The prognostic value of platelet endothelial cell adhesion molecule-1 in non-small-cell lung cancer patients

Kuang, Bo Hua; Xi, Wen; Ding, Ya; Peng, Rui; Cai, Pei; Zhang, Meng Qing; Jiang, Feng; Zhang, Xiao Shi; Zhang, Xing

doi:10.1007/s12032-013-0536-5

Cited by 20 publications

(13 citation statements)

References 19 publications

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“…Moreover, some of the associated adjacent genes are implicated in cancer. For example, PIM3 is a proto‐oncogene that enhances pancreatic cancer growth by modulating tumor vasculogenesis (Kuang et al , ; Liu et al , ); PTP4A3 can promote cancer metastasis particularly in colorectal cancers (Al‐Aidaroos & Zeng, ; Cramer et al , ; Huang et al , ); and TOMM20 expression is associated with tumor size in gastric cancer (Zhao et al , ).…”

Section: Resultsmentioning

confidence: 99%

Comprehensive assembly of novel transcripts from unmapped human RNA‐Seq data and their association with cancer

Kazemian

Ren

Lin

et al. 2015

Molecular Systems Biology

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Crucial parts of the genome including genes encoding microRNAs and noncoding RNAs went unnoticed for years, and even now, despite extensive annotation and assembly of the human genome, RNA-sequencing continues to yield millions of unmappable and thus uncharacterized reads. Here, we examined > 300 billion reads from 536 normal donors and 1,873 patients encompassing 21 cancer types, identified ∼300 million such uncharacterized reads, and using a distinctive approach de novo assembled 2,550 novel human transcripts, which mainly represent long noncoding RNAs. Of these, 230 exhibited relatively specific expression or non-expression in certain cancer types, making them potential markers for those cancers, whereas 183 exhibited tissue specificity. Moreover, we used lentiviral-mediated expression of three selected transcripts that had higher expression in normal than in cancer patients and found that each inhibited the growth of HepG2 cells. Our analysis provides a comprehensive and unbiased resource of unmapped human transcripts and reveals their associations with specific cancers, providing potentially important new genes for therapeutic targeting.

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Section: Resultsmentioning

confidence: 99%

Comprehensive assembly of novel transcripts from unmapped human RNA‐Seq data and their association with cancer

Kazemian

Ren

Lin

et al. 2015

Molecular Systems Biology

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“…Many studies had reported that CDH5 expression is associated with multiple tumors [ 43 , 44 ], such as gastric cancer and breast cancer, but the relationship between CDH5 and LUAD is still to be determined. PECAM1 is a multifunctional cell adhesion molecule involved in numerous physiologic processes within the vasculature; Abraham et al found that the activity of PECAM1 appears to be associated with the tumor microenvironment and tumor cell proliferation [ 45 ]; Kuang et al demonstrated that PECAM1 could be a potential prognostic factor and therapeutic target in NSCLC [ 46 ]. The von Willebrand factor (VWF) is a multimeric glycoprotein and plays an essential role in mediating platelet-tumor cell interactions [ 47 ].…”

Section: Discussionmentioning

confidence: 99%

Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma

Fei

Chen

2020

BioMed Research International

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Background. Lung adenocarcinoma (LUAD) comprises around 40% of all lung cancers, and in about 70% of patients, it has spread locally or systemically when first detected leading to a worse prognosis. Methods. We filtered out differentially expressed genes (DEGs) based on the RNA sequencing data in the Gene Expression Omnibus database and verified and deeply analyzed screened DEGs using a combined bioinformatics approach. Results. Expressions of 11,143 genes in 694 nontumor lung tissues and LUAD cases from 8 independent laboratories were analyzed; 188 mRNAs were identified as differentially expressed genes (DEGs). A PPI network constructed with 188 DEGs screened out 8 hub DEGs (CDH5, PECAM1, VWF, CLDN5, COL1A1, MMP9, SPP1, and IL6) which highly interconnected with other nodes. The expression levels of 8 hub genes in LUAD and control were assessed in the Oncomine database, and the results were consistent. The survival curves of 8 hub genes showed that their expressions are significantly related to the prognosis of lung cancer and LUAD patients except for IL6. Since the expression of IL6 is nonspecific and highly sensitive, we choose the other 7 hub genes we had verified to do the next analysis. Mutual exclusivity or cooccurrence analysis of 7 hub genes identified a tendency towards cooccurrence between CDH5, PECAM1, and VWF in LUAD. The coexpression profiles of CDH5 in LUAD were identified, and we found that PECAM1 and VWF coexpressed with CDH5. Immunohistochemistry and RT-PCR analysis showed that higher levels of CDH5, PECAM1, and VWF were expressed in normal lung tissues but a low or undetectable level was found in LUAD tissues. Conclusions. Taken together, we speculate that CDH5, PECAM1, and VWF played an important role in LUAD.

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“…PECAM1 is involved in LUAD tumourigenesis by regulating the expression of vascular endothelial growth factor. In fact, it can maintain and restore vascular integrity and is commonly used as a marker for angiogenesis 28,32 .…”

Section: Discussionmentioning

confidence: 99%

Identification of Hub Genes, Modules and Metabolic Pathways Associated With Lung Adenocarcinoma: A System Biology Approach

Roudi¹,

Beikzadeh²,

Roviello³

et al. 2020

Preprint

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Lung cancer is the most common and fatal malignant tumour worldwide with a five‐year overall survival rate of only 15%. Lung adenocarcinoma (LUAD) is a heterogeneous disease. The use of microarray datasets along with bioinformatics knowledge might help to clarify the expression profile of cancer, molecular markers for the initial screening of tumour and the underlying biological mechanisms. The present study is designed to identify differential expression genes and molecular mechanisms of LUAD compared to normal lung tissues using systems biology approaches.Methods Four GSE datasets (GSE75037, GSE63459, GSE32863 and GSE10072) were selected from the Gene Expression Omnibus (GEO) database. Data processing and meta-analysis were performed using the R statistical programming language, The differentially expressed genes (DEGs) associated with each stage were obtained. The common and unique DEGs between stages of LUAD and adjacent normal lung tissues were initiated by Venny tool. Common genes, including upregulated and downregulated genes, were then analyzed to a STRING database to obtain protein-protein interaction (PPI). STRING output was analyzed by MCODE and CytoHubba applications of Cytoscape to identify modules of co-expression and hub genes, respectively.Results The shared upregulated and downregulated DEGs among LUAD stages were 22 and 140 genes, respectively, when compared to normal lung tissues. Unique genes for each stage were also identified. The hub genes were PECAM1, TEK, CDH5, VWF and ANGPT1. Most of the top cluster genes were enriched for Gα(s) signalling events, GPCR ligand binding, class B/2 (Secretin family receptors), platelet activation, signalling and aggregation in the main three co-expression clusters. Most of the shared genes (16 genes) were enriched in the metabolic pathway of hemostasis. Meaningful signaling pathways for unique genes were found at each stage.Conclusions In the present study main three co-expression clusters, metabolic pathways and biological processes were identified to understand mechanisms underlying LUAD pathogenesis, development and progression at different stages. Unique upregulated and downregulated DEGs at each stage were identified with FERMT1 and SIX1 as specific early-stage diagnostic biomarkers for stage IB and IIB. 5 hub genes were observed, including PECAM1, TEK, CDH5, vWF and ANGPT1 which might be crucial for the onset and progression of LUAD.

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The prognostic value of platelet endothelial cell adhesion molecule-1 in non-small-cell lung cancer patients

Cited by 20 publications

References 19 publications

Comprehensive assembly of novel transcripts from unmapped human RNA‐Seq data and their association with cancer

Comprehensive assembly of novel transcripts from unmapped human RNA‐Seq data and their association with cancer

Interactive Verification Analysis of Multiple Sequencing Data for Identifying Potential Biomarker of Lung Adenocarcinoma

Identification of Hub Genes, Modules and Metabolic Pathways Associated With Lung Adenocarcinoma: A System Biology Approach

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