LncRNA PSMG3AS1 promotes proliferation of non-small cell lung cancer cells by sponging miR-613 to upregulate SphK1

Prognosis Signature of Cuprotosis-Related lncRNAs Associated with Kidney Renal Clear Cell Carcinoma

Cuprotosis is a novel cell death mechanism that can be explored to treat various tumors. A few studies on the role of cuprotosis-related long noncoding RNA (lncRNA) in the development and prognosis of kidney renal clear cell carcinoma (KIRC) have been reported. We aimed to study the relationship between the prognosis of patients suffering from KIRC and lncRNAs associated with cuprotosis. The Cancer Genome Atlas (TCGA) database was analyzed, and the transcriptome data and clinical information on the patients with KIRC were obtained. The cuprotosis-related lncRNAs were identified by using Pearson correlation analysis, and the significant changes in the lncRNAs associated with KIRC were studied by conducting the T-test. The cuprotosis-related lncRNAs with KIRC prognostic values were identified by using the univariate Cox analysis, least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM) methods. A prognostic marker composed of three cuprotosis-related lncRNAs was identified following the multivariate regression analysis method. Patients with KIRC were divided into two groups based on the expression characteristics of three cuprotosis-related lncRNAs by using the K nearest neighbor (KNN) cluster analysis method. Significant differences in survival were observed between the two groups. In addition, the results obtained following the independent prognostic analysis of the risk score (RS) and clinical correlation revealed that the three cuprotosis-related lncRNA prognostic markers could accurately predict the prognosis of patients with KIRC. The results reported herein provide new insights into the pathogenesis of KIRC and the contribution of lncRNAs associated with cuprotosis. The results also helped identify a prognostic indicator that could potentially provide information for KIRC treatment.

Targeting SPHK1/PBX1 Axis Induced Cell Cycle Arrest in Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for 85~90% of lung cancer cases, with a poor prognosis and a low 5-year survival rate. Sphingosine kinase-1 (SPHK1), a key enzyme in regulating sphingolipid metabolism, has been reported to be involved in the development of NSCLC, although the underlying mechanism remains unclear. In the present study, we demonstrated the abnormal signature of SPHK1 in NSCLC lesions and cell lines of lung cancers with a potential tumorigenic role in cell cycle regulation. Functionally, ectopic Pre-B cell leukemia homeobox-1 (PBX1) was capable of restoring the arrested G1 phase induced by SPHK1 knockdown. However, exogenous sphingosine-1-phosphate (S1P) supply had little impact on the cell cycle arrest by PBX1 silence. Furthermore, S1P receptor S1PR3 was revealed as a specific switch to transport the extracellular S1P signal into cells, and subsequently activated PBX1 to regulate cell cycle progression. In addition, Akt signaling partially participated in the SPHK1/S1PR3/PBX1 axis to regulate the cell cycle, and the Akt inhibitor significantly decreased PBX1 expression and induced G1 arrest. Targeting SPHK1 with PF-543 significantly inhibited the cell cycle and tumor growth in preclinical xenograft tumor models of NSCLC. Taken together, our findings exhibit the vital role of the SPHK1/S1PR3/PBX1 axis in regulating the cell cycle of NSCLC, and targeting SPHK1 may develop a therapeutic effect in tumor treatment.

Long non-coding RNAs and exosomal lncRNAs: Potential functions in lung cancer progression, drug resistance and tumor microenvironment remodeling

Among the different kinds of tumors threatening human life, lung cancer is one that is commonly observed in both males and females. The aggressive behavior of lung cancer and interactions occurring in tumor microenvironment enhances the malignancy of this tumor. The lung tumor cells have demonstrated capacity in developing chemo- and radio-resistance. LncRNAs are a category of non-coding RNAs that do not encode proteins, but their aberrant expression is responsible for tumor development, especially lung cancer. In the present review, we focus on both lncRNAs and exosomal lncRNAs in lung cancer, and their ability in regulating proliferation and metastasis. Cell cycle progression and molecular mechanisms related to lung cancer metastasis such as EMT and MMPs are regulated by lncRNAs. LncRNAs interact with miRNAs, STAT, Wnt, EZH2, PTEN and PI3K/Akt signaling pathways to affect progression of lung cancer cells. LncRNAs demonstrate both tumor-suppressor and tumor-promoting functions in lung cancer. They can be considered as biomarkers in lung cancer and especially exosomal lncRNAs present in body fluids are potential tools for minimally invasive diagnosis. Furthermore, we discuss regulation of lncRNAs by anti-cancer drugs and genetic tools as well as the role of these factors in therapy response of lung cancer cells.

Analysis of the prognostic significance and potential mechanisms of lncRNAs associated with m6A methylation in papillary thyroid carcinoma

BACKGROUND

m6A methylation-related long non-coding RNAs (lncRNAs) play a significant role in the progression of various tumors and can be used as prognostic markers. However, whether m6A-related lncRNAs also play the same function as prognostic markers in papillary thyroid carcinoma (PTC) remains unclear.

METHODS

Consensus cluster analysis was performed to divide PTC samples obtained from The Cancer Genome Atlas database into two clusters according to the expression of m6A-related lncRNAs. Then, the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to create and verify a prognostic model. Furthermore, the relationship among risk scores, clusters, programmed death-ligand 1 (PD-L1), tumor microenvironment (TME), clinicopathological characteristics, immune infiltration, immune checkpoint, and tumor mutation burden (TMB) was analyzed. In addition, a nomogram was created, and subsequently, the drug sensitivity of lncRNAs in the prognostic model was analyzed. Finally, the relationship between these lncRNAs and prognosis in pan-cancer was investigated.

RESULTS

The prognosis, RAS, BRAF, M, and TME were found to be different in two clusters. The prognostic model included three lncRNAs: PSMG3-AS1, BHLHE40-AS1, and AC016747.3. The risk score was associated with clusters, PD-L1, tumor microenvironment, clinicopathological characteristics, immune cell infiltration, immune checkpoint, and TMB, and thus, risk score was confirmed as useful prognostic indicator. Differentially expressed lncRNAs are involved in many malignancies and can be identified as cancer prognostic makers.

CONCLUSION

According to our research, we can regard m6A-related lncRNAs involved in the procession of PTC as a biomarker of progression-free survival for PTC patients, and pan-cancer.