Long Non-coding RNA TMEM220-AS1 Suppressed Hepatocellular Carcinoma by Regulating the miR-484/MAGI1 Axis as a Competing Endogenous RNA

Prognostic value and potential function of a novel heme-related LncRNAs signature in gastric cancer

Heme is a coordination complex formed by the binding of iron ions and porphyrin rings. Its metabolic processes are associated with various cancers, including gastric cancer (GC). In recent years, long non-coding RNAs (LncRNAs) have been identified as key regulatory factors in GC. However, the role of LncRNAs associated with heme metabolism in GC and their relationship with prognosis have not been reported. In this study, we constructed a novel LncRNAs signature related to heme metabolism (HMlncSig) and validated its prognostic value for predicting the survival of GC patients through training, test, and entire cohorts. Kaplan-Meier analysis demonstrated that patients in the high-risk group had shorter survival times. Univariate and multivariate Cox regression analysis showed that HMlncSig was an independent prognostic indicator for GC patients, regardless of other clinical pathological features. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis and gene set variation analysis pathways showed that the activation of these markers may be involved in tumor progression, influencing the survival of GC patients. The nomogram, based on HMlncSig score and clinical features, demonstrated the strong predictive ability of this signature. Additionally, significant differences were observed between the high-risk and low-risk groups in terms of immune cell subtypes, expression of immune checkpoint genes, and response to chemotherapy and immunotherapy. Through clinical validation, we found that the risk score and heme levels of GC patients were both significantly elevated and correlated with the degree of malignancy. Furthermore, we found that AP000692.1, a key gene in this signature, promoted the proliferation, migration, and invasion of GC cells. In conclusion, our HMlncSig model has significant predictive value for the prognosis of GC patients and can provide clinical guidance for personalized immunotherapy.

The pivotal role of EMT-related noncoding RNAs regulatory axes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) remains a major health problem worldwide, being the leading cause of cancer-related deaths, with limited treatment options, especially in its advanced stages. Tumor resistance is closely associated with the activation of the EMT phenomenon and its reversal, being modulated by different molecules, including noncoding RNAs (ncRNAs). Noncoding RNAs have the potential to function as both tumor suppressors and oncogenic molecules, controlling the malignant potential of HCC cells. Basically, these molecules circulate in the tumor microenvironment, encapsulated in exosomes. Their impact on cell biology is more significant than originally expected, which makes related research rather complex. The temporal and spatial expression patterns, precise roles and mechanisms of specific ncRNAs encapsulated in exosomes remain primarily unknown in different stages of the disease. This review aims to highlight the recent advances in ncRNAs related to EMT and classifies the described mechanism as direct and indirect, for a better summarization. Moreover, we provide an overview of current research on the role of ncRNAs in several drug resistance-related pathways, including the emergence of resistance to sorafenib, doxorubicin, cisplatin and paclitaxel therapy. Nevertheless, we comprehensively discuss the underlying regulatory mechanisms of exosomal ncRNAs in EMT-HCC via intercellular communication pathways.

Development and Validation of the Oxidative Stress Related lncRNAs for Prognosis in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell cancer (ESCC) is an aggressive disease associated with a poor prognosis. Long non-coding RNAs (lncRNAs) and oxidative stress play crucial roles in tumor progression. We aimed to identify an oxidative stress-related lncRNA signature that could predict the prognosis in ESCC. In the GSE53625 dataset, we identified 332 differentially expressed lncRNAs (DElncRNAs) between ESCC and control samples, out of which 174 were oxidative stress-related DElncRNAs. Subsequently, seven oxidative stress-related DElncRNAs (CCR5AS, LINC01749, PCDH9-AS1, TMEM220-AS1, KCNMA1-AS1, SNHG1, LINC01672) were selected based on univariate and LASSO Cox to build a prognostic risk model, and their expression was detected by RT-qPCR. The model exhibited an excellent ability for the prediction of overall survival (OS) and other clinicopathological traits using Kaplan-Meier (K-M) survival curves, receiver operating characteristic (ROC) curves, and the Wilcoxon test. Additionally, analysis of infiltrated immune cells and immune checkpoints indicated differences in immune status between the two risk groups. Finally, the in vitro experiments showed that PCDH9-AS1 overexpression inhibited proliferation ability and promoted apoptosis and oxidative stress levels in ESCC cells. In conclusion, our study demonstrated that a novel oxidative stress-related DElncRNA prognostic model performed favorably in predicting ESCC patient prognosis and benefits personalized clinical applications.

ELFN1-AS1 promotes GDF15-mediated immune escape of colorectal cancer from NK cells by facilitating GCN5 and SND1 association

The ability of colorectal cancer (CRC) cells to escape from natural killer (NK) cell immune surveillance leads to anti-tumor treatment failure. The long non-coding RNA (lncRNA) ELFN1-AS1 is aberrantly expressed in multiple tumors suggesting a role as an oncogene in cancer development. However, whether ELFN1-AS1 regulates immune surveillance in CRC is unclear. Here, we determined that ELFN1-AS1 enhanced the ability of CRC cells to escape from NK cell surveillance in vitro and in vivo. In addition, we confirmed that ELFN1-AS1 in CRC cells attenuated the activity of NK cell by down-regulating NKG2D and GZMB via the GDF15/JNK pathway. Furthermore, mechanistic investigations demonstrated that ELFN1-AS1 enhanced the interaction between the GCN5 and SND1 protein and this influenced H3k9ac enrichment at the GDF15 promotor to stimulate GDF15 production in CRC cells. Taken together, our findings indicate that ELFN1-AS1 in CRC cells suppresses NK cell cytotoxicity and ELFN1-AS1 is a potential therapeutic target for CRC.

Downregulated liver-elevated long intergenic noncoding RNA (LINC02428) is a tumor suppressor that blocks KDM5B/IGF2BP1 positive feedback loop in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognoses worldwide. Many studies have reported that long noncoding RNAs (lncRNAs) are related to the progression and prognosis of HCC. However, the functions of downregulated liver-elevated (LE) lncRNAs in HCC remain elusive. Here we report the roles and mechanisms of downregulated LE LINC02428 in HCC. Downregulated LE lncRNAs played significant roles in HCC genesis and development. LINC02428 was upregulated in liver tissues compared with other normal tissues and showed low expression in HCC. The low expression of LINC02428 was attributed to poor HCC prognosis. Overexpressed LINC02428 suppressed the proliferation and metastasis of HCC in vitro and in vivo. LINC02428 was predominantly located in the cytoplasm and bound to insulin-like growth factor-2 mRNA-binding protein 1 (IGF2BP1) to prevent it from binding to lysine demethylase 5B (KDM5B) mRNA, which decreased the stability of KDM5B mRNA. KDM5B was found to preferentially bind to the promoter region of IGF2BP1 to upregulate its transcription. Therefore, LINC02428 interrupts the KDM5B/IGF2BP1 positive feedback loops to inhibit HCC progression. The KDM5B/IGF2BP1 positive feedback loop is involved in tumorigenesis and progression of HCC.

A Novel Cuprotosis-Related lncRNA Signature Effectively Predicts Prognosis in Glioma Patients

Cuprotosis is a novel and different cell death mechanism from the existing known ones that can be used to explore new approaches to treating cancer. Just like ferroptosis and pyroptosis, cuprotosis-related genes regulate various types of tumorigenesis, invasion, and metastasis. However, the relationship between cuprotosis-related long non-coding RNA (cuprotosis-related lncRNA) in glioma development and prognosis has not been investigated. We obtained relevant data from the Genotype-Tissue Expression (GTEx), Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA), and published articles. First, we identified 365 cuprotosis-related lncRNAs based on 10 cuprotosis-related differential genes (|R²|> 0.4, p < 0.001). Then using Lasso and Cox regression analysis methods, 12 prognostic cuprotosis-related lncRNAs were obtained and constructed the CuLncSigi risk score formula. Our next step was to divide the tumor gliomas into two groups (high risk and low risk) based on the median risk score, and we found that patients in the high-risk group had a significantly worse prognosis. We used internal and external validation methods to simultaneously analyze and validate that the risk score model has good predictive power for patients with glioma. Next, we also performed enrichment analyses such as GSEA and aaGSEA and evaluated the relationship between immune-related drugs and tumor treatment. In conclusion, we successfully constructed a formula of cuprotosis-related lncRNAs with a powerful predictive function. More importantly, our study paves the way for exploring cuprotosis mechanisms in glioma occurrence and development and helps to find new relevant biomarkers for glioma early identification and diagnosis and to investigate new therapeutic approaches.

Molecular subtypes and a prognostic model for hepatocellular carcinoma based on immune- and immunogenic cell death-related lncRNAs

Background

Accumulating evidence shows that immunogenic cell death (ICD) enhances immunotherapy effectiveness. In this study, we aimed to develop a prognostic model combining ICD, immunity, and long non-coding RNA biomarkers for predicting hepatocellular carcinoma (HCC) outcomes.

Methods

Immune- and immunogenic cell death-related lncRNAs (IICDLs) were identified from The Cancer Genome Atlas and Ensembl databases. IICDLs were extracted based on the results of differential expression and univariate Cox analyses and used to generate molecular subtypes using ConsensusClusterPlus. We created a prognostic signature based on IICDLs and a nomogram based on risk scores. Clinical characteristics, immune landscapes, immune checkpoint blocking (ICB) responses, stemness, and chemotherapy responses were also analyzed for different molecular subtypes and risk groups.

Result

A total of 81 IICDLs were identified, 20 of which were significantly associated with overall survival (OS) in patients with HCC. Cluster analysis divided patients with HCC into two distinct molecular subtypes (C1 and C2), with patients in C1 having a shorter survival time than those in C2. Four IICDLs (TMEM220-AS1, LINC02362, LINC01554, and LINC02499) were selected to develop a prognostic model that was an independent prognostic factor of HCC outcomes. C1 and the high-risk group had worse OS (hazard ratio > 1.5, p < 0.01), higher T stage (p < 0.05), higher clinical stage (p < 0.05), higher pathological grade (p < 0.05), low immune cell infiltration (CD4⁺ T cells, B cells, macrophages, neutrophils, and myeloid dendritic cells), low immune checkpoint gene expression, poor response to ICB therapy, and high stemness. Different molecular subtypes and risk groups showed significantly different responses to several chemotherapy drugs, such as doxorubicin (p < 0.001), 5-fluorouracil (p < 0.001), gemcitabine (p < 0.001), and sorafenib (p < 0.01).

Conclusion

Our study identified molecular subtypes and a prognostic signature based on IICDLs that could help predict the clinical prognosis and treatment response in patients with HCC.

Four-copy number alteration (CNA)-related lncRNA prognostic signature for liver cancer

The objective of this study was to identify CNA-related lncRNAs that can better evaluate the prognosis of patients with liver cancer. Prognostic molecular subtypes were identified, followed by tumor mutation and differential expression analyses. Genomic copy number anomalies and their association with lncRNAs were also evaluated. A risk model was built based on lncRNAs, as well as a nomogram, and the differences in the tumor immune microenvironment and drug sensitivity between the High_ and Low_risk groups were compared. Weighted gene co-expression network analysis was used to identify modules with significant enrichment in prognostic-related lncRNAs. In total, two subtypes were identified, TP53 and CTNNB1 were common high-frequency mutated genes in the two subtypes. A total of 8,372 differentially expressed (DE) mRNAs and 798 DElncRNAs were identified between cluster1 and cluster2. In addition, a four-lncRNA signature was constructed, and statistically significant differences between the Low_ and High_risk groups were found in terms of CD8 T cells, resting memory CD4 T cells, etc. Enrichment analysis showed that prognostic-related lncRNAs were involved in the cell cycle, p53 signaling pathway, non-alcoholic fatty liver disease, etc. A prognostic prediction signature, based on four-CNA-related lncRNAs, could contribute to a more accurate prognosis of patients with liver cancer.

The Pyroptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Immunotherapeutic Efficiency in Hepatocellular Carcinoma

Pyroptosis was recently demonstrated to be an inflammatory form of gasdermin-regulated programmed cell death characterized by cellular lysis and the release of several proinflammatory factors and participates in tumorigenesis. However, the effects of pyroptosis-related long noncoding RNAs (lncRNAs) on hepatocellular carcinoma (HCC) have not yet been completely elucidated. Based on the regression coefficients of ZFPM2-AS1, KDM4A-AS1, LUCAT1, NRAV, CRYZL2P-SEC16B, AL031985.3, SNHG4, AL049840.5, AC008549.1, MKLN1-AS, AC099850.3, and LINC01224, HCC patients were classified into a low- or high-risk group. The high-risk score according to pyroptosis-related lncRNA signature was significantly associated with poor overall survival even after adjusting for age and clinical stage. Receiver operating characteristic curves and principal component analysis further supported the accuracy of the model. Our study revealed that a higher pyroptosis-related lncRNA risk score was significantly associated with tumor staging, pathological grade, and tumor-node-metastasis stages. The nomogram incorporating the pyroptosis-related lncRNA risk score and clinicopathological factors demonstrated good accuracy. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. Notably, based on the risk model, we found that the risk score is closely related to the expression of immune checkpoint genes, immune subtypes of tumors, and the sensitivity of HCC to chemotherapy drugs and immunotherapy. In conclusion, our novel risk score of pyroptosis-related lncRNA can serve as a promising prognostic biomarker for HCC patients and provide help for HCC patients to guide precision drug treatment and immunotherapy.

The Biological and Molecular Function of LINC00665 in Human Cancers

Long non-coding RNAs (lncRNAs) are more than 200 nucleotides in length and are implicated in the development of human cancers, without protein-coding function. Mounting evidence indicates that cancer initiation and progression are triggered by lncRNA dysregulation. Recently, a growing number of studies have found that LINC00665, a long intergenic non-protein coding RNA, may be associated with various cancers, including gastrointestinal tumors, gynecological tumors, and respiratory neoplasms. LINC00665 was reported to be significantly dysregulated in cancers and has an important clinical association. It participates in cell proliferation, migration, invasion, and apoptosis through different biological pathways. In this review, we summarize the current findings on LINC00665, including its biological roles and molecular mechanisms in various cancers. LINC00665 may be a potential prognostic biomarker and novel therapeutic target for cancers.

miR-484: A Potential Biomarker in Health and Disease

Disorders of miR-484 expression are observed in cancer, different diseases or pathological states. There is accumulating evidence that miR-484 plays an essential role in the development as well as the regression of different diseases, and miR-484 has been reported as a key regulator of common cancer and non-cancer diseases. The miR-484 targets that have effects on inflammation, apoptosis and mitochondrial function include SMAD7, Fis1, YAP1 and BCL2L13. For cancer, identified targets include VEGFB, VEGFR2, MAP2, MMP14, HNF1A, TUSC5 and KLF12. The effects of miR-484 on these targets have been documented separately. Moreover, miR-484 is typically described as an oncosuppressor, but this claim is simplistic and one-sided. This review will combine relevant basic and clinical studies to find that miR-484 promotes tumorigenesis and metastasis in liver, prostate and lung tissues. It will provide a basis for the possible mechanisms of miR-484 in early tumor diagnosis, prognosis determination, disease assessment, and as a potential therapeutic target for tumors.

Pyroptosis-Related LncRNA Signature Predicts Prognosis and Is Associated With Immune Infiltration in Hepatocellular Carcinoma

Pyroptosis is an inflammatory form of programmed cell death that is involved in various cancers, including hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) were recently verified as crucial mediators in the regulation of pyroptosis. However, the role of pyroptosis-related lncRNAs in HCC and their associations with prognosis have not been reported. In this study, we constructed a prognostic signature based on pyroptosis-related differentially expressed lncRNAs in HCC. A co-expression network of pyroptosis-related mRNAs-lncRNAs was constructed based on HCC data from The Cancer Genome Atlas. Cox regression analyses were performed to construct a pyroptosis-related lncRNA signature (PRlncSig) in a training cohort, which was subsequently validated in a testing cohort and a combination of the two cohorts. Kaplan-Meier analyses revealed that patients in the high-risk group had poorer survival times. Receiver operating characteristic curve and principal component analyses further verified the accuracy of the PRlncSig model. Besides, the external cohort validation confirmed the robustness of PRlncSig. Furthermore, a nomogram based on the PRlncSig score and clinical characteristics was established and shown to have robust prediction ability. In addition, gene set enrichment analysis revealed that the RNA degradation, the cell cycle, the WNT signaling pathway, and numerous immune processes were significantly enriched in the high-risk group compared to the low-risk group. Moreover, the immune cell subpopulations, the expression of immune checkpoint genes, and response to chemotherapy and immunotherapy differed significantly between the high- and low-risk groups. Finally, the expression levels of the five lncRNAs in the signature were validated by quantitative real-time PCR. In summary, our PRlncSig model shows significant predictive value with respect to prognosis of HCC patients and could provide clinical guidance for individualized immunotherapy.

Knockdown of LncRNA NEAT1 inhibits myofibroblast activity in oral submucous fibrosis through miR-760/TPM1 axis

Background/purpose

Oral submucous fibrosis (OSF) is a fibrotic disease with high transformation of malignant disorders. Aberrant expression of lncRNA nuclear enriched abundant transcript 1 (NEAT1) was engaged with various fibrosis models, but its mechanism in OSF remained elusive.

Materials and methods

Fibrous buccal mucosa fibroblasts (fBMFs) were from OSF specimens. Myofibroblast activities including the alpha smooth muscle actin (α-SMA) distribution and invasion capacities were determined by Immunocytochemistry and Transwell assays. Gene and protein were identified by quantitative real time polymerase chain reaction or western blotting. Binding relationship was analyzed via Starbase and dual-luciferase reporter or RNA immunoprecipitation assays.

Results

NEAT1 and Tropomyosin-1 (TPM1) were significantly increased in OSF specimens, but miR-760 was decreased. NEAT1 knockdown repressed myofibroblast activities and reduced the fibrosis and Wnt/β-catenin pathway via miR-760/TPM1 axis. MiR-760 inhibition could reverse the regulation of NEAT1 knockdown via TPM1 in fBMFs.

Conclusion

NEAT1 knockdown inhibited myofibroblast activities and Wnt/β-catenin pathway via miR-760/TPM1 axis in fBMFs. NEAT1 could be the target for inhibiting myofibroblast activities in fBMFs for OSF treatment.