scholarly journals Upregulation of EMID1 accelerates to a favorable prognosis and immune infiltration in lung adenocarcinoma.

2020 ◽  
Author(s):  
Chengrui Li ◽  
Yufeng Wan ◽  
Weijun Deng ◽  
Fan Fei ◽  
Linlin Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Enrichment Analysis ◽  
Notch Signaling Pathway ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Rank Test ◽  
Survival Status ◽  
Signed Rank Test

Abstract Background Lung cancer is a kind of refractory cancer. Lung adenocarcinoma (LUAD) is the main subtype of lung cancer. Although there are many ways to treat lung cancer, the survival rate of patients has not improved. Therefore, more new molecules need to be found for the diagnosis and treatment of LUAD. Methods The data from The Cancer Genome Atlas (TCGA) database were used to analyze the value of EMID1 in diagnosis and prognosis of LUAD. The relationship between clinic pathological features and EMID1 was analyzed with the Wilcoxon signed-rank test and logistic regression by R (v.3.5.1). Gene Set Enrichment Analysis (GSEA) was performed to investigate the potential mechanism of EMID1 expression on the prognosis of LUAD. The correlation between tumor infiltrating immune cells and genes was assessed by CIBERSORT. In addition, GEPIA and Gene Expression Omnibus (GEO) database were used to verify the results. Results The decreased expression of EMID1 was significantly related to the late stage and metastasis of lung cancer. Kaplan Meier survival analysis showed that patients with low expression of EMID1 had worse prognosis than those with high expression of EMID1. Notch signaling pathway may be an important biological pathway for EMID1 to play a role in LUAD. In addition, CIBERSORT also found that the infiltration level of B cells was positively correlated with the expression of EMID1, which played an important role in the immune environment of LUAD. All results were validated in GEO and GEPIA database. Conclusion The analysis of EMID1 was helpful to understand the immune microenvironment of LUAD and improve the survival status of patients with LUAD. All the results suggested that EMID1 might be a new immune related prognostic marker of LUAD.

scholarly journals Bioinformatics analysis combined with experiments predicts CENPK as a potential prognostic factor for lung adenocarcinoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jiayu Ma ◽  
Xiaochuan Chen ◽  
Mingqiang Lin ◽  
Zhiping Wang ◽  
Yahua Wu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Biological Behavior ◽  
Tumor Identification

Abstract Background Lung cancer is the most common malignant tumor. Identification of novel diagnostic and prognostic biomarkers for lung cancer is a key research imperative. The role of centromere protein K (CENPK) in cancer is an emerging research hotspot. However, the role of CENPK in the progression of lung adenocarcinoma (LAC) is not well characterized. Methods In this study, we identified CENPK as a potential new gene for lung cancer based on bioinformatics analysis. In addition, in vitro experiments were performed to verify the function of this gene. We investigated the expression of CENPK in LAC by analyses of datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differential expression analyses, gene ontology (GO) enrichment, Kyoto encyclopedia of genes and genomes (KEGG) analysis, and gene set enrichment analysis (GSEA) were conducted to evaluate the diagnostic and prognostic relevance of CENPK. Then, for evaluating the biological behavior and role of CENPK in lung cancer cells, we did a series of vitro experiments, such as immunohistochemistry analysis, Western blot analysis, CCK8 assay, transwell assay, flow cytometry, and wound healing assay. Results We demonstrated overexpression of CENPK in LAC; in addition, increased expression of CENPK was associated with clinical progression. Moreover, CENPK was found to be an independent risk factor in patients with LAC. Furthermore, we observed activation of CENPK-related signaling pathways in patients with LAC. Conclusions Our findings indicate a potential role of CENPK in promoting tumor proliferation, invasion, and metastasis. It may serve as a novel diagnostic and prognostic biomarker in patients with LAC.

scholarly journals Identification and Validation of a Novel Immune-Related Four-lncRNA Signature for Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Jixin Wang ◽  
Xiangjun Yin ◽  
Yin-Qiang Zhang ◽  
Xuming Ji
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Lasso Regression ◽  
Kaplan Meier

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer, the prognosis of patients with which is associated with both lncRNAs and cancer immunity. In this study, we collected gene expression data of 585 LUAD patients from The Cancer Genome Atlas (TCGA) database and 605 subjects from the Gene Expression Omnibus (GEO) database. LUAD patients were divided into high and low immune-cell-infiltrated groups according to the single sample gene set enrichment analysis (ssGSEA) algorithm to identify differentially expressed genes (DEGs). Based on the 49 immune-related DE lncRNAs, a four-lncRNA prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) regression, univariate Cox regression, and stepwise multivariate Cox regression in sequence. Kaplan–Meier curve, ROC analysis, and the testing GEO datasets verified the effectiveness of the signature in predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression suggested that the signature was an independent prognostic factor. The correlation analysis revealed that the infiltration immune cell subtypes were related to these lncRNAs.

Exploring exosome data to identify prognostic gene signatures for lung adenocarcinoma

2021 ◽  
Author(s):  
Jialin Li ◽  
Xinliang Gao ◽  
Suyan Tian ◽  
Mingbo Tang ◽  
Wei Liu
Keyword(s):  
Lung Adenocarcinoma ◽  
Enrichment Analysis ◽  
Risk Groups ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Immune Functions ◽  
Cancer Genome Atlas ◽  
Genome Atlas

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

scholarly journals Increased VEGF-A in solid type of lung adenocarcinoma reduces the patients’ survival

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Woon Yong Jung ◽  
Kyueng-Whan Min ◽  
Young Ha Oh
Keyword(s):  
Immune Response ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Survival Rates ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Solid Type

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

scholarly journals Identification of key genes associated with lung adenocarcinoma by bioinformatics analysis

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042199727
Author(s):  
Xinyu Wang ◽  
Jiaojiao Yang ◽  
Xueren Gao
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Gene Expression Omnibus ◽  
Poor Overall Survival ◽  
Key Genes ◽  
Low Expression

Lung adenocarcinoma (LUAD) is the most common histological type of lung cancer, comprising around 40% of all lung cancer. Until now, the pathogenesis of LUAD has not been fully elucidated. In the current study, we comprehensively analyzed the dysregulated genes in lung adenocarcinoma by mining public datasets. Two sets of gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. The dysregulated genes were identified by using the GEO2R online tool, and analyzed by R packages, Cytoscape software, STRING, and GPEIA online tools. A total of 275 common dysregulated genes were identified in two independent datasets, including 54 common up-regulated and 221 common down-regulated genes in LUAD. Gene Ontology (GO) enrichment analysis showed that these dysregulated genes were significantly enriched in 258 biological processes (BPs), 27 cellular components (CCs), and 21 molecular functions (MFs). Furthermore, protein-protein interaction (PPI) network analysis showed that PECAM1, ENG, KLF4, CDH5, and VWF were key genes. Survival analysis indicated that the low expression of ENG was associated with poor overall survival (OS) of LUAD patients. The low expression of PECAM1 was associated with poor OS and recurrence-free survival of LUAD patients. The cox regression model developed based on age, tumor stage, ENG, PECAM1 could effectively predict 5-year survival of LUAD patients. This study revealed some key genes, BPs, CCs, and MFs involved in LUAD, which would provide new insights into understanding the pathogenesis of LUAD. In addition, ENG and PECAM1 might serve as promising prognostic markers in LUAD.

scholarly journals mRNAsi Index: Machine Learning in Mining Lung Adenocarcinoma Stem Cell Biomarkers

Genes ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 257 ◽  
Author(s):  
Yitong Zhang ◽  
Joseph Ta-Chien Tseng ◽  
I-Chia Lien ◽  
Fenglan Li ◽  
Wei Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Lung Adenocarcinoma ◽  
Tumor Necrosis Factor Receptor ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Clinical Stages ◽  
Key Genes ◽  
Geo Database

Cancer stem cells (CSCs), characterized by self-renewal and unlimited proliferation, lead to therapeutic resistance in lung cancer. In this study, we aimed to investigate the expressions of stem cell-related genes in lung adenocarcinoma (LUAD). The stemness index based on mRNA expression (mRNAsi) was utilized to analyze LUAD cases in the Cancer Genome Atlas (TCGA). First, mRNAsi was analyzed with differential expressions, survival analysis, clinical stages, and gender in LUADs. Then, the weighted gene co-expression network analysis was performed to discover modules of stemness and key genes. The interplay among the key genes was explored at the transcription and protein levels. The enrichment analysis was performed to annotate the function and pathways of the key genes. The expression levels of key genes were validated in a pan-cancer scale. The pathological stage associated gene expression level and survival probability were also validated. The Gene Expression Omnibus (GEO) database was additionally used for validation. The mRNAsi was significantly upregulated in cancer cases. In general, the mRNAsi score increases according to clinical stages and differs in gender significantly. Lower mRNAsi groups had a better overall survival in major LUADs, within five years. The distinguished modules and key genes were selected according to the correlations to the mRNAsi. Thirteen key genes (CCNB1, BUB1, BUB1B, CDC20, PLK1, TTK, CDC45, ESPL1, CCNA2, MCM6, ORC1, MCM2, and CHEK1) were enriched from the cell cycle Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, relating to cell proliferation Gene Ontology (GO) terms, as well. Eight of the thirteen genes have been reported to be associated with the CSC characteristics. However, all of them have been previously ignored in LUADs. Their expression increased according to the pathological stages of LUAD, and these genes were clearly upregulated in pan-cancers. In the GEO database, only the tumor necrosis factor receptor associated factor-interacting protein (TRAIP) from the blue module was matched with the stemness microarray data. These key genes were found to have strong correlations as a whole, and could be used as therapeutic targets in the treatment of LUAD, by inhibiting the stemness features.

Mind Bomb 1 Promotes Pancreatic Cancer Proliferation by Activating β-Catenin Signaling

2020 ◽  
Vol 20 (12) ◽  
pp. 7276-7282
Author(s):  
Xiao Fu ◽  
Neng Tang ◽  
Weiqi Xie ◽  
Liang Mao ◽  
Yudong Qiu
Keyword(s):  
Pancreatic Cancer ◽  
Cancer Metastasis ◽  
Mrna Level ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Pancreatic Tumors ◽  
Mrna Levels ◽  
Cancer Proliferation

Mind bomb 1 (MIB1), an E3 ligase, plays a vital role in chemo-resistance and cancer metastasis. According to The Cancer Genome Atlas (TCGA), MIB1 gene is preferentially amplified in pancreatic cancer. Copy number alterations in MIB1 gene are associated with worse survival. Gene Expression Omnibus (GEO) also showed that pancreatic cancer with high mRNA level of MIB1 tend to be more resistant to gemcitabine and higher mRNA levels of MIB1 are found in pancreatic tumors compared with adjacent normal tissues. MIB1 knockdown (KD) in Panc-1 and HPAF2 cell lines significantly inhibit proliferation and colony formation of pancreatic cancer. The gene set enrichment analysis (GSEA) has also showed that β-catenin is the downstream of MIB1. Western blot analysis showed that total and active β-catenin levels are decreased in MIB1 KD cells. β-catenin inhibitor also inhibits proliferation of Panc-1 and HPAF2 cells. We in this study implanted HPAF2 scramble and MIB1 KD cells orthotopically in athymic nude mice. Gemcitabine was used to treat the mice. Results revealed that after MIB1 KD HPAF2 cells were more sensitive to gemcitabine. In conclusion, we demonstrated that MIB1 promotes pancreatic cancer proliferation through activating β-catenin signaling. MIB1 may thus be a therapeutic target in pancreatic cancer therapy.

scholarly journals BACH1: A Potential Predictor of Survival in Early-Stage Lung Adenocarcinoma

2022 ◽  
Vol 2022 ◽  
pp. 1-16
Author(s):  
Jin Zhou ◽  
Zheming Liu ◽  
Huibo Zhang ◽  
Tianyu Lei ◽  
Jiahui Liu ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Prognostic Model ◽  
Cox Regression ◽  
Early Stage ◽  
External Validation ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Cox Regression Analysis

Purpose. Recent researches showed the vital role of BACH1 in promoting the metastasis of lung cancer. We aimed to explore the value of BACH1 in predicting the overall survival (OS) of early-stage (stages I-II) lung adenocarcinoma. Patients and Methods. Lung adenocarcinoma cases were screened from the Cancer Genome Atlas (TCGA) database. Functional enrichment analysis was performed to obtain the biological mechanisms of BACH1. Gene set enrichment analysis (GSEA) was performed to identify the difference of biological pathways between high- and low-BACH1 groups. Univariate and multivariate COX regression analysis had been used to screen prognostic factors, which were used to establish the BACH1 expression-based prognostic model in the TCGA dataset. The C-index and time-dependent AUC curve were used to evaluate predictive power of the model. External validation of prognostic value was performed in two independent datasets from Gene Expression Omnibus (GEO). Decision analysis curve was finally used to evaluate clinical usefulness of the BACH1-based model beyond pathologic stage alone. Results. BACH1 was an independent prognostic factor for lung adenocarcinoma. High-expression BACH1 cases had worse OS. BACH1-based prognostic model showed an ideal C-index and t -AUC and validated by two GEO datasets, independently. More importantly, the BACH1-based model indicated positive clinical applicability by DCA curves. Conclusion. Our research confirmed that BACH1 was an important predictor of prognosis in early-stage lung adenocarcinoma. The higher the expression of BACH1, the worse OS of the patients.

scholarly journals Identification of a novel glycolysis-related gene signature for predicting metastasis and survival in patients with lung adenocarcinoma

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Lei Zhang ◽  
Zhe Zhang ◽  
Zhenglun Yu
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Single Gene ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Test Series ◽  
Cox Regression Analysis ◽  
Incidence And Mortality

Abstract Background Lung cancer (LC) is one of the most lethal and most prevalent malignant tumors, and its incidence and mortality are increasing annually. Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. Several biomarkers have been confirmed by data excavation to be related to metastasis, prognosis and survival. However, the moderate predictive effect of a single gene biomarker is not sufficient. Thus, we aimed to identify new gene signatures to better predict the possibility of LUAD. Methods Using an mRNA-mining approach, we performed mRNA expression profiling in large LUAD cohorts (n = 522) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and connections between genes and glycolysis were found in the Cox proportional regression model. Results We confirmed a set of nine genes (HMMR, B4GALT1, SLC16A3, ANGPTL4, EXT1, GPC1, RBCK1, SOD1, and AGRN) that were significantly associated with metastasis and overall survival (OS) in the test series. Based on this nine-gene signature, the patients in the test series could be divided into high-risk and low-risk groups. Additionally, multivariate Cox regression analysis revealed that the prognostic power of the nine-gene signature is independent of clinical factors. Conclusion Our study reveals a connection between the nine-gene signature and glycolysis. This research also provides novel insights into the mechanisms underlying glycolysis and offers a novel biomarker of a poor prognosis and metastasis for LUAD patients.

scholarly journals Bioinformatics Analysis Combined With Experiments Predicts CENPK as a Potential Prognostic Factor for Lung Adenocarcinoma

2020 ◽  
Author(s):  
Jiayu Ma ◽  
Xiaochuan Chen ◽  
Mingqiang Lin ◽  
Zhiping Wang ◽  
Yahua Wu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Biological Behavior ◽  
In Vitro Experiments ◽  
Tumor Identification

Abstract BackgroundLung cancer is the most commonly occurring malignant tumor. Identification of novel diagnostic and prognostic biomarkers for lung cancer is a key research imperative. The role of CENPK in cancer is an emerging area of research. However, the role of CENPK in the progression of lung adenocarcinoma (LAC) is not well characterized. MethodsIn this study, we identified centromere protein K (CENPK) as a potential new gene for lung cancer based on bioinformatics analysis. In addition, in vitro experiments, including were performed to verify the function of this gene. We investigated the expression of CENPK in LAC by bioinformatics analyses of datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, differential expression analyses, gene ontology (GO) enrichment, kyoto encyclopedia of genes and genomes (KEGG) analysis, and gene set enrichment analysis (GSEA) were conducted to evaluate its diagnostic and prognostic relevance. In vitro experiments including immunohistochemistry analysis, western blot analysis, CCK8 assay, Transwell assay, flow cytometry, wound healing assay, which were conducted to evaluate the biological behavior and role of CENPK in lung cancer cells.ResultsWe demonstrated overexpression of CENPK in LAC; in addition, increased expression of CENPK was associated with clinical progression. Moreover, CENPK was found to be an independent risk factor in patients with LAC. Furthermore, we observed activation of CENPK related signaling pathways in patients with LAC. ConclusionsIn summary, our findings indicate a potential role of CENPK in promoting tumor proliferation, invasion, and metastasis and its application as a novel diagnostic and prognostic biomarker of LAC.

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