Integrated molecular portrait of non-small cell lung cancers

BMC Medical Genomics

Yudi Pawitan⁹  Johan Hansson²  Philippe Dessen^1,10  Jean-Charles Soria^1,10  Pierre Validire⁷  Fiona Blackhall⁶  Philippe Girard⁷  Benjamin Besse^1,10  Jacques Cadranel⁴  Manfred Schmitt⁸  Alexander Eggermont^1,10  Rudolf Napieralski⁸  Janne Lehtiö⁵  Fabienne Dufour^1,10  Philippe Vielh^1,10  Ludovic Lacroix^1,10  Joakim Lundeberg¹  Johanna Hasmats¹  Stefano Calza⁹  Hugues Ripoche^1,10  Guillaume Meurice^1,10  Bastien Job^1,10  Justine Guegan^1,10  Zsofia Balogh^1,10  Joost van den Oord³  Cedric Orear^1,10  Chen Suo⁹  Vladimir Lazar^1,10 

[1] Royal Institute of Technology, Stockholm, Sweden;Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden;Faculty of Medicine, University of Leuven, Leuven, Belgium;Tenon Hospital, Paris, France;Science of Life Laboratory, Karolinska Institutet, Stockholm, Sweden;Manchester Cancer Research Centre, University of Manchester, Manchester, England;Institut Mutualiste Montsouris, Paris, France;Technical University of Munich, Munich, Germany;Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden;Institut Gustave Roussy, Villejuif, France

关键词: Systems biology;    LCC;    SCC;    AC;    NSCLC;   

Others  :  1091254
DOI  :  10.1186/1755-8794-6-53

 received in 2013-03-20, accepted in 2013-11-08,  发布年份 2013

【 摘 要 】

Background

Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC.

Methods

Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC.

Results

At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944.

Conclusions

Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes.

【 授权许可】

   
2013 Lazar et al.; licensee BioMed Central Ltd.

【 图 表 】

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