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Cancer progression is driven by a small number of genetic alterations accumulating in a precancerous population. These few driver alterations reside in a cancer alongside tens of thousands of other mutations that are widely believed to have no role in cancer and are termed passengers. Many passengers, however, fall within conserved regions of the genome and may have deleterious effects on cancer cells. Here we investigated the potential of mildly deleterious passengers to accumulate and alter the course of cancer. We studied the effects of these passengers using evolutionary simulations of cancer progression, along with analysis of cancer sequencing data.
Surprisingly, in our simulations, passengers accumulate and are seldom weeded out by natural selection during cancer progression. Although individually weak, the collective burden of passengers alter the course of progression and leads to several phenomena observed in oncology inexplicable in a traditional driver-centric view. We tested our model's predictions using cancer genomic data. We found that many passenger mutations are likely to be damaging and have largely evaded natural selection, as seen in our model. Finally, we used our model to explore cancer treatments that exploit the load of passengers by either 1) increasing the rate of mutations, or 2) exacerbating their deleterious effects. While both approaches lead to cancer regression, the later leads to less frequent relapse. Our results suggest a new framework for understanding cancer progression as a balance of driver and passenger mutations.
(A) Evolutionary model of cancer progression by accumulation of driver and passenger mutations. Drivers arrive infrequently, but have a significant beneficial effect (measured by sd) while passengers arise frequently and have a small deleterious effects (sp). (B) Example simulations of cancer progression in our model. Populations of precancerous cells can divide or die stochastically, and acquire beneficial driver mutations or passenger mutations that are deleterious to cancer cells. The overall trajectory of populations was determined by a delicate balance between acquired drivers and passengers, which could lead to cancer growth or shrinkage.
McFarland CD, Korolev KS, Kryukov GV, Sunyaev S, Mirny LA
The impact of deleterious passenger mutations on cancer progression.
PNAS 2013 110(7);
Somatic copy-number alterations (SCNAs) are among the most common genomic alterations observed in cancer, and recurrent alterations have been successfully used to implicate cancer-causing genes. To better understand the mechanisms underlying SCNA formation, we investigated a physically motivated connection between three- dimensional (3D) chromatin organization and patterns of somatic copy-number alterations (SCNAs) observed in cancer.
Until now, unequivocally establishing a genome-wide connection between SCNAs and 3D chromatin organization in cancer has been limited by our ability to characterize 3D chromatin architecture, and the resolution with which we are able to observe SCNAs in cancer. Here we ask whether the ‘landscape’ of SCNAs across cancers (Beroukhim et. al, 2010), can be understood with respect to spatial contacts among distant genomic loci as determined by the recently developed chromosome conformation capture method (Hi-C, Lieberman-Aiden et al., 2009) and described theoretically using the fractal globule (FG) model (Grosberg et al., 1988).
Furthermore, we examined the occurrence of SCNAs in the context of cancer as an evolutionary process. During the somatic evolution of cancer, as in other evolutionary processes, two forces determine the accumulation of genomic changes: generation of new mutations and fixation of these mutations in a population. After an SCNA occurs, it proceeds probabilistically toward fixation or loss according to its effect on cellular fitness. The probability of observing a particular SCNA thus depends upon its rate of occurrence by mutation and the selective advantage or disadvantage conferred by the alteration (see Figure).
We found that patterns of SCNAs observed in cancer samples (Beroukhim et. al, 2010) are best described by a combination of a contact-probability mechanism and purifying selection: Loci forming a spatial contact due to 3D chromasomal organization are likely to serve as end–points of a new SCNA, which is fixed with a probability that depends on its length. Our results argue strongly for the importance of 3D chromatin organization in the formation of chromosomal alterations. Our results additionally suggest that a comprehensive understanding of mutational and selective forces acting on the cancer genome, and not limited to positive selection of cancer-associated genes, is important for explaining SCNAs observed in cancer.
Importance of 3D proximity for SCNA formation. (left) Model of how chromosomal architecture and selection can influence observed patterns of SCNAs. First, spatial proximity of the loop ends makes an SCNA more likely to occur after DNA damage (yellow lightning bolts) and repair. Next, forces of positive selection and purifying selection act on SCNAs that have arisen (deletions (blue) or amplifications (red)), leading to their ultimate fixation or loss. Observed SCNAs in cancer thus reflect both mutational and selective forces. (right, inset) illustrates looping in a simulated fractal globule. Two contact points are highlighted by spheres and represent potential end points of SCNAs.
Fudenberg G, Getz G, Meyerson M, Mirny LA
High order chromatin architecture shapes the landscape of chromosomal alterations in cancer.
Nat Biotechnol. 2011 Nov 20;29(12):1109-13.