Abstract :
[en] Diversity fuels the evolution with a reservoir of populations that compete for their adaptiveness. Such like species, sub–populations of tumour cells support and continuously feed the tumourigenesis. Sustained by their clonal diversity, tumours are therefore able to adapt and resist to many aggres- sions. What supports the tumour development, however, acts as an aggression against the host environment. Besides, such diversity ends up to several issues at diagnosis since numerous informa- tions are mixed together in often a unique sample, leading to a confused analysis. Consequently, the assessment of tumour cellular compositions has to be improved to identify treatment–resistant sub–populations, and thus improve patient care and treatment.
This work describes the signal confusion that often occurs during microarray based tumour anal- ysis. We discuss the impact of both the sample composition and the sampling method currently used for such analyses. We finally report a case of in vitro spontaneous tumourigenesis, and debate about its potential interest as a model to study tumour evolution, which may help to improve the sampling methods.
We conclude on the urge for sampling methods improvement to better identify treatment– resistant sub–populations at the first tumour diagnosis. We also underline the necessity to understand the basics of the tumourigenesis, especially the diversity and the subsequent heterogeneity resulting from the tumour evolution. We believe that a realistic in vitro model can help to understand the intra–tumour heterogeneity, and thus help to define new sampling methodologies. Improving the identification of the exact tumour composition is a great challenge for personalized medicine, patient health and care, and global health economy.
