Whole-exome sequencing and microRNA profiling identifies signatures for relapse prediction of stage I lung adenocarcinomas (ACGH
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ABSTRACT:
PROVIDER: EGAD00010001902 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:This dataset contains CEL files and rma normalized expression value for microarray of stage I lung adenocarcinomas from Asian patients. In total, there are 69 patients and 138 samples, including 69 tumor samples and 69 adjacent normal samples.
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Project description:About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. MicroRNAs (miRNAs) are a class of small non-coding RNAs of 19-25 nt and play important roles in gene regulation in human cancers. The purpose of this study is to identify miRNA expression profiles that would better predict prognosis of stage I NSCLC. MiRNAs extracted from 527 stage I NSCLC patients were profiled on the human miRNA expression profiling v2 panel (Illumina). The expression profiles were analyzed for their association with cancer subtypes, lung cancer brain metastasis and recurrence/relapse free survival (RFS). MiRNA expression patterns between lung adenocarcinoma and squamous cell carcinoma differed significantly with 171 miRNAs, including Let-7 family members and miR-205. Ten miRNAs associated with brain metastasis were identified including miR-145*, which inhibit cell invasion and metastasis. Two miRNA signatures that are highly predictive of RFS were identified. The first contained 34 miRNAs derived from 357 stage I NSCLC patients independent of cancer subtype, whereas the second containing 27 miRNAs was adenocarcinoma specific. Both signatures were validated using formalin-fixed paraffin embedded and/or fresh frozen tissues in independent data set with 170 stage I patients. Our findings have important prognostic or therapeutic implications for the management of stage I lung cancer patients. The identified miRNAs hold great potential as targets for histology-specific treatment or prevention and treatment of recurrent disease.
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Project description:Despite surgical treatment of stage I non-small cell lung cancer (NSCLC), one third of patients will eventually have a recurrence. Robust prognostic markers are required to better manage therapy options. MicroRNAs play important roles in human cancers. The purpose of this study is to identify miRNA expression profiles that would better predict prognosis. Small RNAs extracted from formalin-fixed and paraffin-embedded (FFPE) tumor tissues of 357 stage I NSCLC patients were profiled on the human MicroRNA expression profiling V2 panel (Illumina). The expression differences between cancer subtypes were compared by t tests. The association of miRNA expression profile with recurrence free survival (RFS) was assessed using partial Cox regression models. Two miRNA signatures that are highly predictive of RFS were identified. The first contained 32 miRNAs derived from 357 stage I NSCLC patients independent of cancer subtype; while the second containing 27 miRNAs was adenocarcinoma specific. Both of them were validated using FFPE and/or fresh frozen tissues in independent data set with 170 stage I patients. This has important prognostic or therapeutic implications for the management of patients. The identified miRNAs hold great potential as targets for histology-specific treatment or prevention and treatment of recurrent disease.
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