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Pan-Cancer Analyses Reveal Copy Number Signatures, Chromosomal Instability Patterns

NEW YORK – For a pair of new studies, independent research teams have documented several copy number signatures across cancer types, including informative signatures with ties to cancer types, chromosomal instability patterns, and other genomic or biological features in the tumors profiled.

In one of the papers, published in Nature on Wednesday, researchers from the University College London, the University of California, San Diego, and elsewhere relied on an analytical framework designed for detecting copy number signatures based on whole-genome sequence, exome sequence, reduced-representation bisulfite sequencing, single-cell sequencing, or array-based SNP profiles.

"[W]e presented a copy number signature framework that provides great utility for the exploration of copy number patterns across multiple cancer types and distinct experimental platforms and exceeds the capabilities provided by mutational signatures of substitutions, [small insertions or deletions], or rearrangements," co-senior and co-corresponding authors Nischalan Pillay, a pathology researcher affiliated with the UCL and the Royal National Orthopedic Hospital NHS Trust, and Ludmil Alexandrov, a cellular and molecular medicine, bioengineering, and cancer researcher at UC San Diego, and their colleagues wrote.

When the team analyzed nearly 9,900 tumor samples from 33 cancer types, assessed through the Cancer Genome Atlas project, it tracked down 21 copy number signatures, including signatures that overlapped regardless of whether they were drawn from genome, exome, or SNP data.

Together, the signatures corresponded with the copy number profiles present in 97 percent of the tumor samples considered, the researchers noted, and all but four of the signatures could be linked to other biological events ranging from aneuploidy or whole-genome doubling to chromothripsis, homologous recombination defects, loss-of-heterozygosity, or other mutational features.

The team noted that unlike mutational signatures made up of individual nucleotide changes, the copy number signatures did not seem to reflect cancer-related exposures. Instead, they tended to reflect endogenous mutational processes and features — from cancer-driving oncogenic tumor features to prognostic alterations such as chromothripsis that are found within or across cancer types.

"Our results synthesize the global landscape of copy number alterations in human cancer by revealing a diversity of mutational processes that give rise to these alterations," the authors reported, adding that "[t]he field of copy number signatures is nascent, with multiple distinct methods previously implemented in distinct tumor types."

In a related Nature study, an international team led by investigators at the Spanish National Cancer Research Centre (CNIO) and Cancer Research UK Cambridge Institute focused on copy number signatures that coincided with various forms of chromosomal instability (CIN), highlighting signatures that may eventually serve as biomarkers for cancer aggressiveness and/or anticipated treatment responses.

"Our biomarkers can predict the effectiveness of different therapies for a given tumor," co-senior and co-corresponding author Geoff Macintyre, head of CNIO's computational oncology group, said in a statement.

Authors of that study have reportedly patented methods used in the paper and related strategies used previously through a precision medicine startup called Tailor Bio that is based in the UK.

With the help of array-based SNP profiles, investigators characterized CIN patterns across 7,880 tumor samples from 33 cancer types. They documented CIN in 6,335 tumors — representing around 80 percent of those tested — before delving further into the biological reasons for this instability and relationships between CIN and other tumor features.

"The signature compendium presented here is an important resource to guide future studies into a deeper understanding of the origins and diversity of CIN and how to therapeutically target different types of CIN," the authors of that study noted.

In particular, the team flagged 17 CIN-related copy number signatures. While 10 of the copy number signatures spanned cancer types, another seven copy number signatures appeared to be overrepresented within specific cancer types.

With these signatures, the investigators not only delved into CIN drivers, but also flagged signatures linked to homologous recombination defects or other tumor genome features; survival- or treatment response-related signatures; and signatures pointing to possible drug targets. Together, the findings supported the notion that such signatures may serve as possible biomarkers for treatment response, therapy selection, and future drug development.

"The signatures predict drug response and identify new drug targets," the authors reported, noting that the framework used for that analysis "refines the understanding of impaired homologous recombination, which is one of the most therapeutically targetable types of CIN."

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