The Continuum Model of Selection in Human Tumors: General Paradigm or Niche Product?

Abstract

Berger and colleagues recently proposed a continuum model of how somatic mutations cause tumors to grow, thus supplementing the established binary models, such as oncogene activation and "two hits" at tumor suppressor loci. In the basic continuum model, decreases or increases in gene function, short of full inactivation or activation, impact linearly on cancer development. An extension, called the fail-safe model, envisaged an optimum level of gene derangement for tumor growth, but proposed that the cell gained protection from tumorigenesis because additional mutations caused excessive derangement. Most of the evidence in support of the continuum model came from Pten mutant mice rather than humans. In this article, we assess the validity and applicability of the continuum and fail-safe models. We suggest that the latter is of limited use: In part, it restates the existing "just right" of optimum intermediate gene derangement in tumorigenesis, and in part it is inherently implausible that a cell should avoid becoming cancerous only when it is some way down the road to that state. In contrast, the basic continuum model is a very useful addition to the other genetic models of tumorigenesis, especially in certain scenarios. Fittingly for a quantitative model, we propose that the continuum model is most likely to apply where multiple, cancer-promoting mutations have relatively small, additive effects, either through the well-established case of additive germline predisposition alleles or in a largely hypothetical situation where cancers may have acquired several somatic "mini-driver" mutations, each with weaker effects than classical tumor suppressors or fully activated oncogenes. Cancer Res; 72(13);

Comparison of algorithms for the detection of cancer drivers at subgene resolution

“…Interestingly, conceptual doubts about this paradigm have been formulated for many years. For instance, it was proposed that some drivers may play a role only in specific circumstances, thus being dubbed as latent 12 , mini-drivers 13 , or simply part of a continuum of cancer-promoting mutations each with a relatively small but additive effect 11 . Regardless of the specifics, all these models, at their core, expand on the binary driver/passenger paradigm to go towards a more nuanced classification in which mutations, and the genes they affect, can have different degrees of contribution to cancer growth.…”

“…Next, we show how the results of these methods can be integrated with other biological data to gain a deeper understanding of the consequences of mutations in these driver regions. Finally, we discuss the implications that the existence of such mutation clusters might have regarding novel ideas in cancer biology, such as expanding the drivers/passenger paradigm in favor of more nuanced or even continuous models 11-13 .…”

Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression

“…As with many features of biological systems, a “continuum” model may afford a better representation of reality. 78, 214, 215 Etiologic fields may seamlessly span multiple phases of neoplastic evolution, while their anatomic boundaries are likely to be gradients of tissue microenvironmental change, determined by variation in the magnitude of, and sensitivity to a particular exposure.…”

Finding driver mutations in cancer: Elucidating the role of background mutational processes

“…The majority of these mutations are largely neutral (passenger mutations) in comparison to a few driver mutations that give cells the selective advantage leading to their proliferation [2]. Such a binary driver-passenger model can be adjusted by taking into account additive pleiotropic effect of mutations [3, 4]. Mutations might have different functional consequences in various cancer types and patients, they can lead to activation or deactivation of proteins and dysregulation of a variety of cellular processes.…”