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.

Cancer-associated Fibroblasts Are Associated With Poor Prognosis in Solid Type of Lung Adenocarcinoma: Machine Learning Approach

2021 ◽  
Author(s):  
Kyueng-Whan Min ◽  
Dong-Hoon Kim ◽  
Byoung Kwan Son ◽  
Mi Jung Kwon ◽  
Ji-Yong Moon
Keyword(s):  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Poor Prognosis ◽  
Transforming Growth Factor ◽  
Genetic Alterations ◽  
Gene Set Enrichment Analysis ◽  
Cancer Associated Fibroblasts ◽  
Mesenchymal Transition ◽  
Gene Sets ◽  
Solid Type

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

scholarly journals Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kyueng-Whan Min ◽  
Dong-Hoon Kim ◽  
Yung-Kyun Noh ◽  
Byoung Kwan Son ◽  
Mi Jung Kwon ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Poor Prognosis ◽  
Transforming Growth Factor ◽  
Genetic Alterations ◽  
Gene Set Enrichment Analysis ◽  
Cancer Associated Fibroblasts ◽  
Mesenchymal Transition ◽  
Gene Sets ◽  
Solid Type

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

scholarly journals Six-long Non-coding RNA Signature to Predict the Prognosis of Lung Adenocarcinoma

2020 ◽  
Author(s):  
Yang Wang ◽  
Chengping Hu
Keyword(s):  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Survival Rates ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Protein Coding ◽  
Cox Regression Analysis ◽  
Protein Coding Genes

Abstract Background: Long non-coding RNAs (lncRNAs) have been reported to play essential roles in tumorigenesis and cancers prognosis, and they can be a potential cancer prognostic markers. However, in lung adenocarcinoma(LUAD), how lncRNA signatures predict the survival of patients is poorly understood. Our study aims to explore lncRNA signatures and prognostic function in LUAD.Methods: The expression and prognosis data of lncRNAs in LUAD patients was collected from the Cancer Genome Atlas (TCGA) data. All analyses were performed using the R package (version 3.6.2). Metascape, STRING and Cytoscape were used for enrichment analysis and function prediction of the lncRNA co-expressed protein-coding genes.Results: We have collected lncRNA expression data in 466 LUAD tumors, and a six-lncRNA signature(RP11-79H23.3, RP11-309M7.1, CTD-2357A8.3, RP11-108P20.4, U47924.29, LHFPL3-AS2) has been shown to be significantly related to LUAD patients’ overall survival. According to the lncRNA signatures, the high-risk and low-risk groups were divided in LUAD patients with different survival rates. Further multivariable cox regression analysis showed that the prognostic value of this signature was independent of clinical factors. The potential functional roles and hub co-expressed protein-coding genes in the six prognostic lncRNAs are shown in the functional enrichment analysis.Conclusions: These results showed that these six lncRNAs could be independent predicted prognostic biomarkers in LUAD patients.

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 Profiling pro-neural to mesenchymal transition identifies a lncRNA signature in glioma

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Qingyu Liang ◽  
Gefei Guan ◽  
Xue Li ◽  
Chunmi Wei ◽  
Jianqi Wu ◽  
...  
Keyword(s):  
Cox Regression ◽  
Expression Profiles ◽  
Treatment Strategies ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
Risky Behaviors ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Mesenchymal Transition ◽  
Genome Atlas

Abstract Background Molecular classification has laid the framework for exploring glioma biology and treatment strategies. Pro-neural to mesenchymal transition (PMT) of glioma is known to be associated with aggressive phenotypes, unfavorable prognosis, and treatment resistance. Recent studies have highlighted that long non-coding RNAs (lncRNAs) are key mediators in cancer mesenchymal transition. However, the relationship between lncRNAs and PMT in glioma has not been systematically investigated. Methods Gene expression profiles from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), GSE16011, and Rembrandt with available clinical and genomic information were used for analyses. Bioinformatics methods such as weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), Cox analysis, and least absolute shrinkage and selection operator (LASSO) analysis were performed. Results According to PMT scores, we confirmed that PMT status was positively associated with risky behaviors and poor prognosis in glioma. The 149 PMT-related lncRNAs were identified by WGCNA analysis, among which 10 (LINC01057, TP73-AS1, AP000695.4, LINC01503, CRNDE, OSMR-AS1, SNHG18, AC145343.2, RP11-25K21.6, RP11-38L15.2) with significant prognostic value were further screened to construct a PMT-related lncRNA risk signature, which could divide cases into two groups with distinct prognoses. Multivariate Cox regression analyses indicated that the signature was an independent prognostic factor for high-grade glioma. High-risk cases were more likely to be classified as the mesenchymal subtype, which confers enhanced immunosuppressive status by recruiting macrophages, neutrophils, and regulatory T cells. Moreover, six lncRNAs of the signature could act as competing endogenous RNAs to promote PMT in glioblastoma. Conclusions We profiled PMT status in glioma and established a PMT-related 10-lncRNA signature for glioma that could independently predict glioma survival and trigger PMT, which enhanced immunosuppression.

scholarly journals Development and Validation of an Apoptosis-Related Genes Signature in Patients with Gastric Cancer

2021 ◽  
Author(s):  
Jianqiao Yang ◽  
Liang Shang ◽  
Leping Li ◽  
Zixiao Wang ◽  
Kangdi Dong ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Cox Regression ◽  
External Validation ◽  
Treatment Strategies ◽  
Enrichment Analysis ◽  
Malignant Tumour ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores

Abstract Background: Gastric cancer (GC) is a common malignant tumour of the digestive tract. the prognosis of GC patients is still not optimistic. Apoptosis-related genes (ARGs) plays an important role in the development, invasion, metastasis and drug resistance of GC. Therefore, assessing the interaction between ARGs and the prognosis of GC patients may help identify specific biomarkers.Methods: Differentially expressed genes (DEGs) were identified by integrating gene expression profiling analyses from The Cancer Genome Atlas (TCGA) GC cohort and Gene Set Enrichment Analysis (GSEA) Database. Then, a risk score model was built based on Kaplan-Meier (K-M), least absolute shrinkage and selector operation (LASSO), and multivariate Cox regression analyses. Another cohort (GSE84426) was used for external validation. By combining risk scores with clinical variables, a nomogram was constructed to predict the prognosis of GC patients. Results: We screened 39 DEGS and established a three-gene signature(CAV1、F2、LUM) based on 161 ARGs. In addition, three-gene signature was identified as an independent factor in predicting the prognosis of GC patients and validated in an external independent cohort. Finally, we developed a nomogram that can be applied to clinical practice.Conclusions: Our study established a three-gene signature of GC based on ARGs that has reference significance for in-depth research on the apoptosis mechanism of GC and the exploration of new clinical treatment strategies.

scholarly journals miR-154 Influences HNSCC Development and Progression through Regulation of the Epithelial-To-Mesenchymal Transition Process and Could Be Used as a Potential Biomarker

Biomedicines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1894
Author(s):  
Weronika Tomaszewska ◽  
Joanna Kozłowska-Masłoń ◽  
Dawid Baranowski ◽  
Anna Perkowska ◽  
Sandra Szałkowska ◽  
...  
Keyword(s):  
Immune Response ◽  
Epithelial To Mesenchymal Transition ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Clinicopathological Parameters ◽  
Mesenchymal Transition ◽  
Diagnostic Potential ◽  
Potential Biomarker

MicroRNAs and their role in cancer have been extensively studied for the past decade. Here, we analyzed the biological role and diagnostic potential of miR-154-5p and miR-154-3p in head and neck squamous cell carcinoma (HNSCC). miRNA expression analyses were performed using The Cancer Genome Atlas (TCGA) data accessed from cBioPortal, UALCAN, Santa Cruz University, and Gene Expression Omnibus (GEO). The expression data were correlated with clinicopathological parameters. The functional enrichment was assessed with Gene Set Enrichment Analysis (GSEA). The immunological profiles were assessed using the ESTIMATE tool and RNAseq data from TCGA. All statistical analyses were performed with GraphPad Prism and Statistica. The study showed that both miR-154-5p and miR-154-3p were downregulated in the HNSCC samples and their expression levels correlated with tumor localization, overall survival, cancer stage, tumor grade, and HPV p16 status. GSEA indicated that individuals with the increased levels of miR-154 had upregulated AKT-MTOR, CYCLIN D1, KRAS, EIF4E, RB, ATM, and EMT gene sets. Finally, the elevated miR-154 expression correlated with better immune response. This study showed that miR-154 is highly involved in HNSCC pathogenesis, invasion, and immune response. The implementation of miR-154 as a biomarker may improve the effectiveness of HNSCC treatment.

scholarly journals NRAS Expression is Associated With Prognosis and Tumor Immune Microenvironment in Lung Adenocarcinoma

2021 ◽  
Author(s):  
Yueren Yan ◽  
Zhendong Gao ◽  
Han Han ◽  
Yue Zhao ◽  
Yang Zhang ◽  
...  
Keyword(s):  
T Cells ◽  
Lung Adenocarcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Immune Microenvironment ◽  
Kaplan Meier ◽  
Tumor Immune Microenvironment ◽  
Cox Analysis

Abstract Purpose: NRAS plays a pivotal role in progression of various kinds of somatic malignancies; however, the correlation between NRAS and lung adenocarcinoma is less known. We aim to analyze the prognostic value of NRAS expression in lung adenocarcinoma, and explore the relationship between NRAS and tumor immune microenvironment. Methods: We obtained the transcriptome pofiles and clinical data of LUAD from The Cancer Genome Atlas database and three Genome Expression Omnibus datasets. Specimens from 325 patients with completely resected lung adenocarcinoma were collected for immunohistochemical assays of NRAS, PD-L1, PD-1 and TIM-3. Then we performed gene set enrichment analysis to investigate cancer-related and immune-related signaling pathways. TIMER algorithms were performed to evaluate tumor immune infiltrating cells and immune-related biomarkers.Results: Compared with adjacent non-tumor tissue, NRAS expression was significantly upregulated in LUAD tissue. NRAS expression was significantly correlated with more advanced stage and positive lymph nodes. Kaplan-Meier curves and Cox analysis suggested that high NRAS expression led to a poor prognosis, and could be an independent prognostic factor in LUAD patients. Besides, NRAS expression was positively correlated with CD8+ T cells, macrophages, and neutrophils, and negatively correlated with B cells and CD4+ T cells. The expression level of NRAS was positively correlated with PD-L1, PD-1, and TIM-3 both at RNA and protein level. Conclusions: To conclude, we found NRAS a novel prognostic biomarker in LUAD. Besides, the expression level of NRAS may influence the prognosis of LUAD via various kinds of cancer-related pathways and remodeling TIM.

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 Ferroptosis-Related Long Non-coding RNA Signature for Predicting the Outcome of Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhiyuan Zheng ◽  
Qian Zhang ◽  
Wei Wu ◽  
Yan Xue ◽  
Shuhan Liu ◽  
...  
Keyword(s):  
Immune Response ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Information Criteria ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Regression Analyses ◽  
Cox Regression Analysis ◽  
Kaplan Meier

BackgroundFerroptosis is a recently recognized type of programmed cell death that is involved in the biological processes of various cancers. However, the mechanism of ferroptosis in lung adenocarcinoma (LUAD) remains unclear. This study aimed to determine the role of ferroptosis-associated long non-coding RNAs (lncRNAs) in LUAD and to establish a prognostic model.MethodsWe downloaded ferroptosis-related genes from the FerrDb database and RNA sequencing data and clinicopathological characteristics from The Cancer Genome Atlas. We randomly divided the data into training and validation sets. Ferroptosis-associated lncRNA signatures with the lowest Akaike information criteria were determined using COX regression analysis and the least absolute shrinkage and selection operator. The risk scores of ferroptosis-related lncRNAs were calculated, and patients with LUAD were assigned to high- and low-risk groups based on the median risk score. The prognostic value of the risk scores was evaluated using Kaplan–Meier curves, Cox regression analyses, and nomograms. We then explored relationships between ferroptosis-related lncRNAs and the immune response using gene set enrichment analysis (GSEA).ResultsTen ferroptosis-related lncRNA signatures were identified in the training group, and Kaplan–Meier and Cox regression analyses confirmed that the risk scores were independent predictors of LUAD outcome in the training and validation sets (all P < 0.05). The area under the curve confirmed that the signatures could determine the prognosis of LUAD. The predictive accuracy of the established nomogram model was verified using the concordance index and calibration curve. The GSEA showed that the 10 ferroptosis-related lncRNAs might be associated with tumor immune response.ConclusionWe established a novel signature involving 10 ferroptosis-related lncRNAs (LINC01843, MIR193BHG, AC091185.1, AC027031.2, AL021707.2, AL031667.3, AL606834.1, AC026355.1, AC124045.1, and AC025048.4) that can accurately predict the outcome of LUAD and are associated with the immune response. This will provide new insights into the development of new therapies for LUAD.

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