Overall Survival In Lung Adenocarcinoma Patients Research Articles

A Nomogram Integrating Ferroptosis- and Immune-Related Biomarkers for Prediction of Overall Survival in Lung Adenocarcinoma.

Ferroptosis plays a dual role in cancer, which is known to be affected to antitumor immune responses. However, the association between ferroptosis and antitumor immune responses is uncertain in lung adenocarcinoma (LUAD). In this work, 38 ferroptosis-related genes (FRGs) and 429 immune-related genes (IRGs) were identified as being differentially expressed between tumor and normal samples. Two risk score formulas consisting of seven FRGs and four IRGs, respectively, were developed by Lasso-penalized Cox regression and verified in the GSE13213 dataset. The CIBERSORT algorithm was used to estimate the relative abundance of immune cells in tumors. The correlation between FRGs and immune cells was evaluated using the TIMER database. The results indicated that the development of ferroptosis was synergistic with that of anti-tumor immunity in LUAD. The concordance index and calibration curves showed that the performance of a nomogram that combines clinical staging and risk scores is superior to that of models using a single prognostic factor. In conclusion, ferroptosis might be synergistic with anti-tumor immunity in LUAD. The combined nomogram could reliably predict the probability of overall survival of LUAD patients. These findings may be useful for future investigation of prognostic value and therapeutic potential related to ferroptosis and tumor immunity in LUAD.

Effect of TTN Mutations on Immune Microenvironment and Efficacy of Immunotherapy in Lung Adenocarcinoma Patients

Immune checkpoint inhibitors (ICIs) effectively treat lung adenocarcinoma (LUAD) with fewer side effects. However, for LUAD patients, the lack of predictive markers for ICIs makes their clinical benefits less than ideal. Despite reports suggesting that a TTN (titin) mutation plays an important role in immunotherapy of solid tumors and gastric cancer, the relationship between the TTN mutation and LUAD immunotherapy has not been determined. We collected a LUAD cohort with whole-exome sequencing (WES) and immunotherapy prognosis. The ICI cohort was used to explore the relationship between TTN mutation status and prognosis. Then, the Cancer Genome Atlas (TCGA)-LUAD and Chen-LUAD cohorts were downloaded from the cbioportal website. We also used CIBERSORT, gene-set enrichment analysis (GSEA), and single-sample GSEA (ssGSEA) to evaluate the proportion of immune cells and the degree of pathway activation in LUAD patients, respectively. DDR signaling pathways obtained from the Molecular Signatures Database (MSigDB), tumor mutation burden (TMB), and NAL were used to evaluate the immunogenicity of LUAD patients. In the ICI cohort, TTN-mutant (TTN-MT) had significantly longer overall survival (OS) than TTN-wildtype (TTN-WT) (P = 0.009). Univariate and multivariate COX models showed that TTN mutation status can independently predict immunotherapy prognosis. Notably, the results of tumor immune microenvironment (TIME) analysis showed that TTN-MT patients had inflammatory TIME, which showed enriched activated immune cells and higher immune scores. Immunogenicity analysis showed higher immunogenicity in TTN-MT patients, which indicated high levels of gene mutations in TMB, NAL, and DDR pathways. GSEA and ssGSEA results showed that TTN-MT was substantially enriched in chemokine secretion, inflammatory factor secretion, and antigen presentation. Some pathways related to immunosuppression and immune depletion were significantly downregulated. TTN-MT is associated with significantly prolonged OS in LUAD patients. Additionally, TTN-MT is related to high immunogenicity and inflammatory TIME, suggesting that TTN-MT may be a potential predictive marker for patients with LUAD to accept ICIs.

Evaluation of the Oncogene Function of GOLPH3 and Correlated Regulatory Network in Lung Adenocarcinoma.

BackgroundGolgi phosphoprotein 3 (GOLPH3) is an oncoprotein localized in the Golgi apparatus. Abnormal GOLPH3 expression is potentially related to carcinogenesis. However, the potential biological regulation network of GOLPH3 in lung adenocarcinoma (LUAD) remains to be determined.MethodsExpression of GOLPH3 was identified in LUAD via TIMER, Oncomine, Lung Cancer Explorer (LCE), Human Protein Atlas (HPA), and UALCAN database. Survival analysis was performed using the Kaplan–Meier plotter. GOLPH3 alterations were analyzed through cBioPortal. LinkedOmics was used to perform functional analysis and predict interacted targets. The protein–protein interaction network was constructed by GeneMANIA. In addition, candidate miRNAs and lncRNAs targeting GOLPH3 were generated to construct competing endogenous RNA (ceRNA) network, and survival analysis of ceRNA was performed using LnCeVar. The mRNA or protein expression of TUG1, miR-142-5p, and GOLPH3 in Beas-2B and LUAD cells was verified using qPCR or Western blotting. CCK-8 assay, wound healing assay, and transwell assay were used to detect the ability of cell proliferation, migration, and invasion.ResultsOverexpression of GOLPH3 was identified in LUAD. UALCAN analysis showed that upregulated GOLPH3 was linked to different pathological features of LUAD patients. Importantly, high GOLPH3 expression indicated a negative correlation with the first progression (FP) in LUAD patients. GOLPH3 alterations were also found. Moreover, co-expressed genes with GOLPH3 were analyzed; and they were involved in ribosome and oxidative phosphorylation pathways. Functional network analysis indicated GOLPH3 regulated T-cell receptor signaling pathway and interferon signaling pathway with kinase and transcription factor targets. Notably, TUG1/miR-142-5p/GOLPH3 affected overall survival of LUAD patients. GOLPH3 expression was decreased in the cells with overexpression of miR-142-5p and TUG1 knockdown. GOLPH3 reduction inhibited cell proliferation, migration, and invasion.ConclusionsUpregulation of GOLPH3 has a positive correlation with clinicopathological subtypes and poor FP in LUAD. GOLPH3 promoted LUAD progression. Moreover, TUG1 may act as ceRNA to regulate GOLPH3 expression by competitive binding miR-142-5p.

Screening and evaluation of the role of immune genes of brain metastasis in lung adenocarcinoma progression based on the TCGA and GEO databases.

BackgroundBrain metastasis was one of the factors leading to the poor long-term prognosis of patients with lung adenocarcinoma (LUAD).MethodsThe expression levels of immune genes in LUAD and LUAD brain metastases tissues were analyzed in GSE161116 dataset using the GEO2R, and the levels of differential immune genes in normal lung and LUAD tissues were verified. The biological functions and signaling mechanisms of the differential immune genes were explored via Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Cox regression analysis was used to screen the prognostic factors of LUAD patients, and a risk model was constructed. The role of the model was checked in the development of LUAD via receiver operating characteristic analysis, gene set enrichment analysis, and Cox regression analysis.ResultsDifferentially expressed genes (DEGs) in brain metastasis were involved in the adaptive immune response, B cell differentiation, leukocyte migration, NF-kB signaling pathway, among others. The expression levels of TNFRSF11A, MS4A2, IL11, CAMP, MS4A1, and F2RL1 were independent factors affecting the poor prognosis of LUAD patients via Cox regression analysis and Akaike information criterion. In the constructed risk model, the overall survival of LUAD patients in the high-risk group was poor. The risk model was significantly related to the gender, clinical stage, T stage, lymph node metastasis, and survival status of LUAD patients. In addition, the risk model score was an independent risk factor that affected the poor prognosis of LUAD patients. TNFRSF11A, CAMP, F2RL1, IL11, MS4A1, and MS4A2 of the risk factors had diagnostic significance in LUAD brain metastasis and LUAD. The risk model participated in cytokinetic process, cell cycle, citrate cycle TCA cycle, etc. The risk model score was correlated with the levels of B cells memory, mast cells resting, macrophages M0, mast cells activated, neutrophils, eosinophils, T cells gamma delta, and immune cell markers.ConclusionsThe risk model based on the LUAD brain metastasis immune factors TNFRSF11A, MS4A2, IL11, CAMP, MS4A1, and F2RL1 was related to the diagnosis, poor prognosis, and immune infiltrating cells of LUAD patients, and is expected to provide a reference for the development of treatment strategies for LUAD patients.

Construction and comprehensive analysis of a ceRNA network to reveal potential prognostic biomarkers for lung adenocarcinoma

BackgroundMore and more studies have proven that circular RNAs (circRNAs) play vital roles in cancer development via sponging miRNAs. However, the expression pattern of competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD) remains largely unclear. The current study explored functional roles and the regulatory mechanisms of circRNA as ceRNAs in LUAD and their potential impact on LUAD patient prognosis.MethodsIn this study, we systematically screened differential expression circRNAs (DEcircRNAs), miRNAs (DEmiRNAs) and mRNAs (DEGs) associated with LUAD. Then, DEcircRNAs, DEmiRNAs and DEGs were selected to construct a circRNA–miRNA–mRNA prognosis-related regulatory network based on interaction information from the ENCORI database. Subsequently, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed on the genes in the network to predict the potential underlying mechanisms and functions of circRNAs in LUAD. In addition, Kaplan–Meier survival analysis was performed to evaluate clinical outcomes of LUAD patients, and drug sensitivity analysis was used to screen potential biomarkers for drug treatment of patients with LUAD.ResultsAs a result, 10 circRNAs were aberrantly expressed in LUAD tissues. The ceRNA network was built, which included 3 DEcircRNAs, 6 DEmiRNAs and 157 DEGs. The DEGs in the ceRNA network of hsa_circ_0049271 enriched in biological processes of cell proliferation and the Jak-STAT signaling pathway. We also detected 7 mRNAs in the ceRNA network of hsa_circ_0049271 that were significantly associated with the overall survival of LUAD patients (P < 0.05). Importantly, four genes (PDGFB, CCND2, CTF1, IL7R) identified were strongly associated with STAT3 activation and drugs sensitivity in GDSC.ConclusionsIn summary, a ceRNA network of hsa_circ_0049271 was successfully constructed, which including one circRNA, two miRNAs, and seven mRNAs. Seven mRNAs (PDGFB, TNFRSF19, CCND2, CTF1, IL11RA, IL7R and MAOA) were remarkably associated with the prognosis of LUAD patients. Among seven mRNA species, four genes (PDGFB, CCND2, CTF1, and IL7R) could be considered as drug targets in LUAD. Our research will provide new insights into the prognosis-related ceRNA network in LUAD.

Identification of key genes in the tumor microenvironment of lung adenocarcinoma.

The tumor microenvironment plays an important role in tumor development and progression, but the role of immune and stromal cells in this environment has not been sufficiently studied. In this study, we aimed to identify key genes associated with the microenvironment of lung adenocarcinoma (LUAD). Raw data for stromal and immune cells in malignant tumors were downloaded from The Cancer Genome Atlas (TCGA). These expression data were used to identify the differentially expressed genes (DEGs) in tissue samples of LUAD with high and low immune scores. A protein-protein interaction (PPI) network based on genes with significant differential expression was constructed. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to functionally annotate putative hub genes. These genes were assessed via Kaplan Meier analysis to determine their correlation with overall survival. In total, we identified 216 DEGs which were correlated with immune and stromal scores, including 30 hub genes which were identified based on the PPI network. Further analysis suggested that the expression levels of 10 of these genes were significantly correlated with overall survival of LUAD patients. These key hub genes included CCR2, CCR5, CD53, CYBB, HCK, IRF8, LCP2, PLEK, PTPRC, and TLR7. Moreover, the expression level of CCR2 was found to have strong prognostic value for LUAD patients. Additionally, high expression of CYBB was also correlated with better survival of patients with LUAD. The results of this study open several new avenues to explore in the treatment of LUAD.

A seven-gene prognostic signature predicts overall survival of patients with lung adenocarcinoma (LUAD)

BackgroundLung adenocarcinoma (LUAD) is one of the most common types in the world with a high mortality rate. Despite advances in treatment strategies, the overall survival (OS) remains short. Our study aims to establish a reliable prognostic signature closely related to the survival of LUAD patients that can better predict prognosis and possibly help with individual monitoring of LUAD patients.MethodsRaw RNA-sequencing data were obtained from Fudan University and used as a training group. Differentially expressed genes (DEGs) for the training group were screened. The univariate, least absolute shrinkage and selection operator (LASSO), and multivariate cox regression analysis were conducted to identify the candidate prognostic genes and construct the risk score model. Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC) curve were used to evaluate the prognostic power and performance of the signature. Moreover, The Cancer Genome Atlas (TCGA-LUAD) dataset was further used to validate the predictive ability of prognostic signature.ResultsA prognostic signature consisting of seven prognostic-related genes was constructed using the training group. The 7-gene prognostic signature significantly grouped patients in high and low-risk groups in terms of overall survival in the training cohort [hazard ratio, HR = 8.94, 95% confidence interval (95% CI)] [2.041–39.2]; P = 0.0004), and in the validation cohort (HR = 2.41, 95% CI [1.779–3.276]; P < 0.0001). Cox regression analysis (univariate and multivariate) demonstrated that the seven-gene signature is an independent prognostic biomarker for predicting the survival of LUAD patients. ROC curves revealed that the 7-gene prognostic signature achieved a good performance in training and validation groups (AUC = 0.91, AUC = 0.7 respectively) in predicting OS for LUAD patients. Furthermore, the stratified analysis of the signature showed another classification to predict the prognosis.ConclusionOur study suggested a new and reliable prognostic signature that has a significant implication in predicting overall survival for LUAD patients and may help with early diagnosis and making effective clinical decisions regarding potential individual treatment.

Identification of the pyroptosis\u2011related prognostic gene signature and the associated regulation axis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) remains the most common deadly disease and has a poor prognosis. Pyroptosis could regulate tumour cell proliferation, invasion, and metastasis, thereby affecting the prognosis of cancer patients. However, the role of pyroptosis-related genes (PRGs) in LUAD remains unclear. In our study, comprehensive bioinformatics analysis was performed to construct a prognostic gene model and ceRNA network. The correlations between PRGs and tumour-immune infiltration, tumour mutation burden, and microsatellite instability were evaluated using Pearson’s correlation analysis. A total of 23 PRGs were upregulated or downregulated in LUAD. The genetic mutation variation landscape of PRG in LUAD was also summarised. Functional enrichment analysis revealed that these 33 PRGs were mainly involved in pyroptosis, the NOD-like receptor signalling pathway, and the Toll-like receptor signalling pathway. Prognosis analysis indicated a poor survival rate in LUAD patients with low expression of NLRP7, NLRP1, NLRP2, and NOD1 and high CASP6 expression. A prognostic PRG model constructed using the above five prognostic genes could predict the overall survival of LUAD patients with medium-to-high accuracy. Significant correlation was observed between prognostic PRGs and immune-cell infiltration, tumour mutation burden, and microsatellite instability. A ceRNA network was constructed to identify a lncRNA KCNQ1OT1/miR-335-5p/NLRP1/NLRP7 regulatory axis in LUAD. In conclusion, we performed a comprehensive bioinformatics analysis and identified a prognostic PRG signature containing five genes (NLRP7, NLRP1, NLRP2, NOD1, and CASP6) for LUAD patients. Our results also identified a lncRNA KCNQ1OT1/miR-335-5p/NLRP1/NLRP7 regulatory axis, which may also play an important role in the progression of LUAD. Further study needs to be conducted to verify this result.

Competing endogenous RNA network identifies mRNA biomarkers for overall survival of lung adenocarcinoma: two novel on-line precision medicine predictive tools.

BackgroundIndividual mortality risk predicted curve at the individual level can provide valuable information for directing individual treatment decision. The present study attempted to explore potential post-transcriptional biological regulatory mechanism related with overall survival of lung adenocarcinoma (LUAD) patients through competitive endogenous RNA (ceRNA) network and develop two precision medicine predictive tools for predicting the individual mortality risk curves for overall survival of LUAD patients.MethodsMultivariable Cox regression analyses were performed to explore the potential prognostic indicators, which were used to construct a prognostic model for overall survival of LUAD patients. Time-dependent receiver operating characteristic (ROC) curves were used to assess the predictive performance of prognostic model.ResultsThere were 494 LUAD patients in model cohort and 233 LUAD patients in validation cohort. Differentially expressed mRNAs, miRNAs, and lncRNAs were identified between LUAD tissues and normal tissues. A ceRNA regulatory network was constructed on previous differentially expressed mRNAs, miRNAs, and lncRNAs. Fourteen mRNA biomarkers were identified as independent risk factors by multivariate Cox regression and used to develop a prognostic model for overall survival of LUAD patients. The C-indexes of prognostic model in model group were 0.786 (95% CI [0.744–0.828]), 0.736 (95% CI [0.694–0.778]) and 0.766 (95% CI [0.724–0.808]) for one year, two year and three year overall survival respectively. Two precision medicine predicted tools were developed for predicting individual mortality risk curves for LUAD patients.ConclusionThe current study explored potential post-transcriptional biological regulatory mechanism and prognostic biomarkers for overall survival of LUAD patients. Two on-line precision medicine predictive tools were helpful to predict the individual mortality risk predicted curves for overall survival of LUAD patients. Smart Cancer Survival Predictive System could be used at https://zhangzhiqiao2.shinyapps.io/Smart_cancer_predictive_system_9_LUAD_E1002/.

LncRNA-LINC01089 inhibits lung adenocarcinoma cell proliferation and promotes apoptosis via sponging miR-543

LINC01089, a newly discovered long non-coding RNA (lncRNA), has been reported to inhibit the progression of various types of cancers. This study aimed to characterize LINC01089 in the pathogenesis of lung adenocarcinoma (LUAD). LINC01089 expression in LUAD tissues or/and cells and its association with the overall survival of LUAD patients was analyzed in The Cancer Genome Atlas (TCGA)-LUAD database, by qRT-PCR or by Kaplan-Meier’s curve. Databases of StarBase, LncBase, and DEmiRNA were used to predict and confirm the interaction between LINC01089 and potential LINC01089-targeted microRNAs (miRNAs). The expressions of these miRNAs in LUAD tissues or/and cells were determined by qRT-PCR, and dual-luciferase reporter assay was performed to validate lncRNA-miRNA interaction. The expressions of B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax) and Cleaved caspase-3 in LUAD cells were analyzed by Western blot. LINC01089 improved overall survival of LUAD patients and was low-expressed in LUAD. Upregulating LINC01089 expression reduced LUAD cell viability, inhibited colony formation, enhanced apoptosis, accompanied by downregulated Bcl-2 and miR-543 and upregulated Bax and Cleaved caspase-3. MiR-543 was determined as a target gene of LINC01089, and was high-expressed in LUAD tissues. Upregulating miR-543 expression induced the opposite effects to LINC01089 upregulation on these cellular biological behaviors and the expressions of Bcl-2, Bax and Cleaved caspase-3. Moreover, the effects of miR-543 upregulation and LINC01089 upregulation were mutually counteracted by each other. LINC01089 inhibited lung adenocarcinoma cell proliferation and promoted apoptosis via sponging miR-543.

Meiotic nuclear divisions 1 (MND1) fuels cell cycle progression by activating a KLF6/E2F1 positive feedback loop in lung adenocarcinoma.

BackgroundConsidering the increase in the proportion of lung adenocarcinoma (LUAD) cases among all lung cancers and its considerable contribution to cancer‐related deaths worldwide, we sought to identify novel oncogenes to provide potential targets and facilitate a better understanding of the malignant progression of LUAD.MethodsThe results from the screening of transcriptome and survival analyses according to the integrated Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) data were combined, and a promising risk biomarker called meiotic nuclear divisions 1 (MND1) was selectively acquired. Cell viability assays and subcutaneous xenograft models were used to validate the oncogenic role of MND1 in LUAD cell proliferation and tumor growth. A series of assays, including mass spectrometry, co‐immunoprecipitation (Co‐IP), and chromatin immunoprecipitation (ChIP), were performed to explore the underlying mechanism.ResultsMND1 up‐regulation was identified to be an independent risk factor for overall survival in LUAD patients evaluated by both tissue microarray staining and third party data analysis. In vivo and in vitro assays showed that MND1 promoted LUAD cell proliferation by regulating cell cycle. The results of the Co‐IP, ChIP and dual‐luciferase reporter assays validated that MND1 competitively bound to tumor suppressor Kruppel‐like factor 6 (KLF6), and thereby protecting E2F transcription factor 1 (E2F1) from KLF6‐induced transcriptional repression. Luciferase reporter and ChIP assays found that E2F1 activated MND1 transcription by binding to its promoter in a feedback manner.ConclusionsMND1, KLF6, and E2F1 form a positive feedback loop to regulate cell cycle and confer DDP resistance in LUAD. MND1 is crucial for malignant progression and may be a potential therapeutic target in LUAD patients.

RNF115 promotes lung adenocarcinoma through Wnt/\u03b2-catenin pathway activation by mediating APC ubiquitination

BackgroundPatients with lung adenocarcinoma (LUAD) have high mortality rate and poor prognosis. The LUAD cells display increased aerobic glycolysis, which generates energy required for their survival and proliferation. Deregulation of Wnt/β-catenin signaling pathway induces the metabolism switching and oncogenesis in tumor cells. RING finger protein 115 (RNF115) is an E3 ligase for ubiquitin-mediated degradation. Although the oncogenic functions of RNF115 have been revealed in breast tumor cells, the effect of RNF115 on lung cancer is still not clear.MethodsRNF115 expression and its correlation with the features of LUAD patients were analyzed by using public database and our own cohort. The functions of RNF115 in proliferation and energy metabolism in LUAD cells were explored by downregulating or upregulating RNF115 expression.ResultsWe demonstrated that RNF115 was overexpressed in LUAD tissues and its expression was positively correlated with the poor overall survival of LUAD patients. Moreover, RNF115 overexpression inhibited LUAD cell apoptosis and promoted cellular proliferation and metabolism in LUAD cells. On the contrary, RNF115 knockdown displayed reverse effects. Furthermore, the underlying mechanism of the biological function of RNF115 in LUAD was through regulating Wnt/β-catenin pathway via ubiquitination of adenomatous polyposis coli (APC).ConclusionThe current study reveals a close association between RNF115 expression and prognostic conditions in LUAD patients and the oncogenic roles of RNF115 in LUAD at the first time. These findings may help establish the foundation for the development of therapeutics strategies and clinical management for lung cancer in future.

Integrated analysis of hypoxia-associated lncRNA signature to predict prognosis and immune microenvironment of lung adenocarcinoma patients

ABSTRACT Lung adenocarcinoma (LUAD) represents the main lung cancer (LC) subtype that possesses a disappointing clinical outcome over the decades. Tumor hypoxia is closely bound up with dismal survival for malignant tumor cases. We identified hypoxia-associated long non-coding RNA (lncRNA) signature to be an explicit indicator for predicting prognosis. The present work acquired RNA-seq and associated clinical data from The Cancer Genome Atlas (TCGA) database. Consensus cluster analysis characterized the hypoxia status of LUAD patients. Cox regression analysis with the least absolute shrinkage and selection operator (LASSO) method determined significantly prognosis-related lncRNAs which were used to create a prognostic model. Diverse statistical approaches like the Kaplan-Meier curve, receiver operating characteristic (ROC) curve, and nomogram were adopted to verify the accuracy of the risk score. The potential immune environment landscape was unearthed by the CIBERSORT algorithm. Three hypoxia-related clusters were determined and 221 differentially expressed hypoxia-related lncRNAs were screened out. We developed a new predictive model based on seven lncRNAs (LINC00941, AC022784.1, AC079949.2, LINC00707, AL161431.1, AC010980.2 and AC090001.1). Kaplan-Meier curves and ROC plots uncovered the reliable predictive power of the risk score model. In addition, the immunosuppressive landscape was presented in the high-risk group by immune cell infiltration analysis. The seven hypoxia lncRNAs survival signature in our article are robust, accurate tools for predicting overall survival in LUAD patients.

RHOV promotes lung adenocarcinoma cell growth and metastasis through JNK/c-Jun pathway.

Lung adenocarcinoma (LUAD) is a common type of lung cancer with high frequent metastasis and a high death rate. However, genes responsible for LUAD metastasis are still largely unknown. Here, we identify an important role of ras homolog family member V (RHOV) in LUAD metastasis using a combination of bioinformatic analysis and functional experiments. Bioinformatic analysis shows five hub LUAD metastasis driver genes (RHOV, ZIC5, CYP4B1, GPR18 and TCP10L2), among which RHOV is the most significant gene associated with LUAD metastasis. High RHOV expression predicted shorter overall survival in LUAD patients. RHOV overexpression promotes proliferation, migration, and invasion of LUAD cells, whereas RHOV knockdown inhibits these biological behaviors. Moreover, knockdown of RHOV suppresses LUAD tumor growth and metastasis in nude mice. Mechanistically, RHOV activates Jun N-terminal Kinase (JNK)/c-Jun signalling pathway, an important pathway in lung cancer development and progression, and regulates the expression of markers of epithelial-to-mesenchymal transition, a process involved in cancer cell migration, invasion and metastasis. RHOV-induced malignant biological behaviors are inhibited by pyrazolanthrone, a JNK inhibitor. Our findings indicate a critical role of RHOV in LUAD metastasis and may provide a biomarker for prognostic prediction and a target for LUAD therapy.

A seven-gene prognostic model related to immune checkpoint PD-1 revealing overall survival in patients with lung adenocarcinoma.

We aimed to identify the immune checkpoint Programmed cell death 1 (PD-1)-related gene signatures to predict the overall survival of lung adenocarcinoma (LUAD). RNA-seq datasets associated with LUAD as well as clinical information were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Based on the expression level of PD-1, Kaplan-Meier (K-M) survival analysis was performed to divide samples into PD-1 high- and low- expression groups. Then, differentially expressed genes (DEGs) between high- and low- expression groups were identified. Meanwhile, samples were divided into the high and low immune infiltration groups according to score of immune cell, followed by screening of DEGs between these two groups. Subsequently, DEGs related to both PD-1 expression and immune infiltration was integrated to obtain the overlapping genes. Lasso COX regressions were implemented to construct prognostic signatures. The prognostic model was validated using an independent GEO dataset and TCGA cohorts. In addition, the predictive ability of the seven-gene prognostic model with other molecular biomarkers was compared. A seven-gene signature (DPT, ITGAD, CLECL1, SYT13, DUSP26, AMPD1, and NELL2) related to PD-1 was developed through Lasso Cox regression. Univariate and multivariate regression analyses indicated that the constructed risk model was an independent prognostic factor. K-M survival analysis indicated that patients in the high risk group had significantly worse prognosis than those in the low risk group. Further, the results of validation analysis showed that this model was reliable and effective. The constructed prognostic model can predict overall survival in LUAD patients with great predictive performance, and it may be applied for diagnosis and adjuvant treatment of LUAD in clinical trials.

Prognostic Nomogram Based on Circular RNA-Associated Competing Endogenous RNA Network for Patients with Lung Adenocarcinoma.

Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function and application of circRNAs in lung adenocarcinoma (LUAD) are still unknown. In this study, we constructed a circRNA-associated competitive endogenous RNA (ceRNA) network to investigate the regulatory mechanism of LUAD procession and further constructed a prognostic signature to predict overall survival for LUAD patients. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were selected to construct the ceRNA network. Based on the TargetScan prediction tool and Pearson correlation coefficient, we constructed a circRNA-associated ceRNA network including 11 DEcircRNAs, 8 DEmiRNAs, and 49 DEmRNAs. GO and KEGG enrichment indicated that the ceRNA network might be involved in the regulation of GTPase activity and endothelial cell differentiation. After removing the discrete points, a PPI network containing 12 DEmRNAs was constructed. Univariate Cox regression analysis showed that three DEmRNAs were significantly associated with overall survival. Therefore, we constructed a three-gene prognostic signature for LUAD patients using the LASSO method in the TCGA-LUAD training cohort. By applying the signature, patients could be categorized into the high-risk or low-risk subgroups with significant survival differences (HR: 1.62, 95% CI: 1.12-2.35, log-rank p = 0.009). The prognostic performance was confirmed in an independent GEO cohort (GSE42127, HR: 2.59, 95% CI: 1.32-5.10, log-rank p = 0.004). Multivariate Cox regression analysis proved that the three-gene signature was an independent prognostic factor. Combining the three-gene signature with clinical characters, a nomogram was constructed. The primary and external verification C-indexes were 0.717 and 0.716, respectively. The calibration curves for the probability of 3- and 5-year OS showed significant agreement between nomogram predictions and actual observations. Our findings provided a deeper understanding of the circRNA-associated ceRNA regulatory mechanism in LUAD pathogenesis and further constructed a useful prognostic signature to guide personalized treatment of LUAD patients.

Identification of four methylation-driven genes as candidate biomarkers for monitoring single-walled carbon nanotube-induced malignant transformation of the lung

Long-term exposure to carbon nanotubes (CNTs) has been reported to induce malignant transformation. This study aimed to screen candidate biomarkers for monitoring occupational workers to prevent the development of lung cancer. mRNA (GSE56104) and methylation (GSE153246) profiles of lung epithelial BEAS-2B cells exposed to malignant transformation dose of single-walled CNTs or control medium were downloaded from Gene Expression Omnibus database. A total of 1513 differentially expressed genes (DEGs) and 912 differentially methylated genes (DMGs) were identified using LIMMA method. The weighted correlation network analysis identified blue and turquoise modules were associated with malignant transformation of BEAS-2B cells, 124 DMGs of which were overlapped with DEGs. The mRNA and methylation levels of four methylation-driven DEGs were validated in both lung adenocarcinoma (LUAD) and squamous cell carcinomas (LUSC) of The Cancer Genome Atlas dataset and they were associated with overall survival of LUAD patients. Downregulation of PXMP4 and MCOLN2, while upregulation of MET was confirmed in both LUSC and LUAD via Human Protein Atlas analysis. PXMP4 and MET protein levels were also supported in the proteomic analysis of LUAD. Receiver operating characteristic (ROC) curve analysis showed the combination of four genes may be the optimal biomarker for predicting lung cancer, with the area under ROC curve >0.9. Function analysis revealed BARX2 may interact with CCND1 to regulate cell cycle; MET and PXMP4/MCOLN2 may positively correlate with CCR5/IL-6 or GATA3/HLA-DPB1/HLA-DPA1 to involve immune regulation. In conclusion, these four methylation-driven genes may be candidate prognostic and diagnostic biomarkers for single-walled CNT-related lung cancer.

Identification of a four-gene panel predicting overall survival for lung adenocarcinoma

BackgroundLung cancer is the most frequently diagnosed carcinoma and the leading cause of cancer-related mortality. Although molecular targeted therapy and immunotherapy have made great progress, the overall survival (OS) is still poor due to a lack of accurate and available prognostic biomarkers. Therefore, in this study we aimed to establish a multiple-gene panel predicting OS for lung adenocarcinoma.MethodsWe obtained the mRNA expression and clinical data of lung adenocarcinoma (LUAD) from TCGA database for further integrated bioinformatic analysis. Lasso regression and Cox regression were performed to establish a prognosis model based on a multi-gene panel. A nomogram based on this model was constructed. The receiver operating characteristic (ROC) curve and the Kaplan–Meier curve were used to assess the predicted capacity of the model. The prognosis value of the multi-gene panel was further validated in TCGA-LUAD patients with EGFR, KRAS and TP53 mutation and a dataset from GEO. Gene set enrichment analysis (GSEA) was performed to explore potential biological mechanisms of a novel prognostic gene signature.ResultsA four-gene panel (including DKK1, GNG7, LDHA, MELTF) was established for LUAD prognostic indicator. The ROC curve revealed good predicted performance in both test cohort (AUC = 0.740) and validation cohort (AUC = 0.752). Each patient was calculated a risk score according to the model based on the four-gene panel. The results showed that the risk score was an independent prognostic factor, and the high-risk group had a worse OS compared with the low-risk group. The nomogram based on this model showed good prediction performance. The four-gene panel was still good predictors for OS in LUAD patients with TP53 and KRAS mutations. GSEA revealed that the four genes may be significantly related to the metabolism of genetic material, especially the regulation of cell cycle pathway.ConclusionOur study proposed a novel four-gene panel to predict the OS of LUAD, which may contribute to predicting prognosis accurately and making the clinical decisions of individual therapy for LUAD patients.

Exploration of predictive and prognostic alternative splicing signatures in lung adenocarcinoma using machine learning methods

BackgroundAlternative splicing (AS) plays critical roles in generating protein diversity and complexity. Dysregulation of AS underlies the initiation and progression of tumors. Machine learning approaches have emerged as efficient tools to identify promising biomarkers. It is meaningful to explore pivotal AS events (ASEs) to deepen understanding and improve prognostic assessments of lung adenocarcinoma (LUAD) via machine learning algorithms.MethodRNA sequencing data and AS data were extracted from The Cancer Genome Atlas (TCGA) database and TCGA SpliceSeq database. Using several machine learning methods, we identified 24 pairs of LUAD-related ASEs implicated in splicing switches and a random forest-based classifiers for identifying lymph node metastasis (LNM) consisting of 12 ASEs. Furthermore, we identified key prognosis-related ASEs and established a 16-ASE-based prognostic model to predict overall survival for LUAD patients using Cox regression model, random survival forest analysis, and forward selection model. Bioinformatics analyses were also applied to identify underlying mechanisms and associated upstream splicing factors (SFs).ResultsEach pair of ASEs was spliced from the same parent gene, and exhibited perfect inverse intrapair correlation (correlation coefficient = − 1). The 12-ASE-based classifier showed robust ability to evaluate LNM status of LUAD patients with the area under the receiver operating characteristic (ROC) curve (AUC) more than 0.7 in fivefold cross-validation. The prognostic model performed well at 1, 3, 5, and 10 years in both the training cohort and internal test cohort. Univariate and multivariate Cox regression indicated the prognostic model could be used as an independent prognostic factor for patients with LUAD. Further analysis revealed correlations between the prognostic model and American Joint Committee on Cancer stage, T stage, N stage, and living status. The splicing network constructed of survival-related SFs and ASEs depicts regulatory relationships between them.ConclusionIn summary, our study provides insight into LUAD researches and managements based on these AS biomarkers.

LncRNA ST7-AS1, by regulating miR-181b-5p/KPNA4 axis, promotes the malignancy of lung adenocarcinoma

BackgroundGrowing evidence suggests that suppressor of tumorigenicity 7 antisense RNA 1 (ST7-AS1) is an oncogenic long noncoding RNA (lncRNA). However, little is known on its clinical significance, biological functions, or molecular mechanisms in lung adenocarcinoma (LUAD).MethodsThe expression of ST7-AS1 and miR-181b-5p were examined by qRT-PCR. The correlations between ST7-AS1 level and different clinicopathological features were analysed. In vitro, LUAD cells were examined for cell viability, migration and invasion by MTT, wound healing and Transwell assay, respectively. Epithelial-mesenchymal transition (EMT) biomarkers were detected by Western blot. The regulations between ST7-AS1, miR-181b-5p, and KPNA4 were examined by luciferase assay, RNA immunoprecipitation, RNA pulldown. Both gain- and loss-of-function strategies were used to assess the importance of different signalling molecules in malignant phenotypes of LUAD cells. The in vivo effect was analysed using the xenograft and the experimental metastasis mouse models.ResultsST7-AS1 was upregulated in LUAD tissues or cell lines, correlated with tumours of positive lymph node metastasis or higher TNM stages, and associated with shorter overall survival of LUAD patients. ST7-AS1 essentially maintained the viability, migration, invasion, and EMT of LUAD cells. The oncogenic activities of ST7-AS1 were accomplished by sponging miR-181b-5p and releasing the suppression of the latter on KPNA4. In LUAD tissues, ST7-AS1 level positively correlated with that of KPNA4 and negatively with miR-181b-5p level. In vivo, targeting ST7-AS1 significantly inhibited xenograft growth and metastasis.ConclusionsST7-AS1, by regulating miR-181b-5p/KPNA4 axis, promotes the malignancy of LUAD cells. Targeting ST7-AS1 and KPNA4 or up-regulating miR-181b-5p, therefore, may benefit the treatment of LUAD.