In what is claimed to be the biggest study of its kind, scientists headed by a team at Cambridge University Hospitals (CUH) and the University of Cambridge, have found a “treasure trove” of clues about the causes of cancer. The team, led by Serena Nik-Zainal, MD, PhD, at CUH and the University of Cambridge, carried out whole-genome analysis of more than 12,000 tumors from UK National Health Service (NHS) patients, to identify genetic mutations representing a personal history of the damage and repair processes each patient has been through.

The results, reported in Science (“Substitution mutational signatures in whole-genome-sequence cancers in the U.K. population”) revealed dozens of previously unreported mutational signatures, including tumor-specific rare signatures. Not only do the findings introduce the concept of common versus rare mutational signatures within each cancer type, but also highlight how such insights could be used to enhance personalized cancer treatments and diagnoses.

First author Andrea Degasperi, PhD, a research associate at the University of Cambridge, said, “Whole-genome sequencing gives us a total picture of all the mutations that have contributed to each person’s cancer. With thousands of mutations per cancer, we have unprecedented power to look for commonalities and differences across NHS patients, and in doing so we uncovered 58 new mutational signatures and broadened our knowledge of cancer.”

Worldwide, cancer is the first or second leading cause of mortality before the age of 70, and there were an estimated 19.3 million new cases of cancer worldwide in 2020, and 10 million deaths, the authors wrote. A cancer genome is often a distorted amalgamation of thousands of genetic mutations. Whole-genome sequencing (WGS) technology makes it possible to carry out comprehensive cancer genome analyses, which can uncover characteristic combinations of mutations that have contributed to a particular cancer. These patterns of mutation, or mutational signatures, can describe the mutational processes that led to tumor development.

“Beyond the handful of causative driver mutations, WGS allows exploration of the full landscape of passenger mutations that describe the processes that have arisen during tumorigenesis, resulting in patterns known as mutational signatures,” the authors commented. “Whereas drivers become important targets for therapeutic intervention, mutational signatures provide clues regarding historical environmental exposures and highlight potentially targetable pathway defects.”

Degasperi and colleagues performed mutational signature analysis on 12,222 WGS cancers from patients recruited from NHS Genomic Medicine Centers across England as part of the Genomics England 100,000 Genomes Project. Comparing their results with those from two smaller, open-access cancer WGS datasets, the International Cancer Genome Consortium and the Hartwig Medical Foundation, the researchers’ analysis involved WGS of more than 18,000 cancers in total.

The results indicated that for each tumor type, cancers can have a limited number of common mutational signatures and several rarer signatures, which occur at low frequency in the population. Because of the vast amount of data provided by WGS, the investigators were able to detect mutational signatures that provided clues about whether a patient has had past exposure to environmental causes of cancer such as smoking or UV light, or has internal, cellular malfunctions.

They also identified 58 new mutational signatures—including 40 single base substitution (SBS), and 18 double base substitution (DBS) mutational signatures—suggesting that there are additional causes of cancer that we don’t yet fully understand. “Across organs, we clustered all tissue-specific signatures to ascertain mutational processes that were equivalent but occurring in different tissues (i.e., reference signatures),” they explained. “We obtained 82 high-confidence SBS reference signatures and 27 high-confidence DBS reference signatures. We compared these with previously reported mutational signatures, revealing 40 and 18 previously unidentified SBS and DBS signatures, respectively.”

The team also developed a computer algorithm that can look for mutational signatures in new samples. “Because we are cognizant of increasing complexity in mutational signatures and want to enable general users, we developed an algorithm called Signature Fit Multi-Step (FitMS) that seeks signatures in new samples while taking advantage of our recent findings,” they further explained. “In a first step, FitMS detects common, organ-specific signatures; in a second step, it determines whether an additional rare signature is also present.”

Nik-Zainal, a professor of genomic medicine and bioinformatics at the University of Cambridge and an honorary consultant in clinical genetics at CUH said: “The reason it is important to identify mutational signatures is because they are like fingerprints at a crime scene—they help to pinpoint cancer culprits. Some mutational signatures have clinical or treatment implications—they can highlight abnormalities that may be targeted with specific drugs or may indicate a potential ‘Achilles heel’ in individual cancers.

“We were able to perform a forensic analysis of over 12,000 NHS cancer genomes thanks to the generous contribution of samples from patients and clinicians throughout England. We have also created FitMS, a computer-based tool to help scientists and clinicians identify old and new mutational signatures in cancer patients, to potentially inform cancer management more effectively.”

Notably, the authors concluded, “… the present analysis introduces the concept of common versus rare signatures within each tumor type. It highlights how an increased number of samples may help discern common signatures that occur at low levels for specific tumor types. Greater sample numbers may also help unveil signatures that occur at a low frequency in the population.”

Michelle Mitchell, chief executive of Cancer Research UK, which supported the study, commented, “This study shows how powerful WGS tests can be in giving clues into how the cancer may have developed, how it will behave, and what treatment options would work best. It is fantastic that insight gained through the NHS 100,000 Genomes Project can potentially be used within the NHS to improve the treatment and care for people with cancer.”

Matt Brown, CSO of Genomics England added: “Mutational signatures are an example of using the full potential of WGS. We hope to use the mutational clues seen in this study and apply them back into our patient population, with the ultimate aim of improving diagnosis and management of cancer patients.” As the authors further noted, “Indeed, as many national cancer genomic endeavors get underway worldwide over the next decade, we look forward to applying WGS data maximally to advance individualized cancer care.”