Long Noncoding RNA LINC01116 Contributes to Gefitinib Resistance in Non-small Cell Lung Cancer through Regulating IFI44

A genomic instability-associated lncRNA signature for predicting prognosis and biomarkers in lung adenocarcinoma

Genomic instability (GI) was associated with tumorigenesis. However, GI-related lncRNA signature (GILncSig) in lung adenocarcinoma (LUAD) is still unknown. In this study, the lncRNA expression data, somatic mutation information and clinical survival information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) and performed differential analysis. Functional and prognosis analysis revealed that multiple GI-related pathways were enriched. By using univariate and multivariate Cox regression analysis, 5 GI-associated lncRNAs (AC012085.2, FAM83A-AS1, MIR223HG, MIR193BHG, LINC01116) were identified and used to construct a GILncSig model. Mutation burden analysis indicated that the high-risk GI group had much higher somatic mutation count and the risk score constructed by the 5 GI-associated lncRNAs was an independent predictor for overall survival (OS) (P < 0.05). Overall, our study provides valuable insights into the involvement of GI-associated lncRNAs in LUAD and highlights their potential as therapeutic targets.

Revealing underlying regulatory mechanisms of LINC00313 in Osimertinib-resistant LUAD cells by ceRNA network analysis

BACKGROUND

Osimertinib, a third-generation epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), is the preferred treatment for EGFR-mutated lung cancer. However, acquired resistance inevitably develops. While non-coding RNAs have been implicated in lung cancer through various functions, the molecular mechanisms responsible for osimertinib resistance remain incompletely elucidated.

METHODS

RNA-sequencing technology was employed to determine differentially expressed lncRNAs (DE-lncRNAs) and mRNAs (DE-mRNAs) between H1975 and H1975OR cell lines. Starbase 2.0 was utilized to predict DE-lncRNA and DE-mRNA interactions, constructing ceRNA networks. Subsequently, functional and pathway enrichment analysis were performed on target DE-mRNAs to identify pathways associated with osimertinib resistance. Key target DE-mRNAs were then selected as potential risk signatures for lung adenocarcinoma (LUAD) prognostic modeling using multivariate Cox regression analyses. The Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry staining were used for result validation.

RESULTS

Functional analysis revealed that the identified DE-mRNAs primarily enriched in EGFR-TKI resistance pathways, especially in the PI3K/Akt signaling pathway, where their concerted actions may lead to osimertinib resistance. Specifically, upregulation of LINC00313 enhanced COL1A1 expression by acting as a miR-218-5p sponge, triggering an upstream response that activates the PI3K/Akt pathway, potentially contributing to osimertinib resistance. Furthermore, the expressions of LINC00313 and COL1A1 were validated by qRT-PCR, and the activation of the PI3K/Akt pathway was confirmed by immunohistochemistry staining.

CONCLUSIONS

Our results suggest that the LINC00313/miR-218-5p/COL1A1 axis potentially contributes to osimertinib resistance through the PI3K/Akt signaling pathway, providing novel insights into the molecular mechanisms underlying acquired osimertinib resistance in LUAD. Additionally, our study may aid in the identification of potential therapeutic targets for overcoming resistance to osimertinib.

Genes associated with inflammation for prognosis prediction for clear cell renal cell carcinoma: a multi-database analysis

Background

Clear cell renal cell carcinoma (ccRCC) is the largest subtype of kidney tumour, with inflammatory responses characterising all stages of the tumour. Establishing the relationship between the genes related to inflammatory responses and ccRCC may help the diagnosis and treatment of patients with ccRCC.

Methods

First, we obtained the data for this study from a public database. After differential analysis and Cox regression analysis, we obtained the genes for the establishment of a prognostic model for ccRCC. As we used data from multiple databases, we standardized all the data using the surrogate variable analysis (SVA) package to make the data from different sources comparable. Next, we used a least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model of genes related to inflammation. The data used for modelling and internal validation came from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (GSE29609) databases. ccRCC data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Tumour data from the E-MTAB-1980 cohort were used for external validation. The GSE40453 and GSE53757 datasets were used to verify the differential expression of inflammation-related gene model signatures (IRGMS). The immunohistochemistry of IRGMS was queried through the Human Protein Atlas (HPA) database. After the adequate validation of the IRGM, we further explored its application by constructing nomograms, pathway enrichment analysis, immunocorrelation analysis, drug susceptibility analysis, and subtype identification.

Results

The IRGM can robustly predict the prognosis of samples from patients with ccRCC from different databases. The verification results show that nomogram can accurately predict the survival rate of patients. Pathway enrichment analysis showed that patients in the high-risk (HR) group were associated with a variety of tumorigenesis biological processes. Immune-related analysis and drug susceptibility analysis suggested that patients with higher IRGM scores had more treatment options.

Conclusions

The IRGMS can effectively predict the prognosis of ccRCC. Patients with higher IRGM scores may be better candidates for treatment with immune checkpoint inhibitors and have more chemotherapy options.

LINC01116 affects patient survival differently and is dissimilarly expressed in ER+ and ER- breast cancer samples

BACKGROUND

Breast cancer is the most commonly detected cancer and one of the leading causes of cancer mortality. Emerging evidence supports that aberrant expression of lncRNAs is correlated with tumor progression and various aspects of tumor development.

AIM

This study aimed to evaluate the expression pattern of LINC01116 in breast cancer tissues and investigate the impact of LINC01116 on patients' survival.

METHODS AND RESULTS

Microarray and qRT-PCR data analysis were performed, and the KM-plotter database was used in this study. In addition, the gain of function approach was performed to examine the effect of LINC01116 on breast cancer cells in-vitro. The results exhibited that LINC01116 is meaningfully upregulated in the ER+ tumor specimens compared to the ER- ones. Also, relative to normal tissues, the expression of LINC01116 in ER+ and ER- tumor tissues significantly increased and decreased, respectively. ROC curve analysis revealed the power of LINC01116 in distinguishing ER+ from ER- samples. Additionally, the Kaplan-Meier survival analysis showed that the LINC01116 expression positively correlates with survival probability in all as well as ER+ patients. However, this correlation was negative in ER- patients. Furthermore, our results showed that the overexpression of LINC01116 induces TGF-β signaling in ER- cells (MDA-MB-231), and microarray data analysis revealed that LINC01116 is significantly upregulated in 17β-Estradiol treated MCF7 cells.

CONCLUSION

In conclusion, our results suggest that LINC01116 can be a potential biomarker in distinguishing ER+ and ER- tissues and has different effects on patients' survival based on ER status by affecting TGF-β and ER signaling.

Long non‑coding RNAs as potential therapeutic targets in non‑small cell lung cancer (Review)

Non‑small cell lung cancer (NSCLC) is one of the most common malignancies with a high morbidity and mortality rate. Long non‑coding RNAs (lncRNAs) have been reported to be closely associated with the occurrence and progression of NSCLC. In addition, lncRNAs have been documented to participate in the development of drug resistance and radiation sensitivity in patients with NSCLC. Due to their extensive functional characterization, high tissue specificity and sex specificity, lncRNAs have been proposed to be novel biomarkers and therapeutic targets for NSCLC. Therefore, in the current review, the functional classification of lncRNAs were presented, whilst the potential roles of lncRNAs in NSCLC were also summarized. Various physiological aspects, including proliferation, invasion and drug resistance, were all discussed. It is anticipated that the present review will provide a perspective on lncRNAs as potential diagnostic molecular biomarkers and therapeutic targets for NSCLC.

Long non-coding RNAs in non-small cell lung cancer: implications for EGFR-TKI resistance

Non-small cell lung cancer (NSCLC) is one of the most common types of malignant tumors as well as the leading cause of cancer-related deaths in the world. The application of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) has dramatically improved the prognosis of NSCLC patients who harbor EGFR mutations. However, despite an excellent initial response, NSCLC inevitably becomes resistant to EGFR-TKIs, leading to irreversible disease progression. Hence, it is of great significance to shed light on the molecular mechanisms underlying the EGFR-TKI resistance in NSCLC. Long non-coding RNAs (lncRNAs) are critical gene modulators that are able to act as oncogenes or tumor suppressors that modulate tumorigenesis, invasion, and metastasis. Recently, extensive evidence demonstrates that lncRNAs also have a significant function in modulating EGFR-TKI resistance in NSCLC. In this review, we present a comprehensive summary of the lncRNAs involved in EGFR-TKI resistance in NSCLC and focus on their detailed mechanisms of action, including activation of alternative bypass signaling pathways, phenotypic transformation, intercellular communication in the tumor microenvironment, competing endogenous RNAs (ceRNAs) networks, and epigenetic modifications. In addition, we briefly discuss the limitations and the clinical implications of current lncRNAs research in this field.

The pseudogene DUXAP10 contributes to gefitinib resistance in NSCLC by repressing OAS2 expression

Gefitinib, an epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI),is the currently recommended first-line therapy for advanced EGFR-mutant lung cancer, and understanding the mechanism of resistance is the key to formulating therapeutic strategies for EGFR-TKIs. In this study, we evaluate the expression patterns and potential biological functions of the pseudogene DUXAP10 in gefitinib resistance. We find that pseudogene DUXAP10 expression is significantly upregulated in NSCLC gefitinib-resistant cells and tissues. Gain and loss of function assays reveal that knockdown of DUXAP10 by siRNA reverses gefitinib resistance both in vitro and in vivo. Furthermore, DUXAP10 interacts with the histone methyltransferase enhancer of zeste homolog 2 (EZH2) to repress the expression of 2',5'-oligoadenylate synthetase (OAS2). Overall, our study highlights the pivotal role of DUXAP10 in gefitinib resistance, and the DUXAP10/EZH2/OAS2 axis might be a promising therapeutic target to overcome acquired gefitinib resistance in NSCLC.

IFI44L as a novel epigenetic silencing tumor suppressor promotes apoptosis through JAK/STAT1 pathway during lung carcinogenesis

Numerous evidence showed that the occurrence and development of lung cancer is closely related to environmental pollution. Therefore, new environmental response predictive markers are urgently needed for early diagnosis and screening of lung cancer. Interferon-induced protein 44-like (IFI44L) has been shown to be related in a variety of tumors, but its function and mechanism during lung carcinogenesis still have remained largely unknown. In this study, gene expression and methylation status were analyzed through online tools and malignant transformation models. Differentially expressed cell models and xenograft tumor models were established and used to clarify the gene function. RT-qPCR, western blotting, immunohistochemistry, and co-immunoprecipitation (Co-IP) were used to explore the mechanism. Results showed that IFI44L was dramatically downexpressed during lung carcinogenesis, and its low expression may be attributed to DNA methylation. Overexpression of IFI44L obviously inhibited cell growth and promoted apoptosis. After knockdown of IFI44L expression, the proliferation ability was remarkably increased and the apoptosis was significantly reduced. Functional enrichment showed that IFI44L was involved in apoptosis and JAK/STAT1 signaling pathway, and was highly correlated with downstream molecules. After overexpression of IFI44L, the expression of P-STAT1 and downstream molecules XAF1, OAS1, OAS2 and OAS3 were significantly increased. After knockdown of STAT1 expression, the pro-apoptotic effect of IFI44L was reduced. Co-IP results showed that IFI44L had protein interaction with STAT1. Results proved that IFI44L promoted STAT1 phosphorylation and activated the JAK/STAT1 signaling pathway by directly binding to STAT1 protein, thereby leading to cell apoptosis. Our study revealed that IFI44L promotes cell apoptosis and exerts tumor suppressors by activating the JAK/STAT1 signaling pathway. It further suggests that IFI44L has clinical therapeutic potential and may be a promising biomarker during lung carcinogenesis.

Integrated bioinformatic analyses investigate macrophage-M1-related biomarkers and tuberculosis therapeutic drugs

Tuberculosis (TB) is a common infectious disease linked to host genetics and the innate immune response. It is vital to investigate new molecular mechanisms and efficient biomarkers for Tuberculosis because the pathophysiology of the disease is still unclear, and there aren't any precise diagnostic tools. This study downloaded three blood datasets from the GEO database, two of which (GSE19435 and 83456) were used to build a weighted gene co-expression network for searching hub genes associated with macrophage M1 by the CIBERSORT and WGCNA algorithms. Furthermore, 994 differentially expressed genes (DEGs) were extracted from healthy and TB samples, four of which were associated with macrophage M1, naming RTP4, CXCL10, CD38, and IFI44. They were confirmed as upregulation in TB samples by external dataset validation (GSE34608) and quantitative real-time PCR analysis (qRT-PCR). CMap was used to predict potential therapeutic compounds for tuberculosis using 300 differentially expressed genes (150 downregulated and 150 upregulated genes), and six small molecules (RWJ-21757, phenamil, benzanthrone, TG-101348, metyrapone, and WT-161) with a higher confidence value were extracted. We used in-depth bioinformatics analysis to investigate significant macrophage M1-related genes and promising anti-Tuberculosis therapeutic compounds. However, more clinical trials were necessary to determine their effect on Tuberculosis.

Systematic Analysis of Molecular Subtypes Based on the Expression Profile of Immune-Related Genes in Pancreatic Cancer

Immunotherapy has a good therapeutic effect and provides a new approach for cancer treatment. However, only limited studies have focused on the use of molecular typing to construct an immune characteristic index for gene expression in pancreatic adenocarcinoma (PAAD) and to assess the effectiveness of immunotherapy in patients with PAAD. Clinical follow-up data and gene expression profile of PAAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Based on 184 immune features, molecular subtypes of pancreatic cancer were found by the "ConsensusClusterPlus" package, and the association between clinical features and immune cell subtype distribution was analysed. In addition, the relationship between the proportion of immune subtypes and the expression of immune checkpoints was analysed. The CIBERSORT algorithm was introduced to evaluate the immune scores of different molecular subtypes. We used the tumor immune dysfunction and exclusion (TIDE) algorithm to assess the potential clinical effect of immunotherapy interventions on single-molecule subtypes. In addition, the oxidative stress index was constructed by linear discriminant analysis DNA (LDA), and weighted correlation network analysis was performed to identify the core module of the index and its characteristic genes. Expression of hub genes was verified by immunohistochemical analysis in an independent PAAD cohort. Pancreatic cancer is divided into three molecular subtypes (IS1, IS2, and IS3), with significant differences in prognosis between multiple cohorts. Expression of immune checkpoint-associated genes was significantly reduced in IS3 and higher in IS1 and IS2, suggesting that the three subgroups have different responsiveness to immunotherapy interventions. The results of the CIBERSORT analysis showed that IS1 exhibited the highest levels of immune infiltration, whereas the results of the TIDE analysis showed that the T-cell dysfunction score of IS1 was higher than that of IS2 and IS3. Furthermore, IS3 was found to be more sensitive to 5-FU and to have a higher immune signature index than IS1 and IS2. Based on WGCNA analysis, 10 potential gene markers were identified, and their expression at the protein level was verified by immunohistochemical analysis. Specific molecular expression patterns in pancreatic cancer can predict the efficacy of immunotherapy and influence the prognosis of patients.

Molecular characterization of immunogenic cell death indicates prognosis and tumor microenvironment infiltration in osteosarcoma

Introduction

Osteosarcoma (OS) is a highly aggressive bone malignancy with a poor prognosis, mainly in children and adolescents. Immunogenic cell death (ICD) is classified as a type of programmed cell death associated with the tumor immune microenvironment, prognosis, and immunotherapy. However, the feature of the ICD molecular subtype and the related tumor microenvironment (TME) and immune cell infiltration has not been carefully investigated in OS.

Methods

The ICD-related genes were extracted from previous studies, and the RNA expression profiles and corresponding data of OS were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus database. The ICD-related molecular subtypes were classed by the "ConsensusclusterPlus" package and the construction of ICD-related signatures through univariate regression analysis. ROC curves, independent analysis, and internal validation were used to evaluate signature performance. Moreover, a series of bioinformatic analyses were used for Immunotherapy efficacy, tumor immune microenvironments, and chemotherapeutic drug sensitivity between the high- and low-risk groups.

Results

Herein, we identified two ICD-related subtypes and found significant heterogeneity in clinical prognosis, TME, and immune response signaling among distinct ICD subtypes. Subsequently, a novel ICD-related prognostic signature was developed to determine its predictive performance in OS. Also, a highly accurate nomogram was then constructed to improve the clinical applicability of the novel ICD-related signature. Furthermore, we observed significant correlations between ICD risk score and TME, immunotherapy response, and chemotherapeutic drug sensitivity. Notably, the in vitro experiments further verified that high GALNT14 expression is closely associated with poor prognosis and malignant progress of OS.

Discussion

Hence, we identified and validated that the novel ICD-related signature could serve as a promising biomarker for the OS's prognosis, chemotherapy, and immunotherapy response prediction, providing guidance for personalized and accurate immunotherapy strategies for OS.

Development of a novel hypoxia-immune–related LncRNA risk signature for predicting the prognosis and immunotherapy response of colorectal cancer

Background

Colorectal cancer (CRC) is one of the most common digestive system tumors worldwide. Hypoxia and immunity are closely related in CRC; however, the role of hypoxia-immune–related lncRNAs in CRC prognosis is unknown.

Methods

Data used in the current study were sourced from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA) databases. CRC patients were divided into low- and high-hypoxia groups using the single-sample gene set enrichment analysis (ssGSEA) algorithm and into low- and high-immune groups using the Estimation of STromal and Immune cells in MAlignant Tumours using Expression data (ESTIMATE) algorithm. Differentially expressed lncRNAs (DElncRNAs) between low- and high-hypoxia groups, low- and high-immune groups, and tumor and control samples were identified using the limma package. Hypoxia-immune–related lncRNAs were obtained by intersecting these DElncRNAs. A hypoxia-immune–related lncRNA risk signature was developed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analyses. The tumor microenvironments in the low- and high-risk groups were evaluated using ssGSEA, ESTIMATE, and the expression of immune checkpoints. The therapeutic response in the two groups was assessed using TIDE, IPS, and IC50. A ceRNA network based on signature lncRNAs was constructed. Finally, we used RT-qPCR to verify the expression of hypoxia-immune–related lncRNA signatures in normal and cancer tissues.

Results

Using differential expression analysis, and univariate Cox and LASSO regression analyses, ZNF667-AS1, LINC01354, LINC00996, DANCR, CECR7, and LINC01116 were selected to construct a hypoxia-immune–related lncRNA signature. The performance of the risk signature in predicting CRC prognosis was validated in internal and external datasets, as evidenced by receiver operating characteristic curves. In addition, we observed significant differences in the tumor microenvironment and immunotherapy response between low- and high-risk groups and constructed a CECR7–miRNA–mRNA regulatory network in CRC. Furthermore, RT-qPCR results confirmed that the expression patterns of the six lncRNA signatures were consistent with those in TCGA-CRC cohort.

Conclusion

Our study identified six hypoxia-immune–related lncRNAs for predicting CRC survival and sensitivity to immunotherapy. These findings may enrich our understanding of CRC and help improve CRC treatment. However, large-scale long-term follow-up studies are required for verification.

Emerging Role of Noncoding RNAs in EGFR TKI-Resistant Lung Cancer

Lung cancer accounts for the majority of malignancy-related mortalities worldwide. The introduction of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) has revolutionized the treatment and significantly improved the overall survival (OS) of lung cancer. Nevertheless, almost all EGFR-mutant patients invariably acquire TKI resistance. Accumulating evidence has indicated that noncoding RNAs (ncRNAs), such as microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs), have a central role in the tumorigenesis and progression of lung cancer by regulating crucial signaling pathways, providing a new approach for exploring the underlying mechanisms of EGFR-TKI resistance. Therefore, this review comprehensively describes the dysregulation of ncRNAs in EGFR TKI-resistant lung cancer and its underlying mechanisms. We also underscore the clinical application of ncRNAs as prognostic, predictive and therapeutic biomarkers for EGFR TKI-resistant lung cancer. Furthermore, the barriers that need to be overcome to translate the basic findings of ncRNAs into clinical practice are discussed.

Comprehensive analysis of 7-methylguanosine and immune microenvironment characteristics in clear cell renal cell carcinomas

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. ccRCC has obvious immunological characteristics, and the infiltration of immune cells is related to the prognosis of ccRCC. The effect of immune checkpoint therapy is related to the dynamic changes of the tumor immune microenvironment (TIM). The 7-methylguanosine (m7G) is an additional mRNA modification ability besides m6A, which is closely related to the TIM and affects the occurrence and development of tumors. At present, the correlations between m7G and the immune microenvironment, treatment, and prognosis of ccRCC are not clear. As far as we know, there was no study on the relationship between m7G and the immune microenvironment and survival of clear cell renal cell carcinomas. A comprehensive analysis of the correlations between them and the construction of a prognosis model are helpful to improve the treatment strategy. Two different molecular subtypes were identified in 539 ccRCC samples by describing the differences of 29 m7G-related genes. It was found that the clinical features, TIM, and prognosis of ccRCC patients were correlated with the m7G-related genes. We found that there were significant differences in the expression of PD-1, CTLA4, and PD-L1 between high- and low-risk groups. To sum up, m7G-related genes play a potential role in the TIM, treatment, and prognosis of ccRCC. Our results provide new findings for ccRCC and help to improve the immunotherapy strategies and prognosis of patients.

The role of long non-coding RNAs in angiogenesis and anti-angiogenic therapy resistance in cancer

It is well known that long non-coding RNAs (lncRNAs) play an important role in the regulation of tumor genesis and development. They can modulate gene expression of transcriptional regulation, epigenetic regulation of chromatin modification, and post-transcriptional regulation, thus influencing the biological behavior of tumors, such as cell proliferation, apoptosis, cell cycle, invasion, and migration. Tumor angiogenesis not only provides nutrients and helps excrete metabolites, but it also opens a pathway for tumor metastasis. Anti-angiogenic therapy has become one of the effective treatment methods for tumor. But its drug resistance leads to the limitation of clinical application. Recent studies have shown that lncRNAs are closely related to tumor angiogenesis and anti-angiogenic therapy resistance, which provides a new direction for tumor research. lncRNAs are expected to be new targets for tumor therapy. For the first time to our knowledge, this paper reviews advancement of lncRNAs in tumor angiogenesis and anti-angiogenic therapy resistance and further discusses their potential clinical application.

HMGB1-mediated autophagy promotes gefitinib resistance in human non-small cell lung cancer

Non-small cell lung cancer (NSCLC) ranks the first in incidence and mortality among malignant tumors in China. Molecular targeted therapies such as gefitinib, an oral inhibitor of the epidermal growth factor receptor tyrosine kinase, have shown significant benefits in patients with advanced NSCLC. However, most patients have unsatisfactory outcomes due to the development of drug resistance, and there is an urgent need to better understand the pathways involved in the resistance mechanisms. In this study, we found that HMGB1 is highly expressed in drug-resistant cells and confers to gefitinib resistance in NSCLC cells via activating autophagy process. Gefitinib upregulates HMGB1 expression in time-dependent and dose-dependent manners in human NSCLC cells. RNA interference-mediated knockdown of HMGB1 reduces PC9GR cell viability, induces apoptosis, and partially restores gefitinib sensitivity. Mechanistic analyses indicate that elevated HMGB1 expression contributes to gefitinib resistance by inducing autophagy. Thus, our results suggest that HMGB1 is an autophagy regulator and plays a key role in gefitinib resistance of NSCLC.

Identification of an EMT-related lncRNA signature and LINC01116 as an immune-related oncogene in hepatocellular carcinoma

Background: Epithelial–mesenchymal transition (EMT) plays a critical role in the recurrence and metastasis of hepatocellular carcinoma (HCC). Some long noncoding (lnc)RNAs are involved in this process through the regulation of EMT-related transcription factors.

Methods: In this study, we established a novel EMT-related lncRNA signature in HCC and identified hub lncRNAs that can serve as potential therapeutic targets. Differentially expressed lncRNAs were identified by screening HCC patient data from The Cancer Genome Atlas, and a correlation analysis was performed to identify those associated with EMT. The EMT-related lncRNA signature was established by univariate, least absolute shrinkage and selection operator, and multivariate Cox regression analyses. After verifying the prognostic accuracy of the signature, its relationships to immune cell infiltration and immune checkpoint targets were explored. LINC01116 was identified as a hub lncRNA and its role in HCC was investigated in vitro and in vivo.

Results: A 5-lncRNA signature was developed for HCC and its prognostic accuracy was assessed by survival, time-dependent receiver operating characteristic curve, clinical correlation, and Cox regression analyses. The correlation analysis showed that the lncRNA signature was closely related to immune cell infiltration and 10 immune checkpoint targets and also predicted the prognosis of HCC patients with high accuracy. In vitro and in vivo experiments revealed that LINC01116 stimulated cell proliferation, cell cycle progression, and tumor metastasis. We also found that LINC01116 was closely related to immune regulation.

Conclusions: These results demonstrate that LINC01116 is an immune-related oncogene that is associated with both EMT and immune regulation in HCC. Moreover, the EMT-related lncRNA signature that includes LINC01116 can guide risk stratification and clinical decision-making in HCC management.

Long non-coding RNA ACTA2-AS1 inhibits the cisplatin resistance of non-small cell lung cancer cells through inhibiting autophagy by suppressing TSC2

Long non-coding RNA (lncRNA) ACTA2-AS1 has been reported to play an important role in the progression of multiple human malignancies. The article aims to explore the role of ACTA2-AS1 on the cisplatin resistance of non-small cell lung cancer (NSCLC). RT-qPCR was performed to investigate the expression of ACTA2-AS1 in cisplatin-resistant NSCLC cell lines. Western blot was used to investigate the effects of ACTA2-AS1 on autophagy-related protein expression. RIP assay and RNA pull down were used to analyze the combination of ACTA2-AS1 and enhancer of zeste homolog 2 (EZH2), and CHIP was used to analyze the combination of tuberous sclerosis complex-2 (TSC2) gene promoter and Lys-27 of histone H3 (H3K27me3). In this study, ACTA2-AS1 was downregulated in cisplatin-resistant NSCLC cell lines. ACTA2-AS1 negatively regulated the cell viability and positively regulated the cell apoptosis of cisplatin-resistant NSCLC cell lines. Furthermore, our results demonstrated that ACTA2-AS1 promoted cisplatin-resistant NSCLC cells apoptosis through inhibiting autophagy. The regulation of ACTA2-AS1 to the cisplatin-resistant NSCLC cell autophagy was reversed by TSC2 increasing. Importantly, our results displayed that ACTA2-AS1 bound with EZH2, and TSC2 gene promoter combined with H3k27me3. The inhibition of ACTA2-AS1 to TSC2 expression was recused by EZH2 silencing. In conclusion, ACTA2-AS1 inhibited the cisplatin resistances of NSCLC cell lines through suppressing TSC2 expressing by recruiting EZH2 to TSC2 gene promoter.

Immune-Related lncRNA Pairs as Prognostic Signature and Immune-Landscape Predictor in Lung Adenocarcinoma

BACKGROUND

Suppressive tumor microenvironment is closely related to the progression and poor prognosis of lung adenocarcinoma (LUAD). Novel individual and universal immune-related biomarkers to predict the prognosis and immune landscape of LUAD patients are urgently needed. Two-gene pairing patterns could integrate and utilize various gene expression data.

METHODS

The RNA-seq and relevant clinicopathological data of the LUAD project from the TCGA and well-known immune-related genes list from the ImmPort database were obtained. Co-expression analysis followed by an analysis of variance was performed to identify differentially expressed immune-related lncRNA (irlncRNA) (DEirlncRNA) between tumor and normal tissues. Two arbitrary DEirlncRNAs (DEirlncRNAs pair) in a tumor sample underwent pairwise comparison to generate a score (0 or 1). Next, Univariate analysis, Lasso regression and Multivariate analysis were used to screen survival-related DEirlncRNAs pairs and construct a prognostic model. The Acak information standard (AIC) values of the receiver operating characteristic (ROC) curve for 3 years are calculated to determine the cut-off point for high- or low-risk score. Finally, we evaluated the relationship between the risk score and overall survival, clinicopathological features, immune landscape, and chemotherapy efficacy.

RESULTS

Data of 54 normal and 497 tumor samples of LUAD were enrolled. After a strict screening process, 15 survival-independent-related DEirlncRNA pairs were integrated to construct a prognostic model. The AUC value of the 3-year ROC curve was 0.828. Kaplan-Meier analysis showed that patients with low risk lived longer than patients with high risk (p <0.001). Univariate and Multivariate Cox analysis suggested that the risk score was an independent factor of survival. The risk score was negatively associated with most tumor-infiltrating immune cells, immune score, and microenvironment scores. The low-risk group was correlated with increased expression of ICOS. The high-risk group had a connection with lower half inhibitory centration (IC50) of most chemotherapy drugs (e.g., etoposide, paclitaxel, vinorelbine, gemcitabine, and docetaxel) and targeted medicine-erlotinib, but with higher IC50 of methotrexate.

CONCLUSION

The established irlncRNA pairs-based model is a promising prognostic signature for LUAD patients. Furthermore, the prognostic signature has great potential in the evaluation of tumor immune landscape and guiding individualized treatment regimens.

RALY regulate the proliferation and expression of immune/inflammatory response genes via alternative splicing of FOS

RALY is a multifunctional RNA-binding protein involved in cancer metastasis, prognosis, and chemotherapy resistance in various cancers. However, the molecular mechanism of which is still unclear. We have established RALY overexpression cell lines and studied the effect of RALY on proliferation and apoptosis in HeLa cells. Then we used RNA-seq to analyze the transcriptomes data. Lastly, RT-qPCR experiments had performed to confirm the RNA-seq results. We found that the overexpression of RALY in HeLa cells inhibited proliferation. Moreover, the overexpression of RALY changed the gene expression profile, and the significant upregulation of genes involved immune/inflammatory response related biological process by NOD-like receptor signaling pathway cytokine-cytokine receptor interaction. The significant downregulation genes involved innate immune response by the Primary immunodeficiency pathway. Notably, IFIT1, IFIT2, IFTI3, IFI44, HERC4, and OASL expression had inhibited by the overexpression of RALY. Furthermore, RALY negatively regulates the expression of transcription factors FOS and FOSB. Notably, we found that 645 alternative splicing events had regulated by overexpression of RALY, which is highly enriched in transcription regulation, RNA splicing, and cell proliferation biological process by the metabolic pathway. We show that RALY regulates the expression of immune/inflammatory response-related genes via alternative splicing of FOS in HeLa cells. The novel role of RALY in regulating immune/inflammatory gene expression may explain its function in regulating chemotherapy resistance and provides novel insights into further exploring the molecular mechanism of RALY in regulating cancer immunity and chemo/immune therapies.

Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

BACKGROUND

Lung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.

METHOD

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.

RESULTS

Fourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4⁺ T cells, CD8⁺ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.

CONCLUSION

We developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.

MALAT1 Polymorphisms and Lung Cancer Susceptibility in a Chinese Northeast Han Population

Background: LncRNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) was competitive endogenous RNA (ceRNA) involved in various molecular processes for metastasis development in lung cancer. Single nucleotide polymorphisms (SNPs) in MALAT1 gene might be predictive markers for lung cancer. In our study, we selected rs619586 and rs3200401 in MALAT1 gene to explore their effects on lung cancer susceptibility. Methods: The case-control study included 444 lung cancer cases and 460 healthy controls. Genotyping was performed by Taqman allelic discrimination method. Logistic regression, Student t-test, and Chi-square test (χ² ) were used to analyze the data. Results: The findings of the study showed that rs3200401 was significantly associated with the risk of non-small cell lung cancer (NSCLC) and lung squamous cell carcinoma (LUSC). Compared with homozygous CC genotype, CT heterozygous genotype decreased risk of NSCLC (P^a = 0.034) and LUSC (P^a = 0.025). In addition, no statistical association was detected between rs619586 and lung cancer susceptibility. The interactions between genes and cigarette smoking were discovered via crossover analysis. However, there were no remarkable gene-environment interactions in additive and multiplicative model. Conclusion: Rs3200401 in lncRNA MALAT1 was associated with the susceptibility of non-small-cell lung cancer and lung squamous cell carcinoma. The gene-environmental (cigarette smoking) interactions were not notable.

Identification of Prognostic Model Based on Immune-Related LncRNAs in Stage I-III Non-Small Cell Lung Cancer

Background

Long non-coding RNAs (lncRNAs) participate in the regulation of immune response and carcinogenesis, shaping tumor immune microenvironment, which could be utilized in the construction of prognostic signatures for non-small cell lung cancer (NSCLC) as supplements.

Methods

Data of patients with stage I-III NSCLC was downloaded from online databases. The least absolute shrinkage and selection operator was used to construct a lncRNA-based prognostic model. Differences in tumor immune microenvironments and pathways were explored for high-risk and low-risk groups, stratified by the model. We explored the potential association between the model and immunotherapy by the tumor immune dysfunction and exclusion algorithm.

Results

Our study extracted 15 immune-related lncRNAs to construct a prognostic model. Survival analysis suggested better survival probability in low-risk group in training and validation cohorts. The combination of tumor, node, and metastasis staging systems with immune-related lncRNA signatures presented higher prognostic efficacy than tumor, node, and metastasis staging systems. Single sample gene set enrichment analysis showed higher infiltration abundance in the low-risk group, including B cells (p<0.001), activated CD8+ T cells (p<0.01), CD4+ T cells (p<0.001), activated dendritic cells (p<0.01), and CD56+ Natural killer cells (p<0.01). Low-risk patients had significantly higher immune scores and estimated scores from the ESTIMATE algorithm. The predicted proportion of responders to immunotherapy was higher in the low-risk group. Critical pathways in the model were enriched in immune response and cytoskeleton.

Conclusions

Our immune-related lncRNA model could describe the immune contexture of tumor microenvironments and facilitate clinical therapeutic strategies by improving the prognostic efficacy of traditional tumor staging systems.

A Five Autophagy-Related Long Non-Coding RNA Prognostic Model for Patients with Lung Adenocarcinoma

Purpose

Lung adenocarcinoma is the most common pathological type among non-small cell lung cancer. Although huge progress has been made in terms of early diagnosis and precision treatment in recent years, the overall 5-year survival rate of a patient remains low. In our study, we try to construct an autophagy-related lncRNA prognostic signature that may guide clinical practice.

Methods

The mRNA and lncRNA expression matrix of lung adenocarcinoma patients were retrieved from the TCGA database. Next, we constructed a co-expression network of lncRNAs and autophagy-related genes. Lasso regression and multivariate Cox regression were then applied to establish a prognostic risk model. Subsequently, a risk score was generated to differentiate the high and low risk groups and a ROC curve and nomogram to visualize the predictive ability of the current signature. Finally, gene ontology and pathway enrichment analysis were executed via GSEA.

Results

A total of 1,703 autophagy-related lncRNAs were screened and five autophagy-related lncRNAs (LINC01137, AL691432.2, LINC01116, AL606489.1, and HLA-DQB1-AS1) were finally included in our signature. Judging from univariate (HR=1.075, 95% CI=1.046–1.104) and multivariate (HR=1.088, 95% CI=1.057−1.120) Cox regression analysis, the risk score is an independent factor for LUAD patients. Further, the AUC value based on the risk score for 1-year, 3-years, and 5-years, was 0.735, 0.672, and 0.662, respectively, indicating a reliable model. Drug sensitivity analysis revealed low risk patients were more sensitive to Gemcitabine and Gefitinib, while high risk patients had a better response to Paclitaxel and Erlotinib. Moreover, the lncRNAs included in our signature were primarily enriched in the autophagy process, metabolism, p53 pathway, and JAK/STAT pathway. Finally, a multi-omics analysis of correlated genes showed CFLAR overexpressed in the tumor sample, while GAPDH and MLST8 had a slightly higher expression in the normal sample.

Conclusion

Overall, our study indicated that the prognostic model we generated had certain predictability for LUAD patients’ prognosis and the related genes might be potential biomarkers and therapeutic targets.

Promising Advances in LINC01116 Related to Cancer

Long non-coding RNAs (lncRNAs) are RNAs with a length of no less than 200 nucleotides that are not translated into proteins. Accumulating evidence indicates that lncRNAs are pivotal regulators of biological processes in several diseases, particularly in several malignant tumors. Long intergenic non-protein coding RNA 1116 (LINC01116) is a lncRNA, whose aberrant expression is correlated with a variety of cancers, including lung cancer, gastric cancer, colorectal cancer, glioma, and osteosarcoma. LINC01116 plays a crucial role in facilitating cell proliferation, invasion, migration, and apoptosis. In addition, numerous studies have recently suggested that LINC01116 has emerged as a novel biomarker for prognosis and therapy in malignant tumors. Consequently, we summarize the clinical significance of LINC01116 associated with biological processes in various tumors and provide a hopeful orientation to guide clinical treatment of various cancers in future studies.

M6A associated TSUC7 inhibition contributed to Erlotinib resistance in lung adenocarcinoma through a notch signaling activation dependent way

Background

The small tyrosine kinase inhibitors (TKIs) subversively altered the lung cancer treatments, but patients will inevitably face the therapy resistance and disease recurrence. We aim to explore the potential roles of non-coding RNAs in sensitizing the TKIs effects. Methods: Multiple cellular and molecular detections were applied to confirm the mechanistic regulations and intracellular connections.

Results

We explored the specific gene features of candidates in association with resistance, and found that m6A controlled the stemness of EMT features through METTL3 and YTHDF2. The miR-146a/Notch signaling was sustained highly activated in a m6A dependent manner, and the m6A regulator of YTHDF2 suppressed TUSC7, both of which contributed to the resistant features. Functionally, the sponge type of TUSC7 regulation of miR-146a inhibited Notch signaling functions, and affected the cancer progression and stem cells’ renewal in Erlotinib resistant PC9 cells (PC9ER) and Erlotinib resistant HCC827 cells (HCC827ER) cells. The Notch signaling functions manipulated the cMYC and DICER inner cytoplasm, and the absence of either cMYC or DICER1 lead to TUSC7 and miR-146a decreasing respectively, formed the closed circle to maintain the balance.

Conclusion

PC9ER and HCC827ER cells harbored much more stem-like cells, and the resistance could be reversed by Notch signaling inactivation. The intrinsic miR-146 and TUSC7 levels are monitored by m6A effectors, the alternation of either miR-146 or TUSC7 expression could lead to the circling loop to sustain the new homeostasis. Further in clinics, the combined delivery of TKIs and Notch specific inhibitory non-coding RNAs will pave the way for yielding the susceptibility to targeted therapy in lung cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-021-02137-9.

Long non-coding RNA ZNF674-AS1 regulates miR-23a/E-cadherin axis to suppress the migration and invasion of non-small cell lung cancer cells

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors. The prognosis of patients with advanced NSCLC is poor due to metastasis. In recent years, the role of long non-coding RNAs (lncRNAs), a class of non-coding RNA molecules, in NSCLC has become an increasingly popular focus of studies. This study aimed to investigate the effects of ZNF674-AS1 and microRNA (miR)-23a on the migration and invasion abilities of NSCLC cells in vitro and explore the underpinning molecular mechanisms.

METHODS

The expression levels of ZNF674-AS1 and miR-23a in NSCLC tissues and cells were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Scratch test and transwell test were used to detect the effects of ZNF674-AS1 and miR-23a on the migration and invasion of NSCLC cells. The luciferase reporter gene experiment was used to verify miRNA targets. Western blot experiments were used to analyze protein expression.

RESULTS

ZNF674-AS1 was downregulated in NSCLC tissues and cells, and inhibited the migration and invasion of NSCLC cells in vitro. In contrast, the expression of miR-23a, a downstream target of ZNF674-AS1, was increased in NSCLC tissues and cells. We found that miR-23a could antagonize the role of ZNF674-AS1 in NSCLC. E-cadherin was identified as a downstream target gene of miR-23a, and miR-23a could directly inhibit its expression.

CONCLUSIONS

ZNF674-AS1 inhibits the migration and invasion of NSCLC cells by regulating a miR-23a/E-cadherin axis. ZNF674-AS1 and miR-23a could become potential therapeutic targets for NSCLC.

Development and validation of stemness associated LncRNA based prognostic model for lung adenocarcinoma patients

BACKGROUND

An increasing number of studies are indicating that the stemness phenotype is a critical determinant of the Lung adenocarcinoma (LUAD) patient's response. Thus, it is crucial to identify novel biomarkers for stemness determination.

OBJECTIVE

Here, we aim to develop a robust LncRNAs based prognostic signature with a stemness association for the LUAD patients.

METHODS

RNA-seq and clinical data were downloaded from the existing database. The data were analysed using Cox regression, KM-plot, GSEA, and T-test.

RESULTS

Initially, we used the TCGA dataset to characterize the stemness phenotype in LUAD. The commonly expressed LncRNAs in TCGA and MCTP cohort were then used as input for the Cox-regression analysis. The top three LncRNAs were selected to build a prognostic model, which was the best prognosticator in multivariate analysis with stage and previously published prognosticators. The characterization of poor surviving patients using various analysis showed high stemness properties and low expression of differentiation markers. Furthermore, we validated the prognostic score in an independent MCTP cohort of patients. In the MCTP cohort, prognostic score significantly predicted survival independent of stage and previous prognosticators.

CONCLUSION

Taken together, in this study, we have developed and validated a new prognostic score associated with the stemness phenotype.

A novel prognostic signature of immune-related lncRNA pairs in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, but the prognosis of LUAD patients remains unsatisfactory. Here, we retrieved the RNA-seq data of LUAD cohort from The Cancer Genome Atlas (TCGA) database and then identified differentially expressed immune-related lncRNAs (DEirlncRNAs) between LUAD and normal controls. Based on a new method of cyclically single pairing along with a 0-or-1 matrix, we constructed a novel prognostic signature of 8 DEirlncRNA pairs in LUAD with no dependence upon specific expression levels of lncRNAs. This prognostic model exhibited significant power in distinguishing good or poor prognosis of LUAD patients and the values of the area under the curve (AUC) were all over 0.70 in 1, 3, 5 years receiver operating characteristic (ROC) curves. Moreover, the risk score of the model could serve as an independent prognostic factor for patients with LUAD. In addition, the risk model was significantly associated with clinicopathological characteristics, tumor-infiltrating immune cells, immune-related molecules and sensitivity of anti-tumor drugs. This novel signature of DEirlncRNA pairs in LUAD, which did not require specific expression levels of lncRNAs, might be used to guide the administration of patients with LUAD in clinical practice.

LncRNA LINC01116 facilitates melanoma 1 progression via sequestering miR-3612 and up-regulating GDF11 and SDC3

BACKGROUND

Melanoma is the deadliest cutaneous malignant tumor with high risks. Though increasing evidence has widely referred to the involvement of long non-coding RNAs (lncRNAs) in the mechanism of tumor development, including melanoma, the functional roles of most lncRNAs in melanoma remain to be explored. In this study, we focus on disclosing the role of long intergenic non-protein coding RNA 1116 (LINC01116) in melanoma.

METHODS

Firstly, we detected LINC01116 expression through RT-qPCR. Functional analysis and animal experiments were carried out to assess the role of LINC01116 in vivo and in vitro. Western blot analysis was employed for detection of important markers regarding epithelial mesenchymal transition (EMT). In addition, RNA pulls down, RIP and luciferase reporter assays were performed to probe into the regulatory mechanism of LINC01116.

RESULTS

LINC01116 was significantly up regulated in melanoma cells. LINC01116 deficiency abrogated cell proliferation, migration, invasion and EMT in melanoma. Moreover, LINC01116 enhanced growth differentiation factor 11 (GDF11) and syndecan 3 (SDC3) expression through sponging microRNA-3612 (miR-3612). The oncogenic role of the LINC01116/miR-3612/GDF11/SDC3 axis in melanoma was finally demonstrated.

CONCLUSION

Conclusively, LINC01116 sequestered miR-3612 and targeted GDF11 and SDC3 to contribute to the progression of melanoma.

Long non-coding RNA LINC01116 is activated by EGR1 and facilitates lung adenocarcinoma oncogenicity via targeting miR-744-5p/CDCA4 axis

Background

Lung adenocarcinoma (LAD) is one of the most frequently diagnosed pathological categories of human lung cancer. Nevertheless, the link between long non-coding RNA (lncRNA) LINC01116 and LAD remains poorly investigated.

Methods

QRT-PCR and western blot were applied for quantifying the expression of RNAs and proteins. Both functional experiments assays in vitro and xenografts model in vivo were implemented for analyzing LINC01116 function in LAD while molecular relationship among RNAs was investigated via mechanism experiments.

Results

LINC01116 was expressed at an abnormally high level in LAD, which was induced by transcription activator EGR1. LINC01116 depletion restrained proliferation, migration and invasion, yet facilitated apoptosis of LAD cells. MiR-744-5p could bind to LINC01116. MiR-744-5p inhibitor reversed the inhibitory effects of silencing LINC01116 on LAD malignant behaviors. In addition, cell division cycle-associated protein 4 (CDCA4) shared binding sites with miR-744-5p. Silencing LINC01116 elicited decline in CDCA4 mRNA and protein levels. Moreover, CDCA4 up-regulation could counteract the biological effects of LINC01116 knockdown on LAD cells.

Conclusion

Our data revealed that LINC01116 promoted malignant behaviors of LAD cells by targeting miR-744-5p/CDCA4 axis, implying the theoretical potential of LINC01116 as a novel target for LAD treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-01994-w.

Identification of 4 immune cells and a 5-lncRNA risk signature with prognosis for early-stage lung adenocarcinoma

Background

Lung cancer is the most common cancer and cause of cancer‐related mortality worldwide, increasing evidence indicated that there was a significant correlation between tumors and the long non‐coding RNAs (lncRNAs), as well as tumor immune infiltration, but their role in early lung adenocarcinoma (LUAD) are still unclear.

Methods

Gene expression data and corresponding clinical data of early-stage LUAD patients were downloaded from GEO and TCGA databases. 24 kinds of tumor-infiltrating immune cells were analyzed by quantity analysis and univariate cox regression analysis, we divided patients into two subgroups using consensus clustering, recognized the differentially expressed genes (DEGs) in the subgroups, then, established lncRNA risk signature by least absolute shrinkage and selection operator (LASSO) regression.

Results

A total of 718 patients were enrolled in this study, including 246 from GSE31210 dataset, 127 from GSE50081 dataset and 345 from TCGA-LUAD. We identified that Th2 cells, TFH, NK CD56dim cells and Mast cells were prognosis-related(p < 0.05), then established a 5-lncRNA risk signature (risk score = 0.374600616* LINC00857 + 0.173825706* LINC01116 + (− 0.021398903)* DRAIC + (− 0.113658256)* LINC01140 + (− 0.008403702)* XIST), and draw a nomogram showed that the signature had a well prediction accuracy and discrimination.

Conclusions

We identified 4 immune infiltrating cells related to the prognosis of early-stage LUAD, and established a novel 5 immune-related lncRNA signature for predicting patients’ prognosis.

LINC01116 promotes the proliferation and invasion of glioma by regulating the microRNA‑744‑5p‑MDM2‑p53 axis

Long non-coding RNAs (lncRNAs) have been implicated in the development and progression of tumors. However, the roles and underlying mechanisms of long intergenic non-protein coding RNA 1116 (LINC01116), a member of the lncRNA family, in glioma progression are largely unclear. The expression of LINC01116 and microRNA (miR)-744-5p in glioma tissues and cells was detected by reverse transcription-quantitative PCR. The influences of LINC01116 or miR-744-5p on cell proliferation and invasion were evaluated by Cell Counting Kit-8, colony formation and Transwell assays, and western blotting was used to detect the expression of p53 pathway proteins. A dual-luciferase reporter system was used to locate common binding sites between miR-744-5p and LINC01116 or the 3′ untranslated region of E3 ubiquitin-protein ligase Mdm2 (MDM2). RNA immunoprecipitation was used to determine the interactions between RNAs and proteins. Moreover, a xenograft mouse model was constructed to investigate the effects of LINC01116 in vivo, followed by a TdT-mediated dUTP nick end labeling assay to determine the degree of apoptosis in nude mouse tumors. LINC01116 was found to be highly expressed in glioma tissues, which was associated with a malignant phenotype. LINC01116 promoted the proliferation and invasiveness of glioma cells, and inhibited the p53 pathway by preserving the expression of MDM2 mRNA via miR-744-5p sponging. Furthermore, a low degree of miR-744-5p expression was observed in glioma tissues, which was negatively associated with the expression of LINC01116. Overexpression of miR-744-5p inhibited the proliferation and invasiveness of glioma cells, which was rescued by LINC01116. Finally, LINC01116 knockdown inhibited tumor growth in nude mice. In conclusion, LINC01116 is aberrantly expressed and promotes the progression of glioma by regulating the miR-744-5p-MDM2-p53 pathway. In future, targeting LINC01116 may therefore be a potential therapeutic approach for patients with glioma.

LncRNA OSER1-AS1 interacts with miR-612/FOXM1 axis to modulate gefitinib resistance of lung adenocarcinoma

Long noncoding RNAs (lncRNAs) play crucial roles in the acquired resistance to EGFR-directed therapies in lung cancer. LncRNA OSER1-AS1 has been reported to promote tumorigenesis of hepatocellular carcinoma. However, its functions and underlying molecular mechanisms remain unclear in the acquired gefitinib-resistance of lung cancer. Our study revealed that increased expression of OSER1-AS1 was correlated with gefitinib resistance in lung adenocarcinoma. Higher OSER1-AS1 expression predicted disease progression of lung adenocarcinoma patients. The in vitro assays indicated OSER1-AS1 contributed to gefitinib resistance of lung adenocarcinoma cells via inhibiting cell apoptosis and cell cycle arrest. In vivo experiments showed that the knockdown of OSER1-AS1 restored the sensitivity of lung cancer cells to gefitinib. Further studies showed that OSER1-AS1 functioned as a molecular sponge of miR-612. OSER1-AS1 down-regulated miR-612 to increase FOXM1 expression, suggesting that miR-612/FOXM1 axis was regulated by OSER1-AS1, which was partially responsible for gefitinib resistance of lung adenocarcinoma. In conclusion, OSER1-AS1 promoted gefitinib resistance of lung adenocarcinoma through the miR-612/FOXM1 axis.

LINC01116 Promotes Doxorubicin Resistance in Osteosarcoma by Epigenetically Silencing miR-424-5p and Inducing Epithelial-Mesenchymal Transition

Background: Development of resistance to doxorubicin-based chemotherapy limits its curative effect in osteosarcoma. In the current study, we focused on investigating the mechanisms underlying the development of doxorubicin resistance in osteosarcoma.

Methods: The human osteosarcoma cell line MG-63 and doxorubicin-resistant MG-63/Dox cells were used in this study. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression of the long non-coding RNA LINC01116 in the two cell lines. Then, the specific shRNA for LINC01116 was employed to suppress LINC01116 expression in MG-63/Dox cells. Cell viability was assessed by the CCK-8 and colony formation assays. Cell migration and invasion were evaluated by the transwell assay. Moreover, the epithelial-mesenchymal transition (EMT)-related proteins, E-cadherin, vimentin, and N-cadherin were evaluated by Western blotting. The regulation of LINC01116 on miR-424-5p expression was examined using methylation-specific PCR, RNA immunoprecipitation, and Western blotting assay. The potential targeting of HMGA2 by miR-424-5p was predicted using the bioinformatics databases TargetScan and miRanda and verified by a dual-luciferase reporter assay.

Results: LINC01116 was more highly expressed in MG-63/Dox cells than in MG-63 cells. Inhibition of LINC01116 suppressed cell viability, migration, and invasion, along with upregulating the expression of E-cadherin, downregulating vimentin, and attenuating doxorubicin resistance in MG-63/Dox cells. Further mechanism-related investigations indicated that LINC01116 regulated HMGA2 expression via the EZH2-associated silencing of miR-424-5p.

Conclusion: LINC01116 exerts regulatory effects on doxorubicin resistance through the miR-424-5p axis, providing a potential approach to overcoming chemoresistance in osteosarcoma.

Long intergenic non-coding RNA (lincRNA)-01317 suppresses human gastric cancer growth by inhibiting migration and invasion of cancer cells

Long intergenic noncoding RNAs (lincRNAs) are strongly associated with several kinds of cancer, including gastric cancer. Here, we found significantly decreased lincRNA-01317 levels in cancer tissue compared with paracancer tissue of patients with gastric cancer, and lincRNA-01317 expression levels positively correlated with clinical survival rate. Furthermore, using a gastric cancer cell line and a xenograft mouse model, we found that transfection of a gastric cancer cell line with lincRNA-01317 significantly inhibited the proliferation, migration, and invasion of gastric cancer cells. Finally, we demonstrated that lincRNA-01317 may target KCNQ1, as KCNQ1 was downregulated after transfection of cells with lincRNA-01317. This study aimed to assess lincRNA-01317 as a potential therapeutic target to treat cancers.

Identified GNGT1 and NMU as Combined Diagnosis Biomarker of Non-Small-Cell Lung Cancer Utilizing Bioinformatics and Logistic Regression

Non-small-cell lung cancer (NSCLC) is one of the most devastating diseases worldwide. The study is aimed at identifying reliable prognostic biomarkers and to improve understanding of cancer initiation and progression mechanisms. RNA-Seq data were downloaded from The Cancer Genome Atlas (TCGA) database. Subsequently, comprehensive bioinformatics analysis incorporating gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and the protein-protein interaction (PPI) network was conducted to identify differentially expressed genes (DEGs) closely associated with NSCLC. Eight hub genes were screened out using Molecular Complex Detection (MCODE) and cytoHubba. The prognostic and diagnostic values of the hub genes were further confirmed by survival analysis and receiver operating characteristic (ROC) curve analysis. Hub genes were validated by other datasets, such as the Oncomine, Human Protein Atlas, and cBioPortal databases. Ultimately, logistic regression analysis was conducted to evaluate the diagnostic potential of the two identified biomarkers. Screening removed 1,411 DEGs, including 1,362 upregulated and 49 downregulated genes. Pathway enrichment analysis of the DEGs examined the Ras signaling pathway, alcoholism, and other factors. Ultimately, eight prioritized genes (GNGT1, GNG4, NMU, GCG, TAC1, GAST, GCGR1, and NPSR1) were identified as hub genes. High hub gene expression was significantly associated with worse overall survival in patients with NSCLC. The ROC curves showed that these hub genes had diagnostic value. The mRNA expressions of GNGT1 and NMU were low in the Oncomine database. Their protein expressions and genetic alterations were also revealed. Finally, logistic regression analysis indicated that combining the two biomarkers substantially improved the ability to discriminate NSCLC. GNGT1 and NMU identified in the current study may empower further discovery of the molecular mechanisms underlying NSCLC's initiation and progression.

Genomic and transcriptomic alterations associated with drug vulnerabilities and prognosis in adenocarcinoma at the gastroesophageal junction

Adenocarcinoma at the gastroesophageal junction (ACGEJ) has dismal clinical outcomes, and there are currently few specific effective therapies because of limited knowledge on its genomic and transcriptomic alterations. The present study investigates genomic and transcriptomic changes in ACGEJ from Chinese patients and analyzes their drug vulnerabilities and associations with the survival time. Here we show that the major genomic changes of Chinese ACGEJ patients are chromosome instability promoted tumorigenic focal copy-number variations and COSMIC Signature 17-featured single nucleotide variations. We provide a comprehensive profile of genetic changes that are potentially vulnerable to existing therapeutic agents and identify Signature 17-correlated IFN-α response pathway as a prognostic marker that might have practical value for clinical prognosis of ACGEJ. These findings further our understanding on the molecular biology of ACGEJ and may help develop more effective therapeutic strategies.

Adenocarcinoma at the gastroesophageal junction has a dismal prognosis and few drug options. Here, the authors present genomic and transcriptomic features and potential therapeutic targets and prognostic biomarkers of Chinese and Caucasian tumours, and reveal the molecular similarities.

Interferon-Induced Protein 44 Correlated With Immune Infiltration Serves as a Potential Prognostic Indicator in Head and Neck Squamous Cell Carcinoma

Interferon-induced protein 44 (IFI44) containing a guanosine-5′-triphosphate (GTP) binding domain was reported to play a significant role in the immune response to autoimmune disease. However, its roles involved in cancers remain unclear. Here, we detected the expression of IFI44 in The Cancer Genome Atlas (TCGA) Pan-cancer and generally explored the effect of IFI44 on immune infiltration in the tumor microenvironment (TME). The results displayed that IFI44 was mainly located in the cytoplasm and overexpressed in head and neck squamous cell carcinoma (HNSC) samples compared with normal tissues. Survival analysis exhibited that IFI44 was remarkably associated with the clinical outcomes, particularly in lymph node-positive and locally advanced HNSC patients. Biological analysis showed that IFI44 was correlated with such immune biological processes as antigen-presenting and nuclear factor (NF)-kappa B signaling pathways. Immune signature analysis demonstrated that the expression of IFI44 was positively correlated with the infiltration of CD4⁺ cells and macrophages as well as neutrophils in HNSC. Taken together, these data suggested that IFI44 was abnormally expressed in cancer tissues and indicated the potential impact of IFI44 on the tumor immune infiltration in HNSC.

LncRNA LINC01116 Promotes the Development of Colorectal Cancer by Targeting miR-9-5p/STMN1

Purpose

The aim was to research the role of LINC01116 in the prognosis of colorectal cancer (CRC) patients and development of colorectal cancer cells.

Methods

In total 62 colorectal cancer patient tissues and human CRC cell lines (OUMS23, SW116, SW480 and LOVO) were obtained for this study. SiLINC01116, miR-9-5p mimic, LINC01116, oe-STMN1 and their controls were transfected. The qRT-PCR method and Western blot were used to detect the levels of LINC01116, miR-9-5p and STMN1 in tissues and cells. CCK8 assay and flow cytometry were processed for proliferation and apoptosis, respectively. Transwell assay was undertaken to verify invasion and migration. Luciferase assay and pull down assay were processed to confirm the binding relationship among LINC01116, miR-9-5p and STMN1. Immunohistochemistry assay also detected the expression of STMN1. Kaplan–Meier survival curve was used to analyze patient survival rate. Pearson correlation analysis was used to evaluate the regulatory relationship between LINC01116, miR-9-5p and STMN1 in tissues.

Results

LINC01116 was expressed higher in CRC tissues and cells. Patients with higher expression of LINC01116 had worse prognosis. Knockdown of LINC01116 suppressed development of CRC cell. LINC01116 negatively regulated miR-9-5p, while MiR-9-5p was negatively related to STMN1. miR-9-5p mimic could rescue the effect of LINC01116, inhibit migration and invasion, and improve apoptosis of CRC cells. Oe-STMN1 could also rescue the effect of miR-9-5p on the development of colorectal cancer.

Conclusion

LINC01116 promoted the development of colorectal cancer via modulating miR-9-5p/STMN1 axis.

Long non-coding RNA CASC9 promotes gefitinib resistance in NSCLC by epigenetic repression of DUSP1

Resistance to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs), such as gefitinib, has greatly affected clinical outcomes in non-small cell lung cancer (NSCLC) patients. The long noncoding RNAs (lncRNAs) are known to regulate tumorigenesis and cancer progression, but their contributions to NSCLC gefitinib resistance remain poorly understood. In this study, by analyzing the differentially expressed lncRNAs in gefitinib-resistant cells and gefitinib-sensitive cells in the National Institute of Health GEO dataset, we found that lncRNA CASC9 expression was upregulated, and this was also verified in resistant tissues. Gain and loss of function studies showed that CASC9 inhibition restored gefitinib sensitivity both in vitro and in vivo, whereas CASC9 overexpression promoted gefitinib resistance. Mechanistically, CASC9 repressed the tumor suppressor DUSP1 by recruiting histone methyltransferase EZH2, thereby increasing the resistance to gefitinib. Furthermore, ectopic expression of DUSP1 increased gefitinib sensitivity by inactivating the ERK pathway. Our results highlight the essential role of CASC9 in gefitinib resistance, suggesting that the CASC9/EZH2/DUSP1 axis might be a novel target for overcoming EGFR-TKI resistance in NSCLC.

LncRNA LINC01116 Contributes to Cisplatin Resistance in Lung Adenocarcinoma

Background

Long non-coding RNAs (lncRNAs) have been found to contribute to cisplatin resistance in several cancers; however, the role of lncRNA LINC01116 in cisplatin resistance remains unknown in non-small-cell lung cancer. This study aimed to examine the contribution of LINC01116 to cisplatin resistance in lung adenocarcinoma (LAD).

Materials and Methods

Cisplatin-resistant A549/DDP cells were generated by treatment with cisplatin by dose escalation. LINC01116 expression was compared between A549 and A549/DDP cells, and between cisplatin-resistant and non-resistant LAD specimens. The cell viability, colony formation, proliferation, migration and invasion were measured using MTT and Transwell assays, and cell apoptosis and cell cycle were detected using flow cytometry. The expression of E-cadherin and Vimentin was quantified. LAD xenografts were modeled in nude mice to investigate the role of LINC01116 on the resistance of LAD to cisplatin.

Results

MTT assay measured the IC₅₀ values of 13.49 ± 1.62 and 3.52 ± 1.33 μg/mL for A549/DDP and A549 cells, respectively. LINC01116 was overexpressed in cisplatin-resistant LAD specimens and A549/DDP cells (P < 0.05). Knockdown of LINC01116 inhibited cell viability, proliferation, migration and invasion, promoted apoptosis and enhanced the sensitivity to cisplatin in A549/DDP cells, while LINC01116 overexpression promoted cell viability, proliferation, migration and invasion, inhibited apoptosis and reduced the sensitivity to cisplatin in A549 cells. LINC01116 knockdown resulted in a 2.1-fold increase in E-cadherin expression and a 56% reduction in Vimentin expression in A549/DDP cells, and LINC01116 overexpression resulted in a 45% reduction in E-cadherin expression and a 1.82-fold increase in Vimentin expression in A549 cells.

Conclusion

Dysregulation of lncRNA LINC01116 expression results in resistance of LAD to cisplatin via the EMT process. Our findings support the oncogenic role of LINC01116 to promote the development of cisplatin resistance in LAD, and LINC01116 may be a novel predictor of poor response to cisplatin.

All-Trans Retinoic Acid Rescues the Tumor Suppressive Role of RAR-β by Inhibiting LncHOXA10 Expression in Gastric Tumorigenesis

Numerous long noncoding RNAs (LncRNAs) were having recently been shown to be involved in cancer development, including gastric cancer (GC). However, the precise mechanism and treatments to target these molecules have rarely been studied. Thus, we aimed to investigate the function of LncHOXA10 in gastric tumorigenesis and targeted therapy. First, we measured the differences in LncHOXA10 and retinoic acid receptor β (RAR-β) levels in gastric cancer tissues and cell lines compared with those in noncancerous tissues and cell lines. We observed that LncHOXA10 was significantly upregulated in gastric cancer tissues and cell lines, whereas RAR-β showed the opposite trend. Subsequently, loss and gain of LncHOXA10 cell lines were constructed to determine whether LncHOXA10 plays a role in gastric tumorigenesis. The results showed that LncHOXA10 promoted the proliferation, migration, and invasion of cells, whereas apoptosis was markedly inhibited. Subsequently, mechanistic investigations revealed that LncHOXA10 can repress RAR-β expression and that all-trans retinoic acid (ATRA) can rescue the expression of RAR-β. Finally, we showed that ATRA can reverse the pro-cancerous function of LncHOXA10. We showed that LncHOXA10 may be a prognostic and therapeutic factor of gastric cancer by negatively regulating RAR-β. Furthermore, ATRA can inhibit the role of LncHOXA10 in gastric tumorigenesis.

Progress of long noncoding RNAs in anti-tumor resistance

The resistance of cancer cells to anti-cancer drugs is an important reason for the failure of treatment. Overcoming drug resistance can achieve long-lasting and efficient cancer treatment. Long non-coding RNA (lncRNA) is a class of RNA molecules that does not encode protein and has more than 200 nucleotides. LncRNA not only has a regulatory role in the occurrence and development of malignant tumors, but also has been found to have a potential impact on anti-tumor resistance. Abnormal expression of lncRNA can cause tumor cells to develop resistance to anti-tumor drugs. This article reviews the recent research progress of lncRNA in various tumor resistances and the mechanism of lncRNA acting on tumor drug resistance.

Mechanisms of drug resistance mediated by long non-coding RNAs in non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is the most prevalent form of lung cancer and has a poor five-year survival rate of 15%. Chemotherapy and targeted therapies have significantly improved patients' prognosis. Nevertheless, after a successful initial response, some patients relapse when cancer cells become resistant to drug treatments, representing an important clinical limitation. Therefore, investigating the mechanisms of drug resistance is of significant importance. Recently, considerable attention has been given to long non-coding RNAs (lncRNAs), a heterogeneous class of regulatory molecules that play essential roles in tumorigenesis by modulating genes and signalling pathways involved in cell growth, metastasis and drug response. In this article, we review recent research findings on the role of lncRNAs in drug resistance in NSCLC, highlighting their mechanisms of action.

Long non-coding RNA LINC01116 is overexpressed in lung adenocarcinoma and promotes tumor proliferation and metastasis

Long non-coding RNA LINC01116 is involved in the occurrence and progression of a variety of cancers. However, the specific role of LINC01116 in lung adenocarcinoma (LUAD) remains unclear. In this work, we found that LINC01116 was overexpressed in LUAD tissues and cell lines and that increased expression was significantly associated with worse prognoses in patients with LUAD. Univariate and multivariate Cox regression analyses indicated that LINC01116 was an independent risk factor for the prognosis of patients with LUAD. Downregulation of LINC01116 significantly inhibited cell proliferation and migration, promoted cell apoptosis, and prevented cell progression from G1 to S phase. In addition, downregulation of LINC01116 significantly inhibited the epithelial-mesenchymal transition, leading to an increased expression of the epithelial marker E-cadherin and decreased expression of the mesenchymal markers N-cadherin and vimentin. In summary, our results suggest that LINC01116 may act as an oncogene in LUAD and may be a valuable prognostic biomarker for patients with LUAD.

Stem signatures associated antibodies yield early diagnosis and precise prognosis predication of patients with non-small cell lung cancer

BACKGROUND

This study was designed to detect patients with early NSCLC with tentatively using the stem signatures associated autoantibodies (AAbs), and to evaluate its latent values in the early diagnosis and precise prognosis prediction.

METHODS

The serum concentrations of selective antibodies were quantitated by enzyme-linked immunosorbent assay (ELISA), and a total of 458 cases were enrolled (training set = 401; validation set = 57). TCGA databases were used to analyze the distinct expressions and prognostic values of related genes. The optimal cut-off values were 11.60 U/ml for P53, 4.90 U/ml for MAGEA1, 3.85 U/ml for SOX2, and 7.05U/ml for PGP9.5.

RESULTS

We found that the stem signatures associated antibodies of MAGEA1, PGP9.5, SOX2, and TP53 exhibited high expressions in NSCLC, negatively correlating with the overall survival (OS) (P < 0.05). In the test groups, the diagnosis sensitivity of P53, PGP9.5, SOX2, and MAGEA1 reached to 21.5%, 39.0%, 50.3%, and 35.0%, respectively, and the specificity reached to 98.7%, 99.4%, 92.2%, and 97.4%. The four candidates' panel gave a sensitivity of 71.8% with a specificity of 89%. In the validation group, the detection of the four antibodies in early diagnosis of NSCLC also exhibited high specificity and sensitivity, further consolidating their potential application.

CONCLUSIONS

The detection regarding stem signatures associated antibodies could be used as effective tools in early NSCLC diagnosis, but not for localized screening of cancers, and their abnormal expression was in accordance with poorer survival.

Non-Coding RNAs in Lung Tumor Initiation and Progression

Lung cancer is one of the deadliest forms of cancer affecting society today. Non-coding RNAs, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), through the transcriptional, post-transcriptional, and epigenetic changes they impose, have been found to be dysregulated to affect lung cancer tumorigenesis and metastasis. This review will briefly summarize hallmarks involved in lung cancer initiation and progression. For initiation, these hallmarks include tumor initiating cells, immortalization, activation of oncogenes and inactivation of tumor suppressors. Hallmarks involved in lung cancer progression include metastasis and drug tolerance and resistance. The targeting of these hallmarks with non-coding RNAs can affect vital metabolic and cell signaling pathways, which as a result can potentially have a role in cancerous and pathological processes. By further understanding non-coding RNAs, researchers can work towards diagnoses and treatments to improve early detection and clinical response.