scholarly journals Systematic Analysis of Gene Expression in Lung Adenocarcinoma and Squamous Cell Carcinoma with a Case Study of FAM83A and FAM83B

Cancers ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 886 ◽  
Author(s):  
Ling Cai ◽  
Danni Luo ◽  
Bo Yao ◽  
Donghan M. Yang ◽  
ShinYi Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Expression Data ◽  
Specific Expression

Introduction: In our previous study, we constructed a Lung Cancer Explorer (LCE) database housing lung cancer-specific expression data and clinical data from over 6700 patients in 56 studies. Methods: Using this dataset of the largest collection of lung cancer gene expression along with our meta-analysis method, we systematically interrogated the association between gene expression and overall survival as well as the expression difference between tumor and normal (adjacent non-malignant tissue) samples in lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SQCC). A case study for FAM83A and FAM83B was performed as a demonstration for hypothesis testing with our database. Results: We showed that the reproducibility of results across studies varied by histological subtype and analysis type. Genes and pathways unique or common to the two histological subtypes were identified and the results were integrated into LCE to facilitate user exploration. In our case study, we verified the findings from a previous study on FAM83A and FAM83B in non-small cell lung cancer. Conclusions: This study used gene expression data from a large cohort of patients to explore the molecular differences between lung ADC and SQCC.

scholarly journals UBE2D1 RNA Expression Was an Independent Unfavorable Prognostic Indicator in Lung Adenocarcinoma, but Not in Lung Squamous Cell Carcinoma

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Liyan Hou ◽  
Yingbo Li ◽  
Ying Wang ◽  
Dongqiang Xu ◽  
Hailing Cui ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Survival Data ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Indicator ◽  
The Cancer Genome Atlas ◽  
Rna Expression

In this study, we investigated the potential prognostic value of ubiquitin-conjugating enzyme E2D1 (UBE2D1) RNA expression in different histological subtypes of non-small-cell lung cancer (NSCLC). A retrospective study was performed by using molecular, clinicopathological, and survival data in the Cancer Genome Atlas (TCGA)—Lung Cancer. Results showed that both lung adenocarcinoma (LUAD) (N=514) and lung squamous cell carcinoma (LUSC) (N=502) tissues had significantly elevated UBE2D1 RNA expression compared to the normal tissues (p<0.001 and p=0.036, respectively). UBE2D1 RNA expression was significantly higher in LUAD than in LUSC tissues. Increased UBE2D1 RNA expression was independently associated with shorter OS (HR: 1.359, 95% CI: 1.031–1.791, p=0.029) and RFS (HR: 1.842, 95% CI: 1.353–2.508, p<0.001) in LUAD patients, but not in LUSC patients. DNA amplification was common in LUAD patients (88/551, 16.0%) and was associated with significantly upregulated UBE2D1 RNA expression. Based on these findings, we infer that UBE2D1 RNA expression might only serve as an independent prognostic indicator of unfavorable OS and RFS in LUAD, but not in LUSC.

scholarly journals Weighted gene expression profiles identify diagnostic and prognostic genes for lung adenocarcinoma and squamous cell carcinoma

2019 ◽  
Vol 48 (3) ◽  
pp. 030006051989383 ◽  
Author(s):  
Xing Wu ◽  
Linlin Wang ◽  
Fan Feng ◽  
Suyan Tian
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Prognostic Signature ◽  
Diagnostic Signature

Objective To construct a diagnostic signature to distinguish lung adenocarcinoma from lung squamous cell carcinoma and a prognostic signature to predict the risk of death for patients with nonsmall-cell lung cancer, with satisfactory predictive performances, good stabilities, small sizes and meaningful biological implications. Methods Pathway-based feature selection methods utilize pathway information as a priori to provide insightful clues on potential biomarkers from the biological perspective, and such incorporation may be realized by adding weights to test statistics or gene expression values. In this study, weighted gene expression profiles were generated using the GeneRank method and then the LASSO method was used to identify discriminative and prognostic genes. Results The five-gene diagnostic signature including keratin 5 ( KRT5), mucin 1 ( MUC1), triggering receptor expressed on myeloid cells 1 ( TREM1), complement C3 ( C3) and transmembrane serine protease 2 ( TMPRSS2) achieved a predictive error of 12.8% and a Generalized Brier Score of 0.108, while the five-gene prognostic signature including alcohol dehydrogenase 1C (class I), gamma polypeptide ( ADH1C), alpha-2-glycoprotein 1, zinc-binding ( AZGP1), clusterin ( CLU), cyclin dependent kinase 1 ( CDK1) and paternally expressed 10 ( PEG10) obtained a log-rank P-value of 0.03 and a C-index of 0.622 on the test set. Conclusions Besides good predictive capacity, model parsimony and stability, the identified diagnostic and prognostic genes were highly relevant to lung cancer. A large-sized prospective study to explore the utilization of these genes in a clinical setting is warranted.

scholarly journals The Regulators Associated With N6-Methyladenosine in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma Reveal New Clinical and Prognostic Markers

2021 ◽  
Vol 9 ◽  
Author(s):  
Shuzhen Tan ◽  
Zesong Li ◽  
Kai Li ◽  
Yingqi Li ◽  
Guosheng Liang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Markers ◽  
Cox Regression ◽  
Lung Squamous Cell Carcinoma ◽  
Lung Cancers ◽  
Pathological Characteristics

N6-methyladenosine (m6A) methylation is of significant importance in the initiation and progression of tumors, but how specific genes take effect in different lung cancers still needs to be explored. The aim of this study is to analyze the correlation between the m6A RNA methylation regulators and the occurrence and development of lung cancer. The data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) were obtained through the TCGA database. We systematically analyzed the related pathological characteristics and prognostic factors by applying univariate and multivariate Cox regression, as well as LASSO Cox regression. Some of 23 m6A regulators are identified as having high expression in lung cancer. In addition, risk score has been shown to be an independent prognostic factor in lung cancer. Our research not only fully reveals that m6A regulators and clinical pathological characteristics are potentially useful with respect to survival and prognosis in different lung tumors but also can lay a theoretical root for the treatment for lung cancer—notably, to point out a new direction for the development of treatment.

scholarly journals CENPF driven lung adenocarcinoma and lung squamous cell carcinoma with immune infiltrates

2020 ◽  
Author(s):  
Lei Li ◽  
Pengchao Zheng
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cd8 T Cells ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Marker

Abstract Background: CENPF (centromere protein F) is a critical gene that associates with the centromere-kinetochore complex and plays an important role in the tumor development. However, the associations of CENPF expression and tumor infiltrating lymphocytes in lung cancer remain unknown. Methods : CENPF expression and prognostic factor was analyzed via the Gene Expression Profiling Interactive Analysis (GEPIA) site. The correlation between CENPF and cancer immune infiltrates was investigated via and Tumor Immune Estimation Resource (TIMER) site. Further, correlations between CENPF expression and gene marker sets of immune infiltrates were analyzed by TIMER. Results: The TCGA database of Lung adenocarcinoma(LUAD) and Lung squamous cell carcinoma(LUSC) patients showed that high CENPF expression was associated with poorer overall survival (OS HR=1.5,P=0.01) and disease-free survival (DFS HR=1.4,P=0.027) in LUAD. Specifically, high CENPF expression have no correlated with worse OS(OS HR=0.78,P=0.071) and DFS(DFS HR=1,P=0.87) in LUSC. CENPF expression was positively correlated with infiltrating levels of B cells, macrophage in LUAD, B cells, and CD8+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in LUSC. CENPF expression showed strong correlations with diverse immune marker sets in LUAD, and LUSC. After down-regulating the expression of CENPF, the proliferative capacity of Lung adenocarcinoma and Lung squamous cell carcinoma cells was inhibited. Conclusions: This report suggest that CENPF is high expression, correlated with poor prognosis and immune infiltrating levels of, including those of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and DCs in in LUAD and LUSC. In addition, CENPF expression is potentially closely related to the proliferation and metastasis of lung cancer cells. These studies suggest that CENPF can be used as a new prognostic target for determining prognosis and immune infiltration in Lung adenocarcinoma and Lung squamous cell carcinoma.

scholarly journals CENPF driven lung adenocarcinoma and lung squamous cell carcinoma with immune infiltrates

2020 ◽  
Author(s):  
Lei Li ◽  
Pengfei Zheng
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Cd8 T Cells ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Marker

Abstract Background: CENPF (centromere protein F) is a critical gene that associates with the centromere-kinetochore complex and plays an important role in the tumor development. However, the associations of CENPF expression and tumor infiltrating lymphocytes in lung cancer remain unknown. Methods: CENPF expression and prognostic factor was analyzed via the Gene Expression Profiling Interactive Analysis (GEPIA) site. The correlation between CENPF and cancer immune infiltrates was investigated via and Tumor Immune Estimation Resource (TIMER) site. Further, correlations between CENPF expression and gene marker sets of immune infiltrates were analyzed by TIMER. Results: The TCGA database of Lung adenocarcinoma(LUAD) and Lung squamous cell carcinoma(LUSC) patients showed that high CENPF expression was associated with poorer overall survival (OS HR=1.5,P=0.01) and disease-free survival (DFS HR=1.4,P=0.027) in LUAD. Specifically, high CENPF expression have no correlated with worse OS(OS HR=0.78,P=0.071) and DFS(DFS HR=1,P=0.87) in LUSC. CENPF expression was positively correlated with infiltrating levels of B cells, macrophage in LUAD, B cells, and CD8+ T cells, macrophages, neutrophils, and dendritic cells (DCs) in LUSC. CENPF expression showed strong correlations with diverse immune marker sets in LUAD, and LUSC. After down-regulating the expression of CENPF, the proliferative capacity of Lung adenocarcinoma and Lung squamous cell carcinoma cells was inhibited. Conclusions: This report suggest that CENPF is high expression, correlated with poor prognosis and immune infiltrating levels of, including those of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and DCs in in LUAD and LUSC. In addition, CENPF expression is potentially closely related to the proliferation and metastasis of lung cancer cells. These studies suggest that CENPF can be used as a new prognostic target for determining prognosis and immune infiltration in Lung adenocarcinoma and Lung squamous cell carcinoma.

scholarly journals Genetic Liability to Insomnia and Lung Cancer Risk: A Mendelian Randomization Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Jiayi Shen ◽  
Huaqiang Zhou ◽  
Jiaqing Liu ◽  
Yaxiong Zhang ◽  
Ting Zhou ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Confidence Interval ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Lung Squamous Cell Carcinoma ◽  
Genetic Liability

Lung cancer is the second most frequently diagnosed cancer and the leading cause of cancer death worldwide, making its prevention an urgent issue. Meanwhile, the estimated prevalence of insomnia was as high as 30% globally. Research on the causal effect of insomnia on lung cancer incidence is still lacking. In this study, we aimed to assess the causality between the genetic liability to insomnia and lung cancer. We performed a two-sample Mendelian randomization analysis (inverse variance weighted) to determine the causality between the genetic liability to insomnia and lung cancer. Subgroup analysis was conducted, which included lung adenocarcinoma and lung squamous cell carcinoma. In the sensitivity analysis, we conducted heterogeneity test, MR Egger, single SNP analysis, leave-one-out analysis, and MR PRESSO. There were causalities between the genetic susceptibility to insomnia and increased incidence of lung cancer [odds ratio (95% confidence interval), 1.35 (1.14–1.59); P, &lt; 0.001], lung adenocarcinoma [odds ratio (95% confidence interval), 1.35 (1.07–1.70); P, 0.01], and lung squamous cell carcinoma [odds ratio (95% confidence interval), 1.35 (1.06–1.72), P, 0.02]. No violation of Mendelian randomization assumptions was observed in the sensitivity analysis. There was a causal relationship between the genetic susceptibility to insomnia and the lung cancer, which was also observed in lung adenocarcinoma and lung squamous cell carcinoma. The underlying mechanism remains unknown. Effective intervention and management for insomnia were recommended to improve the sleep quality and to prevent lung cancer. Moreover, regular screening for lung cancer may be beneficial for patients with insomnia.

scholarly journals The bioinformatics analysis of RIOX2 gene in lung adenocarcinoma and squamous cell carcinoma

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0259447
Author(s):  
Bingqing Sun ◽  
Hongwen Zhao
Keyword(s):  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Public Health Issue ◽  
High Morbidity ◽  
Link Type

Lung cancer is characterized by high morbidity and mortality rates, and it has become an important public health issue worldwide. The occurrence and development of tumors is a multi-gene and multi-stage complex process. As an oncogene, ribosomal oxygenase 2 (RIOX2) has been associated with a variety of cancers. In this article, we analyzed the correlation between RIOX2 expression and methylation in lung cancer based on the databases including the cancer genome atlas (TCGA) (https://portal.gdc.cancer.gov/) and the gene expression omnibus (GEO) (https://www.ncbi.nlm.nih.gov/geo/). It was found that RIOX2 is highly expressed in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) tissues, whose expression is negatively correlated with its methylation level. In this regard, methylation at cg09716038, cg14773523, cg14941179, and cg22299097 had a significant negative correlation with RIOX2 expression in LUAD, whereas in LUSC, methylation at cg09716038, cg14773523, cg14941179, cg22299097, cg05451573, cg10779801, and cg23629183 is negatively correlated with RIOX2 expression. According to the analysis based on the databases, RIOX2 gene could not be considered as the independent prognostic biomarker in lung adenocarcinoma or squamous cell lung cancer. However, the molecular mechanism of RIOX2 gene in the development of lung cancer may be helpful in improving lung cancer therapy.

scholarly journals Tumor mutation burden (TMB)-associated signature constructed to predict survival of lung squamous cell carcinoma patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Dan Yan ◽  
Yi Chen
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Clinical Characteristics ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Risk Scores ◽  
Cox Analysis

AbstractLung squamous cell carcinoma (LUSC) is a common type of lung cancer with high incidence and mortality rate. Tumor mutational burden (TMB) is an emerging biomarker for selecting patients with non-small cell lung cancer (NSCLC) for immunotherapy. This study aimed to reveal TMB involved in the mechanisms of LUSC and develop a model to predict the overall survival of LUSC patients. The information of patients with LUSC were obtained from the cancer genome atlas database (TCGA). Differentially expressed genes (DEGs) between low- and the high-TMB groups were identified and taken as nodes for the protein–protein interaction (PPI) network construction. Gene oncology (GO) enrichment analysis and gene set enrichment analysis (GSEA) were used to investigate the potential molecular mechanism. Then, we identified the factors affecting the prognosis of LUSC through cox analysis, and developed a risk score signature. Kaplan–Meier method was conducted to analyze the difference in survival between the high- and low-risk groups. We constructed a nomogram based on the risk score model and clinical characteristics to predict the overall survival of patients with LUSC. Finally, the signature and nomogram were further validated by using the gene expression data downloaded from the Gene Expression Omnibus (GEO) database. 30 DEGs between high- and low-TMB groups were identified. PPI analysis identified CD22, TLR10, PIGR and SELE as the hub genes. Cox analysis indicated that FAM107A, IGLL1, SELE and T stage were independent prognostic factors of LUSC. Low-risk scores group lived longer than that of patients with high-risk scores in LUSC. Finally, we built a nomogram that integrated the clinical characteristics (TMN stage, age, gender) with the three-gene signature to predict the survival probability of LUSC patients. Further verification in the GEO dataset. TMB might contribute to the pathogenesis of LUSC. TMB-associated genes can be used to develope a model to predict the OS of lung squamous cell carcinoma patients.

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