Long non‑coding RNA LINC01748 exerts carcinogenic effects in non‑small cell lung cancer cell lines by regulating the microRNA‑520a‑5p/HMGA1 axis

LncRNA RP11-93B14.5 promotes gastric cancer cell growth through PI3K/AKT signaling pathway

OBJECTIVE

Emerging evidence indicates that long non-coding RNA (lncRNA) RP11-93B14.5 facilitates tumor progression in variety of malignancies. The present study proposed to study the functional effect of lncRNA RP11-93B14.5 in gastric cancer (GC) as well as the underlying mechanism.

METHODS

Bioinformatics analysis was utilized to analyze lncRNA expression in GC tissues. siRNA was used for knockdown of RP11-93B14.5 in GC cells MKN45 and KATO III. The stable knockdown cell lines were constructed by CRISPR-Cas9. Cell counting kit-8 (CCK-8) assay and soft agar colony formation assay were used to analyze GC cell viability. Flow cytometry analysis was performed to analyze the cell cycle distribution of MKN45 and KATO III. RNA sequencing (RNA-seq) was employed to detect differential genes after transfection with siRP11-93B14.5. Quantitative PCR (Q-PCR) was used to examine gene expression in GC cell lines. Western-blot assay was used to measure protein levels. RNA fluorescent in situ hybridization (FISH) was conducted for lncRNA cellular location and expression.

RESULTS

Based on the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) database, RP11-93B14.5 was upregulated in GC tissue, which was also verified in GC cell lines in comparison to the normal gastric epithelial HFE145 cells. Knockdown of RP11-93B14.5 decreased cell viability and the colony number of MKN45 and KATO III cells, and altered cell cycle distribution in vitro. RNA-seq analysis revealed RP11-93B14.5 may modulate genes expression of S100A2 and TIMP2 in MKN45 and KATO III cells. Mechanistically, RP11-93B14.5 may drive the progression of GC via S100A2 related-PI3K/AKT signaling pathway.

CONCLUSIONS

LncRNA RP11-93B14.5 knockdown alleviated the malignant phenotypes of GC cells through regulating PI3K/AKT. Our results provide evidence for the role of lncRNAs in regulating tumor progression.

Various LncRNA Mechanisms in Gene Regulation Involving miRNAs or RNA-Binding Proteins in Non-Small-Cell Lung Cancer: Main Signaling Pathways and Networks

Long non-coding RNAs (lncRNAs) are crucial players in the pathogenesis of non-small-cell lung cancer (NSCLC). A competing binding of lncRNAs and mRNAs with microRNAs (miRNAs) is one of the most common mechanisms of gene regulation by lncRNAs in NSCLC, which has been extensively researched in the last two decades. However, alternative mechanisms that do not depend on miRNAs have also been reported. Among them, the most intriguing mechanism is mediated by RNA-binding proteins (RBPs) such as IGF2BP1/2/3, YTHDF1, HuR, and FBL, which increase the stability of target mRNAs. IGF2BP2 and YTHDF1 may also be involved in m6A modification of lncRNAs or target mRNAs. Some lncRNAs, such as DLGAP1-AS2, MALAT1, MNX1-AS1, and SNHG12, are involved in several mechanisms depending on the target: lncRNA/miRNA/mRNA interactome and through RBP. The target protein sets selected here were then analyzed using the DAVID database to identify the pathways overrepresented by KEGG, Wikipathways, and the Reactome pathway. Using the STRING website, we assessed interactions between the target proteins and built networks. Our analysis revealed that the JAK-STAT and Hippo signaling pathways, cytokine pathways, the VEGFA-VEGFR2 pathway, mechanisms of cell cycle regulation, and neovascularization are the most relevant to the effect of lncRNA on NSCLC.

Cuproptosis-related lncRNA signatures: Predicting prognosis and evaluating the tumor immune microenvironment in lung adenocarcinoma

Background

Cuproptosis, a unique kind of cell death, has implications for cancer therapy, particularly lung adenocarcinoma (LUAD). Long non-coding RNAs (lncRNAs) have been demonstrated to influence cancer cell activity by binding to a wide variety of targets, including DNA, RNA, and proteins.

Methods

Cuproptosis-related lncRNAs (CRlncRNAs) were utilized to build a risk model that classified patients into high-and low-risk groups. Based on the CRlncRNAs in the model, Consensus clustering analysis was used to classify LUAD patients into different subtypes. Next, we explored the differences in overall survival (OS), the tumor immune microenvironment (TIME), and the mutation landscape between different risk groups and molecular subtypes. Finally, the functions of LINC00592 were verified through in vitro experiments.

Results

Patients in various risk categories and molecular subtypes showed statistically significant variations in terms of OS, immune cell infiltration, pathway activity, and mutation patterns. Cell experiments revealed that LINC00592 knockdown significantly reduced LUAD cell proliferation, invasion, and migration ability.

Conclusion

The development of a trustworthy prediction model based on CRlncRNAs may significantly aid in the assessment of patient prognosis, molecular features, and therapeutic modalities and may eventually be used in clinical applications.

Non-coding ribonucleic acid-mediated CAMSAP1 upregulation leads to poor prognosis with suppressed immune infiltration in liver hepatocellular carcinoma

Liver hepatocellular carcinoma (LIHC) is well-known for its unfavorable prognosis due to the lack of reliable diagnostic and prognostic biomarkers. Calmodulin-regulated spectrin-associated protein 1 (CAMSAP1) is a non-centrosomal microtubule minus-end binding protein that regulates microtubule dynamics. This study aims to investigate the specific role and mechanisms of CAMSAP1 in LIHC. We performed systematical analyses of CAMSAP1 and demonstrated that differential expression of CAMSAP1 is associated with genetic alteration and DNA methylation, and serves as a potential diagnostic and prognostic biomarker in some cancers, especially LIHC. Further evidence suggested that CAMSAP1 overexpression leads to adverse clinical outcomes in advanced LIHC. Moreover, the AC145207.5/LINC01748-miR-101–3p axis is specifically responsible for CAMSAP1 overexpression in LIHC. In addition to the previously reported functions in the cell cycle and regulation of actin cytoskeleton, CAMSAP1-related genes are enriched in cancer- and immune-associated pathways. As expected, CAMSAP1-associated LIHC is infiltrated in the suppressed immune microenvironment. Specifically, except for immune cell infiltration, it is significantly positively correlated with immune checkpoint genes, especially CD274 (PD-L1), and cancer-associated fibroblasts. Prediction of immune checkpoint blockade therapy suggests that these patients may benefit from therapy. Our study is the first to demonstrate that besides genetic alteration and DNA methylation, AC145207.5/LINC01748-miR-101-3p-mediated CAMSAP1 upregulation in advanced LIHC leads to poor prognosis with suppressed immune infiltration, representing a potential diagnostic and prognostic biomarker as well as a promising immunotherapy target for LIHC.

Thymic epithelial tumors: examining the GTF2I mutation and developing a novel prognostic signature with LncRNA pairs to predict tumor recurrence

Background

General transcription factor IIi (GTF2I) mutations are very common in thymic epithelial tumors (TETs) and are related to a more favorable prognosis in TET patients. However, limited research has been conducted on the role of GTF2I in the tumor immune microenvironment (TIME). Further, long non-coding RNAs (lncRNAs) have been associated with the survival of patients with TETs. Therefore, this study aimed to explore the relationship between GTF2I mutations and TIME and build a new potential signature for predicting tumor recurrence in the TETs. Research data was downloaded from The Cancer Genome Atlas database and the CIBERSORT algorithm was used to evaluate TIME differences between GTF2I mutant and wild-type TETs. Relevant differentially expressed lncRNAs based on differentially expressed immune-related genes were identified to establish lncRNA pairs. We constructed a signature using univariate and multivariate Cox regression analyses.

Results

GTF2I is the most commonly mutated gene in TETs, and is associated with an increased number of early-stage pathological types, as well as no history of myasthenia gravis or radiotherapy treatment. In the GTF2I wild-type group, immune score and immune cell infiltrations with M2 macrophages, activated mast cells, neutrophils, plasma, T helper follicular cells, and activated memory CD4 T cells were higher than the GTF2I mutant group. A risk model was built using five lncRNA pairs, and the 1-, 3-, and 5-year area under the curves were 0.782, 0.873, and 0.895, respectively. A higher risk score was related to more advanced histologic type.

Conclusion

We can define the GTF2I mutant-type TET as an immune stable type and the GTF2I wild-type as an immune stressed type. A signature based on lncRNA pairs was also constructed to effectively predict tumor recurrence.

High Mobility Group A1 (HMGA1): Structure, Biological Function, and Therapeutic Potential

High mobility group A1 (HMGA1) is a nonhistone chromatin structural protein characterized by no transcriptional activity. It mainly plays a regulatory role by modifying the structure of DNA. A large number of studies have confirmed that HMGA1 regulates genes related to tumours in the reproductive system, digestive system, urinary system and haematopoietic system. HMGA1 is rare in adult cells and increases in highly proliferative cells such as embryos. After being stimulated by external factors, it will produce effects through the Wnt/β-catenin, PI3K/Akt, Hippo and MEK/ERK pathways. In addition, HMGA1 also affects the ageing, apoptosis, autophagy and chemotherapy resistance of cancer cells, which are linked to tumorigenesis. In this review, we summarize the mechanisms of HMGA1 in cancer progression and discuss the potential clinical application of targeted HMGA1 therapy, indicating that targeted HMGA1 is of great significance in the diagnosis and treatment of malignancy.

A Novel Necroptosis-Related lncRNA Signature Predicts the Prognosis of Lung Adenocarcinoma

Background: Necroptosis is closely related to the tumorigenesis and development of cancer. An increasing number of studies have demonstrated that targeting necroptosis could be a novel treatment strategy for cancer. However, the predictive potential of necroptosis-related long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD) still needs to be clarified. This study aimed to construct a prognostic signature based on necroptosis-related lncRNAs to predict the prognosis of LUAD.

Methods: We downloaded RNA sequencing data from The Cancer Genome Atlas database. Co-expression network analysis, univariate Cox regression, and least absolute shrinkage and selection operator were adopted to identify necroptosis-related prognostic lncRNAs. We constructed the predictive signature by multivariate Cox regression. Kaplan–Meier analysis, time-dependent receiver operating characteristics, nomogram, and calibration curves were used to validate and evaluate the signature. Subsequently, we used gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) to explore the relationship between the predictive signature and tumor immune microenvironment of risk groups. Finally, the correlation between the predictive signature and immune checkpoint expression of LUAD patients was also analyzed.

Results: We constructed a signature composed of 7 necroptosis-related lncRNAs (AC026355.2, AC099850.3, AF131215.5, UST-AS2, ARHGAP26-AS1, FAM83A-AS1, and AC010999.2). The signature could serve as an independent predictor for LUAD patients. Compared with clinicopathological variables, the necroptosis-related lncRNA signature has a higher diagnostic efficiency, with the area under the receiver operating characteristic curve being 0.723. Meanwhile, when patients were stratified according to different clinicopathological variables, the overall survival of patients in the high-risk group was shorter than that of those in the low-risk group. GSEA showed that tumor- and immune-related pathways were mainly enriched in the low-risk group. ssGSEA further confirmed that the predictive signature was significantly related to the immune status of LUAD patients. The immune checkpoint analysis displayed that low-risk patients had a higher immune checkpoint expression, such as CTLA-4, HAVCR2, PD-1, and TIGIT. This suggested that immunological function is more active in the low-risk group LUAD patients who might benefit from checkpoint blockade immunotherapies.

Conclusion: The predictive signature can independently predict the prognosis of LUAD, helps elucidate the mechanism of necroptosis-related lncRNAs in LUAD, and provides immunotherapy guidance for patients with LUAD.