Journal of Cancer Research and Immuno-Oncology
Open Access

Tracking the Evolution of Cancer using the Genome

Adam Nennecke^{* *}Correspondence: Adam Nennecke, Department of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, Email:

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Description

How do tumours spread? This fundamental question is still difficult to address for the apparent reason that it is hard to continuously monitor tumour growth in both humans and model systems. Because of this, we must make historical assumptions about the content of tumours that have been removed in order to understand how tumours arise. In other words, data gathered at a single time point the point at which the tumour shows up on the specimen table have mainly contributed to our knowledge of the temporal process of cancer evolution. Fortunately, the tumour genome (or, more precisely, the genomes of all the cells in the tumour) offers a covert but rich record of a tumour's progress, so this state of affairs is not as bad as it may sound errors in DNA replication cause new mutations to be added to the daughter cells' genomes each time a cell divides. Additionally, epigenetics markings, such as DNA methylation, are only partially replicated. A significant percentage of malignancies also have larger-scale chromosomal or part-chromosomal deletions or amplifications, as well as other structural rearrangements. The lineage of the cells in the tumour is recorded by these naturally occurring epigenetic changes, and as tumours are clonally produced, all of the cells in the tumour will inherit the mutations in the first cancer cell. In contrast, later-arising The sequence of clone formation may be deduced by comparing the sets of mutations found in various tumour cell types as sub clones are distinguishable by sharing a particular unique collection of variations.

Phylo-genetic approaches used to study cancer are based on the logic of this type of analysis. Furthermore, counting the number of mutations of a particular type that are exclusive to a particular lineage provides an estimate of the relative time that the lineage originated if a particular type of mutation accrues at a constant rate . The term "constant mutation rate" as a "molecular clock," and if the speed at which the clock "ticks" is known, then the exact timing of occurrences (where time is defined in the number of cell divisions that have passed) may be determined and is also determinable. These techniques have been used to treat a wide range of malignancies and have revealed fresh information on the sequence and timing of mutation accu-mulation. Evolutionary selection also plays a significant influence in altering the cancer genome, in addition to mutation.

When one set of cells inside a tumour is evolutionarily "favoured" over another, selection occurs and the "favoured" cells produce more offspring than the "unfavoured" cells. The favouring is the outcome of the cell evolving an adaptive phenotypic characteristic that offers it a competitive edge in the present microenvironment (context) of the tumour. When two cells are present in a microenvironment that is deficient in nutrients, for instance, a cell with a low metabolic need may develop more quickly than a cell with a high metabolic demand. Negatively chosen clones (not preferred) become substantially less numerous as a result of selection, but any mutation in the selected (favoured) population becomes more prevalent in the tumour population as a whole. As a result, selection is crucial in determining how frequently mutations occur inside a tumour.

Identifying neutrality and selection in the cancer genome

Whatever the biological process behind clonal selection, it eventually leads to the relative expansion of the chosen clone inside the tumour. In contrast to the "null" condition, where the genome develops without selection, the clonal expansion is visible in the cancer's genome through a "over-representation" of the mutations in the clone. Therefore, in theory, detecting selection only requires identifying the distinctive "clonal outgrowths." A variety of bioinformatics tools have been developed to identify the "clusters" of mutations that occur frequently in tumour next-generation sequencing data that are indicative of these outgrowths. As the selected clone multiplies, all of the numerous passenger mutations are carried along to higher frequency, making the selected clone visible against the multitude of unselected mutations in the tumour. It is important to note that the evolutionary dynamics of the selected clone are largely revealed by the passenger mutations in that clone, not the drivers themselves. Therefore, selection affects both driver and passenger mutations in the clone, but because passenger mutations are more common, they tend to be more informative. This is simply due to the fact that, because evolution is a blind force, many "unsuccessful" mutations have happened in a genome as vast as the human one for every "successful" driving mutation. This also implies that, regardless of the biological mechanism providing the selective benefit, clonal selection is always observable in the frequency distribution of mutations in cancer. Imagine, for instance, that a clone gets a selective advantage due to a rapid shift in the microenvironment (such a novel non-cell-autonomous interaction inside the tumour); even though the clone's advantage is cell-extrinsically driven, its passenger mutations would still be overrepresented.