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 ... -  《-》

Anoikis-related subtype and prognosis analyses based on bioinformatics, and an expression verification of ANGPTL4 based on experiments of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common malignant tumors with high mortality. Anoikis resistance is an important mechanism of tumor cell proliferation and migration. Our research is devoted to exploring the role of anoikis in the diagnosis, classification, and prognosis of LUAD. We downloaded the expression profile, mutation, and clinical data of LUAD from The Cancer Genome Atlas (TCGA) database. The "ConsensusClusterPlus" package was then used for the cluster analysis, and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were used to establish the prognostic model. We verified the reliability of the model using a Gene Expression Omnibus (GEO) data set. A gene set variation analysis (GSVA) was conducted to investigate the functional enrichment differences in the different clusters and risk groups. The CIBERSORT algorithm and a single-sample gene set enrichment analysis (ssGSEA) were used to analyze immune cell infiltration. The tumor mutation burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) scores were used to evaluate the patients' sensitivity to immunotherapy. Immunohistochemical staining of tissue microarrays was used to verify the correlation between ANGPTL4 expression and the clinicopathological characteristics and prognosis of LUAD patients. First, we screened 135 differentially expressed anoikis-related genes (ARGs) and 23 prognosis-related ARGs from TCGA-LUAD data set. Next, 494 LUAD samples were allocated to cluster A and cluster B based on the 23 prognosis-related ARGs. The Kaplan-Meier (K-M) analysis showed the overall survival (OS) of cluster B was better than that of cluster A. The clinicopathological characteristics and functional enrichment analyses revealed significant differences between clusters A and B. The tumor microenvironment (TME) analysis showed that cluster B had more immune cell infiltration and a higher TME score than cluster A. Subsequently, a LASSO Cox regression model of LUAD was constructed with ten ARGs. The K-M analysis showed that the low-risk patients had longer OS than the high-risk patients. The receiver operating characteristic curve, nomogram, and GEO data set verification results showed that the model had high accuracy and reliability. The level of immune cell infiltration and TME score were higher in the low-risk group than the high-risk group. The high-risk group had stronger sensitivity to immune checkpoint block therapy and weaker sensitivity to chemotherapy drugs than the low-risk group. ANGPTL4 expression was correlated with stage, tumor differentiation, tumor size, lymph node metastasis, and OS. We discovered novel molecular subtypes and constructed a novel prognostic model of LUAD. Our findings provide important insights into subtype classification and the accurate survival prediction of LUAD. We also identified ANGPTL4 as a prognostic indicator of LUAD.

Shen X ，Xie J ，Liu S ，Cai Y ，Yuan S ，Uehara Y ，Zhu D ，Zheng M ... -  《-》

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》

A cuproptosis-related long non-coding RNA signature to predict the prognosis and immune microenvironment characterization for lung adenocarcinoma.

Cuproptosis or copper-dependent cell death is a newly identified non-apoptotic cell death pathway which plays a critical role in the development of multiple cancers. Long non-coding RNAs (lncRNAs) are increasingly recognized as crucial regulators of programmed cell death and lung adenocarcinoma (LUAD) development, and a comprehensive understanding of cuproptosis-related lncRNAs may improve prognosis prediction of LUAD. However, few studies have explored the association of cuproptosis-related lncRNAs with the prognosis of LUAD. The RNA sequencing data and corresponding clinical information of patients were extracted from The Cancer Genome Atlas (TCGA) database. Five hundred LUAD patients were randomly divided into a training (n=250) and a testing cohort (n=250). Pearson correlations were performed to identify cuproptosis-related lncRNAs, and univariate Cox regression was performed to screen prognostic lncRNAs. A cuproptosis-related lncRNAs prognostic signature (CLPS) was constructed by the least absolute shrinkage and selection operator Cox regression. Kaplan-Meier analysis, receiver operating characteristic curves, and multivariate Cox regression were performed to verify the prognostic performance of CLPS. Additionally, immune cell infiltration was estimated using the single-sample gene-set enrichment analysis. pRRophetic algorithm and Tumor Immune Dysfunction and Exclusion algorithm were used to assess the immunotherapy and chemotherapy response, respectively. CLPS was established based on 61 cuproptosis-related prognostic lncRNAs and exhibited a satisfactory performance predicting LUAD patients' survival (area under the curve at 1, 3, 5 years was 0.784, 0.749, 0.775, respectively). multivariate Cox analysis confirmed the independent prognostic effect of CLPS (hazard ratio: 1.128; 95% confidence interval: 1.071-1.189; P<0.001), and a nomogram containing it exhibited robust validity in prognostic prediction. We further demonstrated a higher CLPS-risk score was associated with lower levels of signatures including immune cell infiltration, immune activation, and immune checkpoints. The CLPS serves as an effective predictor for the prognosis and therapeutic responses of LUAD patients. Our findings provide promising novel biomarkers and therapeutic targets for LUAD.

Ma S ，Zhu J ，Wang M ，Zhu J ，Wang W ，Xiong Y ，Jiang R ，Seetharamu N ，Abrão FC ，Puthamohan VM ，Liu L ，Jiang T ... -  《-》

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 ... -  《-》