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Anoikis, a form of programmed cell death induced by loss of cell contact, is closely associated with tumor invasion and metastasis, making it highly significant in lung cancer research. We examined the expression patterns and prognostic relevance of Anoikis-related genes (ARGs) in lung adenocarcinoma (LUAD) using the TCGA-LUAD database. This study identified molecular subtypes associated with Anoikis in LUAD and conducted functional enrichment analyses. We constructed an ARG risk score using univariate least absolute shrinkage and selection operator (LASSO) Cox regression, validated externally with GEO datasets and clinical samples. The clinical applicability of the prognostic model was evaluated using nomograms, calibration curves, decision curve analysis (DCA), and time-dependent AUC assessments. We identified four prognostically significant genes (PLK1, SLC2A1, CDKN3, PHLDA2) and two ARG-related molecular subtypes. ARGs were generally upregulated in LUAD and correlated with multiple pathways including the cell cycle and DNA replication. The prognostic model indicated that the low-risk group had better outcomes and significant correlations with clinicopathological features, tumor microenvironment, immune therapy responses, drug sensitivity, and pan-RNA epigenetic modification-related genes. Patients with low-risk LUAD were potential beneficiaries of immune checkpoint inhibitor (ICI) therapy. Prognostic ARGs' distribution and expression across various immune cell types were further analyzed using single-cell RNA sequencing. The pivotal role of CDKN3 in LUAD was confirmed through qRT-PCR and gene knockout experiments, demonstrating that CDKN3 knockdown inhibits tumor cell proliferation, migration, and invasion. Additionally, we constructed a ceRNA network involving CDKN3/hsa-miR-26a-5p/SNHG6, LINC00665, DUXAP8, and SLC2A1/hsa-miR-218-5p/RNASEH1-AS1, providing new insights for personalized and immune therapy decisions in LUAD patients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Lung adenocarcinoma (LUAD) is the most common subtype of non-small cell lung cancer (NSCLC) and is characterized by its heterogeneity and poor prognosis. The role of ribosomal proteins RPLP0, RPLP1 and RPLP2 in multiple cancers has been implicated. However, their function in LUAD and their correlation with the poor prognosis of LUAD remains elusive. In this study, we performed a comprehensive bioinformatic analysis of the impact of these ribosomal proteins on LUAD. Our findings reveal that RPLP0, RPLP1 and RPLP2 are overexpressed in LUAD, which are likely attributed to abnormal copy number variations and decreased methylation levels of their promoters. LUAD patients with high expression of RPLP0, RPLP1 or RPLP2 have worse clinical outcomes in terms of overall survival (OS), first progression (FP) and post-progression survival (PPS), indicating poor prognosis. Moreover, the expression of RPLP0, RPLP1 and RPLP2 affects immune cell infiltration in LUAD tissues. Finally, we identified multiple existing drugs that may inhibit the expression of RPLP1 and RPLP2. Collectively, our data implicate the oncogenic role of RPLP0, RPLP1 and RPLP2 in LUAD and underscore their prognostic value in LUAD patients., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Introduction: Lung cancer is a leading cause of cancer-related deaths worldwide. Black/African American (B/AA) populations, in particular, exhibit the highest incidence and mortality rates of lung adenocarcinoma (LUAD) in the United States., Methods: This study aims to explore gene expression patterns linked to LUAD in B/AA and case-matched white patients, with the goal of developing predictive models for prognosis. Leveraging RNA sequencing data from The Cancer Genome Atlas (TCGA) database, genes and pathways associated with overall survival (OS) were identified., Results: The OS-associated genes in B/AA patients were distinct from those in white patients, showing predominant enrichment in immune-related pathways. Furthermore, mRNA co-expression network analysis revealed that OS-associated genes in B/AA patients had higher levels of interaction with various pathways, including those related to immunity, cell-ECM interaction, and specific intracellular signaling pathways. Notably, a potential B/AA-specific biomarker, C9orf64 , demonstrated significant correlations with genes involved in immune response. Unsupervised machine learning algorithms stratified B/AA patients into groups with distinct survival outcomes, while supervised algorithms demonstrated a higher accuracy in predicting survival for B/AA LUAD patients compared to white patients., Discussion: In total, this study explored OS-associated genes and pathways specific for B/AA LUAD patients. Further validation and clinical application of these findings are warranted to address disparities and improve outcomes in diverse patient populations., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Zhu, McHale, Van Scoyk, Riddick, Wu, Chou, Chen and Winn.)

Long non-coding RNAs (lncRNAs) have a notable role in the diagnosis and prognosis of cancer. However, the associations between lncRNA-related hub genes (LRHGs) expression and the corresponding outcomes have not been fully understood in lung adenocarcinoma (LUAD). Here, a total of 71 patients diagnosed with LUAD and 60 healthy volunteers at The First Affiliated Hospital of Huzhou University from April, 2023 to December, 2023 were enrolled in the present study. A LRHGs model was established using least absolute shrinkage and selection operator analyses of The Cancer Genome Atlas-LUAD datasets. The underlying mechanisms of the LRHGs were investigated via Gene Set Enrichment Analysis and Gene Set Variation Analysis. Additionally, the diagnostic role of serum HOXD cluster antisense RNA 2 (HOXD-AS2) was assessed by receiver operating characteristic (ROC) curve analysis. Lastly, TCGA-LUAD samples were divided into high- and low-HOXD-AS2 expression groups based on the median expression. The associations between HOXD-AS2 expression and miR-4538 as well as Calmodulin-Dependent Protein Kinase Type II subunit Beta (CAMK2B) levels were conducted through Pearson correlation analysis. A comprehensive analysis identified 141 differentially expressed lncRNAs between 539 LUAD tissues and 59 normal samples. A prognostic marker for overall survival was established by constructing a predictive signature consisting of 9 LRHGs. Subsequently, 474 LUAD samples were categorized into a high or low-risk group based on the median of the risk score. An independent prognostic model was constructed to confirm the validity of this categorization. Further comparisons of the clinicopathological features and LRHG-related pathways were performed between the two groups. Examinations of LRHG expression in two LUAD clusters and of the association between LRHG expression and immune infiltration were also conducted. HOXD-AS2 expression was shown to be elevated in LUAD tissues compared with matched normal tissues, and the serum HOXD-AS2 level was also notably increased in LUAD samples compared with healthy controls. The results of the ROC analysis indicated that the sensitivity and specificity of HOXD-AS2 were higher than that of cytokeratin-19 fragment (CYFRA21-1), which is a serum marker for LUAD. Pearson analyses indicated that miR-4538 level was negatively associated with HOXD-AS2 expression, but CAMK2B level showed positive correlation in LUAD. The results of the present study therefore indicated that the constructed LRHG model, particularly HOXD-AS2, could independently diagnose and predict the prognosis of LUAD, which suggested the underlying mechanism of the HOXD-AS2/miR-4538/CAMK2B, and might offer efficient strategies for LUAD treatment., (© 2024. The Author(s).)

Non-small cell lung adenocarcinoma (LUAD) is the predominant form of lung cancer originating from lung epithelial cells, making it the most prevalent pathological type. Currently, reliable indicators for predicting treatment efficacy and disease prognosis are lacking. Despite extensive validation of autophagy-dependent cell death (ADCD) in solid tumor studies and its correlation with immunotherapy effectiveness and cancer prognosis, systematic research on ADCD-related genes in LUAD is limited. We utilized AddModuleScore, ssGSEA, and WGCNA to identify genes associated with ADCD across single-cell and bulk transcriptome datasets. The TCGA dataset, comprising 598 cases, was randomly divided into training and validation sets to develop an ADCD-related LUAD prediction model. Internal validation was performed using the TCGA validation set. For external validation, datasets GSE13213 (119 LUAD samples), GSE26939 (115 LUAD samples), GSE29016 (39 LUAD samples), and GSE30219 (86 LUAD samples) were employed. We evaluated the model's accuracy and effectiveness in predicting prognostic risk. Additionally, CIBERSORT, ESTIMATE, and ssGSEA techniques were used to explore immunological characteristics, drug response, and gene expression in LUAD. Real-time RT-PCR was conducted to assess variations in mRNA expression levels of the gene XCR1 between cancerous and normal tissues in 10 lung cancer patients. We identified 249 genes associated with autophagy-dependent cell death (ADCD) at both single-cell and bulk transcriptome levels. Univariate COX regression analysis revealed that 18 genes were significantly associated with overall survival (OS). Using LASSO-Cox analysis, we developed an ADCD signature based on five genes (BIRC3, TAP1, SLAMF1, XCR1, and HLA-DMB) and created the ADCD-related risk scoring system (ADCDRS). Validation of this model demonstrated its ability to predict disease prognosis and its correlation with clinical characteristics, immune cell infiltration, and the tumor microenvironment. To enhance clinical applicability, we integrated an ADCDRS nomogram. Furthermore, we identified potential drugs targeting specific risk subgroups. We successfully identified a model based on five ADCD genes to predict disease prognosis and treatment efficacy in LUAD, as well as to assess the tumor immune microenvironment. An efficient and practical ADCDRS nomogram was designed., (© 2024. The Author(s).)

Lung adenocarcinoma (LUAD), the predominant subtype of lung cancer, has a high incidence and annual mortality worldwide. Members of the cadherin-related (CDHR) family are associated with many malignant tumor types. However, their role and clinical significance in LUAD have not been clarified. We analyzed the association of CDHRs mRNA expression profiles with prognostic significance, immune infiltration, and potential biological functional signatures in several public databases. We constructed a co-expressed mRNA network, and performed an intrinsic molecular structure and function enrichment analysis. Our results showed that CDHR2 mRNA expression was upregulated in LUAD, whereas CDHR1, CDHR3, CDHR4, and CDHR5 mRNAs were downregulated. Upregulation of CDHR2 mRNA is associated with a poor prognosis in patients with LUAD. Next, the correlation between CDHR family members and immune infiltration was observed. A receiver operating characteristic curve showed that the CDHR family is valuable for diagnosing LUAD. In this study, we found that CDHR2 mRNA expression was upregulated in LUAD. Upregulation of CDHR2 mRNA was associated with a poor prognosis in patients with LUAD., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Pyroptosis plays an important role in lung adenocarcinoma (LUAD). In this study, we aimed to explore the pyroptosis-related gene (PRG) expression pattern and to identify promising pyroptosis-related biomarkers to improve the prognosis of LUAD. The gene expression profiles and clinical information of LUAD patients were downloaded from the Cancer Genome Atlas (TCGA), and validation cohort information was extracted from the Gene Expression Omnibus database. Gene expression data were analyzed using the limma package and visualized using the ggplot2 package as well as the pheatmap package in R software. Functional enrichment analysis was also performed for the 44 differentially expressed PRGs (DEPRGs). Then, consensus clustering revealed pyroptosis-related tumor subtypes, and differentially expressed genes (DEGs) were screened according to the subtypes. Next, univariate Cox and multivariate Cox regression analyses were used to identify independent prognostic PRGs. After overlapping DEGs and the Lasso regression analysis-based prognostic genes, the predictive risk model was established and validated. Correlation analysis between PRGs and clinicopathological variables was also explored. Finally, the TIMER and TISIDB databases were used to further explore the correlation analysis between immune cell infiltration levels, the risk score, and clinicopathological variables in the predictive risk model. A total of 52 genes from the PubMed were identified as PRGs, and 44 of the 52 genes were pooled as DEPRGs. The most significant GO term was "collagen trimer" (P = 2.46E-13), and KEGG analysis results indicated that 44 DEPRGs were significantly enriched in Salmonella infection (P < 0.001). Then, consensus clustering analysis divided LUAD patients into two clusters, and a total of 79 DEGs were identified according to these cluster subtypes. Subsequently, univariate and multivariate Cox regression analyses were used to identify 12 genes that could serve as independent prognostic indicators and we also performed Lasso regression analysis and screened 23 DEGs. After overlapping 23 DEGs and 12 genes, only 4 (KLRG2, MAPK4, C6 and SFRP5) of 12 genes were selected for the further exploration of the prognostic pattern. Survival analysis results indicated that this risk model effectively predicted the prognosis (P < 0.001). Combined with the correlation analysis results between the 4 genes and clinicopathological variables, C6 and KLRG2 were screened as prognostic genes. In this study, we constructed a predictive risk model and identified two pyroptosis subtype-related gene expression patterns to improve the prognosis of LUAD. Understanding the subtypes of LUAD is helpful for accurately characterizing the LUAD and developing personalized treatment., (© 2024. The Author(s).)

Objective: Lactate dehydrogenase is dysregulated in several cancer types. However, the mechanism of its dysregulation in lung cancer is not fully understood. We utilized web-based computational databases to conduct gene expression analysis on LDHA, identified its regulator, and explored their role in the prognosis of lung cancer., Methods: We used various web-based computational tools, including the UALCAN, TIMER2.0, ENCORI, TCGA Portal, OncoDB, and GEPIA2 datasets for lung cancer analysis in this study. We also performed survival, biological processes, and metastasis analysis using various computational tools. We also carried out co-expression functional enrichment analysis using the Enrichr and TIMER databases, multivariate analysis of survival and pathological stage, and transcriptional regulation analysis using the ENCORI and OncoDB datasets. Furthermore, LDHA inhibitor binding of withanolides was analyzed using Auto Dock Tools 1.5.6, LigPlot+, and Pymol., Results: The study found that the higher levels of LDHA gene expression were associated with poor prognosis and overall survival in lung cancer patients. We identified 11 key genes co-expressed with LDHA; out of them, two genes, MKI67 and PGK1, showed a strong positive correlation with LDHA and associated poor survival outcomes in LUAD patients. Furthermore, we also identified hsa-let-7c-5p and TMPO-AS1 as potential regulators of LDHA in LUAD. It might be possible that the TMPO-AS1- hsa-let-7c-5p-LDHA ceRNA network could serve as a potential regulator of aerobic glycolysis in LUAD and can serve as prognostic biomarkers. Further, Withanolides can inhibit the activity of LDHA and can be tested as an adjuvant treatment., Conclusion: We conclude that LDHA is overexpressed in LUAD, and the patients with high expression of LDHA exhibit poor prognosis. Further, the TMPO-AS1-hsa-let-7c-5p-LDHA ceRNA network can regulate aerobic glycolysis, thereby facilitating tumor growth in lung cancer.

Despite advances in science and technology, lung cancer remains a major public health issue. The discovery of early diagnostic and prognostic markers is still needed to reduce the mortality rate of lung cancer, which is the highest among all cancer types. Aberrations in the DNA methylation system have an important role in human cancer and are promising for the development of early diagnostic and prognostic markers. The present study focused on zinc finger protein (ZNF)577, whose encoding gene was indicated to exhibit promoter hypermethylation together with 9 other genes in lung adenocarcinoma (LADC) in a previous study by our group. ZN577 is a member of the ZNG family and its functional role has so far remained elusive. LADC tissue samples surgically resected at Tokushima University Hospital (Tokushima, Japan) between April 1999 and November 2013 were collected. A total of 73 tumors and 27 paired tumor-adjacent normal tissues were examined for DNA methylation and mRNA expression of ZNF577. A total of 149 LADC tissue samples were collected and evaluated by immunohistochemistry (IHC) for the tissue expression of ZNF577. High methylation (n=27, P<0.0001) and low mRNA expression levels (n=27, P<0.031) of ZNF577 were identified in LADC tissues, and it was demonstrated that methylation levels were inversely correlated with mRNA expression levels (P=0.0116, ρ=-0.2515). Among the LADC tissues, lepidic-patterned samples had lower methylation levels of ZNF577 than other pathological types. In addition, mRNA expression levels of ZNF577 were significantly higher in females, non-smokers and stage I samples. Overall survival [P<0.0001; area under curve (AUC)=0.8658] and disease-free survival (DFS; P<0.0004; AUC=0.7232) rates were significantly higher in the ZNF577 high mRNA expression group than in the ZNF577 low mRNA expression group. Among the 149 LADC samples examined by IHC, 105 were negative and 44 were positive for the tissue expression of ZNF577. Cox regression analysis showed poorer DFS (hazard ratio: 3.917; P=0.023) in patients with lower expression of ZNF577. In conclusion, higher methylation levels of ZNF577 were observed in LADC tissues than in normal lung tissue and low mRNA expression of ZNF577 was associated with unfavorable prognosis.

Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), subtypes of non-small cell lung cancer (NSCLC), exhibit distinct characteristics. The expression and prognostic significance of Protocadherin Gamma Subfamily A, 12 (PCDHGA12) in NSCLC remain unexplored. This study analyzed transcriptomic and genomic datasets from TCGA to investigate PCDHGA12 expression and its prognostic relevance in LUAD and LUSC. We found PCDHGA12 mRNA and protein levels were downregulated in both LUAD and LUSC tissues compared to adjacent non-cancerous tissues, with high PCDHGA12 expression correlating with lower overall survival in LUSC but not in LUAD. GSEA revealed a unique enrichment pattern associated with PCDHGA12 low expression in LUSC, especially in the DNA repair pathway. Co-expression analysis showed associations of PCDHGA12 with focal adhesion and the PI3K-AKT pathway in LUAD, and additionally with ECM-receptor interaction in LUSC. Hub gene prognosis analysis identified genes correlated with prognosis only in LUSC, reflecting PCDHGA12's influence. Mutation analysis linked with PCDHGA12 identified differential mutations in SPTA1, KEAP1, and TNR in LUAD, and a notable NAV3 mutation in LUSC. Additionally, immuno-infiltration analysis reveals a positive correlation between PCDHGA12 expression and immune cell infiltration. Specifically, lower PCDHGA12 expression in LUSC is associated with higher levels of CD8 T cells and DCs, lower levels of Tregs and M0 macrophages, and increased expression of HMGB1 and TNFRSF18. These genetic and immunological differences may account for the significant prognostic disparity of PCDHGA12 levels between LUAD and LUSC. Further experimental studies are essential to validate these associations and investigate potential targeted and immunotherapeutic strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Lung adenocarcinoma (LUAD) is the dominant histotype of non-small cell lung cancer. Panoptosis, a comprehensive form of programmed cell death, is central to carcinogenesis. In this study, the expression of PANoptosis-related genes (PRGs) and their impact on the development, prognosis, tumor microenvironment, and treatment response of patients with lung adenocarcinoma (LUAD) were systematically evaluated. PRGs were selected from The Cancer Genome Atlas database and Genecards dataset using differential expression analysis. The signature of included PRGs was identified using univariate Cox regression analysis and LASSO regression analysis. Additionally, a nomogram was developed that includes signature and clinical information. Kaplan-Meier survival analysis and receiver operating characteristic curves were used to assess the predictive validity of these risk models. Finally, functional analysis of the selected PRGs in signature and analysis of immune landscape were also performed. Preliminary identification of 10 genes related to PANoptosis has significant implications for prognosis. Subsequently, seven related genes were integrated to classify LUAD patients into different survival risk groups. The prognostic risk score generated from the signature and the TNM stage were as independent prognostic factors and were utilized in creating a nomogram plot. Both the features and the nomogram plot showed accurate performance in predicting the overall survival of LUAD patients. The PRGs were enriched in several biological functions and pathways, and stratified studies were conducted on the differences in immune landscape between high-risk and low-risk groups based on their characteristics. Ultimately, our evaluation focused on the differences in drug treatment efficacy between the high-risk and low-risk groups, providing a foundation for future research directions. Potential associations between PRGs and patient prognosis in LUAD have been identified in this study. Potential biomarkers for clinical application could be considered for the prognostic predictors identified in this study., (© 2024. The Author(s).)

Background: The cancer genome contains several driver mutations. However, in some cases, no known drivers have been identified; these remaining areas of unmet needs, leading to limited progress in cancer therapy. Whole-genome sequencing (WGS) can identify non-coding alterations associated with the disease. Consequently, exploration of non-coding regions using WGS and other omics data such as ChIP-sequencing (ChIP-seq) to discern novel alterations and mechanisms related to tumorigenesis have been attractive these days., Methods: Integrated multi-omics analyses, including WGS, ChIP-seq, DNA methylation, and RNA-sequencing (RNA-seq), were conducted on samples from patients with non-clinically actionable genetic alterations (non-CAGAs) in lung adenocarcinoma (LUAD). Second-level cluster analysis was performed to reinforce the correlations associated with patient survival, as identified by RNA-seq. Subsequent differential gene expression analysis was performed to identify potential druggable targets., Results: Differences in H3K27ac marks in non-CAGAs LUAD were found and confirmed by analyzing RNA-seq data, in which mastermind-like transcriptional coactivator 2 (MAML2) was suppressed. The down-regulated genes whose expression was correlated to MAML2 expression were associated with patient prognosis. WGS analysis revealed somatic mutations associated with the H3K27ac marks in the MAML2 region and high levels of DNA methylation in MAML2 were observed in tumor samples. The second-level cluster analysis enabled patient stratification and subsequent analyses identified potential therapeutic target genes and treatment options., Conclusions: We overcome the persistent challenges of identifying alterations or driver mutations in coding regions related to tumorigenesis through a novel approach combining multi-omics data with clinical information to reveal the molecular mechanisms underlying non-CAGAs LUAD, stratify patients to improve patient prognosis, and identify potential therapeutic targets. This approach may be applicable to studies of other cancers with unmet needs., (© 2024. The Author(s).)

G0 arrest (G0A) is widely recognized as a crucial factor contributing to tumor relapse. The role of genes related to G0A in lung adenocarcinoma (LUAD) was unclear. This study aimed to develop a gene signature based on for LUAD patients and investigate its relationship with prognosis, tumor immune microenvironment, and therapeutic response in LUAD. We use the TCGA-LUAD database as the discovery cohort, focusing specifically on genes associated with the G0A pathway. We used various statistical methods, including Cox and lasso regression, to develop the model. We validated the model using bulk transcriptome and single-cell transcriptome datasets (GSE50081, GSE72094, GSE127465, GSE131907 and EMTAB6149). We used GSEA enrichment and the CIBERSORT algorithm to gain insight into the annotation of the signaling pathway and the characterization of the tumor microenvironment. We evaluated the response to immunotherapy, chemotherapy, and targeted therapy in these patients. The expression of six genes was validated in cell lines by quantitative real-time PCR (qRT-PCR). Our study successfully established a six-gene signature (CHCHD4, DUT, LARP1, PTTG1IP, RBM14, and WBP11) that demonstrated significant predictive power for overall survival in patients with LUAD. It demonstrated independent prognostic value in LUAD. To enhance clinical applicability, we developed a nomogram based on this gene signature, which showed high reliability in predicting patient outcomes. Furthermore, we observed a significant association between G0A-related risk and tumor microenvironment as well as drug susceptibility, highlighting the potential of the gene signature to guide personalized treatment strategies. The expression of six genes were significantly upregulated in the LUAD cell lines. This signature holds the potential to contribute to improved prognostic prediction and new personalized therapies specifically for LUAD patients., Competing Interests: The authors declare no conflict of interest., (Copyright: © 2024 Ma et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: The aim of this study was to investigate the correlation between m 6 A methylation regulators and cell infiltration characteristics in tumor immune microenvironment (TIME), so as to help understand the immune mechanism of early-stage lung adenocarcinoma (LUAD)., Methods: The expression and consensus cluster analyses of m 6 A methylation regulators in early-stage LUAD were performed. The clinicopathological features, immune cell infiltration, survival and functional enrichment in different subtypes were analyzed. We also constructed a prognostic model. Clinical tissue samples were used to validate the expression of model genes through real-time polymerase chain reaction (RT-PCR). In addition, cell scratch assay and Transwell assay were also performed., Results: Expression of m 6 A methylation regulators was abnormal in early-stage LUAD. According to the consensus clustering of m 6 A methylation regulators, patients with early-stage LUAD were divided into two subtypes. Two subtypes showed different infiltration levels of immune cell and survival time. A prognostic model consisting of HNRNPC, IGF2BP1 and IGF2BP3 could be used to predict the survival of early-stage LUAD. RT-PCR results showed that HNRNPC, IGF2BP1 and IGF2BP3 were significantly up-regulated in early-stage LUAD tissues. The results of cell scratch assay and Transwell assay showed that overexpression of HNRNPC promotes the migration and invasion of NCI-H1299 cells, while knockdown HNRNPC inhibits the migration and invasion of NCI-H1299 cells., Conclusions: This work reveals that m 6 A methylation regulators may be potential biomarkers for prognosis in patients with early-stage LUAD. Our prognostic model may be of great value in predicting the prognosis of early-stage LUAD.

Objective: The prognosis of lung adenocarcinoma (LUAD), which is the most common type of lung cancer, remains poor. Little is known about the function and mechanism of whey acidic protein four-disulfide core domain 2 (WFDC2) in LUAD., Methods: In this study, we used online databases to compare WFDC2 expression between LUAD and normal tissues, to analyze the relationship between WFDC2 and overall survival, and to investigate the potential roles of WFDC2., Results: We found that WFDC2 protein and mRNA expression levels were significantly higher in LUAD tissue than in normal tissue, and high WFDC2 mRNA expression was associated with better overall survival. WFDC2 mRNA expression was correlated with the mutation status of TP53. The biological function of WFDC2 was associated with the cell cycle, and low WFDC2 mRNA expression was associated with an elevated tumor mutational burden and neoantigen levels. A negative relationship was observed between WFDC2 and immune gene expression, and high WFDC2 mRNA expression was found in patients with LUAD and low programed cell death 1 mRNA expression., Conclusions: We propose that WFDC2 is associated with clinical benefits of immune checkpoint inhibitors in LUAD., Competing Interests: Declaration of conflicting interestThe authors declare that there is no conflict of interest.

The Lys-Asp-Glu-Leu receptor (KDELR) family genes play critical roles in a variety of biological processes in different tumors. Our study aimed to provide a comprehensive analysis of the potential roles of KDELRs in lung adenocarcinoma (LUAD). Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, as well as clinical samples, we conducted a series of analyses and validations using R software tools and various online resources. The results showed that KDELR family genes and proteins were highly expressed and associated with a poor prognosis of LUAD. Promoter hypomethylation and the competing endogenous RNA (ceRNA) network of PCAT6/hsa-miR-326/KDELR1 might be potential causes of aberrant KDELR1 overexpression in LUAD. Three key Transcription factors (TFs) (SPI1, EP300, and MAZ) and a TFs-miRNAs-KDELRs network (involving 11 TFs) might be involved in modulating KDELRs expression abnormalities. Gene Set Enrichment Analysis (GSEA) indicated enrichment of genes highly expressing KDELR1, KDELR2, and KDELR3 in MTORC1&#95;SIGNALING, P53&#95;PATHWAY, and ANGIOGENESIS. Negative correlations between KDELRs expression and CD8 + T cell infiltration, as well as CTLA-4 expression. Our multiple analyses suggested that the KDELRs are important signaling molecules in LUAD. These results provided novel insights for developing prognostic markers and novel therapies of LUAD., (© 2024. The Author(s).)

Genomic instability (GI) was associated with tumorigenesis. However, GI-related lncRNA signature (GILncSig) in lung adenocarcinoma (LUAD) is still unknown. In this study, the lncRNA expression data, somatic mutation information and clinical survival information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) and performed differential analysis. Functional and prognosis analysis revealed that multiple GI-related pathways were enriched. By using univariate and multivariate Cox regression analysis, 5 GI-associated lncRNAs (AC012085.2, FAM83A-AS1, MIR223HG, MIR193BHG, LINC01116) were identified and used to construct a GILncSig model. Mutation burden analysis indicated that the high-risk GI group had much higher somatic mutation count and the risk score constructed by the 5 GI-associated lncRNAs was an independent predictor for overall survival (OS) (P < 0.05). Overall, our study provides valuable insights into the involvement of GI-associated lncRNAs in LUAD and highlights their potential as therapeutic targets., (© 2024. The Author(s).)

Purpose: Lung adenocarcinoma (LUAD) is a prevalent malignant tumor worldwide, with high incidence and mortality rates. However, there is still a lack of specific and sensitive biomarkers for its early diagnosis and targeted treatment. Disulfidptosis is a newly identified mode of cell death that is characteristic of disulfide stress. Therefore, exploring the correlation between disulfidptosis-related long non-coding RNAs (DRGs-lncRNAs) and patient prognosis can provide new molecular targets for LUAD patients., Methods: The study analysed the transcriptome data and clinical data of LUAD patients in The Cancer Genome Atlas (TCGA) database, gene co-expression, and univariate Cox regression methods were used to screen for DRGs-lncRNAs related to prognosis. The risk score model of lncRNA was established by univariate and multivariate Cox regression models. TIMER, CIBERSORT, CIBERSORT-ABS, and other methods were used to analyze immune infiltration and further evaluate immune function analysis, immune checkpoints, and drug sensitivity. Real-time polymerase chain reaction (RT-PCR) was performed to detect the expression of DRGs-lncRNAs in LUAD cell lines., Results: A total of 108 lncRNAs significantly associated with disulfidptosis were identified. A prognostic model was constructed by screening 10 lncRNAs with independent prognostic significance through single-factor Cox regression analysis, LASSO regression analysis, and multiple-factor Cox regression analysis. Survival analysis of patients through the prognostic model showed that there were obvious survival differences between the high- and low-risk groups. The risk score of the prognostic model can be used as an independent prognostic factor independent of other clinical traits, and the risk score increases with stage. Further analysis showed that the prognostic model was also different from tumor immune cell infiltration, immune function, and immune checkpoint genes in the high- and low-risk groups. Chemotherapy drug susceptibility analysis showed that high-risk patients were more sensitive to Paclitaxel, 5-Fluorouracil, Gefitinib, Docetaxel, Cytarabine, and Cisplatin. Additionally, RT-PCR analysis demonstrated differential expression of DRGs-lncRNAs between LUAD cell lines and the human bronchial epithelial cell line., Conclusions: The prognostic model of DRGs-lncRNAs constructed in this study has certain accuracy and reliability in predicting the survival prognosis of LUAD patients, and provides clues for the interaction between disulfidptosis and LUAD immunotherapy.

Endoplasmic reticulum stress (ERS) is commonly induced by accumulating misfolded or unfolded proteins in tumor microenvironment. Long non-coding RNAs (lncRNAs) play important roles in ERS response and lung adenocarcinoma (LUAD) progression. However, the role of ERS-related lncRNAs in LUAD remains unknown. In this study, we aimed to identify ERS-associated lncRNAs with prognostic value in LUAD and characterize their clinical implications. Cox and least absolute shrinkage and selection operator regression analyses identified nine ERS-related lncRNAs with independent prognostic abilities, including five protective factors (CROCCP2, KIAA0125, LINC0996, RPARP-AS1 and TBX5-AS1) and four risk factors (LINC0857, LINC116, RP11-21L23.2 and RP11-295G20.2). We developed an ERS-related lncRNA risk prediction model in predicting overall survival of LUAD patients, which classified TCGA cohorts into high-risk (HS) and low-risk (LS) groups. Comprehensive bioinformatic analyses revealed HS patients featured with late-stage tumors, greater mutation burdens, weaker anti-tumor immunity/responses, and lower sensitivity to targeted drugs compared to LS patients, contributing to tumor progression and a poor prognosis. Functional enrichment analysis implicated these ERS-related lncRNAs in cell migration, cell death, and immunity. Furthermore, expression of the most significantly upregulated risk lncRNA, RP11-295G20.2, was validated at the mRNA level using clinical LUAD samples. Knockdown of RP11-295G20.2 obviously reduced ERS and suppressed proliferation, invasion, and migration of LUAD cells. This novel ERS-related lncRNA signature provides a new biomarker for prognostic prediction, and ERS-associated RP11-295G20.2 serves as a potential therapeutic target in LUAD., (© 2024. The Author(s).)

Background: Lung adenocarcinoma (LUAD) accounts for a high proportion of tumor deaths globally, while methyltransferase-related lncRNAs in LUAD were poorly studied., Methods: In our study, we focused on two distinct cohorts, TCGA-LUAD and GSE3021, to establish a signature of methyltransferase-related long non-coding RNAs (MeRlncRNAs) in LUAD. We employed univariate Cox and LASSO regression analyses as our main analytical tools. The GSE30219 cohort served as the validation cohort for our findings. Furthermore, to explore the differential pathway enrichments between groups stratified by risk, we utilized Gene Set Enrichment Analysis (GSEA). Additionally, single-sample GSEA (ssGSEA) was conducted to assess the immune infiltration landscape within each sample. Reverse transcription quantitative PCR (RT-qPCR) was also performed to verify the expression of prognostic lncRNAs in both clinically normal and LUAD samples., Results: In LUAD, we identified a set of 32 MeRlncRNAs. We further narrowed our focus to six prognostic lncRNAs to develop gene signatures. The TCGA-LUAD cohort and GSE30219 were utilized to validate the risk score model derived from these signatures. Our analysis showed that the risk score served as an independent prognostic factor, linked to immune-related pathways. Additionally, the analysis of immune infiltration revealed that the immune landscape in high-risk groups was suppressed, which could contribute to poorer prognoses. We also constructed a regulatory network comprising 6 prognostic lncRNAs, 19 miRNAs, and 21 mRNAs. Confirmatory RT-qPCR results aligned with public database findings, verifying the expression of these prognostic lncRNAs in the samples., Conclusion: The prognostic gene signature of LUAD associated with MeRlncRNAs that we provided, may offer us a comprehensive picture of the prognosis prediction for LUAD patients.

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1's potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD., (© 2024. The Author(s).)

Glutathione metabolism (GM) is a crucial part of various metabolic and pathophysiological processes. However, its role in lung adenocarcinoma (LUAD) has not been comprehensively studied. This study aimed to explore the potential relationship between GM genes, the prognosis, and the immune microenvironment of patients with LUAD. We constructed a risk signature model containing seven GM genes using Lasso combined Cox regression and validated it using six GEO datasets. Our analysis showed that it is an independent prognostic factor. Functional enrichment analysis revealed that the GM genes were significantly enriched in cell proliferation, cell cycle regulation, and metabolic pathways. Clinical and gene expression data of patients with LUAD were obtained from the TCGA database and patients were divided into high- and low-risk groups. The high-risk patient group had a poor prognosis, reduced immune cell infiltration, poor response to immunotherapy, high sensitivity to chemotherapy, and low sensitivity to targeted therapy. Subsequently, single-cell transcriptome analysis using the GSE143423 and GSE127465 datasets revealed that the core SMS gene was highly enriched in M2 Macrophages. Finally, nine GEO datasets and multiple fluorescence staining revealed a correlation between the SMS expression and M2 macrophage polarization. Our prognostic model in which the core SMS gene is closely related to M2 macrophage polarization is expected to become a novel target and strategy for tumor therapy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Background: To develop optimal personalized therapy for lung adenocarcinoma (LUAD), potential biomarkers associated with the prognosis are urgently needed. It is unclear what role T Cell Leukemia Homeobox 1 (TLX1) plays in LUAD., Objective: In this study, TLX1's relationship with LUAD was investigated using TCGA database analysis, bioinformatics analysis, and experimental validation., Methods: We examined the expression of TLX1 in pan cancer and LUAD, the relationship between TLX1 expression and clinical features, immune infiltration, its diagnostic and prognostic value, as well as TLX1 related pathways. The analysis included various statistical methods, including the Kaplan-Meier method, Cox regression analysis, GSEA, and immune infiltration analysis. TLX1 expression in LUAD cell lines was validated using qRT-PCR., Result: In LUAD patients, high expression of TLX1 was associated with T stage (P<0.001). High TLX1 expression was associated with worse overall survival (OS) (HR: 1.57; 95% CI: 1.18-2.1; P=0.002). And TLX1 HR: 1.619; 95% CI: 1.012-2.590; P=0.044) was independently correlated with OS in LUAD patients. TLX1 expression was associated with the pathways, including Rho GTPase effectors, DNA repair, TCF dependent signaling in response to WNT, signaling by Nuclear Receptors, signaling by Notch, chromatin-modifying enzymes, ESR-mediated signaling, cellular senescence, and transcriptional regulation by Runx1. TLX1 expression was correlated with aDC, Tcm, and TReg cells. The expression of TLX1 was significantly increased in LUAD cells compared to BEAS-2B cells., Conclusion: An association between high TLX1 expression and poor survival and immune infiltration was found in LUAD patients. There may be a potential role for TLX1 in diagnosis, prognosis, and immunotherapy for LUAD., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Exosomes are involved in tumorigenesis, growth and metastasis. However, the prognostic value of exosome-related genes in lung adenocarcinoma (LUAD) remains unclear. Methods: Clinical and transcriptome data from The Cancer Genome Atlas LUAD cohort were used to construct a model based on exosome-related genes, which was validated with LUAD data from the Gene Expression Omnibus (GEO). Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis were used to explore underlying mechanisms; the single-sample gene set enrichment analysis score was used to determine immune functions. Results: A 19-exosome-related gene signature for overall survival in LUAD was predictive in both The Cancer Genome Atlas and GEO LUAD cohorts. Immune-related and extracellular matrix-related pathways were enriched in differentially expressed genes. Immune states differed between high- and low-risk groups. Conclusion: The novel signature can be used to predict outcomes in LUAD.

Gene-expression profiling can be used to classify human tumors into molecular subtypes or risk groups, representing potential future clinical tools for treatment prediction and prognostication. However, it is less well-known how prognostic gene signatures derived in one malignancy perform in a pan-cancer context. In this study, a gene-rule-based single sample predictor (SSP) called classifier for lung adenocarcinoma molecular subtypes (CLAMS) associated with proliferation was tested in almost 15 000 samples from 32 cancer types to classify samples into better or worse prognosis. Of the 14 malignancies that presented both CLAMS classes in sufficient numbers, survival outcomes were significantly different for breast, brain, kidney and liver cancer. Patients with samples classified as better prognosis by CLAMS were generally of lower tumor grade and disease stage, and had improved prognosis according to other type-specific classifications (e.g. PAM50 for breast cancer). In all, 99.1% of non-lung cancer cases classified as better outcome by CLAMS were comprised within the range of proliferation scores of lung adenocarcinoma cases with a predicted better prognosis by CLAMS. This finding demonstrates the potential of tuning SSPs to identify specific levels of for instance tumor proliferation or other transcriptional programs through predictor training. Together, pan-cancer studies such as this may take us one step closer to understanding how gene-expression-based SSPs act, which gene-expression programs might be important in different malignancies, and how to derive tools useful for prognostication that are efficient across organs., (© The Author(s) 2021. Published by Oxford University Press.)

Objective: Increasing evidence highlights the clinical implications of P2RY12 that belongs to the family of G-protein coupled receptors in carcinogenesis. Here, this study was designed to explore the associations between P2RY12 and tumor immune microenvironment of lung adenocarcinoma (LUAD)., Methods: Based on 352 LUAD samples from The Cancer Genome Atlas (TCGA), stromal and immune scores of each sample were estimated by ESTIMATE algorithm. Differential expression analysis was presented between stromal/immune high- and low-score groups. Protein-protein interaction (PPI) was then constructed by STRING database. Univariate and multivariate Cox regression analysis was utilized to screen prognosis-related factors. Co-expressed genes of P2RY12 were analyzed, followed by functional enrichment analysis. Furthermore, the correlation between P2RY12 and immune cell infiltrations was estimated using the TIMER database. P2RY12 expression was validated between 37 pairs of LUAD and normal tissues using RT-qPCR and immunohistochemistry. After overexpressing P2RY12, the proliferation and migration of A549 cells was detected by CCK-8 and scratch test., Results: 145 up- and 102 down-regulated stromal- and immune-related mRNAs were identified for LUAD. Based on 145 up-regulated mRNAs, a PPI network was conducted, consisting of 95 nodes and 210 relationship pairs. Ten hub genes were then identified. Among them, CCR8, CNR2, CXCR5, GPR18, GPR31 and P2RY12 were in association with overall survival of patients with LUAD. After adjusting other variables, P2RY12 expression was an independent prognostic factor for LUAD. 288 co-expressed genes of P2RY12 were determined and these co-expressed genes were primarily involved in immune-related biological processes or pathways. Moreover, P2RY12 was significantly correlated with M2 macrophage and dendritic cell infiltration. After validation, P2RY12 expression was significantly decreased in LUAD than normal tissues. Its overexpression distinctly suppressed proliferation and migration of A549 cells., Conclusion: Our findings suggest that P2RY12 is an immune infiltration-related prognostic marker for LUAD., (Copyright © 2021 Elsevier B.V. All rights reserved.)

This research aims to explore the diagnostic and prognostic value of ubiquitin-conjugating enzyme E2 variant 2 (UBE2V2) in lung adenocarcinoma (LUAD). The expression of UBE2V2 in clinical specimens was evaluated by bioinformatics analyses and immunohistochemistry. Bioinformatics analyses relying on the The Cancer Genome Atlas (TCGA) database suggested the elevated UBE2V2 mRNA levels in LUAD in comparison to adjacent normal tissues. Gene set enrichment analyses and gene ontology term enrichment analyses further showed the involvement of UBE2V2 in the modulation of cell cycle and immune associated signaling. The correlation analyses in TCGA LUAD data set revealed the positive correlation between UBE2V2 and CCNE1, CCNE2, CCNA2, CCNB1, CCNB2, cyclin-dependent kinase (CDK)2, CDK4, and CDK1 at the mRNA level. Moreover, UBE2V2 mRNA levels were positively correlated with PD-L1 mRNA levels, the T classification, and poor survival of LUAD patients, and were negatively correlated with type II interferon response. Consistent with the results obtained from TCGA data mining, immunohistochemistry demonstrated that UBE2V2 protein levels were upregulated in LUAD in comparison to normal tissues and were positively associated with T classification. Intriguingly, a positive correlation between UBE2V2 protein levels and PD-L1 expression was also elucidated in clinical samples. Besides, UBE2V2 expression indicated a poor prognosis in LUAD patients. Our study found that UBE2V2 was identified as an independent prognostic indicator for LUAD and might serve as an alternative target for LUAD treatment., Competing Interests: The authors declare no conflict of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment, such as extracellular matrix remodeling, reciprocal signaling interactions with cancer cells and crosstalk with infiltrating inflammatory cells. However, the relationships between CAFs and survival are not well known in lung cancer. The aim of this study was to reveal the correlations of CAFs with survival rates, genetic alterations and immune activities. This study reviewed the histological features of 517 patients with lung adenocarcinoma from The Cancer Genome Atlas (TCGA) database. We performed gene set enrichment analysis (GSEA), network-based analysis and survival analysis based on CAFs in four histological types of lung adenocarcinoma: acinar, papillary, micropapillary and solid. We found four hallmark gene sets, the epithelial-mesenchymal transition, angiogenesis, hypoxia, and inflammatory response gene sets, that were associated with the presence of CAFs. CAFs were associated with tumor proliferation, elevated memory CD4+T cells and high CD274 (encoding PD-L1) expression. In the pathway analyses, CAFs were related to blood vessel remodeling, matrix organization, negative regulation of apoptosis and transforming growth factor-β signaling. In the survival analysis of each histological type, CAFs were associated with poor prognosis in the solid type. These results may contribute to the development of therapeutic strategies against lung adenocarcinoma cases in which CAFs are present., (© 2021. The Author(s).)

Background: More 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., Methods: In 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., Results: As 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&#95;circ&#95;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&#95;circ&#95;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., Conclusions: In summary, a ceRNA network of hsa&#95;circ&#95;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., (© 2021. The Author(s).)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), and is highly contagious and pathogenic. TMPRSS2 and Neuropilin-1, the key components that facilitate SARS-CoV-2 infection, are potential targets for treatment of COVID-19. Here we performed a comprehensive analysis on NRP1 and TMPRSS2 in lung to provide information for treating comorbidity of COVID-19 with lung cancer. NRP1 is widely expressed across all the human tissues while TMPRSS2 is expressed in a restricted pattern. High level of NRP1 associates with worse prognosis in multiple cancers, while high level of TMPRSS2 is associated with better survival of Lung Adenocarcinoma (LUAD). Moreover, NRP1 positively correlates with the oncogenic Cancer Associated Fibroblast (CAF), macrophage and endothelial cells infiltration, negatively correlates with infiltration of CD8 + T cell, the tumor killer cell in Lung Squamous cell carcinoma (LUSC). TMPRSS2 shows negative correlation with the oncogenic events in LUAD. RNA-seq data show that NRP1 level is slightly decreased in peripheral blood of ICU admitted COVID-19 patients, unaltered in lung, while TMPRSS2 level is significantly decreased in lung of COVID-19 patients. Our analysis suggests NRP1 as a potential therapeutic target, while sets an alert on targeting TMPRSS2 for treating comorbidity of COVID-19 and lung cancers.

Background: We investigated the roles of breast cancer anti-estrogen resistance 1 (BCAR1/p130Cas) in the formation and immunoevasion of invasive circulating tumor cells (CTCs) in lung adenocarcinoma (LUAD). Methods: Biomarkers of CTCs including BCAR1 and CD274, were evaluated by the CanPatrol method. Proteomics analysis of LUAD cells and exosomes after BCAR1 overexpression (BCAR1-OE) was performed by mass spectrometry. Cell functions and relevant signaling pathways were investigated after BCAR1 knockdown (BCAR1-KO) or BCAR1-OE in LUAD cells. Lastly, in vitro and in vivo experiments were performed to confirm the roles of BCAR1 in the formation and immunoevasion of CTCs. Results : High expression of BCAR1 by CTCs correlated with CD274 expression and epithelial-to-mesenchymal transition (EMT). RAC1, together with BCAR1, was found to play an important role in the carcinogenesis of LUAD. RAC1 functioned with BCAR1 to induce EMT and to enhance cell proliferation, colony formation, cell invasion and migration, and anoikis resistance in LUAD cells. BCAR1 up-regulated CD274 expression probably by shuttling the short isoform of BRD4 (BRD4-S) into the nucleus. CTCs, as well as tumor formation, were prohibited in nude mice xenografted with BCAR1-KO cells. The co-expression of BCAR1/RAC1 and BCAR1/CD274 was confirmed in LUAD. BCAR1 expression in LUAD is an indicator of poor prognosis, and it associates with immunoevasion. Conclusion : BCAR1, as a new target for the treatment of LUAD, plays roles in the formation and immunoevasion of invasive CTCs. The mechanism includes triggering EMT via RAC1 signaling and up-regulating CD274 expression by shuttling BRD4-S into the nucleus., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Long non-coding RNA (lncRNA) is an important regulatory factor in the development of lung adenocarcinoma, which is related to the control of autophagy. LncRNA can also be used as a biomarker of prognosis in patients with lung adenocarcinoma. Therefore, it is important to determine the prognostic value of autophagy-related lncRNA in lung adenocarcinoma. In this study, autophagy-related mRNAs-lncRNAs were screened from lung adenocarcinoma and a co-expression network of autophagy-related mRNAs-lncRNAs was constructed by using The Cancer Genome Atlas (TCGA). The univariate and multivariate Cox proportional hazard analyses were used to evaluate the prognostic value of the autophagy-related lncRNAs and finally obtained a survival model composed of 11 autophagy-related lncRNAs. Through Kaplan-Meier analysis, univariate and multivariate Cox regression analysis and time-dependent receiver operating characteristic (ROC) curve analysis, it was further verified that the survival model was a new independent prognostic factor for patients with lung adenocarcinoma. In addition, based on the survival model, gene set enrichment analysis (GSEA) was used to illustrate the function of genes in low-risk and high-risk groups. These 11 lncRNAs were GAS6-AS1, AC106047.1, AC010980.2, AL034397.3, NKILA, AL606489.1, HLA-DQB1-AS1, LINC01116, LINC01806, FAM83A-AS1 and AC090559.1. The hazard ratio (HR) of the risk score was 1.256 (1.196-1.320) (P < .001) in univariate Cox regression analysis and 1.215 (1.149-1.286) (P < .001) in multivariate Cox regression analysis. And the AUC value of the risk score was 0.809. The 11 autophagy-related lncRNA survival models had important predictive value for the prognosis of lung adenocarcinoma and may become clinical autophagy-related therapeutic targets., (© 2021 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

Background: Teashirt homolog 2 (TSHZ2) is essential for maintaining cellular homeostasis and regulating transcription on neoplasia development. However, the regulation of TSHZ2 in lung tumorigenesis and the underlying mechanisms remain unclear. Objective: To evaluate the relationship between TSHZ2 expression in patients' tumor tissue and prognosis in lung adenocarcinoma. Methods: TSHZ2 expression in different lung adenocarcinoma cell lines and human tissue were detected by Western blotting. The effect of TSHZ2 on cell proliferation, apoptosis and migration in lung adenocarcinoma cells was measured by CCK8, colony formation, flowcytometric analyses and wound-healing, respectively. TSHZ2 expression in different lung adenocarcinoma cell lines and human tissue from patients was detected using Western blotting and immunohistochemical staining. We also retrospectively analyzed 226 lung adenocarcinoma patients after surgical resection using immunohistochemical staining, and the association of TSHZ2 expression with the patient survival was evaluated. Results: TSHZ2 was lowly expressed in certain lung adenocarcinoma cell lines (PC9 and B203L), but other cells showed a high expression. Low expression of TSHZ2 was also observed in most lung adenocarcinoma tissues compared with adjacent tissues. Furthermore, we found that the overexpression of TSHZ2 plasmids led to the dramatic inhibition of cell proliferation, colony formation ability, migration and apoptosis induction in PC9 lung adenocarcinoma cells. In contrast, no obvious effect was found when the TSHZ2 expression was down-regulated by si-TSHZ2. An elevated TSHZ2 expression was observed in 155(68.6%) tumor tissues samples of lung adenocarcinoma patients. Notably, the lung adenocarcinoma patients with a high TSHZ2 expression tended to have EGFR mutations less frequently and a preferable prognosis to those with a lower expression. Conclusion: A high TSHZ2 expression inhabited cell proliferation and predicted a better prognosis of lung adenocarcinoma, possibly representing a useful therapeutic target for lung adenocarcinoma., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Lung adenocarcinoma is the most common subtype of non-small cell lung cancer, and platelet receptor-related genes are related to its occurrence and progression. A new prognostic indicator based on platelet receptor-related genes was developed with multivariate COX analysis. Prognostic markers based on platelet-related risk score perform moderately in prognosis prediction. The functional annotation of this risk model in high-risk patients shows that the pathways related to cell cycle, glycolysis and platelet-derived related factors are rich. It is worth noting that somatic mutation analysis shows that TTN and MUC16 have higher mutation burdens in high-risk patients. Moreover, the differential genes of high- and low-risk groups are regulated by copy number variation and miRNA. And we provide a free online nomogram web tool based on clinical factors and the risk score (https://wsxzaq.shinyapps.io/wsxzaq&#95;nomogram/). The score has been verified among three independent external cohorts (GSE13213, GSE68465 and GSE72094), and is still an independent risk factor for lung adenocarcinoma. In addition, among the other 6 cancers, the OS prognosis of high and low-risk groups of PRS is different (P < 0.05). Our research results have screened multiple platelet differential genes with clinical significance and constructed a meaningful prognostic risk score (PRS).

In this study, we constructed an eight-gene metabolic related signature for LUAD. The eight-gene prognostic signature (including PLAUR, F2, UGT2B17, GNG7, IDO2, ST3GAL6, PIK3CG, and GLS2) exhibited a good prognostic value in the TCGA LUAD training dataset and testing dataset. In addition, the risk score based on the signature model was significantly correlated with immune cell infiltration and expression levels of immune markers in LUAD patients. LUAD cohorts from GEO were used to validate the model, indicating the usefulness of the model. In summary, we developed and validated an eight-gene signature model for LUAD, which can reflect the immune microenvironment characteristics and predict the prognostic outcomes for LUAD patients.

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1 , TGFBR2 , SMAD7 , and NEDD4L ) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2021 Lixian Chen et al.)

The histological classification of lung adenocarcinoma includes 5 types: lepidic, acinar, papillary, micropapillary and solid. The complex gene interactions and anticancer immune response of these types are not well known. The aim of this study was to reveal the survival rates, genetic alterations and immune activities of the five histological types and provide treatment strategies. This study reviewed the histological findings of 517 patients with lung adenocarcinoma from The Cancer Genome Atlas (TCGA) database and classified them into five types. We performed gene set enrichment analysis (GSEA) and survival analysis according to the different types. We found six oncogenic gene sets that were higher in lung adenocarcinoma than in normal tissues. In the survival analysis of each type, the acinar type had a favorable prognosis, and the solid subtype had an unfavorable prognosis; however, the survival differences between the other types were not significant. Our study focused on the solid type, which had the poorest prognosis. The solid type was related to adaptive immune resistance associated with elevated CD8 T cells and high CD274 (encoding PD-L1) expression. In the pathway analyses, the solid type was significantly related to high vascular endothelial growth factor (VEGF)-A expression, reflecting tumor angiogenesis. Non-necrosis/low immune response affected by high VEGF-A was associated with worse prognosis. The solid type associated with high VEGF-A expression may contribute to the development of therapeutic strategies for lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the predominant subtype of lung cancer with a relatively poor prognosis. The dramatic improvements of new immunotherapy strategies have shown promising results in lung cancer patients. This study aimed to elucidate the functions of immune-associated genes in LUAD prognosis and pathogenesis by analyzing public databases. We obtained expression profiles of LUAD patients from The Cancer Genome Atlas (TCGA) database and applied the ESTIMATE algorithm to calculate immune scores and stromal scores. A series of microenvironment-related genes with prognostic value was then identified. Of note, heat shock factor 5 (HSF5) was found to be decreased in LUAD patients and positively correlated with overall survival, which was further confirmed in the Gene Expression Omnibus (GEO) database. Moreover, Gene Ontology (GO) analysis based on the correlated genes of HSF5 demonstrated that HSF5 expression was significantly associated with the immune response and inflammatory activities. Based on the Tumor IMmune Estimation Resource (TIMER) and Gene Expression Profiling Interactive Analysis (GEPIA) datasets, HSF5 expression showed strong correlations with various immune cell infiltration and diverse immune marker sets. These findings suggest that HSF5 can be used as a promising biomarker for determining prognosis and immune infiltration in LUAD patients., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Nearly 1/3 of lung adenocarcinomas have loss of STK11 (LKB1) function. Herein, a bioinformatics approach was used to determine how accurately preclinical model systems reflect the in vivo biology of STK11 loss in human patients. Hierarchical and K-mean clustering, principle component, and gene set enrichment analyses were employed to model gene expression due to STK11 loss in patient cohorts representing nearly 1000 lung adenocarcinoma patients. K-means clustering classified STK11 loss patient tumors into three distinct sub-groups; positive (54%), neuroendocrine (NE) (35%) and negative (11%). The positive and NE groups are both defined by the expression of NKX2-1. In addition to NKX2-1, NE patients express neuroendocrine markers such as ASCL1 and CALCA. In contrast, the negative group does not express NKX2-1 (or neuroendocrine markers) and is characterized by significantly reduced survival relative to the two other groups. Two gene expression signatures were derived to explain both neuroendocrine features and differentiation (NKX2-1 loss) and were validated through two public datasets involving chemical differentiation (DCI) and NKX2-1 reconstitution. Patients results were then compared with established cell lines, transgenic mice, and patient-derived xenograft models of STK11 loss. Interestingly, all cell line and PDX models cluster and show expression patterns similar with the NKX2-1 negative subset of STK11-loss human tumors. Surprisingly, even mouse models of STK11 loss do not resemble patient tumors based on gene expression patterns. Results suggest pre-clinical models of STK11 loss are pronounced by marked elimination of type II pneumocyte identity, opposite of most in vivo human tumors., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: After curative surgical resection, about 30-75% lung adenocarcinoma (LUAD) patients suffer from recurrence with dismal survival outcomes. Identification of patients with high risk of recurrence to impose intense therapy is urgently needed., Materials and Methods: Gene expression data of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were calculated by comparing the recurrent and primary tissues. Prognostic genes associated with the recurrence-free survival (RFS) of LUAD patients were identified using univariate analysis. LASSO Cox regression and multivariate Cox analysis were applied to extract key genes and establish the prediction model., Results: We detected 37 DEGs between primary and recurrent LUAD tumors. Using univariate analysis, 31 DEGs were found to be significantly associated with RFS. We established the RFS prediction model including thirteen genes using the LASSO Cox regression. In the training cohort, we classified patients into high- and low-risk groups and found that patients in the high-risk group suffered from worse RFS compared to those in the low-risk group ( P < 0.01). Concordant results were confirmed in the internal and external validation cohort. The efficiency of the prediction model was also confirmed under different clinical subgroups. The high-risk group was significantly identified as the risk factor of recurrence in LUAD by the multivariate Cox analysis (HR = 13.37, P = 0.01). Compared to clinicopathological features, our prediction model possessed higher accuracy to identify patients with high risk of recurrence (AUC = 96.3%). Finally, we found that the G2M checkpoint pathway was enriched both in recurrent tumors and primary tumors of high-risk patients., Conclusions: Our recurrence-specific gene-based prognostic prediction model provides extra information about the risk of recurrence in LUAD, which is conducive for clinicians to conduct individualized therapy in clinic., Competing Interests: The authors declare that they have no potential conflicts of interest., (Copyright © 2020 Shaohua Xu et al.)

Hypoxia and stemness are important factors in tumor progression. We aimed to explore the ncRNA classifier associated with hypoxia and stemness in lung adenocarcinoma (LUAD). We found that the prognosis of LUAD patients with high hypoxia and stemness index was worse than that of patients with low hypoxia and stemness index. RNA expression profiles of these two clusters were analyzed, and 6867 differentially expressed (DE) mRNAs were screened. Functional analysis showed that DE mRNAs were associated with cell cycle and DNA replication. Protein-protein interaction network analysis revealed 20 hub genes, among which CENPF, BUB1, BUB1B, KIF23 and TTK had significant influence on prognosis. In addition, 807 DE lncRNAs and 243 DE miRNAs were identified. CeRNA network analysis indicated that AC079160.1-miR-539-5p-CENPF may be an important regulatory axis that potentially regulates the progression of LUAD. The expression of AC079160.1 and CENPF were positively correlated with hypoxia and stemness index, while miR-539-5p expression level was negatively correlated with hypoxia and stemness index. Overall, we identified CENPF, BUB1, BUB1B, KIF23 and TTK as potentially key genes involved in regulating hypoxia-induced tumor cell stemness, and found that AC079160.1-miR-539-5p-CENPF axis may be involved in regulating hypoxia induced tumor cell stemness in LUAD.

The present study investigates the role of network topology in lung adenocarcinoma (LUAD) development. Analysis of sex- and stage-specific whole-genome expression data revealed that co-expressed and highly connected prognostic genes common to all cancer stages form a small-world network in each stage of LUAD. These small-world networks are present within stage-specific scale-free networks, conserved across the cancer stages, and linked to cancer-specific events. The presence of small-world networks across the cancer stages presents a synchronized system in the disordered environment of cancer, resulting in the evolution of malignancy. Our study reported that these small-world networks are resilient to random and systematic attacks, indicating the least opportunity to introduce perturbations by drugs as a therapeutic intervention. We concluded that highly clustered small-world networks could be controlled through transcriptional modulation for the improved treatment of LUAD., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Lung cancer is one of the fatal tumors. The tumor microenvironment plays a key role in regulating tumor progression. To figure out the role of tumor microenvironment in lung adenocarcinoma (LUAD), ESTIMATE algorithm was used to evaluate the immune scores in LUAD. Patients with low immune scores had a worse overall survival (OS) compared with high immune scores. Using RNA-Seq data of 489 patients in The Cancer Genome Atlas (TCGA), differentially expressed genes (DEGs) were identified between high- and low-immune score groups. Based on the DEGs, nine-gene signature was constructed by the least absolute shrinkage and selection operator Cox regression model in TCGA set. The signature demonstrated significant prognostic value in both TCGA and Gene Expression Omnibus database. Multivariate Cox regression analyses indicated that nine-genes signature was an independent prognostic factor. Subgroup analysis also revealed a robust prognostic ability of nine-gene signature. A nomogram with a C-index of 0.722 had a favorable power for predicting 3-, 5-, and 10-year survival for clinical use by integrating nine-gene signature and other clinical features. Co-expression and functional enrichment analysis showed that nine-gene signature was significantly associated with immune response and provided potential profound molecules for revealing the mechanism of tumor initiation and progression. In conclusion, we revealed the significance of immune infiltration and built a novel nine-gene signature as a reliable prognostic factor for patients with LUAD., (© 2020 Wiley Periodicals, Inc.)

Recent studies demonstrated that immune associated genes (IAGs) played an important role in the treatment of lung adenocarcinoma (LUAD). In the research, we established an IAGs signature and validated its prognostic value in LUAD by using bioinformatic methods and public databases. Based on the RNA-Seq samples from The Cancer Genome Atlas (TCGA), 576 differentially expressed IAGs were firstly identified. The R package coxph was used to select significant prognostic IAGs using both univariate and multivariate analyses. As a result, four IAGs (SCG2, CCL20, CAT, S100P) were finally screened in an IAGs signature. Based on these four IAGs, LASSO (least absolute shrinkage and selection operator) Cox regression analysis was used to construct a Risk score prognostic model and survival analysis revealed that high risk score was significantly associated with poor survival outcomes, which was validated in the external datasets GSE68465 and GSE31210. In addition, Risk score was found to be significantly associated with stage, lymphatic involvement, tumor metastasis and immune cells (B cells and dendritic cells) infiltration. Moreover, it was found that TP53 and EGFR had a higher mutation frequency in high risk group. Then a nomogram with clinical characteristics was established to superiorly predict prognosis of LUAD patients, and calibration plots and ROC analysis proved its accuracy. We believe that our findings can be conveniently used for individualized prediction of the clinical prognosis for LUAD patients, but further clinical trials and experimental exploration are needed to validate our observations., Competing Interests: Declaration of Competing Interest The authors report no conflicts of interest in this work., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Rationale: The forkhead box A1 (FOXA1) is a crucial transcription factor in initiation and development of breast, lung and prostate cancer. Previous studies about the FOXA1 transcriptional network were mainly focused on protein-coding genes. Its regulatory network of long non-coding RNAs (lncRNAs) and their role in FOXA1 oncogenic activity remains unknown. Methods: The Cancer Genome Atlas (TCGA) data, RNA-seq and ChIP-seq data were used to analyze FOXA1 regulated lncRNAs. RT-qPCR was used to detect the expression of DSCAM-AS1, RT-qPCR and Western blotting were used to determine the expression of FOXA1, estrogen receptor α (ERα) and Y box binding protein 1 (YBX1). RNA pull-down and RIP-qPCR were employed to investigate the interaction between DSCAM-AS1 and YBX1. The effect of DSCAM-AS1 on malignant phenotypes was examined through in vitro and in vivo assays. Results: In this study, we conducted a global analysis of FOXA1 regulated lncRNAs. For detailed analysis, we chose lncRNA DSCAM-AS1, which is specifically expressed in lung adenocarcinoma, breast and prostate cancer. The expression level of DSCAM-AS1 is regulated by two super-enhancers (SEs) driven by FOXA1. High expression levels of DSCAM-AS1 was associated with poor prognosis. Knockout experiments showed DSCAM-AS1 was essential for the growth of xenograft tumors. Moreover, we demonstrated DSCAM-AS1 can regulate the expression of the master transcriptional factor FOXA1. In breast cancer, DSCAM-AS1 was also found to regulate ERα. Mechanistically, DSCAM-AS1 interacts with YBX1 and influences the recruitment of YBX1 in the promoter regions of FOXA1 and ERα. Conclusion: Our study demonstrated that lncRNA DSCAM-AS1 was transcriptionally activated by super-enhancers driven by FOXA1 and exhibited lineage-specific expression pattern. DSCAM-AS1 can promote cancer progression by interacting with YBX1 and regulating expression of FOXA1 and ERα., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Mining disease-related genes contributes momentously to handling lung adenocarcinoma (LUAD). But genetic complexity and tumor heterogeneity severely get in the way. Fortunately, new light has been shed by dramatic progress of bioinformatic technology in the past decades. In this research, we investigated relationships between gene expression and clinical features of LUAD via integrative bioinformatic analysis. First, we applied limma and DESeq2 packages to analyze differentially expressed genes (DEGs) of LUAD from GEO database and TCGA project (tumor tissues versus normal tissues), and acquired 180 down-regulated DEGs and 52 up-regulated DEGs. Then, we investigated genetic and biological assignment of theses DEGs by Bioconductor packages and STRING database. We found these DEGs were distributed dispersedly among chromosomes, enriched observably in extracellular matrix-related processes, and weighted hierarchically in interaction network. Finally, we established DEGs-based statistical models for evaluating TNM stage and survival status of LUAD. And these models (logistic regression models for TNM parameter and Cox regression models for survival probability) all possessed fine predictive efficacy (C-indexes: T, 0.740; N, 0.687; M, 0.823; overall survival, 0.678; progression-free survival, 0.611). In summary, we have successfully established gene expression-based models for assessing clinical characteristics of LUAD, which will assist its pathogenesis investigation and clinical intervention.

Background: Long noncoding RNAs (lncRNAs) have gain increasing attention in lung adenocarcinoma. In this study, we aimed at constructing and analyzing the lncRNAs and the related proteins based competitive endogenous RNA (ceRNA) network., Methods: RNA expression data of lung adenocarcinoma were extracted from the TCGA database. Differentially expressed (DE) lncRNAs, messenger RNAs (mRNAs) and microRNAs (miRNAs) were identified and then a DElncRNA-DEmiRNA-DEmRNA ceRNA network was constructed for lung adenocarcinoma. We also analyzed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEgenes. Kaplan-Meier survival curves were also been further utilized for exploring the prognostic factors., Results: After compared and calculated lncRNA, mRNA and miRNA expression profiles between lung adenocarcinoma and normal samples, 1709 differential expressed lncRNAs, 2554 differential expressed mRNAs and 116 differential expressed miRNAs were finally identified. Afterwards, a lncRNA mediated ceRNA network was constructed, according to the interactions among 544 pairs of DElncRNA-DEmiRNA relationships and 47 pairs of DEmiRNA-DEmRNA relationships. As for the survival analyses, we found 10 DElncRNAs, 25 DEmRNAs and 7 miRNAs have statistically prognostic significance for overall survival, respectively., Conclusions: This study provides meaningful information for deeper understanding the underlying molecular mechanism of lung adenocarcinoma and for evaluating prognosis, which could monitor recurrence, guide clinical treatment drugs and subsequent related researches., Competing Interests: Declaration of Competing Interest None to declare., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Aim: Understanding the cell types and cell compositions in tumor environment (TME) and the gene changes in lung adenocarcinoma (LUAD) may provide insights on immune profiles and treatment targets for LUAD patients. Materials & methods: The RNA-Seq data from The Cancer Genome Atlas database were used to calculate the stromal scores and immune scores and analyzed the fractions of tumor infiltrating immune cells in LUAD samples with ESTIMATE and CIBERSORT algorithm. Results: We extracted a list of TME-related differentially expressed genes and performed the functional enrichment analysis. We found these genes were mainly enriched in immune response and cancer-related signal pathways. The prognosis analysis indicated that LINC00211 , MUC2 , LINC00426 , LY86-AS1 ZEB2-AS1 and EREG were associated with prognosis in LUAD patients. Conclusion: The current study provides novel insights into immune files and gene changes in TME in LUAD patients.

Lung adenocarcinoma (LUAD), as the most common subtype of non-small cell lung cancer, is responsible for more than 500 000 deaths worldwide annually. In this study, we identify a novel microRNA-26b-5p (miR-26b-5p) and elucidated its function on LUAD. The survival rate of parent LUAD cells and radiation-resistant LUAD cells were determined using clonogenic survival assay. We overexpressed or inhibited miR-26b-5p in LUAD, and the correlation between activating transcription factor 2 (ATF2) and miR-26b-5p was determined using integrated bioinformatics analysis and dual-luciferase reporter gene assay. Exosomes derived from A549 cell lines were then detected using Western blot assay, followed by co-transfection with radiation-resistant A549R cells. LUAD tissues and serum were collected, followed by miR-26b-5p relative expression quantification using RT-qPCR. miR-26b-5p was identified as the most differentially expressed miRNA and was down-regulated in LUAD. Radiation-resistant cells were more resistant to X-radiation compared with parent cells. miR-26b-5p overexpression and X-irradiation led to enhanced radiosensitivity of LUAD cells. ATF2 was negatively targeted by miR-26b-5p. Exosomal miR-26b-5p derived from A549 cells could be transported to irradiation-resistant LUAD cells and inhibit ATF2 expression to promote DNA damage, apoptosis and radiosensitivity of LUAD cells, which was verified using serum-based miR-26b-5p. Our results show a regulatory network of miR-26b-5p on radiosensitivity of LUAD cells, which may serve as a non-invasive biomarker for LUAD., (© 2020 The Authors. Journal of Cellular and Molecular Medicine published by Foundation for Cellular and Molecular Medicine and John Wiley & Sons Ltd.)

BACKGROUND Lung adenocarcinoma currently accounts for the highest cancer-related mortality rate worldwide. MiR-21-5p has a vital role in various types of cancers. We have analyzed the miR-21-5p expression level, prognosis, and associated molecular pathways in lung adenocarcinoma with multiple bioinformatics databases. MATERIAL AND METHODS The Cancer Genome Atlas (TCGA) database was employed to fetch the miR-21-5p expression profile in multiple tumors. We used the UALCAN platform to assess the differential regulation of the miR-21-5p in healthy tissue and lung adenocarcinoma. Also, the survival prognosis of the miR-21-5p in each stage of lung adenocarcinoma was done by the Kaplan-Meier database. The STARBASE and UALCAN databases were employed to predict the miR-21-5p target genes, and the levels of target genes and their prognostic value were analyzed. RESULTS MiR-21-5p was overexpressed in the majority of human cancers. MiR-21-5p demonstrated escalated expression in the lung adenocarcinoma tissue in contrast to the normal tissue (P<0.05). Poor prognosis was witnessed in the miR-21-5p high expression group as compared to the low expression group (hazard ratio [HR]= 1.59, P<0.05). PDZD2 was predicted as a miR-21-5p potential target. We found a negative correlation between PDZD2 and miR-21-5p (r=-0.255, P<0.05). PDZD2 was downregulated in lung adenocarcinoma (P<0.05). Overexpression of PDZD2 was associated with a better prognosis of survival in lung adenocarcinoma patients (HR=0.45, P<0.05). CONCLUSIONS MiR-21-5p exhibits the potential to act as a biomarker for the survival prognosis of lung adenocarcinoma. It might be responsible for the onset and progression of lung adenocarcinoma through PDZD2 regulation.