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Integrated molecular portrait of non-small cell lung cancers

Vladimir Lazar1, Chen Suo2, Cedric Orear1, Joost van den Oord3, Zsofia Balogh1, Justine Guegan1, Bastien Job1, Guillaume Meurice1, Hugues Ripoche1, Stefano Calza2, Johanna Hasmats4, Joakim Lundeberg4, Ludovic Lacroix1, Philippe Vielh1, Fabienne Dufour1, Janne Lehtiö5, Rudolf Napieralski6, Alexander Eggermont1, Manfred Schmitt6, Jacques Cadranel7, Benjamin Besse1, Philippe Girard8, Fiona Blackhall9, Pierre Validire8, Jean-Charles Soria1, Philippe Dessen1, Johan Hansson10 and Yudi Pawitan2*

Author Affiliations

1 Institut Gustave Roussy, Villejuif, France

2 Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

3 Faculty of Medicine, University of Leuven, Leuven, Belgium

4 Royal Institute of Technology, Stockholm, Sweden

5 Science of Life Laboratory, Karolinska Institutet, Stockholm, Sweden

6 Technical University of Munich, Munich, Germany

7 Tenon Hospital, Paris, France

8 Institut Mutualiste Montsouris, Paris, France

9 Manchester Cancer Research Centre, University of Manchester, Manchester, England

10 Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden

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BMC Medical Genomics 2013, 6:53  doi:10.1186/1755-8794-6-53

Published: 3 December 2013



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.


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.


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.


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.

NSCLC; AC; SCC; LCC; Systems biology