With a decrease in its incidence and its mortality colorectal cancer (CRC) still remains the fourth most frequently diagnosed cancer and the second leading cause of cancer death worldwide with 40-50% of newly diagnosed patients having a metastatic disease. The introduction into clinical practice of cytotoxic agents such as oxaliplatin and irinotecan has improved the response rates, the progression–free survival (PFS) and the overall survival (OS) compared with single agent 5-FU. Moreover, the combination of chemotherapy with tailored compounds such as anti-epidermal growth factor receptor (EGFR) and anti-vascular endothelial growth factor (VEGF) monoclonal antibodies has allowed increasing the median OS to nearly 24 months.
Nevertheless, the prognosis for metastatic CRC patients still remains poor.
Colorectal cancer is a heterogeneous disease defined by different activating mutations in receptor tyrosine kinases (RTKs), or activating or loss-of-function mutations in downstream components of RTK-activated intracellular pathways, some of which can occur in the same tumour.
Individual mutations within a single cancer gene have distinct roles on the response and resistance to targeted therapies and can only partially explains the puzzling heterogeneity of clinical outcomes observed in patients.
As recently reported by Popovici et al., even tumours carrying the same cancer gene mutation are highly heterogeneous at their gene expression level. This translates into variable prognosis and clinical outcomes and potentially indicates different personalised therapies.
The understanding of colon cancer biology and colon cancer subtypes is essential to improve the therapeutic index of the already available compounds and help the development of new tailored agents for personalised medicine.
In their report, Schlicker et al. characterised the functional differences of primary CRC at pathway level by identifying different subtypes. They further showed these subtypes to be well represented in a panel of CRC cells lines thus implying that cell lines largely reflect the gene expression heterogeneity present in tumours. The integration with pharmacology data let the authors define the sensitivity to target agents for specific CRC subpopulation.
The subtype analysis was performed by considering the genome wide mRNA expression profile data obtained from 62 primary CRC. The application of a non negative matrix factorisation let them first identifying two colorectal cancer subgroups showing strong association with an epithelial-mesenchimal like phenotype and with an epithelial like phenotype. A subsequent second split of these subtypes yielded a total of five subtypes providing a more grained stratification. These data were robustly reproduced on an independent set of 1600 CRC tumours samples from 15 published data set for which gene expression data were available.
By applying the subtyping to a total of 74 different CRC cell lines (AZCL data set, Wagner data set, GSK Cancer Cell panel from caBIG at the National Cancer Institut data set and Cancer Genome Project at the Wellcome Trust Sanger Institute) the authors were able to show that cell lines can reflect the gene expression profile of primary tumours and can be then used as model for drug discovery. Indeed, the integration with pharmacology data let the author reveal the sensitivity profile to target agents for each subtype.
Colorectal cancer patients still have poor prognosis. Although several targeted agents are in use for this disease, most of them still have a low therapeutic index. Therefore, it is crucial to better identify new prognostic and predictive tools, beyond the already assessed clinic-pathologic features, and define the different subtypes that characterise CRC.
Schlicker et al identify for the first time the different subtypes that characterise colorectal tumours. The stratification applied to primary tumours is stable across different data set and can be even applied to CRC cell lines. The approach used by Schlicker et al. can help generating clinically tractable hypotheses for response prediction thus representing the basis for new drug development.
Popovici V, Budinska E, Tejpar S, et al., Identification of a Poor-Prognosis BRAF-Mutant-Like Population of Patients With Colon Cancer, J Clin Oncol 30: 1288-1295, 2012
- Do you think that CRC subtyping is worthwhile? Is it a pure biological scholastic definition or will it be really used in clinical practice to improve personalised medicine?
- Authors were able to identified different CRC subtypes based on the gene expression profile data. How can it be easily translated to the clinic? To identify the different subgroups will we need in the future to use the whole signatures or few biomarkers will be enough?
The content of this article reflects the personal opinion of the author/s and is not necessarily the official position of the European Society for Medical Oncology.