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Integrated classification of lung tumors and cell lines by expression profiling.

ABSTRACT: The utility of cancer cell lines depends largely on their accurate classification, commonly based on histopathological diagnosis of the cancers from which they were derived. However, because cancer is often heterogeneous, the cell line, which also has the opportunity to alter in vitro, may not be representative. Yet without the overall architecture used in histopathological diagnosis of fresh samples, reclassification of cell lines has been difficult. Gene-expression profiling accurately reproduces histopathological classification and is readily applicable to cell lines. Here, we compare the gene-expression profiles of 41 cell lines with 44 tumors from lung cancer. These profiles were generated after hybridization of samples to four replicate 7,685-element cDNA microarrays. After removal of genes that were uniformly up- or down-regulated in fresh compared with cell-line samples, cluster analysis produced four major branch groups. Within these major branches, fresh tumor samples essentially clustered according to pathological type, and further subclusters were seen for both adenocarcinoma (AC) and small cell lung carcinoma (SCLC). Four of eight squamous cell carcinoma (SCC) cell lines clustered with fresh SCC, and 11 of 13 SCLC cell lines grouped with fresh SCLC. In contrast, although none of the 11 AC cell lines clustered with AC tumors, three clustered with SCC tumors and six with SCLC tumors. Although it is possible that preexisting SCC or SCLC cells are being selected from AC tumors after establishment of cell lines, we propose that, even in situ, AC will ultimately progress toward one of two poorly differentiated phenotypes with expression profiles resembling SCC or SCLC.

SUBMITTER: Virtanen C

PROVIDER: S-EPMC129449 | biostudies-literature | 2002 Sep

REPOSITORIES: biostudies-literature

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Integrated classification of lung tumors and cell lines by expression profiling.

Virtanen Carl C Ishikawa Yuichi Y Honjoh Daisuke D Kimura Mami M Shimane Miyuki M Miyoshi Tatsu T Nomura Hitoshi H Jones Michael H MH

Proceedings of the National Academy of Sciences of the United States of America 20020906 19

The utility of cancer cell lines depends largely on their accurate classification, commonly based on histopathological diagnosis of the cancers from which they were derived. However, because cancer is often heterogeneous, the cell line, which also has the opportunity to alter in vitro, may not be representative. Yet without the overall architecture used in histopathological diagnosis of fresh samples, reclassification of cell lines has been difficult. Gene-expression profiling accurately reprodu ...[more]

PMID: 12218176

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Project description:BackgroundNon-small cell lung cancer (NSCLC) is the most common type of lung cancer and has a poor prognosis. Identifying biomarkers based on molecular mechanisms is critical for early diagnosis, timely treatment, and improved prognosis of lung cancer. MALAT1 has been reported to have overexpressed and tumor-promoting functions in NSCLC. It has been proposed as a potential biomarker for the diagnosis and prognosis of cancer. Therefore, this study was conducted to profile the changes in gene expression according to the regulation of expression of MALAT1 in NSCLC cell lines and to investigate the correlation through bioinformatic analysis of differentially expressed genes (DEGs).MethodsMALAT1 expression levels were measured using RT-qPCR. The biological functions of MALAT1 in NSCLC were analyzed by cell counting, colony forming, wound-healing, and Transwell invasion assays. In addition, gene expression profiling in response to the knockdown of MALAT1 was analyzed by transcriptome sequencing, and differentially expressed genes regulated by MALAT1 were performed by GO and KEGG pathway enrichment analyses. Bioinformatic databases were used for gene expression analysis and overall survival analysis.ResultsComparative analysis versus MALAT1 expression in MRC5 cells (a normal lung cell line) and the three NSCLC cell lines showed that MALAT1 expression was significantly higher in the NSCLC cells. MALAT1 knockdown decreased cell survival, proliferation, migration, and invasion in all three NSCLC cell lines. RNA-seq analysis of DEGs in NSCLC cells showed 198 DEGs were upregulated and 266 DEGs downregulated by MALAT1 knockdown in all three NSCLC cell lines. Survival analysis on these common DEGs performed using the OncoLnc database resulted in the selection of five DEGs, phosphoglycerate mutase 1 (PGAM1), phosphoglycerate mutase 4 (PGAM4), nucleolar protein 6 (NOL6), nucleosome assembly protein 1 like 5 (NAP1L5), and sestrin1 (SESN1). The gene expression levels of these selected DEGs were proved to gene expression analysis using the TNMplot database.ConclusionMALAT1 might function as an oncogene that enhances NSCLC cell survival, proliferation, colony formation, and invasion. RNA-seq and bioinformatic analyses resulted in the selection of five DEGs, PGAM1, PGAM4, NOL6, NAP1L5, and SESN1, which were found to be closely related to patient survival and tumorigenesis. We believe that further investigation of these five DEGs will provide valuable information on the oncogenic role of MALAT1 in NSCLC.

Dataset Information

Integrated classification of lung tumors and cell lines by expression profiling.

Publications

Integrated classification of lung tumors and cell lines by expression profiling.

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