The evolution of cancer

Sometimes seen as a disease of modernity, cancer’s origins lie deep in the very earliest stages of evolution, the result of a war between conflict and cooperation.

Like other animals, plants and fungi, humans are multicellular—we are made up of collections of many individual cells that cooperate with each other. The building blocks of the first multicellular organisms were single cells that could reproduce as independent units, but some time in our evolutionary history, events such as mutations which prevented complete separation during cell division meant single cells formed increasingly complex collectives.

Cooperation between cells is essential for multicellular organisms to exist. But sometimes, the needs of individual cells conflict with the needs of the entire organism. Cancer occurs when individual cells become “selfish” and begin to divide without stopping, eventually spreading into other tissues and causing damage.

To counteract this, the body has evolved a variety of mechanisms to suppress selfish cell types. These include ways to control cell growth, distinguish “self” from “other”, and destroy rogue cell types. But still the struggle continues, and cancer occurs. And it is not a new phenomenon—from the earliest stages of multicellularity, conflict between the interests of individual cells and the whole organism fuelled the evolution of cancer.

The origins of cancer are, therefore, tightly connected to the origins of multicellularity.

A team of researchers led by evolutionary geneticist Distinguished Professor Paul Rainey from the New Zealand Institute for Advanced Study at Massey University Auckland is undertaking a Marsden-funded project to understand more about the cooperation and conflict underlying multicellularity—the very mechanisms behind the evolution of cancer.

Primitive organisms

Distinguished Professor Paul RaineyDistinguished Professor Paul Rainey “In previous work, we witnessed the evolution of simple multicellular organisms,” Professor Rainey says. “Using these primitive organisms, we will perform a combined experimental and theoretical analysis of the earliest events underpinning the evolution of cancer and the mechanisms that suppress it.”

Professor Rainey is a Fellow of the Royal Society of New Zealand and a member of international life sciences research group EMBO. In 2011 he was appointed a member of the Max Planck Society and External Director at the Max Planck Institute for Evolutionary Biology in Plön, Germany.

His work focuses on evolutionary processes, particularly evolution by natural selection. Using both theory and experimentation, he and his team make use of microbial populations in order to observe and dissect evolution in real time.

The evolutionary origins of multicellularity has been a growing fascination, as well as the ecological significance of diversity in natural microbial populations, and the genetics and fitness consequences of traits that enhance ecological performance in populations of plant-colonising bacteria.

“In reality, there is not much that we don’t get interested in,” he says. “The more curious the better.”

Remarkable collectives

 In this project, the simple multicellular organisms the team will use consist of bacterial cells that have evolved the ability to cooperate over a number of generations. These remarkable collectives allow evolution to be witnessed in real time. Professor Rainey and his colleagues will grow a variety of different lineages of these organisms, then carry out genetic and theoretical analysis on them. Here, success is not necessarily key—lineages that become extinct because they evolve aggressively selfish cells (in essence, those that “get cancer”) will be just as important in their analysis as those that are successful.

The team will carry out two types of genetic analysis. First, they will sequence the genomes of different lineages of their bacterial collectives, to learn about the spectrum of mutations that evolve, the rate of their occurrence and the reasons why some lineages fail while others succeed. The evolutionary history of selected lineages will be tracked to the point of divergence between future success and failure. Comparisons will allow the team to identify mutations that cause enhanced fitness of collectives (through suppression of cell-level properties) or enhanced fitness of cells (through erosion of collective fitness).

Second, they will carry out detailed genetic analysis of specific mutations in particular genes of interest identified from the genome analysis. The aim will be to understand the phenotypic effects of specific mutations that underpin the success and failure of lineages. Some genes of interest will become the subject of even more detailed analyses using a combination of genetics, biochemistry and cell biology.

Finally, the team will develop theoretical tools for predicting how many, and which, lineages will evolve cancer, a problem which has not previously been easy to analyse. Using their experimental data, they will search for genetic markers in each lineage that might indicate the lineage is becoming cancerous versus markers that indicate that the lineage is likely to remain cancer-free. They will aim to find out how the information content in the cancerous versus non-cancerous lineage changes over time. If the two differ significantly, it will be possible to predict whether a lineage is accumulating mutations that eventually lead to cancer.

The research will not only provide insight into the earliest stages of the emergence of multicellularity but also into the evolution of mechanisms underpinning cancer suppression and emergence. In addition, it will provide new and general models of lineage selection, which are central to understanding the effects of selection at higher levels of biological organisation, and the evolution of complex biological life.

"Using these primitive organisms, we will perform a combined experimental and theoretical analysis of the earliest events underpinning the evolution of cancer and the mechanisms that suppress it."


Research start date

  • 2015

Research end date

  • 2018



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