Five long non-coding RNAs establish a prognostic nomogram and construct a competing endogenous RNA network in the progression of non-small cell lung cancer

A combination of cuproptosis and lncRNAs predicts the prognosis and tumor immune microenvironment in cervical cancer

BACKGROUND

Cuproptosis induces proteotoxic stress and eventually leads to cell death. However, the relationship between cuproptosis and lncRNAs in cervical cancer has not been fully elucidated. Therefore, we aim to explore the association among lncRNAs, cuproptosis and clinical features in cervical cancer.

METHODS

RNA sequencing, genetic mutations, and clinical data of CESC patients were obtained from TCGA. Cuproptosis-associated genes were gathered. WGCNA was used to cluster important modules, and KEGG, GO, GSEA and GSVA were used to explore functional and pathway enrichment. The association between immune microenvironment and cuproptosis-related lncRNAs was performed by using cibersort algorithm and other platforms, including XCELL, TIMER, QUANTISEQ, MCPCOUNTER and EPIC. Fluorescence quantitative PCR was employed to detect the expression of LINC01833 and LINC02321, and CCK-8 and cell scratch assays were used to assess cell proliferation and migration capabilities after LINCRNA interference.

RESULTS

202 upregulated and 45 downregulated lncRNAs were selected. The survival analysis showed that there was a statistically significant difference in survival rates between the high-risk and low-risk groups. The prognosis of tumour mutation burden and the degree of immune infiltration were differed noticeably between the high-risk and low-risk groups. BHG712, TL-2-105, FR-180204, Masitinib, TAK-715, ODI-027, JW-7-24-2, and OSI-930 had substantially higher IC50 values in the high-risk group. Notably, we found AL360178.1 was associated with RNF44 E3 ubiquitin ligase expression. In cervical cancer cell lines, LINC01833 and LINC02321 displayed significant upregulation. Efficient siRNA transfection led to a decreased expression of LINC01833 and LINC02321. This knockdown significantly hindered both cell proliferation and migration capabilities in cervical cancer cells compared to the negative control.

CONCLUSION

In conclusion, we constructed five cuprotosis-related lncRNA prognostic models, which may be new tumor therapeutic targets for the prevention and treatment of cervical cancer.

Long Non-coding RNA LINC00342 Promotes the Proliferation, Invasion, and Migration of Primary Hepatocellular Carcinoma Cells by Regulating the Expression of miRNA-19a-3p, miRNA-545-5p, and miRNA-203a-3p

This study aimed to investigate the role of the long non-coding RNA (lncRNA) LINC00342-207 (LINC00342) in the development and progression of primary hepatocellular carcinoma (HCC). Forty-two surgically resected HCC tissues and corresponding paracancerous tissues were collected from October 2019 to December 2020 and examined for lncRNA LINC00342, microRNA (miR)-19a-3p, miR-545-5p, miR-203a-3p, cell cycle protein D1 (CyclinD1/CCND1), murine double minute 2 (MDM2), and fibroblast growth factor 2 (FGF2) expression. The disease-free survival and overall survival of patients with HCC were followed up. HCC cell lines and the normal hepatocyte cell line HL-7702 were cultured and the expression level of LINC00342 was measured. HepG2 cells were transfected with LINC00342 siRNA, LINC00342 overexpression plasmid, miR-19a-3p mimics and their corresponding suppressors, miR-545-5p mimics and their corresponding suppressors, and miR-203a-3p mimics and their corresponding suppressors. The proliferation, apoptosis, migration, and invasion of HepG2 cells were detected. Stably transfected HepG2 cells were inoculated into the left axilla of male BALB/c nude mice, and the volume and quality of transplanted tumors as well as the expression levels of LINC00342, miR-19a-3p, miR-545-5p, miR-203a-3p, CCND1, MDM2, and FGF2 were examined. LINC00342 played an oncogenic role in HCC and exhibited inhibitory effects on proliferation, migration, and invasion, and promoted the apoptosis of HepG2 cells. Moreover, it inhibited the growth of transplanted tumors in vivo in mice. Mechanistically, the oncogenic effect of LINC00342 was associated with the targeted regulation of the miR-19a-3p/CCND1, miR-545-5p/MDM2, and miR-203a-3p/FGF2 axes.

Sense and anti-sense: Role of FAM83A and FAM83A-AS1 in Wnt, EGFR, PI3K, EMT pathways and tumor progression

An increasing number of studies have shown that FAM83A, a member of the family with sequence similarity 83 (FAM83), which consists of eight members, is a key tumor therapeutic target involved in multiple signaling pathways. It has been reported that FAM83A plays essential roles in the regulation of Wnt/β-catenin, EGFR, MAPK, EMT, and other signaling pathways and physiological processes in models of pancreatic cancer, lung cancer, breast cancer, and other malignant tumors. Moreover, the expression of FAM83A could be significantly affected by multiple noncoding RNAs that are dysregulated in malignant tumors, the dysregulation of which is essential for the malignant process. Among these noncoding RNAs, the most noteworthy is the antisense long noncoding (Lnc) RNA of FAM83A itself (FAM83A-AS1), indicating an outstanding synergistic carcinogenic effect between FAM83A and FAM83A-AS1. In the present study, the specific mechanisms by which FAM83A and FAM83A-AS1 cofunction in the Wnt/β-catenin and EGFR signaling pathways were reviewed in detail, which will guide subsequent research. We also described the applications of FAM83A and FAM83A-AS1 in tumor therapy and provided a certain theoretical basis for subsequent drug target development and combination therapy strategies.

Autoencoder-based multimodal prediction of non-small cell lung cancer survival

The ability to accurately predict non-small cell lung cancer (NSCLC) patient survival is crucial for informing physician decision-making, and the increasing availability of multi-omics data offers the promise of enhancing prognosis predictions. We present a multimodal integration approach that leverages microRNA, mRNA, DNA methylation, long non-coding RNA (lncRNA) and clinical data to predict NSCLC survival and identify patient subtypes, utilizing denoising autoencoders for data compression and integration. Survival performance for patients with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) was compared across modality combinations and data integration methods. Using The Cancer Genome Atlas data, our results demonstrate that survival prediction models combining multiple modalities outperform single modality models. The highest performance was achieved with a combination of only two modalities, lncRNA and clinical, at concordance indices (C-indices) of 0.69 ± 0.03 for LUAD and 0.62 ± 0.03 for LUSC. Models utilizing all five modalities achieved mean C-indices of 0.67 ± 0.04 and 0.63 ± 0.02 for LUAD and LUSC, respectively, while the best individual modality performance reached C-indices of 0.64 ± 0.03 for LUAD and 0.59 ± 0.03 for LUSC. Analysis of biological differences revealed two distinct survival subtypes with over 900 differentially expressed transcripts.

LncRNA LINC01833 is a Prognostic Biomarker and Correlates with Immune Infiltrates in Patients with Lung Adenocarcinoma by Integrated Bioinformatics Analysis

Due to the absence of accurate tools for early detection and successful treatment, lung adenocarcinoma (LUAD) is one of the most aggressive tumors with high morbidity and mortality globally. It is absolutely necessary to investigate the process behind its development and search for new biomarkers that could aid in the early detection of LUAD. There is a correlation between the immune microenvironment of the tumor and the prognosis of lung cancer as well as the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been identified as potential prognostic biomarkers linked to immunological activities. In this study, we identified 1 downregulated lncRNA and 76 upregulated lncRNAs in LUAD samples from TCGA datasets. Among the 77 dysregulated lncRNAs, our attention focused on lncRNA LINC01833 (LINC01833). When compared with nontumor specimens, the level of expression of LINC01833 was shown to be significantly elevated in LUAD samples. In addition, the data of the ROC study revealed that LUAD patients with high LINC01833 expression had an AUC value of 0.840 (95% confidence interval: 0.804 to 0.876). There was a correlation between high LINC01833 expression and an advanced clinical stage. Patients who had a high expression of LINC01833 were shown to have a lower overall survival rate (p < 0.001) and a lower disease-specific survival rate (p = 0.004) in comparison to patients who were in the low LINC01833 group, according to the data on survival. In addition, the results of the multivariate analysis revealed that high LINC01833 expression was an independent predictor of poor survival in LUAD. Moreover, the immune analysis revealed that we found that the expression of LINC01833 was positively associated with Th2 cells, aDC, and Tgd, while negatively associated with Mast cells, Tcm, Eosinophils, iDC, DC, Tem, Th17 cells, and pDC. Overall, our data point to the possibility that the unique lncRNA LINC01833 might be employed as a diagnostic and prognostic marker, and as a result, it has a significant impact on clinical practice.

Diagnostic value of lncRNA HOTAIR as a biomarker for detecting and staging of non-small cell lung cancer

BACKGROUND

Since the role of long non-coding RNA (lncRNA) HOTAIR is yet to be established in non-small cell lung cancer (NSCLC), we tried to explore the expression of lncRNA HOTAIR in NSCLC and evaluate the correlation between the combined detection of lncRNA HOTAIR and routine tumour markers and the pathological staging of lung cancer.

METHODS

This study prospectively included 148 patients with NSCLC selected from our hospital from January 2017 to September 2020 as the lung cancer group, and 148 healthy volunteers who referred for physical examination were selected as the control group. Fluorescence in situ hybridisation was used to detect the expression of lncRNA HOTAIR in the cancerous tissues and adjacent tissues of lung cancer patients; the immunofluorescence method was used to detect the serum NSE, CEA and CYFRA21-1 levels of the two groups of testers. Correlation analysis was used to evaluate any relation between cancer staging and markers. In addition, ROC curve analysis was used to estimate sensitivity, specificity, positive predictive value, and negative predictive value.

RESULTS

The expression of lncRNA HOTAIR in lung cancer tissues was higher than control or surrounding tissue (p < 0.05). Also, high levels of NSE, CEA and CYFRA21-1 were observed in lung cancer group (p < 0.05). In both N and T stage, the expression of lncRNA HOTAIR combined with NSE, CEA and CYFRA21-1 levels increased with the increase in the number of stages (p < 0.05). The results of single factor analysis showed that NSE, CEA, CYFRA21-1 and lncRNA HOTAIR all have appropriate diagnostic value for detecting lung cancer (specificity of 92.6, 91.5, 90.6, 86.9%, respectively and the sensitivity of 61.3, 62.9, 55.4, 52.3%, respectively).

CONCLUSION

LncRNA HOTAIR is a novel diagnostic test with high diagnostic value for detecting of pathological staging of NSCLC; however, the diagnostic accuracy of lncRNA HOTAIR is not higher than other tumour biomarkers.

A nomogram based on A-to-I RNA editing predicting overall survival of patients with lung squamous carcinoma

Background

Adenosine-to-inosine RNA editing (ATIRE) is characterized as non-mutational epigenetic reprogramming hallmark of cancer, while little is known about its predictive role in cancer survival.

Methods

To explore survival-related ATIRE events in lung squamous cell carcinoma (LUSC), ATIRE profile, gene expression data, and corresponding clinical information of LUSC patients were downloaded from the TCGA database. Patients were randomly divided into a training (n = 134) and validation cohort (n = 94). Cox proportional hazards regression followed by least absolute shrinkage and selection operator algorithm were performed to identify survival-related ATIRE sites and to generate ATIRE risk score. Then a nomogram was constructed to predict overall survival (OS) of LUSC patients. The correlation of ATIRE level and host gene expression and ATIREs’ effect on transcriptome expression were analyzed.

Results

Seven ATIRE sites that were TMEM120B chr12:122215052A > I, HMOX2 chr16:4533713A > I, CALCOCO2 chr17:46941503A > I, LONP2 chr16:48388244A > I, ZNF440 chr19:11945758A > I, CLCC1 chr1:109474650A > I, and CHMP3 chr2:86754288A > I were identified to generate the risk score, of which high levers were significantly associated with worse OS and progression-free survival in both the training and validation sets. High risk-score was also associated with advanced T stages and worse clinical stages. The nomogram performed well in predicting OS probability of LUSC. Moreover, the editing of ATIRE sites exerted a significant association with expression of host genes and affected several cancer-related pathways.

Conclusions

This is the first comprehensive study to analyze the role of ATIRE events in predicting LUSC survival. The AITRE-based model might serve as a novel tool for LUSC survival prediction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09773-0.

Methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit-induced long intergenic non-protein coding RNA 1833 N6-methyladenosine methylation promotes the non-small cell lung cancer progression via regulating heterogeneous nuclear ribonucleoprotein A2/B1 expression

Long intergenic non-protein coding RNA 1833 (LINC01833) exhibits elevated expression in the non-small cell lung cancer (NSCLC) tissues, while its molecular mechanism in NSCLC progression remains elusive. Herein, the proliferation, migration, invasion as well as apoptosis of NSCLC cells were assessed. The potential N6-methyladenosine (m6A) modification site was predicted by the m6aVar tool. RNA pulldown and m6A-specific immunoprecipitation assays were used to detect the interaction between LINC01833 and methyltransferase 3, N6-adenosine-methyltransferase complex catalytic subunit (METTL3). RNA pull-down together with mass spectrometry were performed to assess the binding relationship between LINC01833 and heterogeneous nuclear ribonucleoprotein A2/B1 (HNRNPA2B1) in NSCLC. Tumor xenograft mice model was established, and the tumor size and weight were measured. The results demonstrated that LINC01833 expression was elevated in NSCLC samples. Overexpression of LINC01833 promoted proliferative, migratory, and invasive abilities and inhibited HCC827 cell apoptosis. LINC01833 knockdown inhibited tumor growth in mice. LINC01833 is further demonstrated to be modulated by METTL3, which is highly expressed in NSCLC samples. In addition, RNA pulldown and m6A-specific immunoprecipitation assays indicated that LINC01833 might form a complex with HNRNPA2B1. In conclusion, m6A transferase METTL3-induced LINC01833 m6A methylation promotes NSCLC progression through modulating HNRNPA2B1 expression. Our findings indicated that LINC01833 might be a therapeutic target for NSCLC.

Identification of lncRNA-miRNA-mRNA Networks Linked to Non-small Lung Cancer Resistance to Inhibitors of Epidermal Growth Factor Receptor

Background: Tyrosine kinase inhibitors that act against epidermal growth factor receptor (EGFR) show strong efficacy against non-small cell lung cancer (NSCLC) involving mutated EGFRs. However, most such patients eventually develop resistance to EGFR-TKIs. Numerous researches have reported that messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) may be involved in EGFR-TKI resistance, but the comprehensive expression profile and competitive endogenous RNA (ceRNA) regulatory network between mRNAs and ncRNAs in EGFR-TKI resistance of NSCLC are incompletely known. We aimed to define a ceRNA regulatory network linking mRNAs and non-coding RNAs that may mediate this resistance.

Methods: Using datasets GSE83666, GSE75309 and GSE103352 from the Gene Expression Omnibus, we identified long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs differentially expressed between NSCLC cells that were sensitive or resistant to EGFR-TKIs. The potential biological functions of the corresponding differentially expressed genes were analyzed based KEGG pathways. We combined interactions among lncRNAs, miRNAs and mRNAs in the RNAInter database with KEGG pathways to generate transcriptional regulatory ceRNA networks associated with NSCLC resistance to EGFR-TKIs. Kaplan-Meier analysis was used to assess the ability of core ceRNA regulatory sub-networks to predict the progression-free interval and overall survival of NSCLC. The expression of two core ceRNA regulatory sub-networks in NSCLC was validated by quantitative real-time PCR.

Results: We identified 8,989 lncRNAs, 1,083 miRNAs and 3,191 mRNAs that were differentially expressed between patients who were sensitive or resistant to the inhibitors. These DEGs were linked to 968 biological processes and 31 KEGG pathways. Pearson analysis of correlations among the DEGs of lncRNAs, miRNAs and mRNAs identified 12 core ceRNA regulatory sub-networks associated with resistance to EGFR-TKIs. The two lncRNAs ABTB1 and NPTN with the hsa-miR-150–5p and mRNA SERPINE1 were significantly associated with resistance to EGFR-TKIs and survival in NSCLC. These lncRNAs and the miRNA were found to be down-regulated, and the mRNA up-regulated, in a resistant NSCLC cell line relative to the corresponding sensitive cells.

Conclusion: In this study, we provide new insights into the pathogenesis of NSCLC and the emergence of resistance to EGFR-TKIs, based on a lncRNA-miRNA-mRNA network.

Role of lncRNA BANCR in Human Cancers: An Updated Review

Being located in a gene desert region on 9q21.11-q21.12, BRAF-activated non-protein coding RNA (BANCR) is an lncRNA with 693 bp length. It has been discovered in 2012 in a research aimed at assessment of gene expression in the melanocytes in association with BRAF mutation. Increasing numbers of studies have determined its importance in the tumorigenesis through affecting cell proliferation, migration, invasion, apoptosis, and epithelial to mesenchymal transition. BANCR exerts its effects via modulating some tumor-related signaling pathways particularly MAPK and other regulatory mechanisms such as sponging miRNAs. BANCR has been up-regulated in endometrial, gastric, breast, melanoma, and retinoblastoma. Conversely, it has been down-regulated in some other cancers such as those originated from lung, bladder, and renal tissues. In some cancer types such as colorectal cancer, hepatocellular carcinoma and papillary thyroid carcinoma, there is no agreement about BANCR expression, necessitating the importance of additional functional studies in these tissues. In the present manuscript, we review the investigations related to BANCR expression changes in cancerous cell lines, clinical samples, and animal models of cancer. We also discuss the outcome of its deregulation in cancer progression, prognosis, and the underlying mechanisms of these observations.