The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

Lo, Fang Yuh; Chang, Jui-Chi; Chang, I‐Shou; Chen, Yann-Jang; Hsu, Han‐Shui; Huang, Shiu‐Feng; Tsai, Fang‐Yu; Jiang, Shih Sheng; Kanteti, Rajani; Nandi, Sumon; Salgia, Ravi; Wang, Yi‐Ching

doi:10.1186/1471-2407-12-235

Cited by 43 publications

(40 citation statements)

References 28 publications

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“…1B). We further validated the 11 genes in three additional independent datasets 16, 20, 21 (146 ADC, 91 normal; Supplementary Table S2). All genes were significantly over-expressed in the validation datasets at FDR ≤ 5% with at least one meta-analysis method, and all except three ( CACNB3, SLC2A5 and SULT1C2 ) were significantly over-expressed as assessed by both methods (Supplementary Fig.…”

Section: Resultsmentioning

confidence: 99%

“…Meta-analysis can control for such confounding factors by increasing the statistical power to detect consistent changes across multiple datasets. Several groups have made available large NSCLC gene expression datasets that consist of tumor-to-normal comparisons 9, 13-21 . These datasets represent a large and as yet not fully tapped resource for discovering novel genes relevant to the pathogenesis of lung cancer.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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Lung cancer remains the most common cause of cancer-related death worldwide and it continues to lack effective treatment. The increasingly large and diverse public databases of lung cancer gene expression constitute a rich source of candidate oncogenic drivers and therapeutic targets. To define novel targets for lung adenocarcinoma (ADC), we conducted a large scale meta-analysis of genes specifically overexpressed in ADC. We identified an eleven-gene signature that was overexpressed consistently in ADC specimens relative to normal lung tissue. Six genes in this signature were specifically overexpressed in ADC relative to other subtypes of non-small cell lung cancer (NSCLC). Among these genes was the little studied protein tyrosine kinase PTK7. Immunohistochemical analysis confirmed that PTK7 is highly expressed in primary ADC patient samples. RNAi-mediated attenuation of PTK7 decreased cell viability and increased apoptosis in a subset of ADC cell lines. Further, loss of PTK7 activated the MKK7-JNK stress response pathway and impaired tumor growth in xenotransplantation assays. Our work defines PTK7 as a highly and specifically expressed gene in ADC and a potential therapeutic target in this subset of NSCLC.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2014

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“…GSE21933. The gene expression data of tumors and matched normal tissues from 21 NSCLC patients were contributed by a previously public study (8). The NSCLC patients included 10 early-stage cases (6 in stage IB, 3 in stage IIB and 1 in stage IA) and 11 late-stage patients (5 in stage IIIA, 5 in stage IV and 1 in stage IIIB).…”

Section: Methodsmentioning

confidence: 99%

“…The gene expression array of GSE21933 was developed from Asian lung cancer patients. With the microarray data, Lo et al have established that ARHGAP19, FRAT2g, PAFAH1B1 and ZNF322A involved in Rho activity, Wnt signaling, motility control and MAPK signaling are the candidate genes for lung cancer (8). Currently, the integrity analysis of altered gene expression patterns for lung cancer during different stages is rare.…”

Section: Introductionmentioning

confidence: 99%

Analysis of gene expression profiles of non-small cell lung cancer at different stages reveals significantly altered biological functions and candidate genes

et al. 2017

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We attempt to dissect the pathology of non-small cell lung cancer (NSCLC) patients at different stages and discover the novel candidate genes. Microarray data (GSE21933) were retrieved from the Gene Expression Omnibus database. The differential expression profiles of lung tumor tissues during different stages were analyzed. The significantly altered functions and pathways were assessed and the key nodes in a protein-protein interaction (PPI) network were screened out. Then, the coexpression gene pairs and tumor-related genes were assessed. RT-PCR analysis was performed to validate the candidate gene, natural killer-tumor recognition sequence (NKTR). The number of differentially expressed genes (DEGs) for stage IB, IIB, IIIA and IV tumors were 499, 602, 592 and 457, respectively. Most of the DEGs were NSCLC-related genes identified through literature research. A few genes were commonly downregulated in all the 4 stages of tumors, such as CNTN6 and LBX2. The DEGs in early‑stage tumors were closely related with the negative regulation of signal transduction, the apoptosis pathway and the p53 signaling pathway. DEGs in late-stage tumors were significantly enriched in transcription, response to organic substances and synapse regulation-related biological processes. A total of 16 genes (including NKTR) made up the significant coexpression network. NKTR was a key node in the PPI network and was significantly upregulated in lung cancer cells. The mechanism of NSCLC progression in different tumor stages may be different. NKTR may be the target candidate for NSCLC prevention and treatment.

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“…Gene microarrays for human SqCC (GSE21933, 42 ), murine tracheal polidocanol injury (GSE17268, 17 ) and murine SO2 injury (GSE69056, 16 ) were downloaded from the National Centre for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO), (http://www.ncbi.nlm.nih.gov/geo/). Details of experimental procedures including specifics of murine injury are included in each original research study 16,17,42 . All GEO datasets included RefSeq Gene ID, gene name, Gene symbol, microarray ID, adjusted P-value, and experimental group logFC relative to corresponding control groups.…”

Section: Methodsmentioning

confidence: 99%

A comparative microarray analysis identifies a conserved gene expression signature between airway injury and lung cancer

Giangreco

2016

Preprint

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Lung squamous cell carcinoma (SqCC) accounts for 30% of lung cancers, with over 400,000 deaths per year worldwide. Although evidence suggests that chronic lung injury drives carcinogenesis, a comprehensive understanding of this process remains elusive. Here, I used a comparative microarray analysis to identify gene expression differences shared between airway injury and squamous lung cancer. Of the 667 genes that exhibited differential expression following murine polidocanol and SO2 injury, 40.6% were additionally dysregulated in human SqCC. Among these, 150 genes were consistently upregulated and 54 downregulated relative to all controls. Examples included genes associated with increased cell cycling, aberrant cytokinesis and DNA repair, and enhanced tumour cell invasion and metastases. For 88.2% of identified genes, altered expression was associated with increased SqCC progression and patient mortality. These results establish a novel gene expression signature linking airway injury and lung cancer pathogenesis.

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The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

Cited by 43 publications

References 28 publications

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

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

Analysis of gene expression profiles of non-small cell lung cancer at different stages reveals significantly altered biological functions and candidate genes

A comparative microarray analysis identifies a conserved gene expression signature between airway injury and lung cancer

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