A New Gene Expression Meta-Analysis Technique and its Application to Co-Analyze Three Independent Lung Cancer Datasets

BackgroundImmune checkpoint blockade therapy represents an extraordinary advance in lung cancer treatment. It is important to determine the expression of immune checkpoint genes, such as programmed cell death 1 (PD1) and programmed cell death-ligand 1 (PDL1), to develop immunotherapeutic strategies. The aim of this study was to explore the association between PD1 and PDL1 gene expression and prognoses and outcomes in lung cancer.MethodsThis meta-analysis analyzed 1,251 patients from eight different microarray gene expression datasets and were evaluated for their prognostic implications and verified using another independent research.ResultsThe mean expression levels of PDL1 in adenocarcinoma (AD) and squamous cell carcinoma (SC) were significantly higher in patients who died than in patients who did not. There was a trend toward incremental increases in PD1 and PDL1 expression significantly decreasing the risk of relapse and death among AD patients (HR = 0.69; 95% CI = 0.53 ~ 0.91; HR = 0.68; 95% CI = 0.54 ~ 0.84, respectively) and SC patients (HR = 0.53; 95% CI = 0.32 ~ 0.89; HR = 0.78; 95% CI = 0.57 ~ 1.00 respectively), as early-stage patients in this study were more likely to have high expression of both PD1 and PDL1 than late-stage patients (P-trend < 0.05). In contrast, late-stage SC patients expressing one or more of the genes at a high level had a significantly elevated risk of relapse (HR = 1.51; 95% CI = 1.07 ~ 2.11) and death (HR = 1.41; 95% CI = 1.08 ~ 1.84). This result was consistent with the validation data set.ConclusionThese findings indicate that high expression of PD1 and PDL1 is associated with superior outcome in early-stage lung cancer but an adverse outcome in late-stage lung cancer. The expression levels of PD1 and PDL1 individually or jointly are potential prognostic factors for predicting patient outcomes in lung cancer.

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Analysis the susceptibility of lung cancer patients to SARS-CoV-2 infection

10.21203/rs.3.rs-17713/v1 ◽

2020 ◽

Author(s):

Qi Kong

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Meta Analysis ◽

Lung Squamous Cell Carcinoma ◽

Gene Expression Omnibus ◽

Lung Cancers ◽

Lung Cancer Patients ◽

Angiotensin I Converting Enzyme ◽

Novel Coronavirus ◽

Transmembrane Serine Protease

Abstract Recent studies have reported that 2019 novel coronavirus disease (COVID-19) patients with lung cancer have a higher risk of severe events than patients without cancer. In this study, we investigated the expression of severe acute respiratory syndrome coronavirus 2 (SAR-CoV-2) receptor angiotensin I-converting enzyme 2 (ACE2) and the cellular protease transmembrane serine protease 2 (TMPRSS2) and their associations with prognosis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). We found that there are significant differences in susceptibility to SAR-CoV-2 among each age stages of individuals with the expression of ACE2. ACE2 was also high expressed in LUAD and LUSC, and this suggests that COVID-19 patients with lung cancers are susceptible to SAR-CoV-2 infection. Our data showed the differential gene expression level and gene coexpression of ACE2 and TMPRSS2 among each subtypes and pathological stages of LUAD and LUSC and the data were verified by meta-analysis, gene expression omnibus (GEO) data and animal models results.

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A Meta-analysis of Lung Cancer Gene Expression Identifies PTK7 as a Survival Gene in Lung Adenocarcinoma

Cancer Research ◽

10.1158/0008-5472.can-13-2775 ◽

2014 ◽

Vol 74 (10) ◽

pp. 2892-2902 ◽

Cited By ~ 85

Author(s):

Ron Chen ◽

Purvesh Khatri ◽

Pawel K. Mazur ◽

Melanie Polin ◽

Yanyan Zheng ◽

...

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Lung Adenocarcinoma ◽

Meta Analysis ◽

Cancer Gene ◽

Survival Gene

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The association of melanoma-associated antigen-A gene expression with clinicopathological characteristics and prognosis in resected non-small-cell lung cancer: a meta-analysis

Interactive CardioVascular and Thoracic Surgery ◽

10.1093/icvts/ivz196 ◽

2019 ◽

Vol 29 (6) ◽

pp. 855-860

Author(s):

Yan Wang ◽

Yuqing Lu ◽

Jialong Li ◽

Yanming Wu ◽

Guowei Che

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Small Cell Lung Cancer ◽

Squamous Cell ◽

Cell Lung Cancer ◽

Meta Analysis ◽

Clinicopathological Characteristics ◽

Small Cell ◽

Small Cell Lung ◽

Resected Nsclc

Abstract Our goal was to explore the association of melanoma-associated antigen-A (MAGE-A) gene expression with clinicopathological parameters and survival rates in patients with non-small-cell lung cancer (NSCLC) who had surgery. A systematic search of EMBASE, PubMed, Web of Science and The Cochrane Library databases was performed through 20 April 2019. The combined risk ratios (RRs) and hazard ratios (HRs) with their corresponding 95% confidence intervals (CIs) were calculated to assess the association of MAGE-A gene expression with clinicopathological characteristics and prognosis of patients with resected NSCLC, respectively. All statistical analyses were performed with Stata software, version 12.0. A total of 9 articles involving 1538 patients were included in our meta-analysis; most of the studies were from Asian countries. The results indicated that the expression of the MAGE-A gene was significantly correlated with lymph node metastases (RR 1.21, 95% CI 1.09–1.34; P = 0.001), high tumour-node-metastasis stage (RR 1.24, 95% CI 1.12–1.38; P < 0.001), histological type (squamous cell carcinoma) (RR 1.82, 95% CI 1.15–2.87; P = 0.01), poor overall survival (HR 2.11, 95% CI 1.73–2.57; P < 0.001) and cancer-specific survival (HR 1.76, 95% CI 1.12–2.78; P = 0.015). MAGE-A gene expression is related to tumour development and metastasis and is more prevalent in squamous cell carcinomas of the lung; besides, it is an independent prognostic factor for patients with resected NSCLC.

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A Meta-analysis of Comorbidities in COVID-19: Which Diseases increase the Susceptibility of SARS-CoV-2 Infection?

10.20944/preprints202009.0486.v1 ◽

2020 ◽

Author(s):

Srinivasan Ramachandran ◽

Manoj Kumar Singh ◽

Ahmed Mobeen ◽

Amit Chandra ◽

Sweta Joshi

Keyword(s):

Breast Cancer ◽

Gene Expression ◽

Lung Cancer ◽

Type Ii Diabetes ◽

Molecular Mechanisms ◽

Meta Analysis ◽

Specific Gene ◽

Type Ii ◽

Alcoholic Fatty Liver ◽

Cancer Breast

Background: Comorbidities have been frequently reported in COVID-19 patients, which often lead to more severe outcomes. The underlying molecular mechanisms behind these clinical observations have not yet been explained. Herein, we investigated the disease-specific gene expression signatures that may induce susceptibility to SARS-CoV-2 infection. Methods: We studied 30 frequently occurring acute, chronic, or infectious diseases of recent times that have shown comorbidity in one or another respiratory disease(s) caused by pathogenic human infecting coronaviruses, especially SARS-CoV-2. We retrieved array-based gene expression data for each disease and control from relevant datasets. Subsequently, all the datasets were quantile normalized, and log-2 transformed data was used for analysis. Results The expression of ACE2 receptor and host proteases, namely FURIN and TMPRSS2 that are essential for cellular entry of SARS-CoV-2, was upregulated in all six studied subtypes of leukemia (hereafter, referred as leukemia). The expression of ACE2 was also increased in psoriasis, lung cancer, Non-alcoholic fatty liver disease (NAFLD), breast cancer, and pulmonary arterial hypertension patients. The expression of FURIN was higher in psoriasis, NAFLD, lung cancer, and in type II diabetic liver, whereas it was lowered in breast cancer. Similarly, the expression of TMPRSS2 was increased during lung cancer and type II diabetes; it was decreased during psoriasis, NAFLD, lung cancer, breast cancer, and cervical cancer.Furthermore, a heightened expression of genes that are involved in immune response was observed in leukemia patients, as shown by the higher expression of IFNA2, IFNA8, IFNA10, IFNA14, IFNA16, IFNA21, IFNB1, CXCL10, and IL6. The expression of JAK1, STAT1, IL6, and CXCL10 was higher in NAFLD. Besides, JAK1 and STAT1 were upregulated in type II diabetic muscles. In addition, most of the upregulated genes in COVID-19 patients showed a similar trend in leukemia, NAFLD, and psoriasis. Furthermore, SARS-CoV-2, SARS-CoV and MERS CoV, were found to commonly alter two genes, namely, CARBONIC ANHYDRASE 11 and CLUSTERIN.Conclusions: The genes that may confer susceptibility to SARS-CoV-2 infection are mostly upregulated in leukemia patients; hence, leukemia patients are relatively more susceptible to develop COVID-19, followed by other chronic disorders, such as, NAFLD, type II diabetes, psoriasis, and hypertension. This study identifies key genes that are altered in the studied diseases types, which may aid in the infection of SARS-CoV-2 and underlie COVID-19 associated comorbidities.

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Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer

PLoS ONE ◽

10.1371/journal.pone.0014635 ◽

2011 ◽

Vol 6 (1) ◽

pp. e14635 ◽

Cited By ~ 40

Author(s):

Claire Grills ◽

Puthen V. Jithesh ◽

Jaine Blayney ◽

Shu-Dong Zhang ◽

Dean A. Fennell

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Small Cell Lung Cancer ◽

Cell Lung Cancer ◽

Early Stage ◽

Meta Analysis ◽

Small Cell ◽

Small Cell Lung ◽

Poor Outcome

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Transcriptome analysis reveals key signature genes involved in the oncogenesis of lung cancer

Cancer Biomarkers ◽

10.3233/cbm-200110 ◽

2020 ◽

Vol 29 (4) ◽

pp. 475-482

Author(s):

Fanlu Meng ◽

Linlin Zhang ◽

Yaoyao Ren ◽

Qing Ma

Keyword(s):

Gene Expression ◽

Lung Cancer ◽

Expression Profiles ◽

Meta Analysis ◽

Gene Expression Profiles ◽

Interaction Network ◽

Functional Enrichment ◽

Sequencing Platform ◽

Signature Genes ◽

Regulated Expression

Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer.

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