Independent Prognostic Factor For Lung Adenocarcinoma Research Articles

NGEF is a potential prognostic biomarker and could serve as an indicator for immunotherapy and chemotherapy in lung adenocarcinoma.

Neuronal guanine nucleotide exchange factor (NGEF) plays a key role in several cancers; however, its role in lung adenocarcinoma (LUAD) remains unclear. The aim of this study was to evaluate the efficacy of NGEF as a prognostic biomarker and potential therapeutic target for LUAD. NGEF expression data for multiple cancers and LUAD were downloaded from multiple databases. The high- and low-NGEF expression groups were constructed based on median NGEF expression in LUAD samples, and then performed Kaplan-Meier survival analysis. Differentially expressed genes (DEGs) from the two NGEF expression groups were screened and applied to construct a protein-protein interaction network. The primary pathways were obtained using gene set enrichment analysis. The associations between NGEF expression and clinical characteristics, immune infiltration, immune checkpoint inhibitors (ICIs), sensitivity to chemotherapy, and tumor mutation burden (TMB) were investigated using R. Levels of NGEF expression in the lung tissue was validated using single-cell RNA sequencing, quantitative polymerase chain reaction (qPCR), immunohistochemical staining, and western blot analysis. The expression of NGEF mRNA was upregulated in multiple cancers. mRNA and protein expression levels of NGEF were higher in patients with LUAD than in controls, as validated using qPCR and western blot. High NGEF expression was an independent prognostic factor for LUAD and was associated with advanced tumor stage, large tumor size, more lymph node metastasis, and worse overall survival (OS). A total of 182 overlapping DEGs were screened between The Cancer Genome Atlas and GSE31210, among which the top 20 hub genes were identified. NGEF expression was mainly enriched in the pathways of apoptosis, cell cycle, and DNA replication. Moreover, elevated NGEF expression were associated with a high fraction of activated memory CD4+ T cells and M0 macrophages; elevated expression levels of the ICIs: programmed cell death 1 and programmed cell death 1 ligand 1 expression; higher TMB; and better sensitivity to bortezomib, docetaxel, paclitaxel, and parthenolide, but less sensitivity to axitinib and metformin. NGEF expression is upregulated in LUAD and is significantly associated with tumor stages, OS probability, immune infiltration, immunotherapy response, and chemotherapy response. NGEF may be a potential diagnostic and prognostic biomarker and therapeutic target in LUAD.

BZW2 promotes malignant progression in lung adenocarcinoma through enhancing the ubiquitination and degradation of GSK3β

The role of Basic leucine zipper and W2 domains 2 (BZW2) in the advancement of different types of tumors is noteworthy, but its involvement and molecular mechanisms in lung adenocarcinoma (LUAD) remain uncertain. Through this investigation, it was found that the upregulation of BZW2 was observed in LUAD tissues, which was associated with an unfavorable prognosis for individuals diagnosed with LUAD, as indicated by data from Gene Expression Omnibus and The Cancer Genome Atlas databases. Based on the clinicopathologic characteristics of LUAD patients from the tissue microarray, both univariate and multivariate analyses indicated that BZW2 functioned as an independent prognostic factor for LUAD. In terms of mechanism, BZW2 interacted with glycogen synthase kinase-3 beta (GSK3β) and enhanced the ubiquitination-mediated degradation of GSK3β through slowing down of the dissociation of the ubiquitin ligase complex, which consists of GSK3β and TNF receptor-associated factor 6. Moreover, BZW2 stimulated Wnt/β-catenin signaling pathway through GSK3β, thereby facilitating the advancement of LUAD. In conclusion, BZW2 was a significant promoter of LUAD. The research we conducted identified a promising diagnostic and therapeutic target for LUAD.

DLX1 acts as a novel prognostic biomarker involved in immune cell infiltration and tumor progression in lung adenocarcinoma.

The biological function of distal-less homeobox 1 (DLX1) in lung adenocarcinoma (LUAD) remains unclear, despite a growing body of evidence that DLX1 is involved in the initiation and progression of various tumors. This study explored and confirmed the prognostic and immunologic roles of DLX1 in LUAD via bioinformatic analysis and cellular functional validation. MethSurv was used to analyze the DNA methylation levels of DLX1 and the prognostic value of CpG islands. DLX1 mutation rates and prognoses between patients with and without the mutated DLX1 gene were analyzed by cBioPortal. Finally, cellular functional assays were used to investigate the effect of DLX1 on LUAD cells. Our results showed that DLX1 mRNA expression was significantly upregulated in LUAD. High DLX1 expression or promoter methylation was associated with worse prognosis, which confirmed DLX1 as an independent prognostic factor in LUAD. The level of multiple immune cell infiltration was significantly associated with DLX1 expression. Genes in the high DLX1 expression group were mainly enriched in cell cycle checkpoint, DNA replication, DNA repair, Fceri-mediated MAPK activation, TP53 activity regulation, and MET activation of PTK2-regulated signaling pathways. Cellular functional assays showed that the knockdown of DLX1 inhibited the proliferation, migration, and invasion of LUAD cells. Our study identified DLX1 as a potential diagnostic and prognostic biomarker, and a promising therapeutic target in LUAD.

Integrated multi-omic analysis and experiment reveals the role of endoplasmic reticulum stress in lung adenocarcinoma

BackgroundLung cancer is a highly prevalent malignancy worldwide and is associated with high mortality rates. While the involvement of endoplasmic reticulum (ER) stress in the development of lung adenocarcinoma (LUAD) has been established, the underlying mechanism remains unclear.MethodsIn this study, we utilized data from The Cancer Genome Atlas (TCGA) to identify differentially expressed endoplasmic reticulum stress-related genes (ERSRGs) between LUAD and normal tissues. We performed various bioinformatics analyses to investigate the biological functions of these ERSRGs. Using LASSO analysis and multivariate stepwise regression, we constructed a novel prognostic model based on the ERSRGs. We further validated the performance of the model using two independent datasets from the Gene Expression Omnibus (GEO). Additionally, we conducted functional enrichment analysis, immune checkpoint analysis, and immune infiltration analysis and drug sensitivity analysis of LUAD patients to explore the potential biological function of the model. Furthermore, we conducted a battery of experiments to verify the expression of ERSRGs in a real-world cohort.ResultsWe identified 106 ERSRGs associated with LUAD, which allowed us to classify LUAD patients into two subtypes based on gene expression differences. Using six prognostic genes (NUPR1, RHBDD2, VCP, BAK1, EIF2AK3, MBTPS2), we constructed a prognostic model that exhibited excellent predictive performance in the training dataset and was successfully validated in two independent external datasets. The risk score derived from this model emerged as an independent prognostic factor for LUAD. Confirmation of the linkage between this risk model and immune infiltration was affirmed through the utilization of Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The q-PCR results verified significant differences in the expression of prognostic genes between cancer and paracancer tissues. Notably, the protein expression of NUPR1, as determined by immunohistochemistry (IHC), exhibited an opposite pattern compared to the mRNA expression patterns.ConclusionThis study establishes a novel prognostic model for LUAD based on six ER stress-related genes, facilitating the prediction of LUAD prognosis. Additionally, NUPR1 was identified as a potential regulator of stress in LUAD.

Prognostic value of genes related to cancer-associated fibroblasts in lung adenocarcinoma.

Although it has been established that cancer-associated fibroblasts (CAFs) facilitate tumor development, the relationship between CAFs and the prognosis of patients with lung adenocarcinoma (LUAD) has not been extensively explored. This study was formulated to investigate the prognostic value of CAF-related genes in LUAD. Differential analysis was carried out with TCGA-LUAD dataset as the training set. By overlapping differentially expressed genes (DEGs) with genes associated with CAF, CAF-related DEGs specific to LUAD were obtained. A prognostic risk model was constructed by Lasso and Cox regression analysis, and samples were grouped according to median risk score. The efficacy of the model was accessed through survival curve and receiver operating characteristic curve (ROC) analyses, with the validation set for verification. Risk score combined with clinical factors was utilized for Cox analysis to verify the independence of the model, and a nomogram was drawn. GSEA was performed on different risk groups. Immunologic infiltration and tumor mutational burden were assessed in different risk groups. Eleven feature genes including DLGAP5, KCNE2, UPK2, NPAS2, ARHGAP11A, ANGPTL4, ANLN, DKK1, SMUG1, C16orf74, and ACAD8 were identified, based on which a prognostic model was constructed. Risk score could predict the prognosis of LUAD patients and could be an independent prognostic factor for LUAD patients. GSEA outcomes displayed significant enrichment of genes in the high-risk group in the P53 SIGNALING PATHWAY. In comparison to the low-risk group, the high-risk group exhibited a decreased degree of immune infiltration and an elevated level of tumor mutational burden. An 11-gene model was constructed based on CAF-related genes to predict LUAD prognosis. This model represented an independent prognostic factor for LUAD.

DDX52 gene expression in LUAD tissues indicates potential as a prognostic biomarker and therapeutic target

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related morbidity and mortality globally. While DDX52, an ATP-dependent RNA helicase, plays a role in several biological processes, its specific involvement in LUAD is yet to be elucidated. We utilized ROC curves to determine DDX52’s predictive potential for LUAD. Kaplan–Meier survival curves, along with univariate and multivariate Cox analyses, assessed the prognostic implications of DDX52 in LUAD. We constructed nomogram models to further delineate DDX52’s influence on prognosis, employed GSEA for functional analysis, and used qRT-PCR to examine DDX52 expression in LUAD tissues. DDX52 expression was notably higher in LUAD tissues, suggesting its potential as a negative prognostic marker. We observed a direct relationship between DDX52 expression and advanced T and N stages, as well as higher grading and staging in LUAD patients. Cox analyses further underscored DDX52’s role as an independent prognostic determinant for LUAD. GSEA insights indicated DDX52’s influence on LUAD progression via multiple signaling pathways. Our nomogram, founded on DDX52 expression, effectively projected LUAD patient survival, as validated by calibration curves. Elevated DDX52 expression in LUAD tissues signals its potential as a poor prognostic marker. Our findings emphasize DDX52’s role not only as an independent prognostic factor for LUAD but also as a significant influencer in its progression through diverse signaling pathways. The constructed nomogram also underscores the feasibility of predicting LUAD patient survival based on DDX52 expression.

High BRCA1 expression is an independent prognostic biomarker in LUAD and correlates with immune infiltration

High BRCA1 expression is an independent prognostic biomarker in LUAD and correlates with immune infiltration

TEDC2 correlated with prognosis and immune microenvironment in lung adenocarcinoma

Tubulin epsilon and delta complex 2 (TEDC2) is a protein coding gene whose functions are poorly identified yet. This study aimed to identify the role of TEDC2 in prognosis and immune microenvironment of lung adenocarcinoma (LUAD). Through The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, the mRNA expression of TEDC2 was upregulated in LUAD tissues compared to normal tissues. The protein level of TEDC2 was also higher in LUAD in the Human Protein Atlas. The receiver operating characteristic (ROC) curve showed that high TEDC2 level could distinguish LUAD patients from normal subjects. In addition, the impact of TEDC2 expression on prognosis was evaluated by Kaplan–Meier and Cox regression analyses, and the results suggested that high TEDC2 expression was significantly associated with poor prognosis and was the independent prognostic factor in LUAD. GO and KEGG pathway analyses indicated the co-expressed genes of TEDC2 were mainly related to mitotic cell cycle processes. Importantly, high expression of TEDC2 indicated low infiltration of immune cells, especially dendritic cells and B cells. TEDC2 was also positively correlated with immune checkpoints such as PDCD1, LAG3 and CD276. Taken together, this study preliminarily revealed the clinical significance of TEDC2 in LUAD and provided novel insights into the role of TEDC2 in immune microenvironment.

Identification of novel prognostic model based on homologous recombination deficiency associated lncRNAs in lung adenocarcinoma

BackgroundNon-small cell lung cancer with homologous recombination deficiency (HRD) was revealed to have better response to immunotherapy. Long non-coding RNAs (lncRNAs) modulate multiple processes including HRD acting as potential biomarkers in tumors. The function of HRD-associated lncRNAs in lung cancer arouses our interests. MethodsTwo independent cohorts were enrolled containing 838 lung adenocarcinoma (LUAD) patients. HRD-associated lncRNAs were defined as the lncRNAs that were differential expressed in high-HRD group and low-HRD group which were classified in accordance with the HRD score. The least absolute shrinkage and selection operator cox regression was employed to construct a signature according to prognostic HRD-associated lncRNAs. The signature robustness was evaluated by using the prognosis analysis, multivariate-cox analysis, ROC curve, and nomogram. The participating pathways were estimated by gene set enrichment analysis and KEGG pathway analysis. The infiltration of immune cells was estimated by using xCell. The tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) were both utilized for the prediction of immunotherapy response. ResultsSeventeen HRD-associated lncRNAs were screened to classify the LUAD patients into two groups with variant survival that inferior overall survival was found in high-risk patients comparing to those with low-risk. Our model not only was the independent prognostic factor in LUAD but also had better performance on the prognosis prediction when making a comparison with other clinical and molecular signatures. Additionally, the high-risk group was suggested to have increased genomic instability and less response to immunotherapy. ConclusionA great predicative efficient prognostic signature was established based on 17 HRD-associated lncRNAs in LUAD. The signature might be the predictor for genomic instability and immunotherapy response in LUAD. Our findings provided new insight for the improvement of clinical stratification in LUAD.

Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma.

Pyroptosis is a recently identified form of programmed cell death; however, its role in lung adenocarcinoma (LUAD) remains unclear. Therefore, we set out to explore the prognostic potential of pyroptosis-related genes in LUAD. The pyroptosis-related risk score (PRRS) was developed by least absolute shrinkage and selection operator Cox regression and multivariate Cox regression. We found that PRRS was an independent prognostic factor for LUAD. LUAD patients in the high-PRRS group showed a significantly shorter overall survival (OS) and enriched in cell proliferation-related pathways. Then pathway enrichment analyses, mutation profile, tumor microenvironment, and drug sensitivity analysis were further studied in PRRS stratified LUAD patients. Tumor purity (TP) analyses revealed that L-PRRS LUAD patients had a lower TP, and patients in L-TP + L-PRRS subgroup had the most prolonged OS. Mutation analyses suggested that the L-PRRS LUAD patients had a lower tumor mutation burden (TMB), and patients in H-TMB + L-PRRS subgroup had the most prolonged OS. Drug sensitivity analyses showed that PRRS was significantly negatively correlated with the sensitivity of cisplatin, besarotene, etc., while it was significantly positively correlated with the sensitivity of kin001-135. Eventually, a nomogram was constructed based on PRRS and clinical characters of LUAD. Overall, the pyroptosis-related signature is helpful for prognostic prediction and in guiding treatment for LUAD patients.

Prognostic and immunological characteristics of CDK1 in lung adenocarcinoma: A systematic analysis.

Cyclin-dependent kinases (CDKs) play a key role in cell proliferation in lung adenocarcinoma (LUAD). Comprehensive analysis of CDKs to elucidate their clinical significance and interactions with the tumor immune microenvironment is needed. RNA expression, somatic mutation, copy number variation, and single-cell RNA sequencing data were downloaded from public datasets. First, we comprehensively evaluated the expression profile and prognostic characteristics of 26 CDKs in LUAD, and CDK1 was selected as a candidate for further analysis. Then, a systematic analysis was performed to explore the relationships of CDK1 with clinical characteristics and tumor immune microenvironment factors in LUAD. CDK1 was markedly upregulated at both the mRNA and protein level in LUAD. Moreover, overexpression of CDK1 was related to poor clinical outcomes. CDK1 coexpressed genes were mainly involved in the cell cycle, the DNA repair process, and the p53 signaling pathway. In addition, CDK1 expression was found to be correlated with the expression of multiple immunomodulators and chemokines, which participate in activating and suppressing the immune microenvironment. CDK1 expression was also correlated with increased infiltration of numerous immune cells, including CD4+ T cells and M1 macrophages. Patients with high CDK1 expression tended to have a poor response to immunotherapy but were sensitive to multiple chemotherapies and targeted drugs. The MDK-NCL and SPP1-CD44 ligand-receptor pairs were markedly activated in the intercellular communication network. CDK1 was an independent prognostic factor for LUAD and improved the ability to predict overall survival when combined with tumor stage. CDK1 plays an essential role in reshaping the tumor immune microenvironment and might be a prognostic and treatment biomarker in LUAD.

High SERPINH1 expression predicts poor prognosis in lung adenocarcinoma.

Serpine Protease Inhibitorclade H1 (SERPINH1) is abnormally expressed in a variety of tumor tissues and is linked to the biological processes of tumorigenesis, migration, invasion, and metastasis. SERPINH1 expression and prognosis in malignant tumors, such as gastric, colorectal, and breast cancers, have previously been studied, but the gene has not yet been investigated in lung adenocarcinoma (LUAD) in terms of prognosis and the potential mechanisms of action. SERPINH1 was identified as an independent prognostic factor for LUAD in The Cancer Genome Atlas (TCGA) cohort and Affiliated Hospital of Nantong University (NTU) cohort (the LUAD data set) by univariate and multivariate Cox regression analyses. Additionally, we performed immunohistochemical staining to analyze the expression of SERPINH1 in LUAD and normal lung tissue. Based on the TCGA database, we analyzed the correlation of this gene with the tumor mutation burden (TMB), tumor microenvironment, immune infiltration, immune checkpoints, and anti-tumor drugs using the R language-related R package. SERPINH1 was highly expressed in LUAD tissue. Kaplan-Meier survival curves in both the TCGA cohort and the NTU cohort showed that the SERPINH1 low-expression group had a higher survival rate than the high-expression group. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of the SERPINH1 co-expressed genes revealed that the gene was associated with the extracellular matrix and cell proliferation and migration. The analysis of SERPINH1 and the TMB revealed a superior survival advantage for patients with high TMB and high SERPINH1 expression, and worse survival for those with low TMB and high SERPINH1 expression. The analysis of the tumor microenvironment (TME) and immune infiltration revealed that the high and low expression of SERPINH1 was associated with different immune infiltration characteristics. The analysis of the immune checkpoints and anti-tumor drugs showed that immunotherapy and anti-neoplastic treatment were more efficacious in the high SERPINH1 expression group than the low SERPINH1 expression group. Using LUAD tissues and clinical samples, we showed that SERPINH1 can be used as a prognostic biomarker for LUAD. Our findings provide a new approach and strategy for the clinical treatment of LUAD patients.

The role of radiotherapy-related autophagy genes in the prognosis and immune infiltration in lung adenocarcinoma.

BackgroundThere is a close relationship between radiotherapy and autophagy in tumors, but the prognostic role of radiotherapy-related autophagy genes (RRAGs) in lung adenocarcinoma (LUAD) remains unclear.MethodsData used in the current study were extracted from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted gene co-expression network analysis (WGCNA) was executed to recognize module genes associated with radiotherapy. The differentially expressed genes (DEGs) between different radiotherapy response groups were filtered via edgeR package. The differentially expressed radiotherapy-related autophagy genes (DERRAGs) were obtained by overlapping the module genes, DEGs, and autophagy genes (ATGs). Then, prognostic autophagy genes were selected by Cox analyses, and a risk model and nomogram were subsequently built. Gene Set Enrichment Analysis (GSEA) and single-sample Gene Set Enrichment Analysis (ssGSEA) were performed to investigate potential mechanisms through which prognostic autophagy signatures regulate LUAD. Radiotherapy-resistant cell lines (A549IR and PC9IR) were established after exposure to hypo-fractionated irradiation. Ultimately, mRNA expression was validated by quantitative real-time PCR (qRT-PCR), and relative protein levels were measured in different cell lines by western blot.ResultsA total of 11 DERRAGs were identified in LUAD. After Cox analyses, SHC1, NAPSA, and AURKA were filtered as prognostic signatures in LUAD. Then, the risk score model was constructed using the prognostic signatures, which had a good performance in predicting the prognosis, as evidenced by receiver operating characteristics curves. Furthermore, Cox regression analyses demonstrated that risk score was deemed as an independent prognostic factor in LUAD. Moreover, GSEA and ssGSEA results revealed that prognostic RRAGs may regulate LUAD by modulating the immune microenvironment and affecting cell proliferation. The colony formation assay showed that the radiosensitivity of radiation-resistant cell lines was lower than that of primary cells. The western blot assay found that the levels of autophagy were elevated in the radiotherapy-resistant cell lines. Moreover, the expression of DERRAGs (SHC1, AURKA) was higher in the radiotherapy-resistant cells than in primary cells.ConclusionOur study explored the role of RRAGs in the prognosis of LUAD and identified three biomarkers. The findings enhanced the understanding of the relationship between radiotherapy, autophagy, and prognosis in LUAD and provided potential therapeutic targets for LUAD patients.

Deep learning reveals cuproptosis features assist in predict prognosis and guide immunotherapy in lung adenocarcinoma.

BackgroundCuproptosis is a recently found non-apoptotic cell death type that holds promise as an emerging therapeutic modality in lung adenocarcinoma (LUAD) patients who develop resistance to radiotherapy and chemotherapy. However, the Cuproptosis’ role in the onset and progression of LUAD remains unclear.MethodsCuproptosis-related genes (CRGs) were identified by a co-expression network approach based on LUAD cell line data from radiotherapy, and a robust risk model was developed using deep learning techniques based on prognostic CRGs and explored the value of deep learning models systematically for clinical applications, functional enrichment analysis, immune infiltration analysis, and genomic variation analysis.ResultsA three-layer artificial neural network risk model was constructed based on 15 independent prognostic radiotherapy-related CRGs. The risk model was observed as a robust independent prognostic factor for LUAD in the training as well as three external validation cohorts. The patients present in the low-risk group were found to have immune “hot” tumors exhibiting anticancer activity, whereas the high-risk group patients had immune “cold” tumors with active metabolism and proliferation. The high-risk group patients were more sensitive to chemotherapy whereas the low-risk group patients were more sensitive to immunotherapy. Genomic variants did not vary considerably among both groups of patients.ConclusionOur findings advance the understanding of cuproptosis and offer fresh perspectives on the clinical management and precision therapy of LUAD.

Identification of a pyroptosis-related lncRNA signature in the regulation of prognosis, metabolism signals and immune infiltration in lung adenocarcinoma.

Pyroptosis is a cell death pathway that plays a significant role in lung adenocarcinoma (LUAD). Also, studies regarding the correlation between the expression of long non-coding RNAs (lncRNAs) and the mechanism of LUAD has aroused concern around the world. The purpose of this paper is to explore the underlying relationship of differentially expressed lncRNAs and pyroptosis-related genes. The least absolute shrinkage and selection operator (LASSO) algorithm and Cox regression were applied to construct a prognostic risk score model from the TCGA database. A pyroptosis-related five-lncRNA signature (CRNDE, HHLA3, MIR193BHG, LINC00941, LINC01843) was considered to be correlated to the prognosis and immune response of LUAD patients. In addition, the cytological experiments revealed that aberrantly expressed HHLA3 displayed a proliferation promotion role in LUAD cells A549 and H460. Next, the forest and nomogram plots have shown this lncRNA signature could be served as an independent prognostic factor for LUAD. The ROC curves further identified the prognostic value of the five-lncRNA signature. The infiltration of immune cells, such as T cells CD8, T cells CD4 memory resting, T cells CD4 memory activated and M0 macrophages were greatly different between the high-risk group and the low-risk group. It implicated that the signature is significantly effective in immunotherapy of LUAD patients. This study has supplied a novel pyroptosis-related lncRNA signature and provided a predictive model for prognosis and immune response of LUAD patients.

Pan-cancer analysis identifies CDCA3 as a novel prognostic marker associated with immune infiltration in lung adenocarcinoma through bioinformatics analysis.

BackgroundLung adenocarcinoma (LUAD) is the most common subtype of lung malignancy. However, the expression of cell division cycle-associated protein-3 (CDCA3) and its significance in LUAD remain unclear. In this study, we investigated the functional role of CDCA3 in LUAD through bioinformatics analysis and expected to provide a new direction for clinical treatment.MethodsThe expression of CDCA3 was analyzed by online database. The association between the expression of CDCA3 and clinical parameters with LUAD was explored in TCGA. Survival and independent prognostic analysis were performed by TCGA database and the GSE30219 and GSE31210 datasets. Furthermore, Enrichment analyses were conducted to analyze the functions of CDCA3. Afterward, the relationship between CDCA3 and immune infiltration was investigated. Additionally, a competing endogenous RNA (ceRNA) regulatory network related to CDCA3 was constructed. Finally, CDCA3 expression was validated in clinical tissues by immunohistochemistry (IHC), real-time quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), and western blotting (WB).ResultsCDCA3 expression was upregulated in 20 tumors and was significantly higher in LUAD compared with normal tissues in3 datasets. In addition, CDCA3 was significantly correlated with age, gender, stage, N, and smoking status. Kaplan-Meier survival curves showed that LUAD samples with higher CDCA3 expression were associated with poorer overall survival (OS) and disease-free survival (DFS). Univariate Cox regression analysis showed that the p value of CDCA3 expression was less than 0.05 (P<0.05) and it appeared in the results of multivariate Cox regression analysis (HR ≥1), indicating that CDCA3 can be used as an independent prognostic factor for LUAD. Intriguingly, Gene Set Enrichment Analysis (GSEA) suggested that CDCA3 was correlated with DNA-related terms and metabolic-related pathways in LUAD. CDCA3 expression was correlated with four immune scores and 14 immune cells in different groups. Next, a ceRNA network was constructed with CDCA3, and the experimental results of IHC, qRT-PCR, and WB were consistent with the bioinformatic analysis.ConclusionsCDCA3 could serve as a prognostic biomarker for LUAD.

GRSF1 predicts an unfavorable prognosis and promotes tumorigenesis in lung adenocarcinoma based on bioinformatics analysis and in vitro validation.

BackgroundEffective biomarkers play a critical role in improving clinical approaches to treat lung adenocarcinoma (LUAD). However, many existing biomarkers have limitations due to a lot of factors, requiring the development of additional biomarkers to effectively predict the disease course and prognosis of LUAD. Guanine-rich RNA sequence binding factor 1 (GRSF1) participates in multiple biological processes, but its regulatory effect on LUAD remains unknown. The present study aimed to investigate the clinicopathological importance and biological role of GRSF1 in LUAD.MethodsThe expression of GRSF1 was evaluated using multiple service portals. X-Tile software were used to determine the high and low GRSF1 groups and the relationships between GRSF1 expression and clinicopathological characteristics were then analyzed by R packages. Besides, prognostic significance was identified by the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Kaplan-Meier (K-M) Plotter. Overall survival (OS) and disease-free survival (DFS) was the main outcome of prognosis analysis. The DNA copy number alterations (CNAs) and methylations were calculated using cBioPortal and R packages. The co-expressed genes of GRSF1 were obtained from LinkedOmics, and functional networks were then constructed by R clusterProfiler. Additionally, cell counting kit 8 (CCK-8) and colony formation assays were applied to verify the proliferation effects of GRSF1 on LUAD cells.ResultsGRSF1 was significantly upregulated in the LUAD tissues compared to the non-tumor lung tissues (all P<0.05), and its expression was significantly correlated with gender (χ2=6.873, P=0.009) and T classification (χ2=13.62, P=0.003). Higher GRSF1 expression indicated worse OS [hazards ratio (HR) =1.6, P=0.0022] and DFS (HR =1.4, P=0.043), which suggested that GRSF1 was an independent prognostic factor for LUAD. DNA gain/amplification and hypomethylation may also contribute to GRSF1 upregulation. The functional annotation showed that GRSF1 regulates tumorigenesis through several signaling pathways. The knockdown of GRSF1 significantly suppressed lung cancer cell proliferation in vitro.ConclusionsThe high expression of GRSF1 indicated an unfavorable prognosis and was closely related to LUAD tumor occurrence and development, which could be used as an effective prognostic biomarker for patients suffering from LUAD.

Development and validation of endoplasmic reticulum stress-related eight-gene signature for predicting the overall survival of lung adenocarcinoma

BackgroundThe high case-fatality rate of patients with lung adenocarcinoma (LUAD) emphasizes the importance of identifying a robust and reliable prognostic signature for LUAD patients. Endoplasmic reticulum (ER) stress results from protein misfolding imbalance and has been shown to participate in the development of cancer. We aimed to develop and validation a reliable and robust ER stress-related prognostic signature to accurately predict prognosis for patients with LUAD.MethodsThe mRNA expressions data and the clinical information were downloaded from The Cancer Genome Atlas (TCGA) as training set. The data of external validation sets were downloaded from GEO database with the accession number GSE 30219, GSE 31210, GSE 50081 and GSE 37745. Univariate Cox regression analyses was performed to identify mRNAs associated with overall survival (OS) in LUAD. ER-associated genes were retrieved using GeneCards database. Next, we construct the best risk score model by the least absolute shrinkage and selection operator (LASSO) regression with tenfold cross-validation. Subsequently, predictive models and risk scores were developed in the TCGA training dataset. Cox proportional hazards regression models were used for univariate and multivariate analysis of risk score and clinicopathologic characteristics. As a validation set GSE30219, GSE31210 and (GSE50081+GSE37745) were used to validate the predictive performance of the model in TCGA. Finally, functional enrichment analysis, including the gene ontology (GO) enrichment analysis, the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and gene set enrichment analysis (GSEA) were performed to further explore function and mechanisms.ResultsA prognostic prediction model based on eight genes was developed in the TCGA training dataset. As expected, in validation sets, patients with higher risk scores were found to have worse prognosis. Time-dependent ROC curve analyses demonstrated that the risk score model was reliable. The nomograms showed excellent predictive ability. Multivariate Cox regression analyses indicated that the risk score was an independent prognostic factor for LUAD. Additionally, functional enrichment analysis showed that the relevant biomarkers were enriched in cell cycle and glycolysis related signaling pathways.ConclusionsThe 8-gene signature may enable improved the prediction of clinical events and decisions about management of LUAD.

Extra Spindle Pole Bodies-Like 1 Serves as a Prognostic Biomarker and Promotes Lung Adenocarcinoma Metastasis

Extra spindle pole bodies-like 1 (ESPL1), a cysteine endopeptidase, plays a vital role in chromosome inheritance. However, the association of ESPL1 with prognosis and immune infiltration in lung adenocarcinoma (LUAD) has not yet been explored. Here, we analyzed the expression level, prognostic values, diagnostic value, and immune infiltration level in LUAD using various databases. Immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR) assays were used to detect the expression of ESPL1 in LUAD tissues and cell lines. In this study, we found that ESPL1 was upregulated in LUAD and a higher expression of ESPL1 was correlated with unfavorable prognosis in LUAD. Meanwhile, Cox hazard regression analysis results suggested that ESPL1 may be an independent prognostic factor for LUAD. Moreover, we demonstrated that ESPL1 expression was significantly correlated with immune infiltration of Th2 and dendritic cells in LUAD. We also confirmed that DNA copy number amplification and DNA hypo-methylation were positively correlated with ESPL1 expression in LUAD. Additionally, DNA copy number amplification was significantly associated with adverse clinical outcomes in LUAD. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) confirmed that ESPL1 was mainly involved in the DNA replication and glycolysis signaling pathway. Finally, we revealed that ESPL1 was highly expressed in LUAD tissues and cell lines. Knockdown of ESPL1 significantly inhibited cell migration and the invasion abilities of LUAD. Our study comprehensively confirmed that ESPL1 expression may serve as a novel prognostic biomarker for both the clinical outcome and immune cell infiltration in LUAD.

Identification and Validation of lncRNA-AC087588.2 in Lung Adenocarcinoma: A Novel Prognostic and Diagnostic Indicator.

Lung adenocarcinoma (LUAD) is the most common histological lung cancer, and it is the leading cause of cancer-related deaths worldwide. Long non-coding RNAs (lncRNAs) have been implicated in the initiation and progression of various cancers. LncRNA-AC087588.2 (ENSG00000274976) is a novel lncRNA that is abnormally expressed in diverse cancer types, including LUAD. However, the clinical significance, prognostic value, diagnostic value, immune role, and the potential biological function of AC087588.2 LUAD remain elusive. In this study, we found that AC087588.2 was upregulated and associated with a poor prognosis in LUAD. In addition, univariate and multivariate Cox regression analysis indicated that AC087588.2 could be an independent prognostic factor for LUAD. Functionally, the knockdown of AC087588.2 restrained LUAD cell proliferation and migration in vitro. Finally, we constructed a ceRNA network that included hsa-miR-30a-5p and four mRNAs (ANLN, POLR3G, EHBP1, and ERO1A) specific to AC087588.2 in LUAD. The Kaplan–Meier survival analysis showed that lower expression of hsa-miR-30a-5p and higher expression of ANLN, POLR3G, EHBP1, and ERO1A were associated with adverse clinical outcomes in patients with LUAD. This finding provided a comprehensive view of the AC087588.2-mediated ceRNA network in LUAD, thereby highlighting its potential role in the diagnosis and prognosis of LUAD.