Identification of lncRNA biomarkers for lung cancer through integrative cross-platform data analyses

LncRNA MIR100HG affects the proliferation and metastasis of lung cancer cells through mediating the microRNA-5590-3p/DCBLD2 axis

OBJECTIVE

The aim of this paper is to investigate the effect of long noncoding RNA (lncRNA) MIR100HG on the proliferation and metastasis of lung cancer cells by mediating the microRNA (miR)-5590-3p/DCBLD2 axis.

METHODS

RNA levels of MIR100HG, miR-5590-3p, and DCBLD2 in lung cancer tissues and cells were detected by quantitative reverse-transcription polymerase chain reaction, and protein level was assessed by Western blot. Effects of MIR100HG or miR-5590-3p on proliferation, migration, and invasion of lung cancer cells were detected by Cell Counting Kit-8, colony formation, and Transwell assays. Luciferase reporter assay and RNA-immunoprecipitation assay confirmed the target relationship between miR-5590-3p and MIR100HG or DCBLD2.

RESULTS

MIR100HG and DCBLD2 were highly expressed, while miR-5590-3p was lowly expressed in lung cancer tissues and cells. Silencing MIR100HG or upregulating miR-5590-3p impeded lung cancer cell proliferation, migration, and invasion. MIR100HG could up-regulate DCBLD2 by sponging miR-5590-3p. Downregulation of miR-5590-3p partly overturned the suppressive effect of silencing MIR100HG on lung cancer cell proliferation and metastasis, and overexpression of DCBLD2 also reversed the effect of overexpression of miR-5590-3p on lung cancer cell proliferation and metastasis.

CONCLUSION

LncRNA MIR100HG promotes lung cancer progression by targeting and negatively regulating DCBLD2 through binding with miR-5590-3p.

Prognostic significance of LINC01132 in lung cancer and its regulatory role in tumor progression

BACKGROUND

The application of long non-coding RNAs (lncRNAs) in cancer has been the focus of research in recent years. This study aimed to discuss the expression and functional mechanism of lncRNA LINC01132 (LINC01132) in lung cancer and explore its prognostic significance in tumors.

METHODS

The expression of LINC01132 in lung cancer patients was verified using GSE98929 screening and real-time quantitative polymerase chain reaction (RT-qPCR) detection. The prognostic potential of LINC01132 was evaluated by performing the chi-square analysis of clinical indicators, Kaplan-Meier analysis, and Cox proportional hazard model. Cell Counting Kit-8 (CCK-8), flow cytometry, and Transwell assay were used to characterize the biological functions of the lung cancer cells. The targeting relationship between LINC01132 and microRNA-125a-3p (miR-125a-3p), miR-125a-3p and SMAD2 was predicted by bioinformatics and verified by luciferase activity assay.

RESULTS

LINC01132 was upregulated in lung cancer tissues and cells, which was an independent risk factor for survival and prognostic outcomes of lung cancer patients. Silencing LINC01132 suppressed the proliferation and migration of lung cancer cells and accelerated cell death. The target of LINC01132 was miR-125a-3p, and miR-125a-3p inhibitor could eliminate the inhibitory effect of LINC01132 knockdown on the cells. Additionally, SMAD2 is a downstream target of miR-125a-3p, and knockdown of SMAD2 reversed the effects of miR-125a-3p inhibitor on cell migration and invasion.

CONCLUSION

LINC01132 may regulate the progression of lung cancer by targeting the miR-125a-3p /SMAD2 axis and serve as a prognostic biomarker for lung cancer.

Integrated plasma and exosome long noncoding RNA profiling is promising for diagnosing non-small cell lung cancer

OBJECTIVES

Non-small cell lung cancer (NSCLC) accounts for more than 80 % of all lung cancers, and its 5-year survival rate can be greatly improved by early diagnosis. However, early diagnosis remains elusive because of the lack of effective biomarkers. In this study, we aimed to develop an effective diagnostic model for NSCLC based on a combination of circulating biomarkers.

METHODS

Tissue-deregulated long noncoding RNAs (lncRNAs) in NSCLC were identified in datasets retrieved from the Gene Expression Omnibus (GEO, n=727) and The Cancer Genome Atlas (TCGA, n=1,135) databases, and their differential expression was verified in paired local plasma and exosome samples from NSCLC patients. Subsequently, LASSO regression was used to screen for biomarkers in a large clinical population, and a logistic regression model was used to establish a multi-marker diagnostic model. The area under the receiver operating characteristic (ROC) curve (AUC), calibration plots, decision curve analysis (DCA), clinical impact curves, and integrated discrimination improvement (IDI) were used to evaluate the efficiency of the diagnostic model.

RESULTS

Three lncRNAs-PGM5-AS1, SFTA1P, and CTA-384D8.35 were consistently expressed in online tissue datasets, plasma, and exosomes from local patients. LASSO regression identified nine variables (Plasma CTA-384D8.35, Plasma PGM5-AS1, Exosome CTA-384D8.35, Exosome PGM5-AS1, Exosome SFTA1P, Log10CEA, Log10CA125, SCC, and NSE) in clinical samples that were eventually included in the multi-marker diagnostic model. Logistic regression analysis revealed that Plasma CTA-384D8.35, exosome SFTA1P, Log10CEA, Exosome CTA-384D8.35, SCC, and NSE were independent risk factors for NSCLC (p<0.01), and their results were visualized using a nomogram to obtain personalized prediction outcomes. The constructed diagnostic model demonstrated good NSCLC prediction ability in both the training and validation sets (AUC=0.97).

CONCLUSIONS

In summary, the constructed circulating lncRNA-based diagnostic model has good NSCLC prediction ability in clinical samples and provides a potential diagnostic tool for NSCLC.

Non-Coding RNAs: Foes or Friends for Targeting Tumor Microenvironment

Non-coding RNAs (ncRNAs) are a group of molecules critical for cell development and growth regulation. They are key regulators of important cellular pathways in the tumor microenvironment. To analyze ncRNAs in the tumor microenvironment, the use of RNA sequencing technology has revolutionized the field. The advancement of this technique has broadened our understanding of the molecular biology of cancer, presenting abundant possibilities for the exploration of novel biomarkers for cancer treatment. In this review, we will summarize recent achievements in understanding the complex role of ncRNA in the tumor microenvironment, we will report the latest studies on the tumor microenvironment using RNA sequencing, and we will discuss the potential use of ncRNAs as therapeutics for the treatment of cancer.

Serum lncRNA THRIL predicts benign and malignant pulmonary nodules and promotes the progression of pulmonary malignancies

BACKGROUND

This project aimed to research the significance of THRIL in the diagnosis of benign and malignant solitary pulmonary nodules (SPNs) and to investigate the role of THRIL/miR-99a in malignant SPNs.

METHODS

The study groups consisted of 169 patients with SPN and 74 healthy subjects. The differences in THRIL levels were compared between the two groups and the healthy group. The receiver operating characteristic curve (ROC) was utilized to analyze the THRIL's significance in detecting benign and malignant SPN. Pearson correlation and binary regression coefficients represented the association between THRIL and SPN. CCK-8 assay, Transwell assay, and flow cytometry were utilized to detect the regulatory effect of THRIL silencing. The interaction between THRIL, miR-99a, and IGF1R was confirmed by the double luciferase reporter gene.

RESULTS

There were differences in THRIL expression in the healthy group, benign SPN group, and malignant SPN group. High accuracy of THRIL in the diagnosis of benign SPN and malignant SPN was observed. THRIL was associated with the development of SPN. The expression of THRIL was upregulated and miR-99a was downregulated in lung cancer cells. The double luciferase report experiment confirmed the connections between THRIL/miR-99a/IGF1R. Silencing THRIL could suppress cell proliferation, migration, and invasion and promote cell apoptosis by binding miR-99a.

CONCLUSION

The detection of THRIL in serum is useful for the assessment of malignant SPN. THRIL can regulate the expression of IGF1R through miR-99a, thereby promoting the growth of lung cancer cells and inhibiting apoptosis.

Computational analysis of heat shock proteins and ferroptosis-associated lncRNAs to predict prognosis in acute myeloid leukemia patients

Owing to their functional diversity in many cancers, long noncoding RNAs (lncRNAs) are receiving special attention. LncRNAs not only function as oncogenes or tumor suppressors by participating in various signaling pathways but also serve as predictive markers for various types of cancer, including acute myeloid leukemia (AML). Considering this, we investigated lncRNAs that may act as a mediator between two processes, i.e., heat shock proteins and ferroptosis, which appear to be closely related in tumorigenesis. Using a comprehensive bioinformatics approach, we identified four lncRNAs (AL138716.1, AC000120.1, AC004947.1, and LINC01547) with prognostic value in AML patients. Of interest, two of them (AC000120.1 and LINC01547) have already been reported to be AML-related, and AC004947.1 is considered to have oncogenic potential. In particular, the signature obtained showed a lower survival probability with high-risk patients, and vice versa. To our knowledge, this is the first predictive model of lncRNA that may correlate with the processes of heat shock proteins and ferroptosis in AML. Nevertheless, validation using patient samples is warranted.

Comprehensive analysis of cuproptosis-related long noncoding RNA for predicting prognostic and diagnostic value and immune landscape in colorectal adenocarcinoma

BACKGROUND

Cuproptosis, as a copper-induced mitochondrial cell death, has attracted extensive attention recently, especially in cancer. Although some key regulatory genes have been identified in cuproptosis, the related lncRNAs have not been further studied. Exploring the prognostic and diagnostic value of cuproptosis-related lncRNAs (CRLs) in colon adenocarcinoma and providing guidance for individualized immunotherapy for patients are of great significance.

RESULTS

A total of 2003 lncRNAs were correlated with cuproptosis genes and considered as CRLs. We screened 33 survival-associated CRLs and established a prognostic signature base on 7 CRLs in the training group. The patients in the low-risk group had better outcomes in both training group (P < 0.001) and test group (P = 0.016). More exciting, our model showed good prognosis prediction in both stage I-II (P = 0.020) and stage III-IV (P = 0.001). The nomogram model could further improve the accuracy of prognosis prediction. Interestingly, glucose-related metabolic pathways, which were closely related to cuproptosis, were enriched in the low-risk group. Meanwhile, the immune infiltration scores were lower in the high-risk group. The high-risk group was more sensitive to OSI.906 and ABT.888, while low-risk group was more sensitive to Sorafenib. Three lncRNAs, FALEC, AC083967.1 and AC010997.4, were highly expressed in serum of COAD patients, and the AUC was 0.772, 0.726 and 0.714, respectively, indicating their valuable diagnostic value.

CONCLUSIONS

Our research constructed a prognostic signature based on 7 CRLs and found three promising diagnostic markers for COAD patients. Our results provided a reference to the personalized immunotherapy strategies.

EIF4A3 stabilizes the expression of lncRNA AGAP2-AS1 to activate cancer-associated fibroblasts via MyD88/NF-κb signaling

BACKGROUND

Lung cancer (LC) is a fatal malignancy and often accompanied with converting normal fibroblasts to cancer-associated fibroblasts (CAFs). Exosomal lncRNA AGAP2-AS1 has been elucidated to be a potent prognostic factor for LC, while its role in activating CAFs is largely unknown.

METHODS

We first extracted exosomes from LC patients and co-cultured them with MRC5 cells to observe the state of MRC5 cells, detect AGAP2-AS1 using real-time quantitative polymerase chain reaction, and then analyze the interaction between EIF4A3 and AGAP2-AS1 using RNA pull down experiments. CCK-8 assay was used to detect cell proliferation. Transwell experiments demonstrated the regulation of MRC5 cells and, finally, the role of MyD88/NF-κB in the downstream mechanism of EIF4A3/AGAP2-AS1 was explored by RNA interference technology and pyrrolidinedithiocarbamic acid inhibition.

RESULTS

We demonstrated that exosomes from the LC patients (cancer-exo) notably increased the metastatic ability of MRC-5 cells, promoting the expressions of the CAF biomarkers and lncRNA AGAP2-AS1. Overexpression of lncRNA AGAP2-AS1 prominently activated MRC-5 cells. Moreover, EIF4A3 was upregulated in the cancer-exo-treated MRC-5 cells, and EIF4A3 was verified to bind with lncRNA AGAP2-AS1 to improve its stability. The MyD88/NF-κB signaling pathway was subsequently proved to be positively regulated by lncRNA AGAP2-AS1, and the promotive role of lncRNA AGAP2-AS1 in LC and activating CAFs was confirmed in vivo.

CONCLUSIONS

The positive feedback of EIF4A3/AGAP2-AS1/MyD88/NF-κB signaling pathway contributed to the activation of CAFs and exacerbated LC in turn, revealing a novel regulatory axis underlying LC.

MiRNA expression profiling in adenocarcinoma and squamous cell lung carcinoma reveals both common and specific deregulated microRNAs

The current study investigated the expression signatures of miRNAs in lung adenocarcinoma (LUAD) and squamous cell lung carcinoma (LUSC). miRNA profiling was performed using microarray in 12 LUAD and 12 LUSC samples and adjacent normal tissues. In LUAD, 107 miRNAs were significantly deregulated, whereas 235 miRNAs were deregulated in LUSC. Twenty-six miRNAs were common between the 2 cancer subtypes and 8 were prioritized for validation, in addition to 6 subtype-specific miRNAs. The RT-qPCR validation samples included 50 LUAD, 50 LUSC, and adjacent normal tissues. Eight miRNAs were validated in LUAD: 3 upregulated - miR-7-5p, miR-375-5p, miR-6785-3p, and 5 downregulated - miR-101-3p, miR-139-5p, miR-140-3p, miR-144-3p, miR-195-5p. Ten miRNAs were validated in the LUSC group: 3 upregulated - miR-7-5p, miR-21-3p, miR-650, and 7 downregulated - miR-95-5p, miR-140-3p, miR-144-3p, miR-195-5p, miR-375, miR-744-3p, and miR-4689-3p. Reactome pathway analysis revealed that the target genes of the deregulated miRNAs in LUAD were significantly enriched in cell cycle, membrane trafficking, gene expression processes, and EGFR signaling, while in LUSC, they were enriched in the immune system, transcriptional regulation by TP53, and FGFR signaling. This study identified distinct miRNA profiles in LUSC and LUAD, which are common and specific miRNAs that could be further investigated as biomarkers for diagnosis and prognosis.

Construction and validation of a novel prediction system for detection of overall survival in lung cancer patients

BACKGROUND

Many factors have an aberrant effect on the overall survival of lung cancer (LC) patients. In recent years, remarkable progress has been made in immunotherapy, targeted treatment, and promising biomarkers. However, the available treatments and diagnostic methods are not specific for all patients.

AIM

To establish a system for predicting poor survival in patients with LC.

METHODS

The expression matrix and clinical information for this study were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases. After the differential analysis of all screened genes, weighted gene coexpression network analysis was performed to analyze hub genes related to patient survival. A logistic regression model was used to construct the scoring system. The expression of the hub genes was verified by performing quantitative reverse transcription-polymerase chain reaction.

RESULTS

A total of 5007 differentially expressed genes were selected for the Weighted Gene Co-expression Network Analysis algorithm. We found that the turquoise module showed the highest correlation with patient prognosis. The gene module with the greatest positive correlation with patient survival was located in the turquoise area. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses performed for the genes contained in the turquoise module indicated the potential roles of the selected genes in the regulation of LC development. In addition, protein–protein interaction analysis was performed to screen hub genes, which identified 100 hub genes located in the core area of the network. We then intersected the 100 hub genes with 75 key genes sorted by module members to identify real hub genes associated with prognosis. Forty-one genes were finally selected. We then used a logistic regression model to determine 11 independent risk genes, namely CCNB2, CDC20, CENPO, FOXM1, HJURP, NEK2, OIP5, PLK1, PRC1, SKA1, UBE2C and SPARC.

CONCLUSION

We constructed a predictive model based on 11 independent risk genes to establish a system predicting the survival status of patients with non-small-cell lung carcinoma.

Identification of LncRNA CARD8-AS1 as a Potential Prognostic Biomarker Associated With Progression of Lung Adenocarcinoma

Introduction: Long non-coding RNAs (lncRNAs) exhibit crucial roles in human tumors. However, the role of lncRNA CARD8-AS1 in lung adenocarcinoma remains elusive. This study investigated the role of CARD8-AS1 in lung adenocarcinoma.

Materials and Methods: The expression of CARD8-AS1 was detected by RT-qPCR analysis and confirmed using an online database. The clinical value of CARD8-AS1 was evaluated using the Kaplan-Meier curve and multivariate Cox regression analyses. The effects of CARD8-AS1 on cancer cell proliferation, migration, and invasion potential were assessed through several cellular experiments. Western blot assay was used to measure Bcl-2 and Bax protein levels. The interaction among CARD8-AS1, miR-650, and Bax, was assessed using a dual-luciferase reporter assay.

Results: The expression of CARD8-AS1 was decreased in lung adenocarcinoma tissues and cell lines (p &lt; 0.001). Low expression of CARD8-AS1 was related to tumor size (p = 0.042), TNM stage (p = 0.021), lymph node metastasis (p = 0.025), and poor overall survival (p &lt; 0.05). Elevated expression of CARD8-AS1 could suppress cellular viability, migration potential, and invasion ability (p &lt; 0.05). The Bcl-2 protein levels were decreased while Bax levels were increased by overexpression of CARD8-AS1 (p &lt; 0.001). miR-650 may thus be a direct target of CARD8-AS1 and Bax may be a direct target of miR-650.

Discussion: CARD8-AS1 expression was downregulated in lung adenocarcinoma and associated with several clinical parameters. CARD8-AS1 exerted tumor-suppressive effects by targeting the miR-650 and then regulating Bax expression. CARD8-AS1/miR-650 may serve as novel prognostic biomarkers and potential therapeutic targets for the treatment of lung adenocarcinoma.

TBX5-AS1, an enhancer RNA, is a potential novel prognostic biomarker for lung adenocarcinoma

BACKGROUND

Enhancer RNAs (eRNAs) are demonstrated to be closely associated with tumourigenesis and cancer progression. However, the role of eRNAs in lung adenocarcinoma (LUAD) remains largely unclear. Thus, a comprehensive analysis was constructed to identify the key eRNAs, and to explore the clinical utility of the identified eRNAs in LUAD.

METHODS

First, LUAD expression profile data from the Cancer Genome Atlas (TCGA) dataset and eRNA-relevant information were integrated for Kaplan-Meier survival analysis and Spearman's correlation analysis to filtered the key candidate eRNAs that was associated with survival rate and their target genes in LUAD. Then, the key eRNA was selected for subsequent clinical correlation analysis. KEGG pathway enrichment analyses were undertaken to explore the potential signaling pathways of the key eRNA. Data from the human protein atlas (HPA) database were used to validate the outcomes and the quantitative real time-polymerase chain reaction (qRT-PCR) analysis was conducted to measure eRNA expression levels in tumor tissues and paired normal adjacent tissues from LUAD patients. Finally, the eRNAs were validated in pan-cancer.

RESULTS

As a result, TBX5-AS1 was identified as the key eRNA, which has T-box transcription factor 5 (TBX5) as its regulatory target. KEGG analysis indicated that TBX5-AS1 may exert a vital role via the PI3K/AKT pathway, Ras signaling pathway, etc. Additionally, the qRT-PCR results and the HPA database indicated that TBX5-AS1 and TBX5 were significantly downregulated in tumour samples compared to matched-adjacent pairs. The pan-cancer validation results showed that TBX5-AS1 was associated with survival in four tumors, namely, adrenocortical carcinoma (ACC), LUAD, lung squamous cell carcinoma (LUSC), and uterine corpus endometrial carcinoma (UCEC). Correlations were found between TBX5-AS1 and its target gene, TBX5, in 26 tumor types.

CONCLUSION

Collectively, our results indicated that TBX5-AS1 may be a potential prognostic biomarker for LUAD patients and promote the targeted therapy of LUAD.

The function of LncRNAs and their role in the prediction, diagnosis, and prognosis of lung cancer

Lung cancer remains a major threat to human health. Low dose CT scan (LDCT) has become the main method of early screening for lung cancer due to the low sensitivity of chest X-ray. However, LDCT not only has a high false positive rate, but also entails risks of overdiagnosis and cumulative radiation exposure. In addition, cumulative radiation by LDCT screening and subsequent follow-up can increase the risk of lung cancer. Many studies have shown that long noncoding RNAs (lncRNAs) remain stable in blood, and profiling of blood has the advantages of being noninvasive, readily accessible and inexpensive. Serum or plasma assay of lncRNAs in blood can be used as a novel detection method to assist LDCT while improving the accuracy of early lung cancer screening. LncRNAs can participate in the regulation of various biological processes. A large number of researches have reported that lncRNAs are key regulators involved in the progression of human cancers through multiple action models. Especially, some lncRNAs can affect various hallmarks of lung cancer. In addition to their diagnostic value, lncRNAs also possess promising potential in other clinical applications toward lung cancer. LncRNAs can be used as predictive markers for chemosensitivity, radiosensitivity, and sensitivity to epidermal growth factor receptor (EGFR)-targeted therapy, and as well markers of prognosis. Different lncRNAs have been implicated to regulate chemosensitivity, radiosensitivity, and sensitivity to EGFR-targeted therapy through diverse mechanisms. Although many challenges need to be addressed in the future, lncRNAs have bright prospects as an adjunct to radiographic methods in the clinical management of lung cancer.