Silencing LINC01116 suppresses the development of lung adenocarcinoma via the AKT signaling pathway

LncRNA RNF144A-AS1 gene polymorphisms and their influence on lung cancer patients in the Chinese Han population

Lung cancer is primarily classified as NSCLC, which is distinguished by a wide range of genetic variations. This study focused on RNF144A-AS1, a relatively unexplored lncRNA, to explore the impact of its genetic polymorphisms on the susceptibility to NSCLC. We detected RNF144A-AS1 expression and its correlation with prognosis and clinical pathological features using bioinformatics analysis. The association between RNF144A-AS1 polymorphism and NSCLC susceptibility was evaluated using case-control methods. This investigation featured a cohort of 700 NSCLC individuals and 700 healthy controls. The genotype of genetic variation was detected by PCR-RFLP and iMLDR, followed by subsequent calculation of OR and 95 % CI. Our data show that RNF144A-AS1 exhibits high expression levels in LUAD tissues and its expression is closely linked to LUAD progression and prognosis. Carrier of RNF144A-AS1 rs3806609 TT genotype increased NSCLC susceptibility compared to carrier of rs3806609 CC genotype (OR = 2.21, 95%CI = 1.57-3.13). Our study identifies RNF144A-AS1 genetic variants as potential susceptibility markers in NSCLC. RNF144A-AS1 promotes cell proliferation and migration in LUAD through the IFN-γ/JAK2/STAT1 signalling pathway. Collectively, these findings pave the way for developing targeted therapies and diagnostic tools based on RNF144A-AS1 and its variants.

The regulatory role and therapeutic potential of long non-coding RNA in non-small cell lung cancer

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) being the predominant subtype. Recent advances in transcriptome sequencing have highlighted the critical role of long non-coding RNAs (lncRNAs) in NSCLC, with lncRNAs influencing gene expression through epigenetic, transcriptional, and post-transcriptional mechanisms. Despite the growing understanding of lncRNAs, challenges such as delayed diagnosis and drug resistance continue to complicate NSCLC management. This review explores novel findings in the role of lncRNAs (e.g., MALAT1, HOTAIR, and GAS5) in NSCLC, with a particular focus on their encoded small peptides and N6-methyladenosine (m6A) modifications. We further discuss how the interplay between lncRNAs, their encoded peptides, and m6A modifications can provide new strategies for improving NSCLC diagnosis, treatment, and overcoming drug resistance. This review also highlights emerging research avenues that could lead to innovative clinical interventions in NSCLC.

High linc01116 expression may contribute to a poor prognosis in various cancers based on systematic reviews and meta-analyses

BACKGROUND

Long non-coding RNA 01116 (linc01116) has been shown to be dysregulated in many tumors, and is closely related to the prognosis. This meta-analysis aimed to examine the correlation between linc01116 expression and cancer prognosis.

METHODS

Six electronic databases were searched, and eligible studies were screened based on the inclusion and exclusion criteria. Data including hazard ratios (HRs) and 95% confidence intervals (CIs), TNM stage, distant metastasis (DM) status, lymph node metastasis (LNM) status, and tumor size were extracted from the included studies. HRs and odds ratios (ORs) with their corresponding 95% CIs were separately pooled to assess the relationship between linc01116 expression and cancer prognosis. Sensitivity analysis and Begg's test were performed to assess publication or other biases.

RESULTS

A total of 12 studies involving 809 patients were included in this meta-analysis. Analysis of pooled HRs with 95% CIs showed that high linc01116 expression was significantly correlated with poor overall survival (OS) (HR = 2.096; 95% CI: 1.555-2.638), progression-free survival (PFS) (HR, 1.9314; 95% CI: 1.020-3.657), disease-free survival (DFS) (HR = 2.067; 95% CI: 1.0889-3.9238), an advanced TNM stage (OR, 1.803; 95% CI: 1.270-2.562), and a poor histological grade (OR, 1.968; 95% CI: 1.288-3.007). However, no significant correlation was observed between linc01116 expression and LNM (OR, 1.198; 95% CI: 0.831-1.728), DM (OR, 1.114; 95% CI: 0.757-1.638), tumor size (OR, 1.336; 95% CI: 0.989-1.804), depth of invasion (OR, 1.375; 95% CI: 0.756-2.501), age (OR, 0.976; 95% CI: 0.742-1.283), or sex (OR, 0.810; 95% CI: 0.599-1.094). Sensitivity analysis indicated that the overall results of OS analysis were reliable and robust. In addition, Begg's test showed that none of the included studies had significant publication bias.

CONCLUSION

linc01116 is upregulated in most cancers, and this upregulation is associated with a poor prognosis. Therefore, linc01116 serves as a promising therapeutic target and prognostic biomarker for cancer.

Biological functions and molecular mechanisms of LINC01116 in cancer

LINC01116, a long non-coding RNA (lncRNA), serves as an important regulator in the progression of cancer cells and has attracted increased attention in biological fields. It is overexpressed in various cancer cells and is significantly correlated with cancer development and poor prognosis in cancer patients. Moreover, LINC01116 regulates the gene expression of various cancers through intricate pathways, such as sponging the microRNAs or other non-genic manners. These signaling pathways greatly affect the cancer's biological functions, including cell growth, migration, invasion, and chemoresistance. Hence, LINC01116 may serve as a prognostic biomarker and therapeutic target for human cancer. This paper summarizes the current evidence regarding the biological functions and molecular mechanisms of LINC01116 in the progression of cancer, providing theoretical references for LINC01116-related cancer treatment in the future.

Oxidative stress-induced gene expression changes in prostate epithelial cells in vitro reveal a robust signature of normal prostatic senescence and aging

Oxidative stress has long been postulated to play an essential role in aging mechanisms, and numerous forms of molecular damage associated with oxidative stress have been well documented. However, the extent to which changes in gene expression in direct response to oxidative stress are related to actual cellular aging, senescence, and age-related functional decline remains unclear. Here, we ask whether H2O2-induced oxidative stress and resulting gene expression alterations in prostate epithelial cells in vitro reveal gene regulatory changes typically observed in naturally aging prostate tissue and age-related prostate disease. While a broad range of significant changes observed in the expression of non-coding transcripts implicated in senescence-related responses, we also note an overrepresentation of gene-splicing events among differentially expressed protein-coding genes induced by H2O2. Additionally, the collective expression of these H2O2-induced DEGs is linked to age-related pathological dysfunction, with their protein products exhibiting a dense network of protein-protein interactions. In contrast, co-expression analysis of available gene expression data reveals a naturally occurring highly coordinated expression of H2O2-induced DEGs in normally aging prostate tissue. Furthermore, we find that oxidative stress-induced DEGs statistically overrepresent well-known senescence-related signatures. Our results show that oxidative stress-induced gene expression in prostate epithelial cells in vitro reveals gene regulatory changes typically observed in naturally aging prostate tissue and age-related prostate disease.

LINC01116-dependent upregulation of RNA polymerase I transcription drives oncogenic phenotypes in lung adenocarcinoma

BACKGROUND

Hyperactive RNA Polymerase I (Pol I) transcription is canonical in cancer, associated with malignant proliferation, poor prognosis, epithelial-mesenchymal transition, and chemotherapy resistance. Despite its significance, the molecular mechanisms underlying Pol I hyperactivity remain unclear. This study aims to elucidate the role of long noncoding RNAs (lncRNAs) in regulating Pol I transcription in lung adenocarcinoma (LUAD).

METHODS

Bioinformatics analyses were applied to identify lncRNAs interacting with Pol I transcriptional machinery. Fluorescence in situ hybridization was employed to examine the nucleolar localization of candidate lncRNA in LUAD cells. RNA immunoprecipitation assay validated the interaction between candidate lncRNA and Pol I components. Chromatin isolation by RNA purification and Chromatin Immunoprecipitation (ChIP) were utilized to confirm the interactions of candidate lncRNA with Pol I transcriptional machinery and the rDNA core promoter. Functional analyses, including lncRNA knock-in and knockdown, inhibition of Pol I transcription, quantitative PCR, cell proliferation, clonogenicity, apoptosis, cell cycle, wound-healing, and invasion assays, were performed to determine the effect of candidate lncRNA on Pol I transcription and associated malignant phenotypes in LUAD cells. ChIP assays and luminometry were used to investigate the transcriptional regulation of the candidate lncRNA.

RESULTS

We demonstrate that oncogenic LINC01116 scaffolds essential Pol I transcription factors TAF1A and TAF1D, to the ribosomal DNA promoter, and upregulate Pol I transcription. Crucially, LINC01116-driven Pol I transcription activation is essential for its oncogenic activities. Inhibition of Pol I transcription abrogated LINC01116-induced oncogenic phenotypes, including increased proliferation, cell cycle progression, clonogenicity, reduced apoptosis, increased migration and invasion, and drug sensitivity. Conversely, LINC01116 knockdown reversed these effects. Additionally, we show that LINC01116 upregulation in LUAD is driven by the oncogene c-Myc, a known Pol I transcription activator, indicating a functional regulatory feedback loop within the c-Myc-LINC01116-Pol I transcription axis.

CONCLUSION

Collectively, our findings reveal, for the first time, that LINC01116 enhances Pol I transcription by scaffolding essential transcription factors to the ribosomal DNA promoter, thereby driving oncogenic activities in LUAD. We propose the c-Myc-LINC01116-Pol I axis as a critical oncogenic pathway and a potential therapeutic target for modulating Pol I transcription in LUAD.

A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma

Background

Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD).

Methods

We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature.

Results

A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group.

Conclusion

Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

Construction of RNA Methylation Modification-immune-related lncRNA Molecular Subtypes and Prognostic Scoring System in Lung Adenocarcinoma

BACKGROUND

RNA methylation modification is not only intimately interrelated with cancer development and progression but also actively influences immune cell infiltration in the tumor microenvironment (TME). RNA methylation modification genes influence the therapeutic progression of lung adenocarcinoma (LUAD), and mining RNA methylation modification prognosis-related markers in LUAD is crucial for its precise prognosis.

METHODS

RNA-Seq data and Gene sets were collected from online databases or published literature. Genomic variation analysis was conducted by the Maftools package. RNA methylation-immune-related lncRNAs were obtained by Pearson correlation analysis. Then, Consistent clustering analysis was performed to obtain RNA methylation modification- immune molecular subtypes (RMM-I Molecular subtypes) in LUAD based on selected lncRNAs. COX and random survival forest analysis were carried out to construct the RMM-I Score. The receiver operating characteristic (ROC) curve and Kaplan Meier survival analysis were used to assess survival differences. Tumor immune microenvironment was assessed through related gene signatures and CIBERSORT algorithm. In addition, drug sensitivity analysis was executed by the pRRophetic package.

RESULTS

Four RNA methylation modified-immune molecular subtypes (RMM-I1, RMM- I2, RMM-I3, RMM-I4) were presented in LUAD. Patients in RMM-I4 exhibited excellent survival advantages and immune activity. HAVCR2, CD274, and CTLA-4 expression were activated in RMM-I4, which might be heat tumors and a potential beneficial group for immunotherapy. OGFRP1, LINC01116, DLGAP1-AS2, CRNDE, LINC01137, MIR210HG, and CYP1B1-AS1 comprised the RMM-I Score. The RMM-I Score exhibited excellent accuracy in the prognostic assessment of LUAD, as patients with a low RMM- I Score exhibited remarkable survival advantage. Patients with a low RMM-I score might be more sensitive to treatment with Docetaxel, Vinorelbine, Paclitaxel, Cisplatin, and immunotherapy.

CONCLUSION

The RMM-I molecular subtype constituted the novel molecular characteristic subtype of LUAD, which complemented the existing pathological typing. More refined and accurate molecular subtypes provide help to reveal the mechanism of LUAD development. In addition, the RMM-I score offers a reliable tool for accurate prognosis of LUAD.

Hypoxia-induced factor-1α promotes radioresistance of esophageal cancer cells by transcriptionally activating LINC01116 and suppressing miR-3612 under hypoxia

Esophageal cancer (EC) is a challenging tumor to treat with radiotherapy, often exhibiting resistance to this treatment modality. To explore the factors influencing radioresistance, we focused on the role of hypoxia-induced factor-1α (HIF-1α), and its interaction with the long noncoding RNA long intergenic nonprotein coding RNA 1116 (LINC01116). We analyzed the LINC01116 expression in EC and EC cell lines/human normal esophageal epithelial cell line (Het-1A). LINC01116 was silenced/overexpressed in EC109/KYSE30 cells under hypoxia, followed by radioresistance assessment. We measured HIF-1α levels in hypoxic EC cells and further validated the binding of HIF-1α with LINC01116, analyzing their interaction in EC cells. We then performed experiments in EC109 cells by transfection them with sh-HIF-1α/oe-LINC01116 to verify the effects. Additonally, we analyzed the localization of LINC01116 and its binding with miR-3612, followed by a combined experiment performed to validate the results. Our findings indicated that LINC01116 was highly expressed in EC and further elevated in hypoxic EC cells. LINC01116 was expressed at a high level in EC, which was further elevated in EC cells under hypoxic conditions. Knockdown of LINC01116 triggered EC cell apoptosis, thus suppressing radioresistance. Further investigation revealed that HIF-1α transcriptionally activated LINC01116 expression under hypoxia, and silencing HIF-1α lowered EC cell radioresistance by downregulating LINC01116. Under hypoxic conditions, LINC01116 could function as a sponge for miR-3612 and inhibit its expression. This interaction between LINC01116 and miR-3612 played a crucial role in mediating radioresistance in EC cells. Briefly, under hypoxic conditions, HIF-1α facilitates radioresistance of EC cells by transcriptionally activating LINC01116 expression and downregulating miR-3612.

Linc01116 Silencing Inhibits the Proliferation and Invasion, Promotes Apoptosis of Chordoma Cells via Regulating the Expression of Mir-9-5p/PKG1

BACKGROUND

Long intergenic non-protein coding RNA 1116 (LINC01116) plays a carcinogenic role in a variety of cancers. The study aims to investigate the roles of LINC01116 and hsa-miR-9-5p (miR-9-5p) and fathom their interaction in chordoma.

METHODS

The predicted binding sites between miR-9-5p with LINC01116 and phosphoglycerate kinase 1 (PGK1) by starBase were confirmed through dual-luciferase reporter assay. The behaviors of chordoma cells undergoing transfection with siLINC01116 or miR-9-5p inhibitor were determined by Cell Counting Kit-8 (CCK-8), colony formation, Transwell, and flow cytometry assays. The glucose consumption, lactate production, and adenosine triphosphate (ATP) production of chordoma cells were examined with specific kits. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were performed to determine relevant gene expressions in chordoma cells.

RESULTS

Silencing of LINC01116 facilitated the apoptosis and expressions of Bcl-2- associated X (Bax), cleaved caspase-3 (C caspase-3) and miR-9-5p while repressing the cell cycle, viability, proliferation, invasion, glucose consumption, lactate production, ATP production, and expressions of PGK1 and Bcl-2. Meanwhile, LINC01116 sponged miR-9-5p, which could target PGK1. Moreover, the miR-9-5p inhibitor acted contrarily and reversed the role of siLINC01116 in chordoma cells. Besides, LINC01116 downregulation facilitated apoptosis and attenuated the proliferation and invasion of chordoma cells as well as PGK1 expression by upregulating miR-9-5p expression.

CONCLUSION

LINC01116/miR-9-5p plays a regulatory role in the progression of chordoma cells and is a potential biomarker for chordoma.

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.

A novel senescence-related lncRNA signature that predicts prognosis and the tumor microenvironment in patients with lung adenocarcinoma

Background: Cellular senescence has recently been considered a new cancer hallmark. However, the factors regulating cellular senescence have not been well characterized. The aim of this study is to identify long non-coding RNAs (lncRNAs) associated with senescence and prognosis in patients with lung adenocarcinoma (LUAD). Methods: Using RNA sequence data from the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) and senescence genes from the CellAge database, a subset of senescence-related lncRNAs was first identified. Then, using univariate and multivariate Cox regression analyses, a senescence lncRNA signature (LUADSenLncSig) associated with LUAD prognosis was developed. Based on the median LUADSenLncSig risk score, LUAD patients were divided into high-risk and low-risk groups. Kaplan-Meier analysis was used to compare the overall survival (OS) in the high- and low-risk score subgroups. Differences in Gene Set Enrichment Analysis (GSEA), immune infiltration, tumor mutation burden (TMB), tumor immune dysfunction and exclusion (TIDE) module score, chemotherapy, and targeted therapy selection were also compared between the high-risk and low-risk groups. Results: A prognostic risk model was obtained consisting of the following nine senescence-related lncRNAs: LINC01116, AC005838.2, SH3PXD2A-AS1, VIMS-AS1, SH3BP5-AS1, AC092279.1, AC026355.1, AC027020.2, and LINC00996. The LUADSenLncSig high-risk group was associated with poor OS (hazard ratio = 1.17, 95% confidence interval = 1.102-1.242; p < 0.001). The accuracy of the model was further supported based on receiver operating characteristic (ROC), principal component analysis (PCA), and internal validation cohorts. In addition, a nomogram was developed consisting of LUADSenLncSig for LUAD prognosis, which is consistent with the actual probability of OS. Furthermore, immune infiltration analysis showed the low-risk group had a stronger anti-tumor immune response in the tumor microenvironment. Notably, the levels of immune checkpoint genes such as CTLA-4, PDCD-1, and CD274, and the TIDE scores were significantly higher in the low-risk subgroups than in high-risk subgroups (p < 0.001). This finding indicates the LUADSenLncSig can potentially predict immunotherapy efficacy. Conclusion: In this study, a lncRNA signature, LUADSenLncSig, that has dual functions of senescence phenotype identification and prognostic prediction as well as the potential to predict the LUAD response to immunotherapy was developed.

Identification of an autophagy-related 12-lncRNA signature and evaluation of NFYC-AS1 as a pro-cancer factor in lung adenocarcinoma

Objective: To develop an autophagy-related lncRNA-based risk signature and corresponding nomogram to predict overall survival (OS) for LUAD patients and investigate the possible meaning of screened factors.

Methods: Differentially expressed lncRNAs and autophagy genes were screened between normal and LUAD tumor samples from the TCGA LUAD dataset. Univariate and multivariate Cox regression analyses were performed to construct the lncRNA-based risk signature and nomogram incorporating clinical information. Then, the accuracy and sensitivity were confirmed by the AUC of ROC curves in both training and validation cohorts. qPCR, immunoblot, shRNA, and ectopic expression were used to verify the positive regulation of NFYC-AS1 on BIRC6. CCK-8, immunofluorescence, and flow cytometry were used to confirm the influence of NFYC-AS1 on cell proliferation, autophagy, and apoptosis via BIRC6.

Results: A 12-lncRNA risk signature and a nomogram combining related clinical information were constructed. Furthermore, the abnormal increase of NFYC-AS1 may promote LUAD progression through the autophagy-related gene BIRC6.

Conclusion: 12-lncRNA signature may function as a predictive marker for LUAD patients, and NFYC-AS1 along with BIRC6 may function as carcinogenic factors in a combinatorial manner.

Construction of an algorithm based on oncosis-related LncRNAs comprising the molecular subtypes and a risk assessment model in lung adenocarcinoma

Background

As an important non‐apoptotic cell death method, oncosis has been reported to be closely associated with tumors in recent years. However, few research reported the relationship between oncosis and lung cancer.

Methods

In this study, we established an oncosis‐based algorithm comprised of cluster grouping and a risk assessment model to predict the survival outcomes and related tumor immunity of patients with lung adenocarcinomas (LUAD). We selected 11 oncosis‐related lncRNAs associated with the prognosis (CARD8‐AS1, LINC00941, LINC01137, LINC01116, AC010980.2, LINC00324, AL365203.2, AL606489.1, AC004687.1, HLA‐DQB1‐AS1, and AL590226.1) to divide the LUAD patients into different clusters and different risk groups. Compared with patients in clsuter1, patients in cluster2 had a survival advantage and had a relatively more active tumor immunity. Subsequently, we constructed a risk assessment model to distinguish between patients into different risk groups, in which low‐risk patients tend to have a better prognosis. GO enrichment analysis revealed that the risk assessment model was closely related to immune activities. In addition, low‐risk patients tended to have a higher content of immune cells and stromal cells in tumor microenvironment, higher expression of PD‐1, CTLA‐4, HAVCR2, and were more sensitive to immune checkpoint inhibitors (ICIs), including PD‐1/CTLA‐4 inhibitors. The risk score had a significantly positive correlation with tumor mutation burden (TMB). The survival curve of the novel oncosis‐based algorithm suggested that low‐risk patients in cluster2 have the most obvious survival advantage.

Conclusion

The novel oncosis‐based algorithm investigated the prognosis and the related tumor immunity of patients with LUAD, which could provide theoretical support for customized individual treatment for LUAD patients.

An Immune-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer

Background

Endometrial cancer is among the most common malignant tumors threatening the health of women. Recently, immunity and long noncoding RNA (lncRNA) have been widely examined in oncology and shown to play important roles in oncology. Here, we searched for immune-related lncRNAs as prognostic biomarkers to predict the outcome of patients with endometrial cancer.

Methods

RNA sequencing data for 575 endometrial cancer samples and immune-related genes were downloaded from The Cancer Genome Atlas (TCGA) database and gene set enrichment analysis (GSEA) gene sets, respectively. Immune-related lncRNAs showing a coexpression relationship with immune-related genes were obtained, and Cox regression analysis was performed to construct the prognostic model. Survival, independent prognostic, and clinical correlation analyses were performed to evaluate the prognostic model. Immune infiltration of endometrial cancer samples was also evaluated. Functional annotation of 12 immune-related lncRNAs was performed using GSEA software. Prognostic nomogram and survival analysis for independent prognostic risk factors were performed to evaluate the prognostic model and calculate the survival time based on the prognostic model.

Results

Twelve immune-related lncRNAs (ELN-AS1, AC103563.7, PCAT19, AF131215.5, LINC01871, AC084117.1, NRAV, SCARNA9, AL049539.1, POC1B-AS1, AC108134.4, and AC019080.5) were obtained, and a prognostic model was constructed. The survival rate in the high-risk group was significantly lower than that in the low-risk group. Patient age, pathological grade, the International Federation of Gynecology and Obstetrics (FIGO) stage, and risk status were the risk factors. The 12 immune-related lncRNAs correlated with patient age, pathological grade, and FIGO stage. Principal component analysis and functional annotation showed that the high-risk and low-risk groups separated better, and the immune status of the high-risk and low-risk groups differed. Nomogram and receiver operating characteristic (ROC) curves effectively predicted the prognosis of endometrial cancer. Additionally, age, pathological grade, FIGO stage, and risk status were all related to patient survival.

Conclusion

We identified 12 immune-related lncRNAs affecting the prognosis of endometrial cancer, which may be useful as therapeutic targets and molecular biomarkers.

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.

Construction of a Novel Lung Adenocarcinoma Immune-Related lncRNA Pair Signature

Background

A growing number of studies have demonstrated that immune-related long noncoding ribonucleic acids (irlncRNAs) are potential prognostic factors for lung adenocarcinoma. Two-gene combination patterns could improve the sensitivity of prognostic models, providing us a novel signature construction concept that we applied to lung adenocarcinoma.

Methods

Gene expression and clinical data were downloaded from the Lung Adenocarcinoma project of The Cancer Genome Atlas (TCGA) database. We applied a co-expression analysis with immune genes obtained from the ImmPort database to recognize irlncRNA. The matrix of irlncRNA pairs was established by a cyclic comparison of each lncRNA pair expression level. Univariate and multivariate Cox regressions and Lasso penalized regression analysis were applied to construct the risk model. Patients with lung adenocarcinoma were divided into high- and low-risk groups, according to the Akaike Information Criterion (AIC) values of the receiver operating characteristic (ROC) curve. Then, we evaluated our signature under various clinical settings: clinical-pathological characteristics, tumor-infiltrating immune cells, checkpoint-related biomarkers, targeted therapy, and chemotherapy.

Results

Based on the 239 differently expressed irlncRNAs, we constructed an 11-irlncRNA pair signature. The area under the curve (AUC) of the ROC curve for the signature to predict the 4-year survival rate was 0.819, and the cut-off point was recognized as 1.003. Subsequent analysis showed that our signature can effectively distinguish unfavorable survival outcomes, prognostic clinic-pathological characteristics, and specify tumor infiltration status. Highly expressed immune checkpoint-related genes, as well as higher chemosensitivity, were correlated to the low-risk group.

Conclusion

We constructed a novel lung adenocarcinoma irlncRNA signature with promising prognostic value using the TCGA database, based on paired irlncRNAs and not relying on lncRNAs special expression levels.

Silencing LINC01116 suppresses the development of lung adenocarcinoma via the AKT signaling pathway

Background

A growing body of evidence has proven that long noncoding ribonucleic acids (lncRNAs) are important epigenetic regulators that play crucial parts in the pathogenesis of human cancers. Previous studies have shown that long intergenic nonprotein coding RNA 01116 (LINC01116) is a carcinogen in several carcinomas; however, its function in lung adenocarcinoma (LUAD) has not been clarified. Here, we aimed to investigate the role of LINC01116 in LUAD.

Methods

The relative expression levels of LINC01116 in LUAD cell lines and tissues were detected by quantitative reverse transcription polymerase chain reaction. A Kaplan–Meier survival analysis was performed using patient information from the Gene Expression Profiling Interactive Analysis (GEPIA) database. LUAD proliferation, invasion, migration, and apoptosis were measured by performing cell counting kit‐8, colony formation, transwell, wound healing, and flow cytometric assays. A xenograft animal experiment was performed to investigate the effect of LINC01116 in vivo. Protein kinase B (AKT) signaling pathway‐related protein expressions were tested by Western blot assay.

Results

LINC01116 expression was upregulated in LUAD cells and tissues. The loss‐of‐function experiments on LUAD cells revealed that silencing LINC01116 expression could decrease cell viability both in vitro and in vivo. Furthermore, silencing LINC01116 inhibited LUAD cell invasion and migration and induced cell apoptosis. Mechanically, silencing LINC01116 significantly decreased p‐AKT protein levels, and an AKT pathway stimulator could rescue the suppressive effects of small interfering LINC011116‐specific RNAs on LUAD development.

Conclusions

Our study demonstrated that silencing LINC01116 suppresses the development of LUAD via the AKT signaling pathway.