Comprehensive Analysis of a ceRNA Network Identifies lncR-C3orf35 Associated with Poor Prognosis in Osteosarcoma

Identification and prognostic evaluation of differentially expressed long noncoding RNAs associated with immune infiltration in osteosarcoma

Osteosarcoma is a malignant bone cancer that originates from the bone with the strongest invasiveness. Tumor formation strongly correlates with immune cell infiltration into the tumor immune microenvironment (TIME). Therefore, we aimed to identify TIME-related biomarkers as potential prognostic markers of osteosarcoma. The mRNA and long noncoding RNA (lncRNA) transcriptome data of 88 patients with osteosarcoma and the expression profile of GSE99671 were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus, respectively. Immune infiltration scores and types were evaluated using ESTIMATE and CIBERSORT. A linear model was established to identify the differentially expressed genes (DEGs) and lncRNAs (DElncRNAs). Functional enrichment analysis of DEGs was conducted by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, gene set enrichment analysis, and gene set variation analysis. DElncRNAs were analyzed using a weighted gene co-expression network. Least absolute shrinkage and selection operator regression was applied to screen for prognostic markers. Patient survival was predicted by the risk score and analyzed by receiver operating characteristic curve. Clinical features affecting patient survival were assessed. Immune infiltration positively correlated with osteosarcoma patient survival. Different immune cell infiltrates in patients with osteosarcma may serve as prognostic indicators and targets for immunotherapy. In total, 1125 DEGs, 80 DElncRNAs, and 11 pairs of co-expressed lncRNA-mRNAs were identified. DEGs in the three modules were associated with immune infiltration into the TIME. Four DElncRNAs, namely AC015819.1, AC015911.3, AL365361.1, and USP30-AS1, showed good prognostic ability for osteosarcoma and were positively correlated with the immune score. Tumor metastasis and risk scores alone were good prognostic indicators, and a combination of the two variables can better predict the prognosis of osteosarcoma. We identified four lncRNAs, AC015819.1, AC015911.3, AL365361.1, and USP30-AS1, as potential biomarkers for osteosarcoma prognosis.

C10orf55, CASC2, and SFTA1P lncRNAs Are Potential Biomarkers to Assess Radiation Therapy Response in Head and Neck Cancers

Long non-coding RNAs have proven to be important molecules in carcinogenesis. Due to little knowledge about them, the molecular mechanisms of tumorigenesis are still being explored. The aim of this work was to study the effect of ionizing radiation on the expression of lncRNAs in head and neck squamous cell carcinoma (HNSCC) in patients responding and non-responding to radiotherapy. The experimental model was created using a group of patients with response (RG, n = 75) and no response (NRG, n = 75) to radiotherapy based on the cancer genome atlas (TCGA) data. Using the in silico model, statistically significant lncRNAs were defined and further validated on six HNSCC cell lines irradiated at three different doses. Based on the TCGA model, C10orf55, C3orf35, C5orf38, CASC2, MEG3, MYCNOS, SFTA1P, SNHG3, and TMEM105, with the altered expression between the RG and NRG were observed. Analysis of pathways and immune profile indicated that these lncRNAs were associated with changes in processes, such as epithelial-to-mesenchymal transition, regulation of spindle division, and the p53 pathway, and differences in immune cells score and lymphocyte infiltration signature score. However, only C10orf55, CASC2, and SFTA1P presented statistically altered expression after irradiation in the in vitro model. In conclusion, the expression of lncRNAs is affected by ionization radiation in HNSCC, and these lncRNAs are associated with pathways, which are important for radiation response and immune response. Potentially presented lncRNAs could be used as biomarkers for personalized radiotherapy in the future. However, these results need to be verified based on an in vitro experimental model to show a direct net of interactions.

Bioinformatics and Experimental Analyses Reveal Immune-Related LncRNA-mRNA Pair AC011483.1-CCR7 as a Biomarker and Therapeutic Target for Ischemic Cardiomyopathy

Ischemic cardiomyopathy (ICM), which increases along with aging, is the leading cause of heart failure. Currently, immune response is believed to be critical in ICM whereas the roles of immune-related lncRNAs remain vague. In this study, we aimed to systematically analyze immune-related lncRNAs in the aging-related disease ICM. Here, we downloaded publicly available RNA-seq data from ischemic cardiomyopathy patients and non-failing controls (GSE116250). Weighted gene co-expression network analysis (WGCNA) was performed to identify key ICM-related modules. The immune-related lncRNAs of key modules were screened by co-expression analysis of immune-related mRNAs. Then, a competing endogenous RNA (ceRNA) network, including 5 lncRNAs and 13 mRNAs, was constructed using lncRNA-mRNA pairs which share regulatory miRNAs and have significant correlation. Among the lncRNA-mRNA pairs, one pair (AC011483.1-CCR7) was verified in another publicly available ICM dataset (GSE46224) and ischemic cell model. Further, the immune cell infiltration analysis of the GSE116250 dataset revealed that the proportions of monocytes and CD8⁺ T cells were negatively correlated with the expression of AC011483.1-CCR7, while plasma cells were positively correlated, indicating that AC011483.1-CCR7 may participate in the occurrence and development of ICM through immune cell infiltration. Together, our findings revealed that lncRNA-mRNA pair AC011483.1-CCR7 may be a novel biomarker and therapeutic target for ICM.