scholarly journals Immune Infiltration Landscape in Lung Squamous Cell Carcinoma Implications

2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Jungang Zhao ◽  
Wenming Bao ◽  
Weiyang Cai
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Clustering Analysis ◽  
Immune Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Immune Microenvironment

Intrinsic cancer cells and the tumor-infiltrating immune cells (TIICs) recruited to the immune microenvironment define the malignant phenotype of lung squamous cell carcinoma (LUSC). Understanding more about the immune microenvironment of LUSC enables the selection of high-risk patients who would derive benefit from immunotherapy. Based on large public LUSC cohorts obtained from TCGA and GEO datasets, 22 types of infiltrating immune cell subgroups were evaluated by CIBERSORT. Meta-analysis, principal component analysis (PCA), single-sample gene set enrichment analysis (ssGSEA), and hierarchical clustering analysis were used to evaluate specific immune responses of LUSC. The distribution of TIICs of LUSC was entirely different from normal. TIIC subpopulations were also found to be closely associated with clinical features and molecular subtypes. Unsupervised clustering analysis revealed that three distinct TIIC subgroups existed with different survival patterns. TIICs are extensively implicated in the pathogenesis and development of LUSC. Characterizing the composition of TIICs influences the metabolism, pathological stage, and survival of tumor patients. It is hoped that this immune landscape could provide a more accurate understanding of the development and immunotherapy of LUSC.

scholarly journals Human sperm-associated antigen 4 as a potential prognostic biomarker of lung squamous cell carcinoma

2021 ◽  
Vol 49 (7) ◽  
pp. 030006052110328
Author(s):  
Yongheng Wang ◽  
Yao Tang ◽  
Jianhui Li ◽  
Danfang Wang ◽  
Wenhan Li
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Malignant Tumors ◽  
Lung Squamous Cell Carcinoma ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Tissue Samples

Objective Lung cancer (LC) is one of the most prevalent malignant tumors worldwide. As a subtype of LC, lung squamous cell carcinoma (LUSC) has a 5-year survival rate of less than 15%. In this study, we aimed to evaluate the prognostic value of a glycolysis-related gene signature in LUSC patients. Methods We obtained RNA-Seq data from The Cancer Genome Atlas (TCGA) database. Prognosis-related genes were screened out by Gene Set Enrichment Analysis (GSEA) and Cox proportional regression models. Quantitative reverse transcription polymerase chain reaction (RT-qPCR) was used to verify the mRNA expression levels in relevant tissues. Results We found that sperm-associated antigen 4 (SPAG4) overexpression was an independent risk factor for overall survival (OS) in LUSC. Patients with high-risk scores had higher mortality rates than those with low-risk scores. Moreover, by using RT-qPCR, we validated that SPAG4 mRNA was overexpressed in LUSC tissue samples compared with their paired para-cancerous histological normal tissues. Conclusions Analysis of aberrantly overexpressed SPAG4 may provide a further useful approach to complement existing methods and predict prognosis in LUSC patients.

scholarly journals Defining Metabolic Rewiring in Lung Squamous Cell Carcinoma

Metabolites ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 47 ◽  
Author(s):  
Rachel Paes de Araújo ◽  
Natália Bertoni ◽  
Ana Seneda ◽  
Tainara Felix ◽  
Márcio Carvalho ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
High Throughput Screening ◽  
High Resolution Mass Spectrometry ◽  
Screening Method ◽  
Lung Squamous Cell Carcinoma ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Normal Lung

Metabolomics based on untargeted flow infusion electrospray ionization high-resolution mass spectrometry (FIE-HRMS) can provide a snap-shot of metabolism in living cells. Lung Squamous Cell Carcinoma (SCC) is one of the predominant subtypes of Non-Small Cell Lung Cancers (NSCLCs), which usually shows a poor prognosis. We analysed lung SCC samples and matched histologically normal lung tissues from eight patients. Metabolites were profiled by FIE-HRMS and assessed using t-test and principal component analysis (PCA). Differentially accumulating metabolites were mapped to pathways using the mummichog algorithm in R, and biologically meaningful patterns were indicated by Metabolite Set Enrichment Analysis (MSEA). We identified metabolic rewiring networks, including the suppression of the oxidative pentose pathway and found that the normal tricarboxylic acid (TCA) cycle were decoupled from increases in glycolysis and glutamine reductive carboxylation. Well-established associated effects on nucleotide, amino acid and thiol metabolism were also seen. Novel aspects in SCC tissue were increased in Vitamin B complex cofactors, serotonin and a reduction of γ-aminobutyric acid (GABA). Our results show the value of FIE-HRMS as a high throughput screening method that could be exploited in clinical contexts.

scholarly journals A glycolysis-based three-gene signature predicts survival in patients with lung squamous cell carcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Guichuan Huang ◽  
Jing Zhang ◽  
Ling Gong ◽  
Yi Huang ◽  
Daishun Liu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Risk Score ◽  
Squamous Cell ◽  
Cox Regression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Cox Regression Analysis

Abstract Background Lung cancer is one of the most lethal and most prevalent malignant tumors worldwide, and lung squamous cell carcinoma (LUSC) is one of the major histological subtypes. Although numerous biomarkers have been found to be associated with prognosis in LUSC, the prediction effect of a single gene biomarker is insufficient, especially for glycolysis-related genes. Therefore, we aimed to develop a novel glycolysis-related gene signature to predict survival in patients with LUSC. Methods The mRNA expression files and LUSC clinical information were obtained from The Cancer Genome Atlas (TCGA) dataset. Results Based on Gene Set Enrichment Analysis (GSEA), we found 5 glycolysis-related gene sets that were significantly enriched in LUSC tissues. Univariate and multivariate Cox proportional regression models were performed to choose prognostic-related gene signatures. Based on a Cox proportional regression model, a risk score for a three-gene signature (HKDC1, ALDH7A1, and MDH1) was established to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis indicated that the risk score for this three-gene signature can be used as an independent prognostic indicator in LUSC. Additionally, based on the cBioPortal database, the rate of genomic alterations in the HKDC1, ALDH7A1, and MDH1 genes were 1.9, 1.1, and 5% in LUSC patients, respectively. Conclusion A glycolysis-based three-gene signature could serve as a novel biomarker in predicting the prognosis of patients with LUSC and it also provides additional gene targets that can be used to cure LUSC patients.

scholarly journals Prognostic Impact of Immune Microenvironment in Lung Squamous Cell Carcinoma

2015 ◽  
Vol 10 (9) ◽  
pp. 1301-1310 ◽  
Author(s):  
Kyuichi Kadota ◽  
Jun-ichi Nitadori ◽  
Hideki Ujiie ◽  
Daniel H. Buitrago ◽  
Kaitlin M. Woo ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Prognostic Impact ◽  
Immune Microenvironment

scholarly journals PPARG Could Work as a Valid Therapeutic Strategy for the Treatment of Lung Squamous Cell Carcinoma

PPAR Research ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Shunbin Shi ◽  
Guiping Yu ◽  
Bin Huang ◽  
Yedong Mi ◽  
Yan Kang ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Nonsmall Cell Lung Cancer ◽  
Ppar Gamma ◽  
Gene Set Enrichment Analysis ◽  
Marker Genes ◽  
Molecular Pathways ◽  
Regulatory Pathways

Previous studies showed that PPAR-gamma (PPARG) ligands might serve as potential therapeutic agents for nonsmall cell lung cancer (NSCLC). However, a few studies reported the specific relationship between PPARG and lung squamous cell carcinoma (LSCC). Here, we made an effort to explore the relationship between PPARG and LSCC. First, we used mega-analysis and partial mega-analysis to analyze the effects of PPARG on LSCC by using 12 independent LSCC expression datasets (285 healthy controls and 375 LSCC cases). Then, literature-based molecular pathways between PPARG and LSCC were established. After that, a gene set enrichment analysis (GSEA) was conducted to study the functionalities of PPARG and PPARG-driven triggers within the molecular pathways. Finally, another mega-analysis was constructed to test the expression changes of PPARG and its driven targets. The partial mega-analysis showed a significant downregulated expression of PPARG in LSCC (LFC=−1.08, p value=0.00073). Twelve diagnostic markers and four prognostic markers were identified within multiple PPARG-LSCC regulatory pathways. Our results suggested that the activation of PPARG expression may inhibit the development and progression of LSCC through the regulation of LSCC upstream regulators and downstream marker genes, which were involved in tumor cell proliferation and protein polyubiquitination/ubiquitination.

scholarly journals Upregulated Glycolysis Correlates With Clinical and Transcriptomic Significances in Head and Neck Squamous Cell Carcinoma

2021 ◽  
Author(s):  
Hideyuki Takahashi ◽  
Reika Kawabata-Iwakawa ◽  
Shota Ida ◽  
Ikko Mito ◽  
Hiroe Tada ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Head And Neck ◽  
Squamous Cell ◽  
Enrichment Analysis ◽  
Janus Kinase ◽  
Gene Set Enrichment Analysis ◽  
Neck Squamous Cell Carcinoma ◽  
Tumor Type ◽  
High Group

Abstract Altered metabolism is an emerging hallmark of cancer. Cancer cells preferentially utilize glycolysis for energy production, termed “aerobic glycolysis.” In this study, we performed a comprehensive analysis of the glycolysis status in the tumor microenvironment (TME) of head and neck squamous cell carcinoma (HNSCC) using data from The Cancer Genome Atlas database. We first divided 520 patients with HNSCC into two groups based on the mRNA expression of 16 glycolysis-related genes. The glycolysis-high signature positively correlated with human papillomavirus-negative tumor type, advanced T factor, and unfavorable prognosis. The gene set enrichment analysis revealed upregulation of several pathways, including interferon-alpha response, myc targets, hypoxia, epithelial-mesenchymal transition, transforming growth factor-β signaling, and interleukin 6-Janus kinase-signal transducer and activator of transcription 3 signaling, in the glycolysis-high group. Immune cell enrichment analysis revealed decreased infiltration of T cells, dendritic cells, and B cells in the glycolysis-high group, suggesting impaired tumor antigen presentation, T cell activation, and antibody production in TME. Moreover, the expression of TGFB1, CD274, and PDCD1LG2, which facilitate immunosuppression in the TME, was upregulated in the glycolysis-high group. Collectively, these findings suggest the potential of glycolysis monitoring as a biomarker for tumor progression and immunosuppression in the TME of HNSCC.

scholarly journals Construction and Validation of an Immune-Related Gene Prognostic Index for Esophageal Squamous Cell Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Qinghua Ji ◽  
Yingying Cai ◽  
Sachin Mulmi Shrestha ◽  
Duo Shen ◽  
Wei Zhao ◽  
...  
Keyword(s):  
Squamous Cell Carcinoma ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Index ◽  
Enrichment Analysis ◽  
Response To Therapy ◽  
Gene Set Enrichment Analysis ◽  
Related Gene ◽  
Immune Related Gene

Immune checkpoint inhibitor (ICI) therapy may benefit patients with advanced esophageal squamous cell carcinoma (ESCC); however, novel biomarkers are needed to help predict the response of patients to treatment. Differentially expressed immune-related genes within The Cancer Genome Atlas ESCC dataset were selected using the weighted gene coexpression network and lasso Cox regression analyses. Based on these data, an immune-related gene prognostic index (IRGPI) was constructed. The molecular characteristics of the different IRGPI subgroups were assessed using mutation information and gene set enrichment analysis. Differences in immune cell infiltration and the response to ICI therapy and other drugs were also analyzed. Additionally, tumor and adjacent control tissues were collected from six patients with ESCC and the expression of these genes was verified using real-time quantitative polymerase chain reaction. IRGPI was designed based on CLDN1, HCAR3, FNBP1L, and BRCA2, the expression of which was confirmed in ESCC samples. The prognosis of patients in the high-IRGPI group was poor, as verified using publicly available expression data. KMT2D mutations were more common in the high-IRGPI group. Enrichment analysis revealed an active immune response, and immune infiltration assessment showed that the high-IRGPI group had an increased infiltration degree of CD8 T cells, which contributed to the improved response to ICI treatment. Collectively, these data demonstrate that IRGPI is a robust biomarker for predicting the prognosis and response to therapy of patients with ESCC.

scholarly journals Identification of Cell cycle Gene Signatures Predicting Survival in Patients with Lung Squamous Cell Carcinoma

2019 ◽  
Author(s):  
Lei Zhang ◽  
Zhe Zhang ◽  
Zhenglun Yu
Keyword(s):  
Cell Cycle ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Test Series ◽  
Gene Signatures ◽  
Gene Set

Abstract Background:Lung cancer (LC) is one of the most important and common malignant tumors, and its incidence and mortality are increasing annually. Lung squamous cell carcinoma (LUSC) is the common pathological type of lung cancer. A small part of biomarkers have been confirmed to be related to the prognosis and survival by data excavation. However, the moderate forecast effect of a single gene biomarker is not accurate. Thus, we aimed to identify new gene signatures to better predict Lung squamous cell carcinoma ( LU SC). Methods : Using the mRNA-mining approach, we performed mRNA expression profiling in large lung squamous cell carcinoma cohorts (n= from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis(GSVA) were accomplished, and connections between genes and cell cycle were found in the Cox proportional regression model. Results : We have confirmed a set of four genes (CDKN1A, CHEK2, E2F4 and RAD21) that were importantly associated with overall survival (OS) in the test series. Based on the research of the four-gene signature, the patients in the test series could be divided into high-risk and low-risk teams. Additionally, multivariate Cox regression analysis revealed that the prognostic power of the four-gene signature is independent of the clinical factors. Conclusion : Our study demonstrated the connections between the four-gene signature and cell cycle. Novel insights into the research mechanisms of cell cycle was also revealed regarding the biomarkers of a poor prognosis for lung squamous cell carcinoma patients.

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