For years, the prevailing wisdom has been that our cells contain genes that are essentially carbon copies of each other. That notion is being dashed by studies painting a different picture — one in which even “normal” cells and tissues accumulate mutations over time.
New research out of the Broad Institute of MIT and Harvard has identified mutations in normal tissues throughout the body, including some known to drive cancer.
A large-scale analysis published Thursday in Science examined more than 6,700 samples of normal human tissue from 29 major tissue groups — from brain and bladder to breast and prostate tissue. The researchers used RNA sequencing data to look in these tissues for large mutational clones — groups of cells that have the same mutations. They found many more clones than they had expected, including some that contained mutations that drive cancer.
“This study opens up the big question of what is normal?” said Cristian Tomasetti, an associate professor of oncology at Johns Hopkins University who was not involved with the study. “This is now a picture of our normal tissues being quite messy and full of these mutational clones. We are really at the beginning of knowing how to evaluate them.”
The team assessed normal tissue samples from nearly 500 different people and observed mutations in 95% of them.
“We didn’t know if we would find anything,” said senior author Gad Getz, professor of pathology at Harvard Medical School and director of the Cancer Genome Computational Analysis Group at the Broad Institute. “But we found macroscopic clones in essentially every tissue that we looked at in the body.”
Scott Kennedy and Rosana Risques, assistant professors of pathology at the University of Washington who weren’t involved with the research, said these findings are consistent with work from their lab and others that have uncovered cancer-associated mutations in normal skin and blood. But, they said, this new study is an important step toward understanding mutations found throughout the body. “Until we had the technology, we didn’t know all of these mutations existed in normal tissue,” said Risques. “Now that we have the methods, we really need to explore this.”
Getz and his colleagues leveraged an enormous RNA sequencing dataset gathered for a separate Broad Institute effort and developed a novel method to analyze the RNA data.
Keren Yizhak, the paper’s first author, conducted the study as a postdoctoral researcher at the Broad Institute. She said the findings could change the way we think about what constitutes normal tissue. “Normal tissue is constantly developing and changing,” she said. “We are all like a puzzle made up of different cells.”
Scientists use the term “mosaicism” to describe this kind of cellular makeup, wherein an individual can have cells with different genetic material.
Some of the tissue types investigated in this study had more mutations than others. The researchers found that tissues of the lung, esophagus, and sun-exposed skin had the highest number of mutations. Getz said this was somewhat expected, since these tissues are often subject to environmental factors like cigarette smoke, hot and cold beverages, and ultraviolet radiation that could incite mutations. They also found an association between mutation number and age: tissue samples from older individuals had more mutations. Getz said future studies could reveal more about factors linked to a high number of mutations in normal tissue.
Genomic technologies now allow researchers to sequence the genetic makeup of tumors and identify the mutations found in tumor tissue. But Yizhak pointed out that analyzing a fully formed tumor provides little information about which mutations initially led to its formation. Understanding more about the mutations found in normal tissue and whether they develop into cancer could help researchers better understand how these diseases originate and progress.
Longitudinal studies that follow individuals for years could clarify how normal tissues change over time, as well as which mutations ultimately lead to cancer versus those that stop growing.
“We could detect mutations and then observe how they change in frequency during the course of the person’s lifetime and see whether they do develop into cancer,” said Selina Vattathil, a postdoctoral researcher at Princeton University who was not involved in the study. “But of course that’s really hard to do.” The technology for this type of work is available, Vattathil explained, but it is challenging to conduct studies of this kind and collect multiple samples from healthy individuals.
The emerging knowledge that normal tissues have more mutations than previously thought could throw a wrench into one ongoing area of research: the development of methods for the early detection of cancer.
Early detection is important and can improve treatment outcomes, but many tumors and blood cancers are elusive until after they have advanced to a more difficult-to-treat stage. To address this, scientists are developing techniques to identify disease-driving mutations sooner. The new findings about mosaicism present a challenge — figuring out which mutations are truly red flags that signal disease and which are harmless and normal.
Some early detection techniques, for example, involve collecting blood samples and sequencing cell-free DNA — genetic material that cells have shed into the bloodstream. Until recently, the detection of cancer-associated mutations suggested they were likely shed by cancerous or pre-cancerous cells. But the work by Getz’s team and others indicates that some of these mutations —even those known to drive cancer — may be shed by non-cancerous, normal cells.
“It really calls into question the specificity of seeing these mutations,” said Kennedy. “Just because you see a cancer-associated mutation, it doesn’t necessarily mean the patient has cancer. That’s something that diagnosticians and clinicians definitely have to take into account.”
Yizhak and Getz agree that scientists developing these techniques simply need to acknowledge the possibility that mutations they uncover may come from normal tissues.
“When we develop these tools of early detection, we want to make sure that we don’t have false positives in healthy people,” said Getz. “We just need to be careful.”
