The molecular landscape of colorectal cancer cell lines unveils clinically actionable kinase targets2015-04-30 00:01:42
Nature Communications; 30 APR 2015; DOI:10.1038/ncomms8002
Enzo Medico, Mariangela Russo, Gabriele Picco, Carlotta Cancelliere, Emanuele Valtorta, Giorgio Corti, Michela Buscarino, Claudio Isella, Simona Lamba, Barbara Martinoglio, Silvio Veronese, Salvatore Siena, Andrea Sartore-Bianchi, Marco Beccuti, Marcella Mottolese, Michael Linnebacher, Francesca Cordero, Federica Di Nicolantonio, Alberto Bardelli
The development of molecularly targeted anticancer agents relies on large panels of tumour-specific preclinical models closely recapitulating the molecular heterogeneity observed in patients. Here we describe the mutational and gene expression analyses of 151 colorectal cancer (CRC) cell lines. We find that the whole spectrum of CRC molecular and transcriptional subtypes, previously defined in patients, is represented in this cell line compendium. Transcriptional outlier analysis identifies RAS/BRAF wild-type cells, resistant to EGFR blockade, functionally and pharmacologically addicted to kinase genes including ALK, FGFR2, NTRK1/2 and RET. The same genes are present as expression outliers in CRC patient samples. Genomic rearrangements (translocations) involving the ALK and NTRK1 genes are associated with the overexpression of the corresponding proteins in CRC specimens. The approach described here can be used to pinpoint CRCs with exquisite dependencies to individual kinases for which clinically approved drugs are already available.
Knowledge of tumour biology and the development of new anticancer agents depend on robust preclinical model systems that reflect the genomic heterogeneity of human cancers and for which detailed genetic and pharmacologic annotations are available. Cell lines represent a mainstay to functionalize molecular data as they allow experimental manipulation, global and detailed mechanistic studies and high throughput applications. Virtually all commonly used cancer cells were continuously grown in vitro for years, and decades have often passed since they were originally derived from patients. The in vitro culture conditions used to propagate cancer cells are far from the histological landscape in which they originated. These considerations are often cited to question the relevance of cell lines as cancer models. We further observe that, for a given cancer type, only few cell lines (o10) are employed in most preclinical studies. The evidence that cancer patients have heterogeneous genetic features implies that a large number of lineage-specific cell lines is needed to capture the diversity observed in the clinic. Furthermore, cells commonly used to model a tumour type may not represent the patients that they intend to recapitulate. For instance, colorectal cancer (CRC) cell lines ordinarily used in preclinical studies often display microsatellite instability (MSI). MSI colorectal tumours are found in 10-15% patients, but they show an indolent clinical behaviour and are less prevalent in more advanced stages of the disease, accounting for o5% in the metastatic setting. Consequently, MSI cell lines do not properly recapitulate the clinical setting in which targeted agents are most commonly administered to CRC patients.
In addition to the ‘genetic’ driven subtypes, tumour lineages can be subdivided based on their transcriptional profiles. Transcriptional profiling has been recently used to identify distinct CRC subtypes. The subtypes are associated with biological and clinical features such as cell of origin, MSI, prognosis and response to treatments. Whether the transcriptional subtypes are maintained in CRC cell models and how this knowledge can be used to discover novel pharmacogenetic relationships has not been explored. To address these challenges, we assembled and annotated a comprehensive collection of 151 human CRC cells.
We find that the molecular heterogeneity (oncogenic mutations and transcriptional subtypes), previously defined in CRC patients, is maintained in CRC cells. Individual lines can be stratified as responders or non-responders to epidermal growth factor receptor (EGFR) blockade based on clinically validated biomarkers. Transcriptional outlier analysis identifies CRC cells, resistant to EGFR blockade, pharmacologically addicted to kinase genes including ALK, FGFR2, NTRK1/2 and RET.
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Biological sciences | Cancer | Molecular biology