MEDICINE AND HEALTH

Largest cancer whole genome sequencing to discover new oncogenic mutations


Lung cancer cells. Photo credit: Anne Weston, EM STP, The Francis Crick Institute/Science Photo Library

On April 22, a large-scale study published in Science analyzed hundreds of millions of mutations hidden in the genomes of cancer cells in more than 12,000 patients, screening for dozens of new DNA mutation signatures that may provide clues to the genetic and environmental causes of cancer. In some cases, this may also help clinicians choose the best individual treatment for a patient.

Núria López-Bigas, a computational cancer biologist at the Biomedical Research Institute in Barcelona, Spain, said the “size of the scale” of the cancer genomic mutation analysis was important. The study revealed rare mutation patterns in cancer that cannot be found in smaller datasets.

“When you have so many whole genomes, you have more power and you can figure out more complete mutational signatures.” While it’s still in its early stages, there’s great potential in the future in terms of diagnosing and understanding how these cancers arise. Núria López-Bigas said.

A single cancer cell may contain hundreds of thousands of mutations, sometimes more than 1 million, but only a few of them can directly lead to the development of tumors. For years, researchers have searched genomic data for these carcinogenic factors in hopes of finding new treatments.

Many of the remaining “bystander” mutations can also provide information. Some carcinogens produce characteristic patterns of DNA changes. For example, ultraviolet light can cause cytosines in DNA bases to be replaced by thymine at certain locations in the genome, a change commonly found in melanoma.

Study corresponding author Serena Nik-Zainal, a computational biologist at the University of Cambridge in the United Kingdom, believes that these mutation patterns can be likened to footprints on the beach. “Footprints may seem random, but they all appear for a reason. If you look closely at the footprints, some features reveal whether they are animals or people, dogs or birds, adults or children, and whether they are walking or running. She said.

The previous largest study on the characteristics of cancer mutations, published in 2020, analyzed the whole genome sequences of about 5,000 tumor samples collected in an international study.

In the new study, the researchers analysed more than 12,000 cancer genome samples from 19 tumor types collected by the UK’s National Health Service as part of the UK Genomics’ 100,000 Genomes project. The researchers used a previously published dataset to validate their findings. Study co-author Andrea Degasperi, a computational biologist at the University of Cambridge, describes the development of new analytical tools and an algorithm capable of handling hundreds of thousands of mutations.

Dozens of previously unknown mutation footprints were produced through validation, some of which can be traced back to defects in methods to repair DNA-specific cells.

Dávid Szüts, a cancer biologist at the Natural Science Research Center in Budapest, Hungary, said researchers may now have identified all the most common mutational features. “At this point, it seems unlikely that the main process will be missed. But as the Cancer Genome Project thrives around the world, the search for rare features that occur in less than 1 percent of tumors in specific organs is likely to continue.

In addition to looking for further mutant signatures, Degasperi hopes to be able to trace the origin of more mysterious genes that have not yet been linked to cancer-causing events. He also wants to study other kinds of genetic variations, with current research focusing on changes between 1 and 3 DNA bases, but DNA sequences can also be deleted, inserted, or reassembled into larger chunks.

He hopes the studies will eventually lead to individual-specific cancer treatments. “When you understand this mechanism, you may understand how it might relate to drugs.” (Source: China Science Daily Xin Yu)

Related paper information:

https://doi.org/10.1126/science.abl9283

https://doi.org/10.1038/s41586-020-1943-3



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