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Copy Number Signatures Predict Chromothripsis, Prognosis in Newly Diagnosed MM


Using whole genome sequencing, copy number signatures were successful in predicting both the presence of chromothripsis and clinical outcomes in patients with newly diagnosed multiple myeloma (MM).

Copy number (CN) signatures detected using whole genome sequencing (WGS) were found to be a potential tool for identifying chromothripsis early in patient with newly diagnosed multiple myeloma (NDMM), according to a recent study.

The study, published in Nature Communications, also showed that CN signatures can be derived from whole exome sequencing (WES) in addition to WGS to predict the presence of chromothripsis and any adverse prognostic impact.

“CN signature analysis can accelerate our ongoing quest to accurately define high-risk MM, and to translate WGS-based prognostication into the clinic,” wrote the investigators.

Chromothripsis is a catastrophic event where mass amounts of chromosomal arrangements occur, and it is emerging as a strong independent prognostic factor for multiple malignancies. Typically, detection of chromothripsis requires WGS and the integration of structural variants (SVs) and CN data.

It can also be detected in patients with myeloma potentially decades prior to a diagnosis. The structure of chromothripsis is stable during spontaneous progression of MM. However, in solid cancers, it is often found in late-stage disease, often in metastatic disease or posttherapy samples, and can have an unstable structure over time.

SV and CN signatures have been observed in ovarian cancer and may be related to BRCA genes. They can be important markers for prognosis and treatment responsiveness. Considering the genome-wide distribution and lower complexity of chromothripsis in MM, the investigators wanted to see whether a comprehensive signature analysis approach using SV and CN can lead to an accurate estimation of chromothripsis in MM.

The investigators gathered data from the ongoing CoMMpass study, a prospective observational clinical trial that features information on comprehensive genomic and transcriptomic characterization for 752 patients with NDMM. According to the most recent data available, at least 1 chromothripsis event was recorded in 24% of the entire series.

“Utilizing comprehensive signature assessment in WES data potentially accelerates the clinical translation of testing for chromothripsis where WGS data is not available,” said the investigators.

A validation series of the WGS comprised samples showed that CN signatures were strongly predictive of the presence of chromothripsis in MM (area under the curve [AUC] = 0.96). Additionally, CN signatures alone retained a highly accurate prediction (AUC = 0.90).

The investigators validated their prediction model using an extended data set of 269 full coverage WGS from previously published hematological cancer samples, which included 34 NDMM cases, 92 chronic lymphocytic leukemia samples, 29 chronic myeloid leukemia cases, 104 B-cell lymphoma samples, and 10 acute myeloid leukemia cases.

Across the cohort of non-MM hematological malignancies (n = 235), the analysis had an AUC of 0.97 for predicting chromothripsis, and an AUC of 0.87 was observed when testing in the 34 NDMM samples.

Survival analysis on the CoMMpass data demonstrated that CN signatures were also strongly predictive of MM clinical outcomes, showing a median progression-free survival (PFS) of 32.2 months (95% CI, 25.2-48.3) in those with chromothripsis compared with those without (PFS, 41.1; 95% CI, 37.8-47.2; P = .00011).

Supplementary and median overall survival of 53.3 months was achieved with chromothripsis but was not reached in those without (P < .0001).

“Given these relevant translational and clinical data in MM and other malignancies, it follows that the integration of complex SV data has the potential to improve the current prognostic scoring systems,” noted the investigators.


Maclachlan KH, Rustad EH, Derkach A. Copy number signatures predict chromothripsis and clinical outcomes in newly diagnosed multiple myeloma. Nat Commun. 2021;12:5172. doi:10.1038/s41467-021-25469-8

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