Quantitative genetic analysis of tumor progression

Abstract

Metastasis and resistance to chemotherapy are common features of progressed cancers. With respect to the latter phenotype, it is thought that during tumor growth drug-resistant cells arise spontaneously at rates characteristic of the genetic alterations involved. On application of chemotherapy, such variant tumor cells are more likely to survive, and they may eventually dominate, resulting in a non-responsive malignancy. Aspects of this model have been confirmed in a number of experimental systems and in patients. In contrast to our understanding of drug resistance, steps involved in the progression to metastatic spread of tumor cells are much less well-understood. In this review we describe methodologies of quantitative genetic analysis with reference to development of drug resistance. We then describe attempts by ourselves and others to use a similar approach to investigate metastatic properties. Based on these studies, we have proposed the quantitative 'dynamic heterogeneity' model of tumor metastasis, which is presented here. Using an 'experimental' metastasis assay and Luria-Delbruck fluctuation analysis, we determined that in murine KHT fibrosarcoma and B16 melanoma lines, 'metastatic' variants with a distinct phenotype are generated at high rates. These variants are relatively unstable resulting in a dynamic equilibrium between generation and loss of metastatic variants. The metastatic ability of such a tumor population is thus dependent on the frequency of a subpopulation of metastatic variants which are turning over rapidly. This dynamic heterogeneity model is able to quantitatively provide a unifying explanation for a wide range of observations concerning tumor heterogeneity and clonal instability. Genetic mechanisms involving rapid rates have been characterized in drug-resistant variants. We speculate that similar processes may be involved in different aspects of tumor progression such as those resulting in metastasis.