Dataset Information

Investigation of radiation-induced transcriptome profile of radioresistant non-small cell lung cancer A549 cells using RNA-seq.

ABSTRACT: Radioresistance is a main impediment to effective radiotherapy for non-small cell lung cancer (NSCLC). Despite several experimental and clinical studies of resistance to radiation, the precise mechanism of radioresistance in NSCLC cells and tissues still remains unclear. This result could be explained by limitation of previous researches such as a partial understanding of the cellular radioresistance mechanism at a single molecule level. In this study, we aimed to investigate extensive radiation responses in radioresistant NSCLC cells and to identify radioresistance-associating factors. For the first time, using RNA-seq, a massive sequencing-based approach, we examined whole-transcriptome alteration in radioresistant NSCLC A549 cells under irradiation, and verified significant radiation-altered genes and their chromosome distribution patterns. Also, bioinformatic approaches (GO analysis and IPA) were performed to characterize the radiation responses in radioresistant A549 cells. We found that epithelial-mesenchymal transition (EMT), migration and inflammatory processes could be meaningfully related to regulation of radiation responses in radioresistant A549 cells. Based on the results of bioinformatic analysis for the radiation-induced transcriptome alteration, we selected seven significant radiation-altered genes (SESN2, FN1, TRAF4, CDKN1A, COX-2, DDB2 and FDXR) and then compared radiation effects in two types of NSCLC cells with different radiosensitivity (radioresistant A549 cells and radiosensitive NCI-H460 cells). Interestingly, under irradiation, COX-2 showed the most significant difference in mRNA and protein expression between A549 and NCI-H460 cells. IR-induced increase of COX-2 expression was appeared only in radioresistant A549 cells. Collectively, we suggest that COX-2 (also known as prostaglandin-endoperoxide synthase 2 (PTGS2)) could have possibility as a putative biomarker for radioresistance in NSCLC cells.

SUBMITTER: Yang HJ

PROVIDER: S-EPMC3606344 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

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Investigation of radiation-induced transcriptome profile of radioresistant non-small cell lung cancer A549 cells using RNA-seq.

Yang Hee Jung HJ Kim Namshin N Seong Ki Moon KM Youn HyeSook H Youn BuHyun B

PloS one 20130322 3

Radioresistance is a main impediment to effective radiotherapy for non-small cell lung cancer (NSCLC). Despite several experimental and clinical studies of resistance to radiation, the precise mechanism of radioresistance in NSCLC cells and tissues still remains unclear. This result could be explained by limitation of previous researches such as a partial understanding of the cellular radioresistance mechanism at a single molecule level. In this study, we aimed to investigate extensive radiation ...[more]

PMID: 23533613

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Project description:BackgroundWhile RNA-sequencing (RNA-seq) is becoming a powerful technology in transcriptome profiling, one significant shortcoming of the first-generation RNA-seq protocol is that it does not retain the strand specificity of origin for each transcript. Without strand information it is difficult and sometimes impossible to accurately quantify gene expression levels for genes with overlapping genomic loci that are transcribed from opposite strands. It has recently become possible to retain the strand information by modifying the RNA-seq protocol, known as strand-specific or stranded RNA-seq. Here, we evaluated the advantages of stranded RNA-seq in transcriptome profiling of whole blood RNA samples compared with non-stranded RNA-seq, and investigated the influence of gene overlaps on gene expression profiling results based on practical RNA-seq datasets and also from a theoretical perspective.ResultsOur results demonstrated a substantial impact of stranded RNA-seq on transcriptome profiling and gene expression measurements. As many as 1751 genes in Gencode Release 19 were identified to be differentially expressed when comparing stranded and non-stranded RNA-seq whole blood samples. Antisense and pseudogenes were significantly enriched in differential expression analyses. Because stranded RNA-seq retains strand information of a read, we can resolve read ambiguity in overlapping genes transcribed from opposite strands, which provides a more accurate quantification of gene expression levels compared with traditional non-stranded RNA-seq. In the human genome, it is not uncommon to find genomic loci where both strands encode distinct genes. Among the over 57,800 annotated genes in Gencode release 19, there are an estimated 19 % (about 11,000) of overlapping genes transcribed from the opposite strands. Based on our whole blood mRNA-seq datasets, the fraction of overlapping nucleotide bases on the same and opposite strands were estimated at 2.94 % and 3.1 %, respectively. The corresponding theoretical estimations are 3 % and 3.6 %, well in agreement with our own findings.ConclusionsStranded RNA-seq provides a more accurate estimate of transcript expression compared with non-stranded RNA-seq, and is therefore the recommended RNA-seq approach for future mRNA-seq studies.

Dataset Information

Investigation of radiation-induced transcriptome profile of radioresistant non-small cell lung cancer A549 cells using RNA-seq.

Publications

Investigation of radiation-induced transcriptome profile of radioresistant non-small cell lung cancer A549 cells using RNA-seq.

Similar Datasets

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