Prognostic Biomarker In Lung Adenocarcinoma Research Articles

EP03.05-01 Aberrant Methylation of ZNF577 As a Potential Prognostic Biomarker for Lung Adenocarcinoma

EP03.05-01 Aberrant Methylation of ZNF577 As a Potential Prognostic Biomarker for Lung Adenocarcinoma

Low UPB1 Level Correlates With Poor Prognosis in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is a critical cancer with high mortality, worse prognosis, and crucial lymphatic metastasis. Consequently, prognostic biomarkers for LUAD are truly required. β-Ureidopropionase (UPB1) is abnormally expressed in various cancers. However, the function of UPB1 in LUAD is still ambiguous. This study aimed to explore the expression profile and prognostic significance of UPB1 in LUAD. The differential UPB1 levels in pan cancers and their prognostic significance were comprehensively investigated through Gene Expression Profiling Interactive Analysis, UALCAN, Tumor Immune Estimation Resource, and Kaplan-Meier plotter platform. The correlation between UPB1 and tumor infiltration immune cells was explored using Tumor Immune Estimation Resource, Gene Expression Profiling Interactive Analysis, and Tumor-Immune System Interactions and Drug Bank database databases. The UPB1 level was abnormally expressed in pan-tumor tissue than in adjacent tissue from The Cancer Genome Atlas tool. Low UPB1 level was correlated with poor overall survival in patients with LUAD. Furthermore, a comparison of the various pathologic characteristics of LUAD between high and low UPB1 level subgroups revealed that low UPB1 expression was correlated with lymph node metastasis. Kaplan-Meier survival analysis indicated that a low UPB1 level was associated with worse progression‑free survival and overall survival in patients with LUAD. Univariate and multivariate analyses suggested that UPB1 could be a useful prognostic indicator for LUAD. Abnormal UPB1 may be correlated with aberrant LUAD immune infiltration, prompting a worse survival outcome. Results showed that low UPB1 is correlated with a worse prognosis of LUAD and may be a valuable prognostic indicator for LUAD.

Identification of TLRs as potential prognostic biomarkers for lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common tumors with the highest cancer-related death rate worldwide. Early diagnosis of LUAD can improve survival. Abnormal expression of the Toll-like receptors (TLRs) is related to tumorigenesis and development, inflammation and immune infiltration. However, the role of TLRs as an immunotherapy target and prognostic marker in lung adenocarcinoma is not well understood and needs to be analyzed. Relevant data obtained from databases such as ONCOMINE, UALCAN, GEPIA, and the Kaplan-Meier plotter, GSCALite, GeneMANIA, DAVID 6.8, Metascape, LinkedOmics and TIMER, to compare transcriptional TLRs and survival data of patients with LUAD. The expression levels of TLR1/2/3/4/5/7/8 in LUAD tissues were significantly reduced while the expression levels of TLR6/9/10 were significantly elevated. LUAD patients having low expression of TLR1/2/3/5/8 and high expression of TLR9 had a poor overall survival while patients with low expression of TLR2/3/7 presented with worse first progress. TLR4, TLR7 and TLR8 are the 3 most frequently mutated genes in the TLR family. Correlation suggested a low to moderate correlation among TLR family. TLR family was also involved in the activation or inhibition of the famous cancer related pathways. Analysis of immune infiltrates analysis suggested that TLR1/2/7/8 levels significantly correlated with immune infiltration level. Enrichment analysis revealed that TLRs were involved in TLR signaling pathway, immune response, inflammatory response, primary immunodeficiency, regulation of IL-8 production and PI3K-Akt signaling pathway. Our results provided information on TLRs expression and potential regulatory networks in LUAD. Moreover, our results suggested TLR2/7/8 as a potential prognostic biomarker for lung adenocarcinoma.

Identification of ALG3 as a potential prognostic biomarker in lung adenocarcinoma

BackgroundThe abnormal expression of Alpha-1,3-mannosyltransferase (ALG3) has been implicated in tumor promotion. However, the clinical significance of ALG3 in Lung Adenocarcinoma (LUAD) remains poorly understood. Therefore, we aimed to assess the prognostic value of ALG3 and its association with immune infiltrates in LUAD. MethodsThe transcriptional expression profiles of ALG3 were obtained from the Cancer Genome Atlas (TCGA), comparing lung adenocarcinoma tissue with normal tissues. To determine the prognostic significance of AGL3, Kaplan-Meier plotter, and Cox regression analysis were employed. Logistic regression was utilized to analyze the association between ALG3 expression and clinical characteristics. Additionally, a receiver operating characteristic (ROC) curve and a nomogram were constructed. To explore the underlying mechanisms, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and gene set enrichment analysis (GSEA) was conducted. The relationship between AGL3A mRNA expression and immune infiltrates was investigated using the tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB). Furthermore, an in vitro experiment was performed to assess the impact of ALG3 mRNA on lung cancer stemness abilities and examine key signaling pathway proteins. ResultsOur results revealed the ALG3 mRNA and protein expression in patients with LUAD was much higher than that in adjacent normal tissues. High expression of ALG3 was significantly associated with N stage (N0, HR = 1.98, P = 0.002), pathological stage (stage I, HR = 2.09, P = 0.003), and the number of pack years (<40, HR = 2.58, P = 0.001). Kaplan–Meier survival analysis showed that high expression of ALG3 was associated with poor overall survival (P < 0.001), disease-free survival (P < 0.001), and progression-free interval (P = 0.007). Through multivariate analysis, it was determined that elevated ALG3 expression independently impacted overall survival (HR = 1.325, P = 0.04). The Tumor Immune Estimation Resource discovered a link between ALG3 expression and tumor-infiltrating immune cells in LUAD. Additionally, ROC analysis proved that ALG3 is a reliable diagnostic marker for LUAD (AUC:0.923). Functional pathways analysis identified that ALG3 is negatively correlated with FAT4. We performed qRT-PCR to assess that knockdown ALG3 expression significantly upregulated FAT4 expression. Spheroid assay and flow cytometry analysis results showed that downregulated of ALG3 inhibited H1975 cell line stemness. Western blot analysis revealed that decreased ALG3 inhibited the YAP/TAZ signal pathway. ConclusionHigh expression of ALG3 is strongly associated with poor prognosis and immune infiltrates in LUAD.

Identification of lysosomal genes associated with prognosis in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, representing 40% of all cases of this tumor. Despite immense improvements in understanding the molecular basis, diagnosis, and treatment of LUAD, its recurrence rate is still high. RNA-seq data from The Cancer Genome Atlas (TCGA) LUAD cohort were download from Genomic Data Commons Portal. The GSE13213 dataset from Gene Expression Omnibus (GEO) was used for external validation. Differential prognostic lysosome-related genes (LRGs) were identified by overlapping survival-related genes obtained via univariate Cox regression analysis with differentially expressed genes (DEGs). The prognostic model was built using Kaplan-Meier curves and least absolute shrinkage and selection operator (LASSO) analyses. In addition, univariate and multivariate Cox analyses were employed to identify independent prognostic factors. The responses of patients to immune checkpoint inhibitors (ICIs) were further predicted. The pRRophetic package and rank-sum test were used to compute the half maximal inhibitory concentrations (IC50) of 56 chemotherapeutic drugs and their differential effects in the low- and high-risk groups. Moreover, quantitative real-time polymerase chain reaction, Western blot, and human protein atlas (HPA) database were used to verify the expression of the four prognostic biomarkers in LUAD. Of the nine candidate differential prognostic LRGs, GATA2, TFAP2A, LMBRD1, and KRT8 were selected as prognostic biomarkers. The prediction of the risk model was validated to be reliable. Cox independent prognostic analysis revealed that risk score and stage were independent prognostic factors in LUAD. Furthermore, the nomogram and calibration curves of the independent prognostic factors performed well. Differential analysis of ICIs revealed CD276, ICOS, PDCD1LG2, CD27, TNFRSF18, TNFSF9, ENTPD1, and NT5E to be expressed differently in the low- and high-risk groups. The IC50 values of 12 chemotherapeutic drugs, including epothilone.B, JNK.inhibitor.VIII, and AKT.inhibitor.VIII, significantly differed between the two risk groups. KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in LUAD cell lines. In addition, KRT8 and TFAP2A were highly expressed, while GATA2 and LMBRD1 were poorly expressed in tumor tissues. Four key prognostic biomarkers-GATA2, TFAP2A, LMBRD1, and KRT8-were used to construct a significant prognostic model for LUAD patients.

A novel defined pyroptosis-related gene signature predicts prognosis and correlates with the tumour immune microenvironment in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common causes of cancer-related death. The role of pyroptosis in LUAD remains unclear. Our study aimed to identify a prognostic signature of pyroptosis-related genes (PRGs) and explore the connection of PRGs with the tumour microenvironment in LUAD. Gene expression and clinical information were obtained from The Cancer Genome Atlas database. Consensus clustering was applied to classify LUAD patients. The least absolute shrinkage and selection operator Cox and multivariate Cox regression models were used to generate a PRG-related prognostic signature. The correlations between PRGs and tumour-infiltrating immune cells or the tumour mutational burden were analysed by Spearman’s correlation analysis. In this study, 44 PRGs significantly differed in expression between LUAD and normal tissues. Based on these genes, patients were clustered into three clusters with significantly different distributions of tumour-infiltrating immune cells and immune checkpoint regulators. A total of four PRGs (NLRP1, HMGB1, CYCS, and BAK1) were used to construct a prognostic model. Significant correlations were observed between these prognostic PRGs and immune cell infiltration or the tumour mutational burden. Predictive nomogram results showed that BAK1 could be an independent prognostic biomarker in LUAD. Additionally, the expression level of BAK1 was validated in two independent Gene Expression Omnibus cohorts. Our identified prognostic PRG signature may provide insight for future studies targeting pyroptosis and the tumour microenvironment in LUAD. Future studies are needed to verify our current findings.

Identification of Novel Prognostic Long Non-coding RNAs in Lung Adenocarcinoma Using WGCNA Analysis.

Long non-coding RNAs play crucial role in the tumorigenesis of lung adenocarcinoma (LUAD). However, the function of a large number of lncRNAs in LUAD has not been investigated yet. Weighted gene correlation network analysis (WGCNA) was applied to construct the co-expression module in the TCGA-LUAD cohort. Protein-protein interaction (PPI) network was used to explore the relationship of genes in the key module. The function of the key module on the prognosis in LUAD was analyzed using GO and KEGG analysis. Finally, we constructed the mRNA-lncRNA co-expression network in the key module to identify the hub lncRNAs that play crucial role in the prognosis in LUAD. The most highly expressed 2500 mRNAs and 2500 lncRNAs in the TCGA-LUAD cohort were clustered into 21 modules. After analyzing the correlation between the module and prognostic clinical traits, the Tan module, consisting of 130 genes, was selected as the key module on the prognosis in LUAD. And then, we found that genes in the key module were majorly enriched in ten multiple signaling pathways. Subsequently, we constructed the mRNA-lncRNA co-expression network based on the genes in the key module. Finally, we identified three lncRNAs and nineteen mRNAs that could be the promising prognostic biomarkers for LUAD. We identified three lncRNAs (MIR99AHG, ADAMTS9-AS2, and AC037459.2) and nineteen mRNAs as potential prognostic biomarkers in LUAD, which provided new insight for prognosis monitoring and therapy development in LUAD.

Integrated Single-Cell and Transcriptome Sequencing Analyses Identify Dipeptidase 2 as an Immune-Associated Prognostic Biomarker for Lung Adenocarcinoma.

Dipeptidase 2 (DPEP2) is a dipeptidyl peptidase that plays an important role in the hydrolysis of leukotriene D4 (LTD4) to leukotriene E4 (LTE4). Previous studies have suggested that LTD4 promotes tumor progression and survival in non-small cell lung cancer (NSCLC). Therefore, we hypothesized that DPEP2 may play a pivotal role in this tumor. Given that lung adenocarcinoma (LUAD) is the most common subtype of NSCLC, our study aimed to examine the expression and function of DPEP2 in LUAD. Based on bioinformatics and the analysis of clinical samples, our findings revealed that DPEP2 is highly expressed in normal lung tissues, but downregulated in LUAD tissues, and its expression levels were significantly associated with clinical indicators of tumor grade and prognosis. Pathway enrichment analysis showed that DPEP2 is involved in biological processes such as chemokine signaling pathways, leukocyte trans-endothelial migration, and humoral immune responses in LUAD. In addition, DPEP2 expression was significantly associated with various immune cells, especially monocytes-macrophages. Single-cell transcriptome data further confirmed the expression of DPEP2 dominantly in macrophages from normal lung tissues. Analysis of the TCIA database revealed that high DPEP2 expression is associated with a stronger response to immune checkpoint inhibitors such as CTLA4 and PD1, and determines sensitivity to LUAD therapeutic agents. Furthermore, we found that DPEP2 inhibits the migration and invasion of LUAD cells. Therefore, DPEP2 may serve as a potential immune biomarker and therapeutic target for LUAD, providing novel therapeutic approaches for this disease.

LncRNA PCBP1-AS1 mediated downregulation of ITGAL as a prognostic biomarker in lung adenocarcinoma.

Integrin alpha L (ITGAL) seemed to play a critical role in carcinogenesis and immune regulation. Nevertheless, the effects of ITGAL on non-small cell lung cancer (NSCLC) remain elusive. The present paper intended to determine the effects of ITGAL in NSCLC via the integration of bioinformatic analyses. In this study, we found that the mRNA and protein levels of ITGAL were downregulated in NSCLC tissues. Significantly, low ITGAL expression was related to poorer prognosis and increased malignancy of NSCLC. In addition, GO analysis and KEGG pathway analysis revealed that the coexpressed genes of ITGAL were predominantly associated with various immune-associated signaling pathways, like the T cell receptor signaling pathway, Th17 cell differentiation, chemokine signaling pathway, and NF-κB signaling pathway. Our result indicated that lncRNA-mediated downregulation of integrin alpha L expression was tightly related to immunocyte infiltration, immune modulators, and chemotactic factors in NSCLC, which potentially serves as a biomarker for clinical prognosis prediction and immunotherapy of NSCLC. This is the first comprehensive analysis of ITGAL in the prognosis, immune microenvironment, and immunotherapy of lung adenocarcinoma. ITGAL are promising biomarkers for predicting clinical outcomes and immunotherapy responses in patients with NSCLC.

Key genes involved with prognosis were identified in lung adenocarcinoma by integrated bioinformatics analysis

ObjectiveBy screening the core genes in lung adenocarcinoma (LUAD) with bioinformatics, our study evaluated its prognosis value and role in infiltration process of immune cells. MethodsUsing GEO database, we screened 5 gene chips, including GSE11072, GSE32863, GSE43458, GSE115002, and GSE116959. Then, we obtained the corresponding differentially expressed genes by analyzed 5 gene chips online by GEO2R (P < 0.05, |logFC| > 1). Then, through DAVID online platform, Cytoscape 3.6.1 software and PPI network analysis, the network was visualized and obtain the final core genes. Next, we plan to use the GEPIA, UALCAN, Kaplan–Meier plotter and Time 2.0 database for corresponding analysis. The GEPIA database was used to verify the expression of core genes in LUAD and normal lung tissues, and survival analysis was used to evaluate the value of core genes in the prognosis of LUAD patients. UALCAN was used to verify the expression of the LUAD core gene and promoter methylation status, and the predictive value of core genes was evaluated in LUAD patients by the Kaplan–Meier plotter online tool. Then, we used the Time 2.0 database to identify the relationship to immune infiltration in LUAD. Finally, we used the human protein atlas (HPA) database for online immunohistochemical analysis of the expressed proteins. ResultsThe expression of CCNB2 and CDC20 in LUAD were higher than those in normal lung tissues, their increased expression was negatively correlated with the overall survival rate of LUAD, and they were involved in cell cycle signal transduction, oocyte meiosis signal transduction as well as the infiltration process of immune cells in LUAD. The expression proteins of CCNB2 and CDC20 were also different in lung cancer tissue and normal lung tissue. Therefore, CCNB2 and CDC20 were identified as the vital core genes. ConclusionCCNB2 and CDC20 are essential genes that may constitute prognostic biomarkers in LUAD, they also participate the immune infiltration process and protein expression process of LUAD, and might provides basis for clinical anti-tumor drug research.

LINC00943 regulates miR-1252-5p/YWHAH axis to promote tumor proliferation and metastasis in lung adenocarcinoma

Lung cancer is the most common malignant tumor worldwide. In recent years, the incidence of lung adenocarcinoma (LAD) has increased significantly, with an unfavorable 5-year survival rate. Long non-coding RNAs (lncRNAs) have been shown to play a significant role in the emergence, growth, and metastasis of tumors. However, the functional role and mechanism of LINC00943 in LAD progression have not yet been investigated. Aberrant expressions of LINC00943, miR-1252-5p, and YWHAH were determined by RT-qPCR and Western blot analyses. The binding relationship between miR-1252-5p and LINC00943 or YWHAH was examined by Pearson's correlation analysis, RNA pull-down, and dual-luciferase reporter assays. MTT assay was conducted to measure cell viability and colony formation assay was performed to evaluate cell proliferation potential. Transwell assay was used to investigate cell migration and invasion and flow cytometry was applied to evaluate cell apoptosis. We found that LINC00943 was highly expressed in LAD tissue samples and cell lines and was a reliable biomarker with high sensitivity, and specificity (P < 0.0001; AUC: 0.8966) for LAD detection. LINC00943 was mainly localized in the cytoplasm. In vitro, LINC00943 promoted LAD cell proliferation, migration, and invasion; however, silencing LINC00943 inhibited LAD tumor metastasis. Mechanistically, LINC00943 was competitively bound with miR-1252-5p to enhance YWHAH expression. Moreover, LINC00943 silencing sponged miR-1252-5p to inhibit YWHAH, thereby retraining LAD cell malignant behaviors. In summary, LINC00943 facilitates LAD cell malignancy through sponging miR-1252-5p to upregulate YWHAH. LINC00943 is a novel lncRNA that serves as an oncogene and might be used as a prognostic biomarker for LAD.

Aberrant methylation of dipeptidyl peptidase‑like 6 as a potential prognostic biomarker for lung adenocarcinoma.

We previously performed the genome-wide screening of aberrantly methylated CpG islands (CGIs) using the paired tumorous and non-tumorous tissues of 12 lung adenocarcinomas (LADC). In comparisons with paired normal lung tissues, dipeptidyl peptidase-like 6 (DPP6) has been identified as the most significantly hypermethylated CGI in LADC. DPP6 is a protein that modulates A-type potassium channels in the somatodendritic compartments of neurons, which play a role in synaptic plasticity. Previous studies have showed that DPP6 is downregulated in cancers, such as acute myeloid leukemia and melanoma, but upregulated in colon cancer, which is attributed to hyper- and hypomethylation, respectively. The present study investigated the methylation and expression levels of DPP6 and its prognostic value in patients with LADC. The DNA methylation and mRNA expression levels of DPP6 in surgically resected LADC tissues were examined by bisulfite pyrosequencing and reverse transcription-quantitative PCR, respectively. The DNA methylation and mRNA expression levels of DPP6 were both significantly higher in LADC tissues compared with in normal lung tissues (n=25; P<0.0001). Overall and disease-free survival rates were significantly higher in LADC with high mRNA expression levels compared with those with low levels. In conclusion, epigenetic alterations in DPP6 were significantly higher in LADC tissues compared with in normal lung tissues, which may contribute to the malignant features and worse prognosis of these patients.

Integrative learning in developing an immunologic lncRNA signature as a consensus risk-stratification tool for lung adenocarcinoma.

In the tumor immune microenvironment, the contribution of innate and adaptive immune cells to tumor progression has been consistently demonstrated. However, reliable prognostic biomarkers for lung adenocarcinoma (LUAD) have not yet been identified. We thus developed and validated an immunologic long noncoding RNA (lncRNA) signature (ILLS) to facilitate the classification of patients with high and low risk and provide potential "made-to-measure" treatment choices. The LUAD data sets were obtained and processed from public databases of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The abundance of immune infiltration and its related pathways were calculated through consensus clustering, weighted gene coexpression network analysis (WGCNA), and an integrated ImmLnc to identify immune-related lncRNAs and extract immune-related prognostic lncRNAs. Based on the integrative procedure, the best algorithm composition was least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression in both directions to develop the ILLS in the TCGA-LUAD data set and validate the predictive power of 4 independent data sets, GSE31210, GSE37745, GSE30219, and GSE50081 through survival analysis, receiver operating characteristic (ROC) analysis, and multivariate Cox regression. The concordance index (C-index) analysis was transversely compared with 49 published signatures in the above 5 data sets to further confirm its stability and superiority. Finally, drug sensitivity analysis was conducted to explore potential therapeutic agents. Patients from the high-risk groups consistently had worse overall survival (OS) compared to the low-risk groups. ILLS proved to be an independent prognostic factor with favorable sensitivity and specificity. Among the 4 GEO data sets, compared to those reported in the other literature, ILLS maintained stable prediction ability and was more suitable as a consensus risk-stratification tool. However, The Cancer Immunome Atlas and IMvigor210 data sets demonstrated practical utility in recognizing target populations with effective immunotherapy, while the high-risk group exhibited potential targets for certain chemotherapy drugs, such as carmustine, etoposide, arsenic trioxide, and alectinib. ILLS demonstrated superior and stable prognostic prediction ability and thus has potential as a tool for assisting in risk classification and clinical decision-making in patients with LUAD.

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

Screening and biomarker assessment of ferroptosis genes FLT3 and ALOX5 in lung adenocarcinoma

Abstract Objectives Ferroptosis is a unique process of cell death that specifically requires iron. We investigated ferroptosis genes and their function in lung adenocarcinoma (LUAD) patients. Methods Data on the expression levels of genes associated with ferroptosis were collected from the FerrDb and the Cancer Genome Atlas database. Kaplan-Meier Plotter was employed to generate the survival curves of LUAD patients with high vs low expression of ferroptosis genes. The relationship between immune cell infiltration and ferroptosis genes was analyzed via TIMMER. Immunohistochemical staining was employed to quantitatively evaluate gene expression in 43 LUAD patients. Results A total of 89 ferroptosis genes were found to have significant differential expression between LUAD and normal tissues (p&lt;0.05), 23 of which were selected and consistent prognostic trends were observed based on analysis of RNA-Seq and RNA microarray data (p&lt;0.05). These 23 ferroptosis genes were assigned to 10 high-abundance pathways and 18 functional categories. Besides, the expression of ALOX5 and FTL3 demonstrated a positive correlation with sets of immune markers. The expression of ALOX5 exhibited a positive correlation with the levels of infiltration of dendritic cells, macrophages, neutrophils, and CD4+ T cells, while FLT3 expression correlated with the infiltration of B cells, CD4+ T cells, neutrophils, and dendritic cells. Furthermore, ALOX5 was confirmed to be downregulated in lung tumor tissues (p&lt;0.01). Conclusions Our findings show that the ferroptosis genes FLT3 and ALOX5 play prominent roles in immune cell infiltration during LUAD progression and may serve as prognostic biomarkers for LUAD.

Molecular Characterization and Prognosis of Lactate-Related Genes in Lung Adenocarcinoma.

To explore the lactate-related genes (LRGs) in lung adenocarcinoma (LUAD) by various methods, construct a prognostic model, and explore the relationship between lactate subtypes and the immune tumor microenvironment (TME). 24 LRGs were collected. The mutation landscape and the prognosis value of LRGs were explored by using The Cancer Genome Atlas (TCGA) data. Consensus clustering analysis was used for different lactate subtype identification. Based on the lactate subtypes, we explore the landscape of TME cell infiltration. A risk-score was calculated by using the LASSO-Cox analysis. A quantitative real-time PCR assay was utilized to validate the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients. Comparing the normal samples, 18 LRGs were differentially expressed in tumor samples, which revealed that the differential expression of LRGs may be related to Copy Number Variation (CNV) alterations. The two distinct lactate subtypes were defined. Compared to patients in the LRGcluster A group, LUAD patients in the LRGcluster B group achieved better survival. The prognostic model was constructed based on differentially expressed genes (DEGs) via the LASSO-Cox analysis, which showed the accuracy of predicting the prognosis of LUAD patients using the ROC curve. A high-risk score was related to a high immune score, stromal score, and tumor mutation burden (TMB). Patients had better OS with low risk compared with those with high risk. The sensitivities of different risk groups to chemotherapeutic drugs were explored. Finally, the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients was verified via qRT-PCR. The lactate subtypes were independent prognostic biomarkers in LUAD. Additionally, the difference in the lactate subtypes was an indispensable feature for the individual TME. The comprehensive evaluation of the lactate subtypes in the single tumor would help us to understand the infiltration characteristics of TME and guide immunotherapy strategies.

TTYH3 is a Prognostic Biomarker and Associates with Immune Cell Infiltrations of Lung Adenocarcinoma

We investigated Tweety Family Member 3 (TTYH3) level in lung adenocarcinoma (LUAD) and its relationship with immune infiltration in tumors by bioinformatics. Differential expressions of TTYH3 in lung cancer were analyzed with Oncomine, TIMER, GEO, UALCAN and HPA. Relationship of TTYH3 mRNA/protein levels with clinical parameters was analyzed by UALCAN. Co-expressed genes of TTYH3 in LUAD were analyzed using Cbioportal. Its relationship with LUAD prognosis was analyzed by Kaplan-Meier plotter. GO and KEGG analysis were performed. Correlation between TTYH3 and tumor immune infiltration were tested by TIMER, TISIDB and GEPIA. We found that TTYH3 was significantly increased in LUAD tissues. TTYH3 high expression was closely related to poor overall survival, post progression survival and first progression in LUAD patients. TTYH3 mRNA/protein levels were significantly associated with multiple pathways. Specifically, TTYH3 up-regulation was mostly related to biological regulation, metabolic process, protein blinding, extracellular matrix organization and pathways in cancer. Moreover, TTYH3 was positively associated with immune cell infiltration in LUAD. Finally, TTYH3 was highly expressed in LUAD as revealed by meta-analysis. TTYH3 is closely related to the prognosis of LUAD and immune cell infiltration, and it can be used as a prognostic biomarker for LUAD and immune infiltration.

STARD12/14 are diagnostic and prognostic biomarkers of lung adenocarcinoma associated with epigenetic regulation, immune infiltration and ferroptosis.

Background: Metabolic reprogramming plays an important role in tumor progression and antitumor immunity. START domain-containing proteins (STARDs) are responsible for lipid metabolism. However, the underlying functions of STARDs in lung adenocarcinoma (LUAD) have not been clarified yet. Methods: Oncomine, UALCAN, TCGA and CPTAC were used to explore the expression landscape and clinicopathological characteristics of STARDs in LUAD. Diagnostic and prognostic values were assessed by Kaplan-Meier Plotter, Cox regression analysis, and ROC curve. GeneMANIA, GO, KEGG and GSEA were applied for exploring the potential biological functions. Epigenetic process, including mutation and m6A modification were analyzed by cBioPortal and TCGA. TIMER, TISIDB and TCGA cohort provided an immune signature. The correlation between STARDs expression and ferroptosis was analyzed by TCGA. Finally, the STARDs expression were confirmed by RT-qPCR and western blot. Results: STARD5/10/14 were overexpressed in LUAD compared with normal, while STARD4/7/8/11/12/13 were relatively low. STARD5/12/14 levels were positively related to clinical and lymph node stage. Survival analysis showed high STARD12 expression was associated with favorable overall survival, disease special survival as well as disease free survival, while STARD14 showed the opposite. GSEA analysis found STARD12 and STARD14 were associated with glycolysis, oxidative phosphorylation and tumor related signaling pathways. STARD12 co-expressed genes participated in cell cycle and DNA replication, and STARD14 were enriched in ECM-receptor interaction. Both STARD12 and STARD14 were corelated with epigenetic regulation, especially TP53 mutation and m6A modification. STARD12 expression was positively correlated with TMB level. The level of STARD12 was significantly associated with the abundance of infiltrating immune cells, including B cells, CD8+T cells, macrophages, dendritic cells, and chemokine, receptor, MHC, immunostimulatory related genes. STARD14 was negatively associated with the infiltration of CD8+T cells, while positively with CCL28 and immune checkpoints, including CTLA4 as well as PD-L2. In addition, STARD12/14 could regulate the ferroptosis related genes. Conclusion: STARD12 and STARD14 were expected to be potential biomarkers for LUAD, which were associated with epigenetic regulation, immune infiltration and ferroptosis.

Cancer/testis antigen HEMGN correlated with immune infiltration serves as a prognostic biomarker in lung adenocarcinoma

HEMGN belongs to the Cancer/testis antigens (CTAs), which are expressed in various types of human cancers and have received particular attention in cancer immunotherapy. However, the potential function of HEMGN involved in lung cancer and the immune response is not yet elucidated. HEMGN expression in lung adenocarcinoma (LUAD) was estimated via the Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA), The University of Alabama at Birmingham Cancer data analysis Portal (UALCAN), and Human Protein Atlas databases. The prognostic role of HEMGN was investigated by Gene Expression Profiling Interactive Analysis (GEPIA), PrognoScan, and Kaplan-Meier plotter databases. The associations between HEMGN and clinicopathological parameters were analyzed with UALCAN database. Then, immunohistochemical and Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) analysis were performed to further verify the associations in tissue or serum samples. Serum from patients were detected for HEMGN antibody by enzyme-linked immunosorbent assay (ELISA). Flow cytometry was used to detect immune cell infiltration in peripheral blood of patients with LUAD. In addition, Gene Set Enrichment Analysis (GSEA) was conducted to investigate the functional role of HEMGN. Furthermore, we obtained the somatic mutation data from the TCGA LUAD dataset and analyzed the mutation profiles with “maftools” package. Finally, we evaluated the associations between HEMGN and immune infiltration level and the characteristic markers of immune cells in TIMER, GEPIA, and CIBERSORT. The mRNA and protein expressions of HEMGN were significantly decreased in LUAD patients. High HEMGN expression was remarkably associated with better prognosis in LUAD patients. The concentration levels of anti-HEMGN antibody in LUAD were significantly higher than that in healthy individuals and were closely correlated with clinical stage. In addition, HEMGN was involved in distinct typical genomic alterations in LUAD. GSEA demonstrated that HEMGN was significantly connected with immunity and substance metabolism. Notably, HEMGN was significantly related to immune infiltrates, including B cells, CD8 + T cells, CD4 + T cells, neutrophils, macrophages, dendritic cells (DCs), and various kinds of functional T cells. Furthermore, HEMGN had a significant association with diverse immune gene markers. HEMGN can be considered as a prognostic biomarker of LUAD and is associated with immune infiltration.

A novel long noncoding RNA AC092718.4 as a prognostic biomarker and promotes lung adenocarcinoma progression.

Long noncoding RNAs (lncRNAs) reportedly play critical roles in the pathogenesis of various cancers, including lung adenocarcinoma (LUAD). However, the expression level, clinical significance, and potential function of lncRNA-AC092718.4 in LUAD remain unclear. In this study, we found that AC092718.4 was highly expressed in LUAD and high expression of AC092718.4 was correlated with poor overall survival (OS) and disease-specific survival (DSS) in LUAD. Cox regression analysis confirmed that AC092718.4 was an independent factor for LUAD prognosis. Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that AC092718.4 was involved in the PI3K-Akt signaling pathway, Th17 cell differentiation, and cell apoptosis. AC092718.4 expression was correlated with immune cell infiltration. Finally, we found that the knockdown of AC092718.4 inhibited lung adenocarcinoma (LUAD) cell growth and promote cell apoptosis. Our findings confirmed that AC092718.4 may serve as a potential prognostic biomarker in LUAD.