Prognostic Value and Immune Landscapes of Four Types of RNA Modification Writer-Related LncRNAs Signature in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the predominant pathological subtype of non-small cell lung cancer (NSCLC). The four primary forms of RNA adenosine modifications, N6-methyladenosine (m6A), N1-methyladenosine (m1A), alternative polyadenylation (APA) and adenosine-to-inosine (A-to-I) RNA editing, play a critical role in tumor progression. However, the clinical significance of RNA modification writer-related long non-coding RNAs (lncRNAs) in LUAD remains unclear. Methods: The Cancer Genome Atlas (TCGA) database was used to obtain transcriptomic and clinicopathological data. Univariate Cox regression analysis, consensus cluster analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression were used to establish the molecular subtypes and prognostic signatures of LUAD based on the expression levels of lncRNAs. ESTIMATE, CIBERSORT, ssGSEA, and TIDE algorithms were used to investigate immune cell infiltration and immunotherapy. In addition, IC50 of chemotherapeutic agents were calculated for different risk subgroups using the "pRRophetic" R package. Finally, the expression of prognosis-associated lncRNAs in lung cancer tissues was verified using qPCR. Results: A prognostic risk signature containing seven lncRNAs associated with four types of RNA modification writers was established. The high-risk group had a poorer prognosis and higher clinicopathological grade. Most immune checkpoint genes and immune cell infiltration differed significantly between the two risk groups. The high-risk group had a higher tumor mutation burden (TMB), lower TIDE score, and was more sensitive to immunotherapy. Conclusion: We developed an RNA modification writer-related seven-lncRNA signature prognostic model that was associated with prognosis, tumor microenvironment, and response to immunotherapy in LUAD patients. Among them, LINC01352, AC024075.1, AC005070.3, AL133445.2, AC005856.1, and LINC00968 were downregulated in LUAD, whereas AC092168.2 was upregulated. This model may be a valuable tool for personalized LUAD therapies.

Qian Y ，Zhang Q ，Ren Y ，Cao L ，Zheng S ，Li B ，Wu X ，Meng Z ，Xu K ... -  《Journal of Cancer》

Molecular typing and prognostic model of lung adenocarcinoma based on cuprotosis-related lncRNAs.

Previous research has shown the heterogeneity of lung adenocarcinoma (LUAD) accounts for the different effects and prognoses of the same treatment. Cuprotosis is a newly discovered form of programmed cell death involved in the development of tumors. Therefore, it is important to study the long non-coding RNAs (lncRNAs) that regulate cuprotosis to identify molecular subtypes and predict survival of LUAD. The expression profile, clinical, and mutation data of LUAD were downloaded from The Cancer Genome Atlas (TCGA), and the "ConsensusClusterPlus" package was used to cluster LUADs based on cuprotosis-related lncRNAs (CR-lncRNAs). The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were used to construct a prognostic model. CIBERSORT and single-sample gene set enrichment analysis (ssGSEA) were used for assessing immune cells infiltration and immune function. The tumor microenvironment (TME) score was calculated by ESTIMATE, and the tumor mutational burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) were used to evaluate the efficacy of immunotherapy. Firstly, 501 CR-lncRNAs were identified based on the co-expression relationship of 19 cuprotosis genes. And univariate Cox further obtained 34 prognosis-related CR-lncRNAs. The unsupervised consensus clustering divided LUAD samples into cluster A and cluster B, and showed cluster A had better prognosis, more immune cells infiltration, stronger immune function, and a higher TME score. Subsequently, we used Lasso Cox regression to construct a prognostic model, and univariate and multivariate Cox analyses showed the risk score could be an independent prognostic indicator. Immune cells infiltration, immune function, and TME score were increased markedly in the low-risk group, while TMB and TIDE suggested the efficacy of immunotherapy might be increased in high-risk group. Our research identified two new molecular subtypes and constructed a novel prognostic model of LUAD which could provide new direction for its diagnosis, treatment, and prognosis.

Zheng M ，Zhou H ，Xie J ，Zhang H ，Shen X ，Zhu D ... -  《-》

Relationships of N6-Methyladenosine-Related Long Non-Coding RNAs With Tumor Immune Microenvironment and Clinical Prognosis in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and is associated with very high mortality. Emerging studies have shown that N6-methyladenosine (m6A)-related long non-coding (lnc) RNAs play crucial roles in tumor prognosis and the tumor immune microenvironment (TME). We aimed to explore the expression patterns of different m6A-related lncRNAs concerning patient prognosis and construct an m6A-related lncRNA prognostic model for LUAD. Methods: The prognostic value of m6A-related lncRNAs was investigated in LUAD samples from The Cancer Genome Atlas (TCGA). Potential prognostic m6A-related lncRNAs were selected by Pearson's correlation and univariate Cox regression analysis. Patients were divided into clusters using principal component analysis and the m6A-related lncRNA prognostic signature was calculated using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Based on 91 prognostic m6A-related lncRNAs, we identified two m6A-related-lncRNA pattern clusters with different overall survival (OS) and different TMEs. We subsequently verified our findings multidimensionally by constructing a 13 m6A-related lncRNA prognostic signature (m6A-LPS) to calculate the risk score, which was robust in different subgroups. The receiver operating characteristic (ROC) curves and concordance index demonstrated that m6A-LPS harbored a promising ability to predict OS in TCGA data set and independent GSE11969 cohort. The risk score was also related to OS, TME, and clinical stage, and the risk score calculated by our model was also identified as independent prognostic predictive factors for LUAD patients after adjustment for age, smoking, gender, and stage. Enrichment analysis indicated that malignancy and drug resistance-associated pathways were more common in cluster2 (LUAD-unfavorable m6A-LPS). Furthermore, the results indicated that the signaling pathway enriched by the target gene of 13 m6A-related lncRNAs may be associated with metastasis and progression of cancer according to current studies. Conclusion: The current results indicated that different m6A-related-lncRNA patterns could affect OS and TME in patients with LUAD, and the prognostic signature based on 13 m6A-related lncRNAs may help to predict the prognosis in LUAD patients.

Zhao J ，Lin X ，Zhuang J ，He F ... -  《Frontiers in Genetics》

Identification of immune activation-related gene signature for predicting prognosis and immunotherapy efficacy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is a major subtype of non-small cell lung cancer (NSCLC) with a highly heterogeneous tumor microenvironment. Immune checkpoint inhibitors (ICIs) are more effective in tumors with a pre-activated immune status. However, the potential of the immune activation-associated gene (IAG) signature for prognosis prediction and immunotherapy response assessment in LUAD has not been established. Therefore, it is critical to explore such gene signatures. RNA sequencing profiles and corresponding clinical parameters of LUAD were extracted from the TCGA and GEO databases. Unsupervised consistency clustering analysis based on immune activation-related genes was performed on the enrolled samples. Subsequently, prognostic models based on genes associated with prognosis were built using the last absolute shrinkage and selection operator (LASSO) method and univariate Cox regression. The expression levels of four immune activation related gene index (IARGI) related genes were validated in 12 pairs of LUAD tumor and normal tissue samples using qPCR. Using the ESTIMATE, TIMER, and ssGSEA algorithms, immune cell infiltration analysis was carried out for different groups, and the tumor immune dysfunction and rejection (TIDE) score was used to evaluate the effectiveness of immunotherapy. Based on the expression patterns of IAGs, the TCGA LUAD cohort was classified into two clusters, with those in the IAG-high pattern demonstrating significantly better survival outcomes and immune cell infiltration compared to those in the IAG-low pattern. Then, we developed an IARGI model that effectively stratified patients into different risk groups, revealing differences in prognosis, mutation profiles, and immune cell infiltration within the tumor microenvironment between the high and low-risk groups. Notably, significant disparities in TIDE score between the two groups suggest that the low-risk group may exhibit better responses to ICIs therapy. The IARGI risk model was validated across multiple datasets and demonstrated exceptional performance in predicting overall survival in LUAD, and an IARGI-integrated nomogram was established as a quantitative tool for clinical practice. The IARGI can serve as valuable biomarkers for evaluating the tumor microenvironment and predicting the prognosis of LUAD patients. Furthermore, these genes probably provide valuable guidance for establishing effective immunotherapy regimens for LUAD patients.

Zeng W ，Wang J ，Yang J ，Chen Z ，Cui Y ，Li Q ，Luo G ，Ding H ，Ju S ，Li B ，Chen J ，Xie Y ，Tong X ，Liu M ，Zhao J ... -  《Frontiers in Immunology》

Identification and validation of tryptophan metabolism-related lncRNAs in lung adenocarcinoma prognosis and immune response.

Tryptophan (Trp) is an essential amino acid. Increasing evidence suggests that tryptophan metabolism plays a complex role in immune escape from Lung adenocarcinoma (LUAD). However, the role of long non-coding RNAs (lncRNAs) in tryptophan metabolism remains to be investigated. This study uses The Cancer Genome Atlas (TCGA)-LUAD dataset as the training cohort, and several datasets from the Gene Expression Omnibus (GEO) database are merged into the validation cohort. Genes related to tryptophan metabolism were identified from the Molecular Signatures Database (MSigDB) database and further screened for lncRNAs with Trp-related expression. Subsequently, a prognostic signature of lncRNAs related to tryptophan metabolism was constructed using Cox regression analysis, (Least absolute shrinkage and selection operator regression) and LASSO analysis. The predictive performance of this risk score was validated by Kaplan-Meier (KM) survival analysis, (receiver operating characteristic) ROC curves, and nomograms. We also explored the differences in immune cell infiltration, immune cell function, tumor mutational load (TMB), tumor immune dysfunction and exclusion (TIDE), and anticancer drug sensitivity between high- and low-risk groups. Finally, we used real-time fluorescence quantitative PCR, CCK-8, colony formation, wound healing, transwell, flow cytometry, and nude mouse xenotransplantation models to elucidate the role of ZNF8-ERVK3-1 in LUAD. We constructed 16 tryptophan metabolism-associated lncRNA prognostic models in LUAD patients. The risk score could be used as an independent prognostic indicator for the prognosis of LUAD patients. Kaplan-Meier survival analysis, ROC curves, and risk maps validated the prognostic value of the risk score. The high-risk and low-risk groups showed significant differences in phenotypes, such as the percentage of immune cell infiltration, immune cell function, gene mutation frequency, and anticancer drug sensitivity. In addition, patients with high-risk scores had higher TMB and TIDE scores compared to patients with low-risk scores. Finally, we found that ZNF8-ERVK3-1 was highly expressed in LUAD tissues and cell lines. A series of in vitro experiments showed that knockdown of ZNF8-ERVK3-1 inhibited cell proliferation, migration, and invasion, leading to cell cycle arrest in the G0/G1 phase and increased apoptosis. In vivo experiments with xenografts have shown that knocking down ZNF8-ERVK3-1 can significantly inhibit tumor size and tumor proliferation. We constructed a new prognostic model for tryptophan metabolism-related lncRNA. The risk score was closely associated with common clinical features such as immune cell infiltration, immune-related function, TMB, and anticancer drug sensitivity. Knockdown of ZNF8-ERVK3-1 inhibited LUAD cell proliferation, migration, invasion, and G0/G1 phase blockade and promoted apoptosis.

Gao M ，Wang M ，Chen Y ，Wu J ，Zhou S ，He W ，Shu Y ，Wang X ... -  《-》