DNA - also known as the 'book of life' - is written in a language that is still being deciphered, which is why it remains a challenge to translate what genes say into physical traits that make up an organism. For example, why do mutations only cause cancer sometimes and not others?

Researchers at the CNIO, the CRG and the IRB Barcelona have just discovered one reason; that the power of a mutation depends on its interaction with another, and that the relationship between this pair of mutations can often be intertwined with a third. This is the first time researchers have characterised the landscape of what are known as third-order interactions in cancer.

The finding is equivalent to revealing new grammatical rules of the genetic language, one that, following the metaphor of the book of life, says that the same word (mutation) has different meanings depending on the other words in the sentence, and on the context in which it appears.

The study, led by Solip Park, Head of the Computational Cancer Genomics Group at the CNIO, is co-authored by ICREA Research Professor Ben Lehner at the Centre for Genomic Regulation (CRG) and Fran Supek, ICREA Reseaerch Professor at the IRB Barcelona (Institute for Research in Biomedicine). It has just been published in Nature Communications.

According to Dr. Park, "this is the first systematic, in-depth, multi-data analysis of the interactions between genetic alterations involved in cancer. There are several works that study a single gene or a single type of cancer, but this is the first large-scale systematic one."

The research paves the way to deciphering the functioning of the half thousand or so mutations known to be involved in cancer. If successful, the clinical implications would be significant. Genetic diagnosis would be more precise and new therapeutic targets could be sought, since the best way to counteract a given mutation could be by acting on another. So far, research has tended to focus on alterations in a single gene that can be targeted with drugs, but this approach means that associations between different genes involved in cancer must be considered," explains Dr. Park.

Researchers in cancer genetics have known for years that in the vast majority of cases, cancer results from different genetic alterations acting at the same time. But only now, thanks to big data techniques and great computational power, has it been possible to tackle the challenge of deciphering these interaction networks.

The computational biologists and authors of the paper turned to The Cancer Genome Atlas (TCGA). They analyzed the interactions between the genetic alterations in 10,000 human tumors of about 30 different types, affecting more than 200 genes.

By analyzing the interactions between genetic alterations the authors dismantled the so-called 'two-hit' model, one of the most widely accepted hypotheses on how genes that promote tumor development are activated.

An oncogene promotes cancer when it is activated. Meanwhile, tumour suppressor genes act the other way around, their inactivation drives cancer. "The classic theory," explains Dr. Park, "is that a single mutation in an oncogene can be enough to promote cancer, whereas for a tumor suppressor gene to act, inactivation of both copies of the gene, the father's and the mother's, is required. This is the 'two-hit' model. But many exceptions to this classic model are coming to light, and this work finds an explanation."

Their analysis of the networks of interactions between genetic alterations in 10,000 tumors reveals that many genes involved in cancer, whether oncogenes or tumor suppressor genes, may require one or two hits depending on what other mutations are at work.

"The correct genetic model for a gene thus depends on the other mutations in the genome," write the authors. "A second hit in the same gene, or an alteration in a different gene in the same pathway, represent alternative evolutionary pathways to cancer."

In other words, we must not only take into account the effects of individual mutations or pairwise interactions, “but also what happens when three or more alterations are combined," adds Dr. Park.

The researchers hypothesise that this new grammatical rule of genetic language is universal, i.e., not just involved in cancer. "These principles of genetic architecture are likely to apply to other diseases as well. We believe that systematically analyzing higher-order genetic interactions may also help to understand the molecular mechanisms that cause other human diseases," conclude the authors.

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