Characterizing the Copy Number Variation of Non-Coding RNAs Reveals Potential Therapeutic Targets and Prognostic Markers of LUSC

LINC01133 regulates MARCKS expression via sponging miR-30d-5p to promote the development of lung squamous cell carcinoma

LncRNAs are vital regulators for lung squamous cell carcinoma (LUSC). However, the detailed role that LINC01133 plays in LUSC is unclear. This work sought to explore the potential function of LINC01133.Levels of LINC01133, miR-30d-5p, and MARCKS were separately tested in both tissues and cells using qRT-PCR. Proliferation was assessed through MTT experiment and apoptosis was detected upon flow cytometry. Transwell experiments were implemented to evaluate migratory and invasive abilities. The interaction between two genes was affirmed through luciferase reporter assay and RNA pull-down experiment. Western blotting measured the protein level of MARCKS. Animal models were established and tissues were taken for IHC analysis of MARCKS and Ki67.LINC01133 was elevated in LUSC and its downregulation could suppress proliferation, migration and invasion but induced apoptosis. LINC01133 interacted with and regulated the binding of miR-30d-5p to MARCKS. LINC01133/miR-30d-5p axis mediated proliferation, apoptosis, migration and invasion in LUSC cells, as well as modulated tumor growth in animal models. LINC01133 interacted with miR-30d-5p to modulate MARCKS expression, contributes to promoted cell proliferation, migration, invasion, and inhibited cell apoptosis in vitro, and promoted tumor growth in vivo. These findings could provide possible therapeutic targets in view of LUSC treatment in the future.

lncRNA GPRC5D-AS1 as a ceRNA inhibits skeletal muscle aging by regulating miR-520d-5p

Sarcopenia induced by muscle aging is associated with negative outcomes in a variety of diseases. Long non-coding RNAs are a class of RNAs longer than 200 nucleotides with lower protein coding potential. An increasing number of studies have shown that lncRNAs play a vital role in skeletal muscle development. According to our previous research, lncRNA GPRC5D-AS1 is selected in the present study as the target gene to further study its effect on skeletal muscle aging in a dexamethasone-induced human muscle atrophy cell model. As a result, GPRC5D-AS1 functions as a ceRNA of miR-520d-5p to repress cell apoptosis and regulate the expression of muscle regulatory factors, including MyoD, MyoG, Mef2c and Myf5, thus accelerating myoblast proliferation and differentiation, facilitating development of skeletal muscle. In conclusion, lncRNA GPRC5D-AS1 could be a novel therapeutic target for treating sarcopenia.

LINC01936 inhibits the proliferation and metastasis of lung squamous cell carcinoma probably by EMT signaling and immune infiltration

Purpose

To discover the biological function and potential mechanism of LINC01936 in the development of lung squamous cell carcinoma (LUSC).

Methods

Transcriptome data of LUSC from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to analyze the differentially expressed lncRNAs in LUSC and normal tissues by R "DEseq2", "edgeR" and "limma" packages. The subcellular localization of LINC01936 was predicted by lncLocator. Cell proliferation and apoptosis were measured by CCK-8, MTT assay and Hoechst fluorescence staining. The migration and invasion were detected by Transwell assay. The function and pathway enrichment analysis were performed by Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set variation analysis (GSVA). The downstream targets of LINC01936 were predicted using RNA-Protein Interaction Prediction (RPISeq) program. The effect of LINC01936 on tumor immune infiltration was analyzed using Pearson Correlation Analysis using R "ggpubr" package.

Results

Based on the gene expression data of LUSC from TCGA database, 1,603, 1,702 and 529 upregulated and 536, 436 and 630 downregulated lncRNAs were obtained by DEseq2, edgeR and limma programs, respectively. For GSE88862 dataset, we acquired 341 differentially expressed lncRNAs (206 upregulated and 135 downregulated). Venn plot for the intersection of above differential expressed lncRNAs showed that there were 29 upregulated and 23 downregulated genes. LINC01936 was one of downregulated lncRNAs in LUSC tissues. The biological analysis showed that the overexpression of LINC01936 significantly reduced proliferation, migration and invasion of LUSC cells, and promoted cell apoptosis. The knockdown of LINC01936 promoted cell proliferation and metastasis. Pathway and GSVA analysis indicated that LINC01936 might participated in DNA repair, complement, cell adhesion and EMT, etc. LINC01936 was predicted to interact with TCF21, AOC3, RASL12, MEOX2 or HSPB7, which are involved in EMT and PI3K-AKT-MTOR pathway, etc. The expression of LINC01936 was also positively correlated with the infiltrating immune cells in LUSC.

Conclusions

LINC01936 is downregulated in LUSC. LINC01936 affected proliferation, migration and invasion of LUSC cells probably by EMT and immune infiltration, which might serve as a new target for the treatment of LUSC.

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

In this review, we provide a general overview of the current panorama of mining strategies for multi-omics data to investigate lncRNAs with an actual or potential role as biological markers in cancer. Several multi-omics studies focusing on lncRNAs have been performed in the past with varying scopes. Nevertheless, many questions remain regarding the pragmatic application of different molecular technologies and bioinformatics algorithms for mining multi-omics data. Here, we attempt to address some of the less discussed aspects of the practical applications using different study designs for incorporating bioinformatics and statistical analyses of multi-omics data. Finally, we discuss the potential improvements and new paradigms aimed at unraveling the role and utility of lncRNAs in cancer and their potential use as molecular markers for cancer diagnosis and outcome prediction.

Identification of a dysregulated ceRNA network modulated by copy number variation-driven lncRNAs in lung squamous cell carcinoma

Lung cancer is primarily responsive for cancer death, and its progression is aggressively affected by copy number variation (CNV). Through bioinformatics approach, a ceRNA network of CNV-driven lncRNAs in lung squamous cell carcinoma (LUSC) patients was constructed. Data on normal and LUSC tumor tissue from The Cancer Genome Atlas (TCGA)-LUSC dataset were subjected to differential analysis, and differentially expressed lncRNAs (DElncRNAs), DEmiRNAs, and DEmRNAs were obtained. Based on TCGA-LUSC, CNVs of normal and tumor tissue samples were then compared using a Chi-square test, and lncRNAs were intersected based on their CNVs and expression alternation. In combination with the Kruskal-Wallis test, CNV-driven lncRNAs were acquired. Afterwards, miRNAs and mRNAs that interacted with CNV-driven lncRNAs were obtained based on databases (LncBase, starBase, miRDB, mirDIP and TargetScan), DElncRNAs, DEmiRNAs and DEmRNAs, and correlation analysis. The acquired lncRNAs, miRNAs and mRNAs were subjected to Cytoscape software to construct a CNV-driven ceRNA network, which involved 5 lncRNAs (MIR143HG, LINC00702, MIR22HG, RP11-180 N14.1, RP11-473 M20.9), 6 miRNAs (miR-3200-3p, miR-1301-3p, miR-93-3p, miR-96-5p, miR-96-5p, miR-130b-5p, miR-205-5p) and 80 mRNAs. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses indicated that downstream mRNAs were mainly correlated with blood vessel development and T cell-mediated immunity. In summary, we devoted to analyzing CNV-related lncRNAs, mRNAs, and miRNAs in LUSC, thus clarifying 5 lncRNAs that may influence the malignant progression of LUSC. The ceRNA network regulated by these lncRNAs may be the novel pathogenesis of LUSC.

Copy Number Variation of Circulating Tumor DNA (ctDNA) Detected Using NIPT in Neoadjuvant Chemotherapy-Treated Ovarian Cancer Patients

Analysis of circulating tumor DNA (ctDNA) can be used to characterize and monitor cancers. Recently, non-invasive prenatal testing (NIPT) as a new next-generation sequencing (NGS)-based approach has been applied for detecting ctDNA. This study aimed to investigate the copy number variations (CNVs) utilizing the non-invasive prenatal testing in plasma ctDNA from ovarian cancer (OC) patients who were treated with neoadjuvant chemotherapy (NAC). The plasma samples of six patients, including stages II–IV, were collected during the pre- and post-NAC treatment that were divided into NAC-sensitive and NAC-resistant groups during the follow-up time. CNV analysis was performed using the NIPT via two methods “an open-source algorithm WISECONDORX and NextGENe software.” Results of these methods were compared in pre- and post-NAC of OC patients. Finally, bioinformatics tools were used for data mining from The Cancer Genome Atlas (TCGA) to investigate CNVs in OC patients. WISECONDORX analysis indicated fewer CNV changes on chromosomes before treatment in the NAC-sensitive rather than NAC-resistant patients. NextGENe data indicated that CNVs are not only observed in the coding genes but also in non-coding genes. CNVs in six genes were identified, including HSF1, TMEM249, MROH1, GSTT2B, ABR, and NOMO2, only in NAC-resistant patients. The comparison of these six genes in NAC-resistant patients with The Cancer Genome Atlas data illustrated that the total alteration frequency is amplification, and the highest incidence of the CNVs (≥35% based on TCGA data) is found in MROH1, TMEM249, and HSF1 genes on the chromosome (Chr) 8. Based on TCGA data, survival analysis showed a significant reduction in the overall survival among chemotherapy-resistant patients as well as a high expression level of these three genes compared to that of sensitive samples (all, p < 0.0001). The continued Chr8 study using WISECONDORX revealed CNV modifications in NAC-resistant patients prior to NAC therapy, but no CNV changes were observed in NAC-sensitive individuals. Our findings showed that low coverage whole-genome sequencing analysis used for NIPT could identify CNVs in ctDNA of OC patients before and after chemotherapy. These CNVs are different in NAC-sensitive and -resistant patients highlighting the potential application of this approach in cancer patient management.