Phenotypic variation in cancer cells is often not due to mutations

MOther models of how tumors develop have postulated that the process is based mostly on the genetics of cancer cells, and that many cancer therapies specifically target mutations associated with the disease. But comparing whole-genome sequencing data with RNA-seq data from colorectal tumor samples revealed that the vast majority of gene expression differences between cancer cells cannot be explained by genetics, the researchers report in temper nature Today (26 October).

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“So far, much of the work that has been done exploring the evolution of cancer in the development of cancer has focused a lot on genes alone,” he says. Nicholas McGranahan, a computational cancer researcher at CRUK UCL of the University of London Cancer Institute and was not involved in the research. But according to the new study, “there are a lot of these alterations that they can’t clearly identify [genetic] prop for. . . . It’s a beautiful study because it highlights some of the limitations of what we were doing before.”

Computational biologist Andrea Sutoreva It is these limitations, he says, that led him and his colleagues to consider the transcriptome in the development of cancer. “Essentially, looking at genetic evidence wasn’t explaining everything we were seeing,” says Sutoreva, group leader at the Institute of Cancer Research London and head of the Computational Biology Research Center at Human Technopole in Milan, Italy. For example, he explains, “If you just look at . . . the mutations in the genes involved in cancer, it’s not very easy to distinguish benign cancer from malignant cancer: in benign cancer, there are as many mutations that cause cancer as there are in malignant cancer” .

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To get a better understanding of how cancer cells differ at the level of gene expression, the team performed whole-transcript RNA-seq as well as whole-genome sequencing on samples from 27 surgically removed human rectal tumors, eight of which gave enough data to perform comparisons. between the two types of sequence. In those eight tumors, of the 8,368 differentially expressed genes included in the analysis, differences in transcript levels could be traced back to the core genes in a mean of 166. “A large proportion of [cancer research] Society has always thought that everything is under genetic control,” says Sutoreva, but these findings suggest that “the answer is not entirely genetic. “

Sotoreva says that while some of the difference may be due to transcription noise, where gene expression constantly fluctuates in cells, he suspects that cells’ microenvironments also play a large role, with factors such as Hypoxia or having macrophages Impact on transcription software. He notes that cancer cells “can adapt to a lot of different environments.”

This potentially has implications for the emergence of treatment resistance, Sutoreva adds. Often when cancers fail to respond to chemotherapy or targeted therapies, there are transcription mechanisms at play that are influenced by the tumor microenvironment, he explains, such as latent autophagy, aging, or dormancy. “This means that a lot of evolutionary models need to adapt to this, because a lot of the phenotypic diversity that can lead to drug resistance is not. [based in] Genetics. “

McGranahan agrees that the apparent large role of non-genetic variation among cancer cells could affect the effectiveness of treatments, especially if targeted therapy is chosen based on a specific mutation present in the cancer. “Since we see it in genetics, we assume, therefore, that [that] It drives the tumor. But what they also suggest is that in certain cases. . . What do we call the driver? [is] Actually a passenger.”

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One caveat, McGranahan adds, is that the study included pooled analyzes of tumor samples, meaning some immune cells and other healthy cells were included. “Finally . . . I think one cell [analyses] It will really help, really.” Sutoreva agrees that single-cell techniques can provide additional insight, but notes that researchers will need much larger numbers of samples to produce sufficient data, since gene expression changes over time and the genome sequence obtained. of single cells by current assays ‘almost always’ is incomplete.

Another extension of the research, McGranahan says, is to repeat this type of study using more patients with different types of cancers. “What they did here is great, because they really go deep, but that necessarily means they just look at it [a small number of] The patients.”

However, he adds, this study is an important first step in looking at variance in cancer outside of the genome. “Given that evolution acts on the phenotype, not the genotype, we need to begin to understand . . . to what extent one of these genes has a functional relevance to tumor development.”

Sutoreva reflects this sentiment. “While genes paved the way for the development of cancer, they do not write a script.”

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