding RNA chromosome 2 open reading frame 48 (C2orf48) has been shown to influence the prognosis of many cancers. However, C2orf48's function in NPC has not been clarified. In this investigation, C2orf48 expression in NPC was measured by quantitative real-time PCR (qRT-PCR) at the cellular and tissue levels, and the association between C2orf48 expression and the prognosis of patients with NPC was examined. Additionally, the effects of C2orf48 and high mobility group AT-hook 2 (HMGA2) upon NPC proliferation, migration, and invasion were examined employing the MTT assay, colony formation assay, and transwell assay, respectively. Furthermore, the association between C2orf48 and HMGA2 in NPC was investigated. Our research demonstrated that C2orf48 was overexpressed in NPC tissues and cell lines, and compared to patients with lower levels of C2orf48 expression, those with higher levels had poorer 5-year overall survival and progression-free survival. Functionally, C2orf48 overexpression accelerated NPC cells proliferation, migration, and invasion. Besides, the tandem mass tag (TMT) quantitative proteomic analysis indicated that HMGA2 may be a target of C2orf48. Moreover, upregulation of C2orf48 could increase HMGA2 expression, and HMGA2 silencing could counteract the proliferation, migration, and invasion changes induced by C2orf48 in NPC cells. These results reveal that overexpression of C2orf48 can promote NPC cells proliferation, migration, and invasion via regulating the expression of HMGA2 and C2orf48 may be a potentially important prognostic marker for NPC.

Cuproptosis-related lncRNA signatures predict prognosis and immune relevance of kidney renal papillary cell carcinoma

Kidney renal papillary cell carcinoma (KIRP) has a high mortality rate and a poor prognosis. Cu concentrations differed significantly between renal cancer tissues and adjacent normal tissues. Cuproptosis is a newly identified cell death. Long non-coding RNAs (lncRNAs) play a crucial role in the progression of KIRP. In this study, we focused on constructing and validating cuproptosis-related lncRNA signatures to predict the prognosis of KIRP patients and their immune correlation. We created prognosis models using Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. We found that patients in the high-risk group had poorer overall survival (OS) and progression-free survival (PFS) and higher mortality. Risk score and stage are prognosis factors independent of other clinical features. Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and C-index curves showed that cuproptosis-related lncRNA signatures could more accurately predict the prognosis of patients. Functional enrichment analysis suggests that the function of differentially expressed genes (DEGs) is associated with KIRP development and immunity. In immune-related function analysis, we found a significant difference in parainflammation responses between high-risk and low-risk groups. The mutation frequencies of TTN, MET, KMT2C, PKHD1, SETD2, and KMT2D genes in the high-risk group were higher than those in the low-risk group, but the mutation frequencies of MUC16, KIAA109, CUBN, USH2A, DNAH8 and HERC2 genes were significantly lower than those in the low-risk group. Survival analysis of tumor mutation burden (TMB) and combined TMB-risk showed better OS in patients with high TMB. Immune infiltration and immune checkpoint analysis assessed the immune association of six high mutation frequency genes (TTN, MET, KMT2C, PKHD1, SETD2, and KMT2D) with KIRP. Finally, we performed a drug sensitivity analysis and screened 15 potential drugs that differed between high-risk and low-risk patients. In this study, we constructed and validated cuproptosis-related lncRNA signatures that can more accurately predict the prognosis of KIRP patients and provide new potential therapeutic targets and prognosis markers for KIRP patients.

Comprehensive bioinformatics analysis and molecular validation of lncRNAs-mediated ceRNAs network in schizophrenia

AIMS

The present study aimed to investigate how Schizophrenia (SCZ)-specific long non-coding RNAs (lncRNAs) served as competing endogenous RNAs (ceRNAs) to modulate the biological functions and pathways involved in the pathogenesis of SCZ.

MAIN METHODS

Microarray dataset (GSE54913) was obtained from Gene Expression Omnibus (GEO) database. Differently expressed (DE) lncRNAs and mRNAs were identified by "limma" package. The binding miRNAs of lncRNAs and target mRNAs of shared miRNAs were predicted by miRcode, miRDB, miRTarbase and targetscan databases. Following the ceRNAs theory, interaction network was established and visualized with the cytoscape. Functional enrichment analysis uncovered the concentrated functions and signaling pathways that may be associated with SCZ progression. Protein-protein interaction (PPI) analysis was utilized to determine hub genes. Quantitative real-time PCR (qRT-PCR) and receiver operating characteristic curve (ROC) were performed to evaluate the expression and diagnostic value of ceRNAs members, respectively.

KEY FINDINGS

DElncRNAs and DEmRNAs were initially screened from GSE54913 to construct the SCZ-related ceRNAs network with 42 nodes and 53 edges. Functional enrichment analysis revealed that ceRNAs members appeared to be highly correlated with transcription factor activation, cell replication and tumor-related pathways. Once validated, a significant ceRNAs subnetwork was proposed as being implicated in the pathogenesis of SCZ. ROC analysis indicated that SCZ-related ceRNAs members may be sensitive diagnostic biomarkers for SCZ.

SIGNIFICANCE

The significant SCZ-related ceRNAs subnetworks (lncRNA-C2orf48A/hsa-miR-20b-5p,-17-5p/KIF23, FOXJ2) may represent promising predictive and diagnostic biomarkers and provide novel insights into the mechanism by which lncRNAs act as microRNA sponges and contribute to the pathogenesis of SCZ.