LINC00968 accelerates the progression of epithelial ovarian cancer via mediating the cell cycle progression

LncRNA-FAM66C Was Identified as a Key Regulator for Modulating Tumor Microenvironment and Hypoxia-Related Pathways in Glioblastoma

Although the role of hypoxia has been greatly explored and unveiled in glioblastoma (GBM), the mechanism of hypoxia-related long non-coding (lnc) RNAs has not been clearly understood. This study aims to reveal the crosstalk among hypoxia-related lncRNAs, tumor microenvironment (TME), and tumorigenesis for GBM. Gene expression profiles of GBM patients were used as a basis for identifying hypoxia-related lncRNAs. Unsupervised consensus clustering was conducted for classifying samples into different molecular subtypes. Gene set enrichment analysis (GSEA) was performed to analyze the enrichment of a series of genes or gene signatures. Three molecular subtypes were constructed based on eight identified hypoxia-related lncRNAs. Oncogenic pathways, such as epithelial mesenchymal transition (EMT), tumor necrosis factor-α (TNF-α) signaling, angiogenesis, hypoxia, P53 signaling, and glycolysis pathways, were significantly enriched in C1 subtype with poor overall survival. C1 subtype showed high immune infiltration and high expression of immune checkpoints. Furthermore, we identified 10 transcription factors (TFs) that were highly correlated with lncRNA-FAM66C. Three key lncRNAs (ADAMTS9-AS2, LINC00968, and LUCAT1) were screened as prognostic biomarkers for GBM. This study shed light on the important role of hypoxia-related lncRNAs for TME modulation and tumorigenesis in GBM. The eight identified hypoxia-related lncRNAs, especially FAM66C may serve as key regulators involving in hypoxia-related pathways.

Long noncoding RNA LINC00968 inhibits proliferation, migration and invasion of lung adenocarcinoma through targeting miR-22-5p/CDC14A axis

Lung adenocarcinoma (LUAD) is a high aggressive human cancer which usually diagnosed at advanced stages. Accumulating evidences indicate that long noncoding RNAs (lncRNAs) are crucial participants in LUAD progression. In the present study, we found that lncRNA LINC00968 was significantly down-regulated in LUAD tissues and cell lines. LINC00968 level was positively correlated to survival rate, and negatively correlated to tumor node metastasis (TNM) stage, tumor size and lymph node metastasis of LUAD patients. We over-expressed LINC00968 in LUAD cells using lentivirus, inhibited proliferation and cell cycle arrest at G1 phase were detected. LINC00968 over-expression also suppressed migration, invasion and epithelial mesenchymal transition. We further validated that LINC00968 localized in cytoplasm and acted as an upstream regulator of microRNA miR-22-5p, which was up-regulated in LUAD tissues and cell lines. Besides, elevated miR-22-5p expression abolished the effect of LINC00968 over-expression on LUAD progression including in vivo tumor growth. In addition, we first validated that cell division cycle 14A (CDC14A), which was down-regulated in LUAD tissues, was a downstream target of miR-22-5p. We over-expressed CDC14A in LUAD cells and miR-22-5p induced LUAD progression was partially reversed. In conclusion, our study demonstrated that LINC00968 inhibited proliferation, migration and invasion of LUAD by sponging miR-22-5p and further restoring CDC14A. This novel regulatory axis might provide us with promising diagnostic and therapeutic target in LUAD treatment.

Identification of a Ferroptosis-Related LncRNA Signature as a Novel Prognosis Model for Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is a highly heterogeneous malignancy, which makes prognosis prediction of LUAD very challenging. Ferroptosis is an iron-dependent cell death mechanism that is important in the survival of tumor cells. Long non-coding RNAs (lncRNAs) are considered to be key regulators of LUAD development and are involved in ferroptosis of tumor cells, and ferroptosis-related lncRNAs have gradually emerged as new targets for LUAD treatment and prognosis. It is essential to determine the prognostic value of ferroptosis-related lncRNAs in LUAD. In this study, we obtained RNA sequencing (RNA-seq) data and corresponding clinical information of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database and ferroptosis-related lncRNAs by co-expression analysis. The best predictors associated with LUAD prognosis, including C5orf64, LINC01800, LINC00968, LINC01352, PGM5-AS1, LINC02097, DEPDC1-AS1, WWC2-AS2, SATB2-AS1, LINC00628, LINC01537, LMO7DN, were identified by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis, and the LUAD risk prediction model was successfully constructed. Kaplan-Meier analysis, receiver operating characteristic (ROC) time curve analysis and univariate and multivariate Cox regression analysis and further demonstrated that the model has excellent robustness and predictive ability. Further, based on the risk prediction model, functional enrichment analysis revealed that 12 prognostic indicators involved a variety of cellular functions and signaling pathways, and the immune status was different in the high-risk and low-risk groups. In conclusion, a risk model of 12 ferroptosis related lncRNAs has important prognostic value for LUAD and may be ferroptosis-related therapeutic targets in the clinic.

Long non‑coding RNA fer‑1‑like family member 4 serves as a tumor suppressor in laryngeal squamous cell carcinoma cells via regulating the AKT/ERK signaling pathway

Laryngeal squamous cell carcinoma (LSCC) is a common type of malignant tumor of the head and neck. An increasing number of studies have illustrated that long non-coding RNAs (lncRNAs) serve an important role in the occurrence and development of LSCC. Therefore, the present study aimed to investigate the expression changes and mechanism of lncRNA fer-1-like family member 4 (FER1L4) in the progression of LSCC. The expression levels of FER1L4 in LSCC cell lines (AMC-HN-8, Tu 686, M4E and M2E) and a normal cell line (HBE135-E6E7) were analyzed using reverse transcription-quantitative PCR. The FER1L4 overexpression plasmid (plasmid-FER1L4) was subsequently transfected into Tu 686 cells to upregulate the expression levels of FER1L4. Cell viability was detected using a Cell Counting Kit-8 assay, cell proliferation was analyzed using a colony formation assay, apoptosis was examined by flow cytometry, and cell migration and invasion were determined using wound healing and Transwell assays, respectively. In addition, the plasmid-FER1L4 cells were also treated with insulin-like growth factor 1 (IGF-1) to determine the effect of FER1L4 on the AKT/ERK signaling pathway, and the effect of the plasmid-FER1L4 on the expression levels of AKT/ERK signaling pathway-related proteins were analyzed using western blotting. The results of the present study revealed that FER1L4 expression levels were downregulated in AMC-HN-8 and Tu 686 cells. Notably, FER1L overexpression significantly reduced the cell viability, proliferation, migration and invasion of LSCC cells, while promoting apoptosis. Meanwhile, the plasmid-FER1L4 also significantly suppressed the phosphorylation levels of AKT and ERK. Further studies indicated that the aforementioned changes could be reversed by IGF-1, indicating FER1L4 may regulate the progression of LSCC cells by inhibiting the AKT/ERK signaling pathway. In conclusion, the present study provided a potential novel direction for the treatment of LSCC in the future and suggested that FER1L4 may be a new target in this field.

lncRNAs classifier to accurately predict the recurrence of thymic epithelial tumors

Background

Long non‐coding RNAs (lncRNAs), which have little or no ability to encode proteins, have attracted special attention due to their potential role in cancer disease. In this study we aimed to establish a lncRNAs classifier to improve the accuracy of recurrence prediction for thymic epithelial tumors (TETs).

Methods

TETs RNA sequencing (RNA‐seq) data set and the matched clinicopathologic information were downloaded from the Cancer Genome Atlas. Using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis, we developed a lncRNAs classifier related to recurrence. Functional analysis was conducted to investigate the potential biological processes of the lncRNAs target genes. The independent prognostic factors were identified by Cox regression model. Additionally, predictive ability and clinical application of the lncRNAs classifier were assessed, and compared with the Masaoka staging by receiver operating characteristic (ROC) analysis and decision curve analysis (DCA).

Results

Four recurrence‐free survival (RFS)‐related lncRNAs were identified, and the classifier consisting of the identified four lncRNAs was able to effectively divide the patients into high and low risk subgroups, with an area under curve (AUC) of 0.796 (three‐year RFS) and 0.788 (five‐year RFS), respectively. Multivariate analysis indicated that the lncRNAs classifier was an independent recurrence risk factor. The AUC of the lncRNAs classifier in predicting RFS was significantly higher than the Masaoka staging system. Decision curve analysis further demonstrated that the lncRNAs classifier had a larger net benefit than the Masaoka staging system.

Conclusions

A lncRNAs classifier for patients with TETs was an independent risk factor for RFS despite other clinicopathologic variables. It generated more accurate estimations of the recurrence probability when compared to the Masaoka staging system, but additional data is required before it can be used in clinical practice.