Identification of long noncoding RNAs for the detection of early stage lung squamous cell carcinoma by microarray analysis

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.

Comprehensive landscape and future perspective of long noncoding RNAs in non-small cell lung cancer: it takes a village

Long noncoding RNAs (lncRNAs) are a distinct subtype of RNA that lack protein-coding capacity but exert significant influence on various cellular processes. In non-small cell lung cancer (NSCLC), dysregulated lncRNAs act as either oncogenes or tumor suppressors, contributing to tumorigenesis and tumor progression. LncRNAs directly modulate gene expression, act as competitive endogenous RNAs by interacting with microRNAs or proteins, and associate with RNA binding proteins. Moreover, lncRNAs can reshape the tumor immune microenvironment and influence cellular metabolism, cancer cell stemness, and angiogenesis by engaging various signaling pathways. Notably, lncRNAs have shown great potential as diagnostic or prognostic biomarkers in liquid biopsies and therapeutic strategies for NSCLC. This comprehensive review elucidates the significant roles and diverse mechanisms of lncRNAs in NSCLC. Furthermore, we provide insights into the clinical relevance, current research progress, limitations, innovative research approaches, and future perspectives for targeting lncRNAs in NSCLC. By summarizing the existing knowledge and advancements, we aim to enhance the understanding of the pivotal roles played by lncRNAs in NSCLC and stimulate further research in this field. Ultimately, unraveling the complex network of lncRNA-mediated regulatory mechanisms in NSCLC could potentially lead to the development of novel diagnostic tools and therapeutic strategies.

Pathogenicity and virulence of Entamoeba histolytica, the agent of amoebiasis

The amoeba parasite Entamoeba histolytica is the causative agent of human amebiasis, an enteropathic disease affecting millions of people worldwide. This ancient protozoan is an elementary example of how parasites evolve with humans, e.g. taking advantage of multiple mechanisms to evade immune responses, interacting with microbiota for nutritional and protective needs, utilizing host resources for growth, division, and encystation. These skills of E. histolytica perpetuate the species and incidence of infection. However, in 10% of infected cases, the parasite turns into a pathogen; the host-parasite equilibrium is then disorganized, and the simple lifecycle based on two cell forms, trophozoites and cysts, becomes unbalanced. Trophozoites acquire a virulent phenotype which, when non-controlled, leads to intestinal invasion with the onset of amoebiasis symptoms. Virulent E. histolytica must cross mucus, epithelium, connective tissue and possibly blood. This highly mobile parasite faces various stresses and a powerful host immune response, with oxidative stress being a challenge for its survival. New emerging research avenues and omics technologies target gene regulation to determine human or parasitic factors activated upon infection, their role in virulence activation, and in pathogenesis; this research bears in mind that E. histolytica is a resident of the complex intestinal ecosystem. The goal is to eradicate amoebiasis from the planet, but the parasitic life of E. histolytica is ancient and complex and will likely continue to evolve with humans. Advances in these topics are summarized here.

Non-invasive detection of tumor markers in salivary extracellular vesicles based on digital PCR chips

The World Health Organization (WHO) has stated that countless cancer patients could be saved if early detection and treatment were available. However, current clinical evaluation of tumors still relies primarily on imaging examinations and tissue biopsies. These methods not only require sophisticated equipment, but also have high false positive rates or invasive problems. Here, we describe a digital polymerase chain reaction (dPCR) chip for the detection of biomarkers in salivary extracellular vesicles (SEVs), which can be used to identify markers for the early diagnosis of tumors. Based on microfluidic technology fine microstructure and microfluidics operations, this dPCR chip can accurate quantitative SEVs in a variety of tumor markers, and shows extremely strong sensitivity (10 copies). In the detection of clinical samples, the chip can effectively distinguish lung cancer cases from normal controls (P < 0.001; two-tailed t-test), and in the detection of extremely low concentration samples, it shows considerably higher precise quantitative ability than quantitative real-time polymerase chain reaction (qPCR). Overall, this study may shed new light on non-invasive early screening of tumor markers by detecting extracellular vesicle-associated markers in saliva.

Programmable Ligation-Transcription Circuit-Driven Cascade Amplification Machinery for Multiple Long Noncoding RNAs Detection in Lung Tissues

The measurement of long noncoding RNAs (lncRNAs) is essential to diagnosis and treatment of various diseases such as cancers. Herein, we develop a simple method to simultaneously detect multiple lncRNAs using programmable ligation-transcription circuit-driven cascade amplification and single-molecule counting. The presence of targets lncRNA HOTAIR and lncRNA MALAT1 activates the ligation-transcription circuits to produce two corresponding functional RNAs. The functional RNAs then cyclically initiate the digestion of signal probes by duplex-specific nuclease to liberate Cy5 and Cy3 molecules. After magnetic separation, the liberated Cy5 and Cy3 molecules are measured by single-molecule counting. In this assay, a single lncRNA can activate ligation-transcription circuit to generate abundant functional RNAs, endowing this assay with high sensitivity. Integration of single-molecule counting ensures the high sensitivity. This method shows extremely high sensitivity with a limit of detection (LOD) of 0.043 aM for HOX gene antisense intergenic RNA (lncRNA HOTAIR) and 0.126 aM for mammalian metastasis-related lung adenocarcinoma transcript 1 (lncRNA MALAT1). Importantly, this method enables simultaneous measurement of multiple endogenous lncRNAs at the single-cell level, and it may discriminate the expressions of various lncRNA in lung tumor tissues of nonsmall cell lung cancer (NSCLC) patients and their corresponding healthy adjacent tissues, offering a promising platform for clinical diagnosis and biomedical research.

LncRNA LINC00649 recruits TAF15 and enhances MAPK6 expression to promote the development of lung squamous cell carcinoma via activating MAPK signaling pathway

Lung squamous cell carcinoma (LUSC) represents one of the commonest types of lung cancer featured with high morbidity and poor prognosis. Many types of research have documented that long noncoding RNAs (lncRNAs) exert crucial functions in the development of cancers, and LUSC is included. In our study, we aimed at unveiling the mechanism underlying long intergenic nonprotein coding RNA 0649 (LINC00649) in LUSC cells. As a result, LINC00649 was discovered to be with high expression in LUSC cells. Moreover, it was confirmed through functional assays that the knockdown of LINC00649 hindered the occurrence and progression of LUSC. Results of mechanism assays validated that E2F transcription factor 7 (E2F7) was a transcription activator of LINC00649 and induced its up-regulation in LUSC cells. Furthermore, LINC00649 recruited TAF15, which is TATA-box binding protein associated factor 15 to stabilize mitogen-activated protein kinase 6 (MAPK6) expression and activate the transcription of MAPK6, thereby enhancing MAPK6 expression to activate the MAPK signaling pathway. Eventually, results of rescue assays suggested that overexpression of MAPK6 offset the influence of LINC00649 silencing on LUSC progression. In summary, our research determined the E2F7/LINC00649/TAF15/MAPK6/MAPK signaling pathway in regulating LUSC development, which made LINC00649 a potential biomarker for LUSC treatment.

Clinicopathological implications of lncRNAs, immunotherapy and DNA methylation in lung squamous cell carcinoma: a narrative review

Objective

To explore the clinicopathological impact of lncRNAs, immunotherapy, and DNA methylation in lung squamous cell carcinoma (LUSC), emphasizing their exact roles in carcinogenesis and modes of action.

Background

LUSC is the second most prevalent form, accounting for around 30% of non-small cell lung cancer (NSCLC). To date, molecular-targeted treatments have significantly improved overall survival in lung adenocarcinoma patients but have had little effect on LUSC therapy. As a result, there is an urgent need to discover new treatments for LUSC that are based on existing genomic methods.

Methods

In this review, we summarized and analyzed recent research on the biological activities and processes of lncRNA, immunotherapy, and DNA methylation in the formation of LUSC. The relevant studies were retrieved using a thorough search of Pubmed, Web of Science, Science Direct, Google Scholar, and the university's online library, among other sources.

Conclusions

LncRNAs are the primary components of the mammalian transcriptome and are emerging as master regulators of a number of cellular processes, including the cell cycle, differentiation, apoptosis, and growth, and are implicated in the pathogenesis of a variety of cancers, including LUSC. Understanding their role in LUSC in detail may help develop innovative treatment methods and tactics for LUSC. Meanwhile, immunotherapy has transformed the LUSC treatment and is now considered the new standard of care. To get a better knowledge of LUSC biology, it is critical to develop superior modeling systems. Preclinical models, particularly those that resemble human illness by preserving the tumor immune environment, are essential for studying cancer progression and evaluating novel treatment targets. DNA methylation, similarly, is a component of epigenetic alterations that regulate cellular function and contribute to cancer development. By methylating the promoter regions of tumor suppressor genes, abnormal DNA methylation silences their expression. DNA methylation indicators are critical in the early detection of lung cancer, predicting therapy efficacy, and tracking treatment resistance. As such, this review seeks to explore the clinicopathological impact of lncRNAs, immunotherapy, and DNA methylation in LUSC, emphasizing their exact roles in carcinogenesis and modes of action.

Differential expression of long non-coding RNAs as diagnostic markers for lung cancer and other malignant tumors

Due to advances in chip and sequencing technology, several types and numbers of long non-coding RNAs (lncRNAs) have been identified. LncRNAs are defined as non-protein-coding RNA molecules longer than 200 nucleotides, and are now thought as a new frontier in the study of human malignant diseases including NSCLC. Diagnosis of numerous malignant tumors has been closely linked to the differential expression of certain lncRNAs. LncRNAs are involved in gene expression regulation at multiple levels of epigenetics, transcriptional regulation, and post-transcriptional regulation. Mutations, deletions, or abnormal expression levels lead to physiological abnormalities, disease occurrence and are closely associated with human tumor diseases. LncRNAs play a crucial role in cancerous processes as either oncogenes or tumor suppressor genes. The expression of lncRNAs can regulate tumor cell in the proliferation, migration, apoptosis, cycle, invasion, and metastasis. As such, lncRNAs are potential diagnostic and treatment targets for cancer. And that, tumor biomarkers need to be detectable in easily accessible body samples, should be characterized by high specificity and sufficient sensitivity. Herein, it is significant clinical importance to screen and supplement new biomarkers for early diagnosis of lung cancer. This study aimed at systematically describing lncRNAs from five aspects based on recent studies: concepts, classification, structure, molecular mechanism, signal pathway, as well as review lncRNA implications in malignant tumor.

Simultaneous Enzyme-Free Detection of Multiple Long Noncoding RNAs in Cancer Cells at Single-Molecule/Particle Level

Aberrant change in long noncoding RNA (lncRNA) is associated with various diseases and cancers. So far, simultaneous detection of lncRNAs has remained a great challenge due to their large size and extensive secondary structure. Herein, we develop an enzyme-free single-molecule/particle detection method for simultaneous detection of multiple lncRNAs in cancer cells based on target-catalyzed strand displacement. We designed the magnetic bead-capture probe-multiple Cy5/Cy3-modified reporter unit complexes to isolate and identify lncRNA MALAT1 and lncRNA HOTAIR. The target-catalyzed strand displacement reactions lead to the release of Cy5 and Cy3 fluorescent molecules from the complexes, which can be subsequently quantified by single-molecule/particle detection. The dual-targetability, good selectivity and high sensitivity of this method enables simultaneous detection of multiple lncRNAs in even single cancer cell. Importantly, this method can discriminate cancer cells from normal cells and has significant advantages in the simple sequence design and in being free of enzymes, holding great potential in living cell imaging and early clinical diagnosis.

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

This study was designed to identify lncRNA biomarker candidates using lung cancer data from RNA-Seq and microarray platforms separately.Lung cancer datasets were obtained from the Gene Expression Omnibus (GEO, n = 287) and The Cancer Genome Atlas (TCGA, n = 216) repositories, only common lncRNAs were used. Differentially expressed (DE) lncRNAs in tumors with respect to normal were selected from the Affymetrix and TCGA datasets. A training model consisting of the top 20 DE Affymetrix lncRNAs was used for validation in the TCGA and Agilent datasets. A second similar training model was generated using the TCGA dataset.First, a model using the top 20 DE lncRNAs from Affymetrix for training and validated using TCGA and Agilent, achieved high prediction accuracy for both training (98.5% AUC for Affymetrix) and validation (99.2% AUC for TCGA and 92.8% AUC for Agilent). A similar model using the top 20 DE lncRNAs from TCGA for training and validated using Affymetrix and Agilent, also achieved high prediction accuracy for both training (97.7% AUC for TCGA) and validation (96.5% AUC for Affymetrix and 80.9% AUC for Agilent). Eight lncRNAs were found to be overlapped from these two lists.

Insights into amebiasis using a human 3D-intestinal model

Entamoeba histolytica is the causative agent of amebiasis, an infectious disease targeting the intestine and the liver in humans. Two types of intestinal infection are caused by this parasite: silent infection, which occurs in the majority of cases, and invasive disease, which affects 10% of infected persons. To understand the intestinal pathogenic process, several in vitro models, such as cell cultures, human tissue explants or human intestine xenografts in mice, have been employed. Nevertheless, our knowledge on the early steps of amebic intestinal infection and the molecules involved during human-parasite interaction is scarce, in part due to limitations in the experimental settings. In the present work, we took advantage of tissue engineering approaches to build a three-dimensional (3D)-intestinal model that is able to replicate the general characteristics of the human colon. This system consists of an epithelial layer that develops tight and adherens junctions, a mucus layer and a lamina propria-like compartment made up of collagen containing macrophages and fibroblast. By means of microscopy imaging, omics assays and the evaluation of immune responses, we show a very dynamic interaction between E. histolytica and the 3D-intestinal model. Our data highlight the importance of several virulence markers occurring in patients or in experimental models, but they also demonstrate the involvement of under described molecules and regulatory factors in the amoebic invasive process.

Long non-coding RNA dysregulation is a frequent event in non-small cell lung carcinoma pathogenesis

Background

Long non-coding RNAs compose an important level of epigenetic regulation in normal physiology and disease. Despite the plethora of publications of lncRNAs in human cancer, the landscape is still unclear.

Methods

Microarray analysis in 44 NSCLC paired specimens was followed by qPCR-based validation in 29 (technical) and 38 (independent) tissue pairs. Cross-validation of the selected targets was achieved in 850 NSCLC tumours from TCGA datasets.

Results

Twelve targets were successfully validated by qPCR (upregulated: FEZF1-AS1, LINC01214, LINC00673, PCAT6, NUTM2A-AS1, LINC01929; downregulated: PCAT19, FENDRR, SVIL-AS1, LANCL1-AS1, ADAMTS9-AS2 and LINC00968). All of them were successfully cross validated in the TCGA datasets. Abnormal DNA methylation was observed in the promoters of FENDRR, FEZF1-AS1 and SVIL-AS1. FEZF1-AS1 and LINC01929 were associated with survival in the TCGA set.

Conclusions

Our study provides through multiple levels of internal and external validation, a comprehensive list of dysregulated lncRNAs in NSCLC. We therefore envisage this dataset to serve as an important source for the lung cancer research community assisting future investigations on the involvement of lncRNAs in the pathogenesis of the disease and providing novel biomarkers for diagnosis, prognosis and therapeutic stratification.

Diagnostic efficacy of long non-coding RNA in lung cancer: a systematic review and meta-analysis

The detection of long non-coding RNA (lncRNA) is a novel method for lung cancer diagnosis. However, the diagnostic efficacy of lncRNA in different studies is inconsistent. Therefore, we conducted this meta-analysis to elucidate the diagnostic efficacy of lncRNA in identification of lung cancer including small cell lung cancer. The online PubMed, Medline, EMBASE, CNKI and Wanfang literature databases were searched to identify all related articles about the diagnostic efficacy of lncRNA for lung cancer. 28 articles including 3044 patients with lung cancer and 2598 controls were enrolled in our meta-analysis. lncRNA sustained a high diagnostic efficacy, pooled sensitivity of 0.82 (95% CI 0.79 to 0.84), specificity of 0.82 (95% CI 0.78 to 0.84) and area under the curve (AUC) of 0.88 (95% CI 0.85 to 0.91) in identification of patients with lung cancer from controls. Furthermore, the diagnostic efficacy of paralleled lncRNA was better than single lncRNA (sensitivity: 0.86 vs 0.80; specificity: 0.88 vs 0.78; AUC: 0.93 vs 0.86). MALAT1 had a better diagnostic efficacy than GAS5 (AUC: 0.90 vs 0.81; sensitivity: 0.83 vs 0.70; specificity: 0.83 vs 0.78). lncRNA in tissues was observed to achieve lower diagnostic efficacy than that in plasma or serum (AUC: 0.87 vs 0.90 vs 0.90) when stratified by sample types. In summary, our meta-analysis suggests that lncRNA might be a promising biomarker(s) for identifying lung cancer and the combination of lncRNA or with other biomarkers had a better diagnostic efficacy.

Accuracy of the urine UCA1 for diagnosis of bladder cancer: a meta-analysis

Urine UCA1 has been reported as a potential novel diagnostic biomarker for bladder cancer in several studies, but their results are inconsistent. As a result of this, a diagnostic meta-analysis to assess the diagnostic performance of urine UCA1 in detecting bladder cancer was conducted. A systematic electronic and manual search was performed for relevant literatures through PubMed, Cochrane library, Chinese Wan Fang and the China National Knowledge Infrastructure (CNKI) databases up to December 30, 2016. The quality of the studies included in this meta-analysis was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. All analyses were conducted using stata12.0 software. Six studies collectively included 578 bladder cancer patients and 562 controls met the eligible criteria. The overall diagnostic accuracy was measured by the following: sensitivity 0.81 (95% CI = 0.75-0.86), specificity 0.86 (95% CI = 0.73-0.93), positive likelihood ratio 5.85 (95% CI = 2.72-12.57), negative likelihood 0.22 (95% CI = 0.15-0.32), diagnostic odds ratio 27.01 (95% CI = 8.69-83.97), and area under the curve 0.88 (95% CI = 0.85-0.91). Meta-regression analysis suggested that ethnicity significantly accounted for the heterogeneity of sensitivity. Deeks' funnel plot asymmetry test (P = 0.33) suggested no potential publication bias. According to our results, urine UCA1 has greater diagnostic value in diagnosing bladder cancer, however further research studies with more well-designed and large sample sizes are required to confirm our findings.

LncRNAs in Secondary Hair Follicle of Cashmere Goat: Identification, Expression, and Their Regulatory Network in Wnt Signaling Pathway

Long noncoding RNAs (lncRNAs) are a novel class of eukaryotic transcripts. They are thought to act as a critical regulator of protein-coding gene expression. Herein, we identified and characterized 13 putative lncRNAs from the expressed sequence tags from secondary hair follicle of Cashmere goat. Furthermore, we investigated their transcriptional pattern in secondary hair follicle of Liaoning Cashmere goat during telogen and anagen phases. Also, we generated intracellular regulatory networks of upregulated lncRNAs at anagen in Wnt signaling pathway based on bioinformatics analysis. The relative expression of six putative lncRNAs (lncRNA-599618, -599556, -599554, -599547, -599531, and -599509) at the anagen phase is significantly higher than that at telogen. Compared with anagen, the relative expression of four putative lncRNAs (lncRNA-599528, -599518, -599511, and -599497) was found to be significantly upregulated at telogen phase. The network generated showed that a rich and complex regulatory relationship of the putative lncRNAs and related miRNAs with their target genes in Wnt signaling pathway. Our results from the present study provided a foundation for further elucidating the functional and regulatory mechanisms of these putative lncRNAs in the development of secondary hair follicle and cashmere fiber growth of Cashmere goat.

Integrated analysis of competing endogenous RNA network revealing lncRNAs as potential prognostic biomarkers in human lung squamous cell carcinoma

Accumulating evidence shows the important role of long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks for predicting survival in tumor patients. However, prognostic biomarkers for lung squamous cell carcinoma (LUSC) are still lacking. The objective of this study is to identify a lncRNA signature for evaluation of overall survival (OS) in 474 LUSC patients from The Cancer Genome Atlas (TCGA) database. A total of 474 RNA sequencing profiles in LUSC patients with clinical data were obtained, providing a large sample of RNA sequencing data, and 83 LUSC-specific lncRNAs, 26 miRNAs, and 85 mRNAs were identified to construct the ceRNA network (fold change>2, P<0.05). Among these above 83 LUSC-specific lncRNAs, 22 were assessed as closely related to OS in LUSC patients using a univariate Cox proportional regression model. Meanwhile, two (FMO6P and PRR26) of the above 22 OS-related lncRNAs were identified using a multivariate Cox regression model to construct a risk score as an independent indicator of the prognostic value of the lncRNA signature in LUSC patients. LUSC patients with low-risk scores were more positively correlated with OS (P<0.001). The present study provides a deeper understanding of the lncRNA-related ceRNA network in LUSC and suggests that the two-lncRNA signature could serve as an independent biomarker for prognosis of LUSC.