Biomarker For Lung Adenocarcinoma Research Articles

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.

Intrinsic and Extrinsic Transcriptional Profiles That Affect the Clinical Response to PD-1 Inhibitors in Patients with Non-Small Cell Lung Cancer.

Using a machine learning method, we investigated the intrinsic and extrinsic transcriptional profiles that affect the clinical response to PD-1 inhibitors in 57 patients with non-small cell lung cancer (NSCLC). Among the top 100 genes associated with the responsiveness to PD-1 inhibitors, the proportion of intrinsic genes in lung adenocarcinoma (LUAD) (69%) was higher than in NSCLC overall (36%) and lung squamous cell carcinoma (LUSC) (33%). The intrinsic gene signature of LUAD (mean area under the ROC curve (AUC) = 0.957 and mean accuracy = 0.9) had higher predictive power than either the intrinsic gene signature of NSCLC or LUSC or the extrinsic gene signature of NSCLC, LUAD, or LUSC. The high intrinsic gene signature group had a high overall survival rate in LUAD (p = 0.034). When we performed a pathway enrichment analysis, the cell cycle and cellular senescence pathways were related to the upregulation of intrinsic genes in LUAD. The intrinsic signature of LUAD also showed a positive correlation with other immune checkpoint targets, including CD274, LAG3, and PDCD1LG2 (Spearman correlation coefficient > 0.25). PD-1 inhibitor-related intrinsic gene patterns differed significantly between LUAD and LUSC and may be a particularly useful biomarker in LUAD.

LIPG is a novel prognostic biomarker and correlated with immune infiltrates in lung adenocarcinoma.

Although many biomarkers for lung adenocarcinoma (LUAD) have been identified, their specificity and sensitivity remain unsatisfactory. Endothelial lipase gene (LIPG) plays an important role in a variety of cancers, but its role in lung adenocarcinoma remains unclear. TCGA, GEO, K-M plotter, CIBERSORT, GSEA, HPA, and GDSC were used to analyze LIPG in LUAD. Data analysis was mainly achieved by R 4.0.3. The expression of LIPG in LUAD tissues was higher than that in adjacent normal tissues, especially in women, patients aged >65 years, and those with lymph node metastasis. High expression predicted a poor prognosis. The results of enrichment analysis suggest that LIPG may exert profound effects on the development of LUAD through multiple stages of lipid metabolism and immune system regulation. In addition, LIPG expression was significantly correlated with the expression levels of multiple immune checkpoint genes and the abundance of multiple immune infiltrates, including the activated memory CD4 T cell, M1 macrophage, neutrophil, plasma cells, and T follicular helper (Tfh) cells in the LUAD microenvironment content. At the same time, patients with high LIPG expression respond well to a variety of antitumor drugs and have a low rate of drug resistance. LIPG is a prognostic marker and is associated with lipid metabolism and immune infiltration in LUAD.

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.

Comprehensive analysis identifies ARHGEF6 as a potential prognostic and immunological biomarker in lung adenocarcinoma

Lung adenocarcinoma (LUAD), the most common histological type in lung cancer, is one of leading cancers with considerable morbidity/mortality worldwide. Treating LUAD remains an outstanding challenge due to the lack of early diagnosis and the poor therapeutic effects. Rac/Cdc42 guanine nucleotide exchange factor 6 (ARHGEF6), one of cytoskeletal regulators, exerts crucial biological functions in T cell migration. The potential biological role of ARHGEF6 in LUAD has yet to be established. Using multiple bioinformatics tools and statistical methods, we discovered that the mRNA and protein expression level of ARHGEF6 was significantly downregulated in tumor tissues comparing to normal controls. Moreover, ARHGEF6 presented high diagnostic value in LUAD patients (AUC = 0.949), and the patients with low ARHGEF6 expression had more somatic mutations and poor T stage, N stage, clinical prognosis. Experimental validation indicated that ARHGEF6 was low expressed in A549 and PC-9 cells comparing to the normal lung epithelial cells. The overexpression of ARHGEF6 remarkably attenuated the abilities of cell proliferation and colony formation. Furthermore, the immune landscape analysis in TME revealed that ARHGEF6 expression was positively associated with immune cell infiltration and immune checkpoints. Single-cell transcriptome analysis indicated that ARHGEF6 expression was also distributed in immune cell types in TME based on TISCH database. Additionally, differentially expressed genes (DEGs) and functional enrichment analyses uncovered that ARHGEF6 was involved in T cell activation. Finally, LUAD samples were classified two clusters based on DEGs for subgroups analysis. In summary, this study comprehensively uncovered that ARHGEF6 could be identified as a potential prognostic and immunological biomarker in lung adenocarcinoma.

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.

Identification of immune-associated prognostic biomarkers in lung adenocarcinoma on the basis of gene co-expression network

Objective: We aimed to explore immune-related prognosis genes of lung adenocarcinoma (LUAD). Materials and methods: TCGA-LUAD and GSE31210 data sets were accessed from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) respectively. By using “WGCNA” R package, we established a gene co-expression network and clustered genes into various modules. The correlation between immune scores and module eigengenes by using Pearson analysis. Screened hub genes and constructed prognostic model by using LASSO and Cox regression analysis. Evaluated model by survival analysis and receiver operating characteristic (ROC) curves. Hub genes expression in clinical tissues of LUAD patients by qRT-PCR analysis. ssGSEA and TIMER (a website tool for examination of different immune cells in different cancers) analyzed immune correlation of hub genes. Gene set variation analysis (GSVA) uncovered difference of signal pathway between high- and low-risk score group. Results: We found that brown module significantly correlated with the immune scores of immune cells. Therefore, we constructed a 7-gene prognostic model based on brown module genes, and indicated that this model possessed good predictive performance. Patients in training and validation sets were stratified into the high- and low-risk group using this model. Also, hub genes CDCP1, PLSCR1 and CD79A were highly expressed in clinical tissues of LUAD patients, while ID1, CLEC7A, KIAA1324 and CMTM7 were lowly expressed. Both ssGSEA and TIMER revealed a significant negative correlation between risk score and B cell infiltration. Additionally, some signal pathways were suppressed in the high-risk group. Conclusion: We identified 7 immune-associated prognostic markers, which may play vital roles in LUAD and could be used as hopeful targets for immunotherapy of LUAD.

Circadian rhythm-related factors of PER and CRY family genes function as novel therapeutic targets and prognostic biomarkers in lung adenocarcinoma.

The period (PER) and cryptochrome (CRY) families play critical roles in circadian rhythms. The imbalance of circadian factors may lead to the occurrence of cancer. Expressions of PER and CRY family members decrease in various cancers. Nevertheless, expression levels, genetic variations, and molecular mechanisms of PER and CRY family members in lung adenocarcinoma (LUAD) and their correlations with prognoses and immune infiltration in LUAD patients are still unclear. In this study, to identify their biological functions in LUAD development, comprehensive high-throughput techniques were applied to analyze the relationships of expressions of PER and CRY family members with genetic variations, molecular mechanisms, and immune infiltration. The present results showed that transcription levels of PER1 and CRY2 in LUAD were significantly downregulated. High expression levels of PER2, PER3, CRY1, and CRY2 indicated longer overall survival. Some cancer signaling pathways were related to PER and CRY family members, such as cell-cycle, histidine metabolism, and progesterone-mediated oocyte maturation pathways. Expressions of PER and CRY family members significantly affected the infiltration of different immune cells. In conclusion, our findings may help better understand the molecular basis of LUAD, and provide new perspectives of PER and CRY family members as novel biomarkers for LUAD.

A neutrophil extracellular traps-associated lncRNA signature predicts the clinical outcomes in patients with lung adenocarcinoma.

Backgrounds: Neutrophil extracellular traps (NETs) play an important role in the occurrence, metastasis, and immune escape of cancers. We aim to investigate Long non-coding RNAs (lncRNAs) that are correlated to NETs to find some potentially useful biomarkers for lung adenocarcinoma (LUAD), and to explore their correlations with immunotherapy and chemotherapy, as well as the tumor microenvironment. Methods: Based on the The Cancer Genome Atlas (TCGA) database, we identified the prognosis-related lncRNAs which are associated with NETs using cox regression. The patients were then separated into two clusters based on the expression of NETs-associated lncRNAs to perform tumor microenvironment analysis and immune-checkpoint analysis. Least absolute shrinkage and selection operator (LASSO) regression was then performed to establish a prognostic signature. Furthermore, nomogram analysis, tumor mutation burden analysis, immune infiltration analysis, as well as drug sensitivity analysis were performed to test the signature. Results: Using univariate cox regression, we found 10 NETs-associated lncRNAs that are associated with the outcomes of LUAD patients. Also, further analysis which separated the patients into 2 clusters showed that the 10 lncRNAs had significant correlations with the tumor microenvironment. Using LASSO regression, we finally constructed a signature to predict the outcomes of the patients based on 4 NETs-associated lncRNAs. The 4 NETs-associated lncRNAs were namely SIRLNT, AL365181.3, FAM83A-AS1, and AJ003147.2. Using Kaplan-Meier (K-M) analysis, we found that the risk model was strongly associated with the survival outcomes of the patients both in the training group and in the validation group 1 and 2 (p < 0.001, p = 0.026, and p < 0.01). Using receiver operating characteristic (ROC) curve, we tested the sensitivity combined with the specificity of the model and found that the risk model had a satisfactory level of 1-year, 3-year, and 5-year concordance index (C-index) (C = 0.661 in the training group, C = 0.679 in validation group 1, C = 0.692 in validation group 2). We also explored the immune microenvironment and immune checkpoint correlation of the risk model and found some significant results. Conclusion: We constructed a NETs-associated lncRNA signature to predict the outcome of patients with LUAD, which is associated with immunephenoscores and immune checkpoint-gene expression.

354P Decreased INPP5B expression predicts poor prognosis in lung adenocarcinoma

INPP5B, a inositol 5-phosphatase, plays an important role in many biological processes through phosphorylating PI(4,5)P2 and/or PI(3,4,5)P3 at the 5-position. Nevertheless, little is known about its function and cellular pathways in tumors. This study aims to investigate the potential role of INPP5B as a diagnostic and prognostic biomarker for lung adenocarcinoma (LUAD), as well as its biological functions and molecular mechanisms in LUAD.

Identification of EGFR-Related LINC00460/mir-338-3p/MCM4 Regulatory Axis as Diagnostic and Prognostic Biomarker of Lung Adenocarcinoma Based on Comprehensive Bioinformatics Analysis and Experimental Validation.

Simple SummaryWhile the epidermal growth factor receptor (EGFR) is an important target for lung adenocarcinoma (LUAD) therapy, acquired resistance is still inevitable. A comprehensive bioinformatics analysis strongly suggested that the closely related LINC00460-mir-338-3p-MCM4 ceRNA network of EGFR plays an important role in the diagnosis and prognosis of LUAD. High expression of LINC00460 and MCM4 predicts shorter patient survival. Univariate and multivariate regression analyses demonstrated that higher expression of LINC00460 and MCM4 was significantly associated with tumor size, lymph node metastasis, distant metastasis and TNM stage. A multi-gene regulation model analysis revealed that the LINC00460 (downregulation)—mir-338-3p (upregulation))—MCM4 (downregulation) pattern significantly improved the overall survival of LUAD patients. We also verified the expression of these genes in LUAD cell lines and tumor tissues by RT-PCR and immunohistochemistry. Finally, the possible targeted drugs of MCM4 were queried through the drug database platform, hoping to solve its drug resistance problem by targeting EGFR-related genes.Background: Lung adenocarcinoma (LUAD) is one of the most aggressive and lethal tumor types and requires effective diagnostic and therapeutic targets. Though the epidermal growth factor receptor (EGFR) is an important target for LUAD therapy, acquired resistance is still inevitable. In recent years, the regulation of the EGFR by competing endogenous RNAs (ceRNAs) has been extensively studied and significant progress has been made. Therefore, we aim to find new targets for the diagnosis and treatment of LUAD by analyzing the EGFR-related ceRNA network in LUAD and expect to address the problem of EGFR resistance. Methods: We identified differentially expressed lncRNAs, miRNAs and mRNAs closely associated with the EGFR by analyzing transcriptome data from LUAD samples. Comprehensive bioinformatics analysis strongly suggests that the LINC00460—mir-338-3p—MCM4 ceRNA network plays an important role in the diagnosis and prognosis of LUAD. The effects of different patterns of the LINC00460/MCM4 axis on the overall survival of patients with LUAD were analyzed by a polygene regulation model. We also verified the expression of these genes in LUAD cell lines and tumor tissues by RT-PCR and immunohistochemistry. The functional enrichment analysis and targeted drug prediction of the MCM4 gene were performed. Results: Survival analysis indicated that high expressions of LINC00460 and MCM4 predict a shorter survival period for patients. Univariate and multivariate regression analyses demonstrated that higher expressions of LINC00460 and MCM4 were significantly associated with tumor size, lymph node metastasis, distant metastasis and TNM stage. A multi-gene regulation model analysis revealed that the LINC00460 (downregulation)—mir-338-3p (upregulation)—MCM4 (downregulation) pattern significantly improved the overall survival of LUAD patients (p = 0.0093). RT-PCR and immunohistochemical experiments confirmed our analytical results. In addition, the functional enrichment analysis indicated that MCM4-related genes were mainly enriched in the cell cycle and cell division. A functional association network analysis showed that MCM4 was closely related to the EGFR. Finally, the possible targeted drugs of MCM4 were queried through the drug database platform, hoping to solve its drug resistance problem by targeting EGFR-related genes. Conclusions: In summary, the LINC00460/MCM4 axis can be used as a potential new perspective for targeting EGFR genes in precision medicine and is expected to serve as a diagnostic, prognostic and drug target for LUAD.

ECE2 is a prognostic biomarker associated with m6A modification and involved in immune infiltration of lung adenocarcinoma.

BackgroundThe targeted therapy for lung cancer relies on prognostic genes and requires further research. No research has been conducted to determine the effect of endothelin-converting enzyme 2 (ECE2) in lung cancer.MethodsWe analyzed the expression of ECE2 in lung adenocarcinoma (LUAD) and normal adjacent tissues and its relationship with clinicopathological characteristics from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). Immunohistochemical staining was used to further validate the findings. GO/KEGG enrichment analysis and gene set enrichment analysis (GSEA) of ECE2 co-expression were performed using R software. Data from TIMER, the GEPIA database, and TCGA were analyzed to determine the relationship between ECE2 expression and LUAD immune infiltration. To investigate the relationship between ECE2 expression levels and LUAD m6A modification, TCGA data and GEO data were analyzed.ResultsECE2 is highly expressed in various cancers including LUAD. ECE2 showed high accuracy in distinguishing tumor and normal sample results. The expression level of ECE2 in LUAD was significantly correlated with tumor stage and prognosis. GO/KEGG enrichment analysis showed that ECE2 was closely related to mitochondrial gene expression, ATPase activity and cell cycle. GSEA analysis showed that ECE2-related differential gene enrichment pathways were related to mitotic cell cycle, MYC pathway, PLK1 pathway, DNA methylation pathway, HIF1A pathway and Oxidative stress-induced cellular senescence. Analysis of the TIMER, GEPIA database, and TCGA datasets showed that ECE2 expression levels were significantly negatively correlated with B cells, CD4+ cells, M2 macrophages, neutrophils, and dendritic cells. TCGA and GEO datasets showed that ECE2 was significantly associated with m6A modification-related genes HNRNPC, IGF2BP1, IGF2BP3 and RBM1.ConclusionECE2 is associated with m6A modification and immune infiltration and is a prognostic biomarker in LUAD.

ARNTL2 is an indicator of poor prognosis, promotes epithelial-to-mesenchymal transition and inhibits ferroptosis in lung adenocarcinoma

ObjectivesARNTL2, as a circadian transcription factor, has been recently proposed to play an important role in a variety of tumors. however, the role of ARNTL2 in lung carcinogenesis and progression remains unclear. The purpose of this study was to investigate the effect of ARNTL2 on the clinical characteristics and prognosis of lung adenocarcinoma and to explore the relationship between ARNTL2 and EMT, ferroptosis in lung adenocarcinoma. MethodsThe Cancer Genome Atlas (TCGA) database's multi-omics data were downloaded using the Xena browser. Based on the expression levels of ARNTL2, patients with lung adenocarcinoma from TCGA were divided into two groups: those with high ARNTL2 expression and those with low ARNTL2 expression. ARNTL2 was studied for its effects on lung adenocarcinoma's clinicopathological, genomic, and immunological characteristics. Furthermore, in vivo and in vitro assays were used to confirm the impact of ARNLT2 knockdown on lung adenocarcinoma cells. ResultsWe found ARNTL2 is highly expressed in lung adenocarcinoma and was an independent predictor of a poor prognosis in patients with lung adenocarcinoma. In addition, we demonstrated that knockdown of ARNTL2 promoted ferroptosis, inhibited EMT, cell proliferation, migration and invasion in lung adenocarcinoma. In contrast, overexpressing ARNTL2 yielded the opposite results. ConclusionsARNTL2 is an independent unfavorable prognostic factor for lung adenocarcinoma. It plays a facilitating role in the development of lung adenocarcinoma, especially in promoting EMT and inhibiting ferroptosis, revealing that ARNTL2 may be a potential biomarker for lung adenocarcinoma.

Prognostic Value of GIMAP4 and Its Role in Promoting Immune Cell Infiltration into Tumor Microenvironment of Lung Adenocarcinoma.

GIMAPs are recognized as an important regulator in the carcinogenesis and development of lung cancer, but the function of GIMAP4 in the tumor microenvironment (TME) of lung cancers is unclear. In this study, we investigated the expression and variation of GIMAP4 in lung adenocarcinoma (LUAD), to explore its association with infiltration of immune cells. The Cancer Genome Atlas (TCGA) data and Gene Expression Omnibus (GEO) data were analyzed. Infiltration of immune cells was identified with TIMER (Tumor Immune Estimation Resource) and TISIDB (an integrated repository portal for tumor-immune system interactions). GIMAP4 expression declined in non-small-cell lung cancer (NSCLC), correlated with a poor overall survival (OS) in LUAD, indicating that GIMAP4 was a promising prognostic biomarker in LUAD. GIMAP4 mutation frequency was 1.76% in TCGA cohort and was relevant to the expression of immune components. TIMER and CIBERSORT analysis further confirmed that high GIMAP4 expression possibly promoted immune cell infiltration into the TME, with low GIMAP4 impairing the efficacy of immunotherapies targeting common immune check point inhibitors (ICI). GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses were performed to provide insights into biological processes involved in LUAD. GIMAP4 was expected to be a prognostic biomarker in LUAD and provides potential adjuvant or neoadjuvant therapeutic strategies for targeting ICIs.

Comprehensive analysis of DTYMK for estimating the immune microenvironment, diagnosis, prognosis effect in patients with lung adenocarcinoma.

The expression of deoxythymidylate kinase (DTYMK) is up-regulated in liver cancer. However, the underlying biological function and potential mechanisms of DTYMK driving the progression of lung adenocarcinoma remains unclear. In this study, we investigated the role of DTYMK in lung adenocarcinoma and found that the expression of DTYMK in LUAD tissues was significantly higher than that of DTYMK expression in adjacent normal tissues. Kaplan-Meier survival analysis showed that patients with higher DTYMK expression correlated with adverse prognosis. ROC curve analysis showed that the AUC value of DTYMK was 0.914. Correlation analysis showed that DTYMK expression was associated with immune infiltration in LUAD. Finally, we determine that DTYMK regulated cell proliferation, cell migration, and cell cycle of lung adenocarcinoma in vitro. In conclusion, our data demonstrated that DTYMK was correlated with progression and immune infiltration, and could serve as a prognostic biomarker for lung adenocarcinoma.

Plasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 as novel diagnostic biomarkers for lung adenocarcinoma.

ObjectiveTRNA-derived fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs) are recognized as novel and potential types of non-coding RNAs (ncRNAs), and several tRF/tiRNA signatures are closely associated with tumor diagnosis. This study aimed to analyze the expression profiles of plasma tRFs/tiRNAs and to clarify their diagnostic value in lung adenocarcinoma (LUAD).MethodsThe differential expression profiles of plasma tRFs/tiRNAs in patients with four patients with early LUAD, four patients with advanced LUAD, and four healthy controls were analyzed using high-throughput sequencing technology. Then, plasma tRFs/tiRNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR), and their diagnostic efficiency was appraised by receiver operating characteristic curve analysis. The correlation of candidate plasma tRFs/tiRNAs with clinicopathological features was also analyzed. Finally, bioinformatics analysis was performed to explore and identify the potential biological pathways induced by tRFs/tiRNAs.ResultsThe sequencing results revealed that tRFs/tiRNAs from plasma samples in patients with LUAD were differently expressed, supporting the necessity of exploring their potential as biomarkers. The validation results of qRT-PCR demonstrated that the expression level of tRF-1:29-Pro-AGG-1-M6 was downregulated in LUAD, while that of tRF-55:76-Tyr-GTA-1-M2 was upregulated, which was consistent with the sequencing data. The areas under the receiver operating characteristic curve of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 were 0.882 and 0.896, respectively, which have significant values in the diagnosis of LUAD. The expressions of tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 in LUAD were obviously correlated with various clinicopathological features such as tumor–node–metastasis stage, node stage, and the expression levels of carcinoembryonic antigen. In addition, their expression was significantly altered from before to after tumor resection in LUAD patients. The results of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses further indicated that tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 are widely distributed and apparently enriched in several tumor-related signaling pathways.ConclusionsPlasma tRF-1:29-Pro-AGG-1-M6 and tRF-55:76-Tyr-GTA-1-M2 may be promising components in the development of highly sensitive and non-invasive biomarkers for LUAD diagnosis.

Microarray data analysis to identify miRNA biomarkers and construct the lncRNA-miRNA-mRNA network in lung adenocarcinoma.

MicroRNAs (miRNAs), regulatory noncoding RNAs, are involved in gene regulation and may play a role in cancer development. The aim of this study was to identify miRNAs involved in lung adenocarcinoma (LUAD) using bioinformatics analysis. MiRNA (GSE135918), mRNA (GSE136043) and lncRNA (GSE130779) microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed miRNAs (DEMis), mRNAs (DEMs), and lncRNA (DELs) in LUAD. We used DEMs for functional enrichment analysis. MiRNA expression quantification from The Cancer Genome Atlas (TCGA) was used to validate DEMis. LncBase Predicted v.2, Targetscan, and MiRBase were used to predict lncRNAs and mRNAs. The LUAD data in TCGA were used for overall survival (OS) analysis. We screened the downregulation of 8 DEMis and upregulation of 6 DEMis, and found that 70 signal pathways changed. We chose 3 relevant signaling pathways in lung cancer development, WNT, PI3K-Akt, and Notch, and scanned for mRNAs involved in them that are potential targets of these miRNAs. Then a lncRNA-miRNA-mRNA network was constructed. We also found 7 miRNAs that were associated with poor OS in LUAD. Low expression level of hsa-miR-30a was highly associated with poor OS in LUAD (P < .001) and the target genes of hsa-miR-30a-3p were abundant in the Wnt and AKT signaling pathways. In addition, our results reported for the first time that hsa-miR-3944 and hsa-miR-3652 were highly expressed in LUAD. And the high expression level of hsa-miR-3944 was associated with poor OS (P < .05). Hsa-miR-30a-3p may suppress the occurrence and progression of lung cancer through Wnt and AKT signaling pathways and become a good biomarker in LUAD. Hsa-miR-3944 and hsa-miR-3652 may serve as new biomarkers in LUAD.

Comprehensive analysis to identify GNG7 as a prognostic biomarker in lung adenocarcinoma correlating with immune infiltrates.

Background: G Protein Subunit Gamma 7 (GNG7), an important regulator of cell proliferation and cell apoptosis, has been reported to be downregulated in a variety of tumors including lung adenocarcinoma (LUAD). However, the correlation between low expression of GNG7 and prognosis of LUAD as well as the immune infiltrates of LUAD remains unclear. Methods: The samples were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). R software was performed for statistical analysis. GNG7 expression and its prognostic value in LUAD were assessed through statistically analyzing the data from different databases. A nomogram was constructed to predict the impact of GNG7 on prognosis. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analyses GSEA (ssGSEA) were employed to determine the potential signal pathways and evaluated the immune cell infiltration regulated by GNG7. The prognostic significance of GNG7 expression associated with immune cell infiltration was investigated using the Tumor Immune Estimation Resource 2.0 (TIMER2.0) and the Kaplan-Meier plotter database. The UALCAN, cBio Cancer Genomics Portal (cBioPortal) and MethSurv database were used to analyze the correlation between the methylation of GNG7 and its mRNA expression as well as prognostic significance. Results: GNG7 was demonstrated to be down-regulated in LUAD and its low expression was associated with poor prognosis. A clinical reliable prognostic-predictive model was constructed. Pathway enrichment showed that GNG7 was highly related to the B cell receptor signaling pathway. Further analysis showed that GNG7 was positively associated with B cell infiltration and low levels of B cell infiltration tended to associate with worse prognosis in patients with low GNG7 expression. Moreover, methylation analysis suggested hypermethylation may contribute to the low expression of GNG7 in LUAD. Conclusion: Decreased expression of GNG7 at least partly caused by hypermethylation of the GNG7 promoter is closely associated with poor prognosis and tumor immune cell infiltration (especially B cells) in LUAD. These results suggest that GNG7 may be a promising prognostic biomarker and a potential immunotherapeutic target for LUAD, which provides new insights into immunotherapy for LUAD.

EP16.04-007 ALDH2 Downregulation, Aberrant DNA Methylation, and Loss of Stemness Pathways as an Enhanced Biomarker in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common type of lung cancer and is one of the major causes of growing mortality. Previous studies showed an association between LUAD and Aldehyde Dehydrogenase 2 (ALDH2), an essential enzyme involved in the detoxification of acetaldehyde. We aimed at discovering more informative prognosis signatures for early LUAD detection and targets for LUAD treatment by investigating the expression level, epigenetic mechanism, and signaling activities of ALDH2 in LUAD patients.

Identification of Novel Multi-Omics Expression Landscapes and Meta-Analysis of Landscape-Based Competitive Endogenous RNA Networks in ALDH+ Lung Adenocarcinoma Stem Cells.

ALDH+ H1975 lung adenocarcinoma stem cells (LSCs) are a rare cell population identified in lung adenocarcinoma (LUAD). LSCs can self-renew, drive tumor initiation, growth, metastasis, and recurrence and are also the predominant cause of poor prognosis due to their intrinsic resistance to drugs and chemotherapy. Consequently, LSCs are a promising target for LUAD therapy. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), exert many significant regulatory functions in the pathogenesis of human cancers, showing the necessity for a comprehensive understanding of the mechanisms that underlie lung carcinogenesis. Nonetheless, research on many known transcripts and messenger RNAs (mRNAs) has already generated new information. Unknown biomarkers in ncRNAs and systematic and comprehensive interrelation with unknown ncRNAs and mRNAs may provide further insights into the biology of LUAD. Herein, a set of novel ncRNAs that include miRNAs, lncRNAs, and circRNAs were identified, and differentially expressed patterns of ncRNAs and mRNAs in LSCs and ALDH-H1975 LUAD tumor cells (LTCs) were obtained using stringent bioinformatics pipelines. Through a meta-analysis of the identified landscapes, novel competitive endogenous RNA (ceRNA) networks were constructed to reveal the potential molecular mechanisms that regulate the hallmarks of LSCs and LTCs. This study presents a summary of novel ncRNAs and the fundamental roles of differentially expressed ncRNAs implicated in the activity of LSCs and LTCs. In addition, the study also provides a comprehensive resource for the future identification of diagnostic, therapeutic, and prognostic biomarkers in LUAD.