Abstract
Researchers have developed a highly sensitive single-molecule sequencing technique that could be used to study somatic mutations in a wide range of normal tissues, including those that aren't actively dividing. The technique, called NanoSeq, has several potential cancer applications, including studying mutagenesis and exploring somatic mutations that occur prior to cancer.
Researchers have developed a highly sensitive single-molecule sequencing technique that can be used to study somatic mutations in a wide range of normal tissues, including those that aren't actively dividing (Nature 2021;593:405–10). The approach, called NanoSeq, has several potential cancer applications, including studying mutagenesis and exploring somatic mutations that occur before cancer arises.
“At a technical level, the achievement is amazing,” says Jamie Blundell, PhD, of the University of Cambridge in the UK, who was not involved in the work. “It's a major advance to be able to look at mutational processes going on in normal tissues.”
Researchers have used genomic sequencing to comprehensively characterize mutations in cancer cells. However, studying somatic mutations in healthy tissues, which could elucidate how cancer develops, has presented more of a challenge. This is because somatic mutations occur in such small numbers of cells in a tissue that they aren't easily detected with conventional sequencing.
Senior author Iñigo Martincorena, PhD, of the Wellcome Sanger Institute in Hinxton, UK, and his colleagues had used a biopsy-based approach to quantify somatic mutations in tissues with actively dividing cells, such as the skin and esophagus (Science 2015;348;880–6; Science 2018;362:911–7). Yet, “we didn't have a way of reliably measuring mutation rates in tissues like brain that don't actively proliferate,” Martincorena says, which is what motivated the latest work.
NanoSeq is a duplex sequencing protocol that improves how DNA is prepared to achieve an error rate of less than 5 per billion base pairs in sequencing single DNA molecules from cell populations—two orders of magnitude lower than typical mutation rates. “That means that we can now take any tissue of interest and quantify mutation rates, no matter whether the tissue divides,” Martincorena explains. “It is quite a powerful tool.”
To demonstrate the utility of NanoSeq, the researchers compared somatic mutations in differentiated blood cells that had divided many times with blood stem cells that infrequently divide. They found similar numbers of somatic mutations—regardless of how many times cells had divided. The team then sequenced nondividing neurons and infrequently dividing smooth muscle cells to confirm that somatic mutations accumulate over time regardless of cell division.
One potential application of NanoSeq to cancer research, Martincorena says, is in vitro and in vivo mutagenesis screens. A cell line could be treated with a mutagen and immediately sequenced for somatic mutations, rather than expanding each cell of interest into a full colony. Similarly, instead of exposing a mouse to a carcinogen and waiting to perform sequencing until a tumor develops, somatic mutations could be quantified in normal tissues immediately after exposure. According to Martincorena, the technique could also provide a noninvasive approach for assessing somatic mutations in normal tissues from large cohorts of healthy individuals, some of whom eventually develop cancer. Such data would offer insight into mutations that develop based on age and lifestyle factors, and how they correlate with cancer risk.
Technological advances aside, Blundell finds the conclusion that somatic mutations accumulate with time, independent of cell division, intriguing. “In my head there has always been this idea that a substantial number of somatic mutations are contributed during the process of cell division,” he says. “I think this finding questions some of the assumptions that went into some of the very simple cancer models.”
Blundell now wants to know whether NanoSeq might allow for targeted sequencing of specific genes or sections of the genome in healthy tissues. Such a “very, very deep dive on a region” could enable the identification of precancerous mutations that are only present in one or two cells of a tissue, he says. “I think this could potentially have real impacts for early detection and screening.” –Catherine Caruso
