Whole-genome sequencing (WGS) provided more information on the genetics of myeloid malignancies and changed the risk category in 16% of patients in a comparison with standard cytogenetic analysis.
WGS identified all of the translocations and copy-number alterations detected by cytogenetic analysis plus an additional 40 abnormalities in 235 patients. In a prospective evaluation involving 117 consecutive patients, WGS provided new genetic information in a fourth of patients, and the median wait for results was 5 days.
Risk groups defined by WGS correlated with clinical outcomes, and WGS risk-stratified patients with inconclusive cytogenetic results, reported David H. Spencer, MD, PhD, of Washington University in St. Louis, and colleagues in the .
"We found that whole-genome sequencing provided rapid and accurate genomic profiling in patients with AML [acute myeloid leukemia] and MDS [myelodysplastic syndromes]," they stated. "Such sequencing also provided a greater diagnostic yield than conventional cytogenetic analysis and more efficient risk stratification on the basis of standard risk categories."
WGS could prove to be cost-competitive with cytogenetic analysis and has applicability to a broad range to malignancies.
"Implementing whole-genome sequencing for clinical testing can provide a unified, stable, and extensible platform that minimizes laboratory-specific bias and that can be standardized throughout the world," they added. "Although our study focused on myeloid cancers, many of the advantages of whole-genome sequencing that we observed will directly apply to patients with other cancers."
Analysis of tumor genetics has become a standard part of the diagnostic workup for a growing number of cancers. However, clinically actionable mutations span a wide range of genomic events, requiring multiple platforms to obtain genetic information for clinical management, Spencer and colleagues noted.
WGS offers an unbiased method to detect all types of mutations and potentially could replace current testing methods, they continued. Sequencing requires a limited amount of DNA and can identify genomic changes that might elude other types of analyses. Collectively, the advantages of WGS suggest a potential to improve genomic profiling of patients with cancer.
Historically, WGS has been time consuming and costly, limiting the technology to research settings, Spencer's group acknowledged. Recent technologic advances have simplified the analytic process and made it faster and less expensive.
To examine the feasibility of WGS for routine analysis of patients with cancer, investigators developed a streamlined approach to WGS for patients with AML or MDS. They analysed clinical samples in real time to evaluate the feasibility, accuracy, and utility of WGS in the clinical setting.
The streamlined approach involved use of scalable methods of sample preparation performed within 8 hours by a single technician, using commercially available reagents, followed by standard high-throughput sequencing. Investigators used automated tumor-only variant analysis to detect mutations in selected genes, copy-number alterations of more than 5 megabase pairs, and recurrent structural variants.
WGS was used to analyze samples from 235 patients with confirmed or suspected hematologic cancers. Previous cytogenetic analysis had identified 91 copy-number alterations and 40 recurrent translocations. WGS identified all of those abnormalities and an additional 40 new clinically reportable genomic events, meaning 17% of the patients had findings that were not detected by conventional cytogenetics.
To examine the feasibility of routine use of WGS in clinical oncology practice, investigators prospectively evaluated 117 consecutive patients. WGS was performed weekly in batches of one to 11 samples (bone marrow aspirates). The median time required for processing was 5.1 days. Seven samples required manual review of automated, but the remaining 110 required no additional interventions to produce a final sequencing report.
WGS provided new genetic information in 29 (24.8%) of the 117 patients, and the new information led to a change in risk category for 19 (16.2%) patients. Risk groups defined by WGS results correlated with clinical outcomes.
The authors estimated the cost of WGS, as performed in their study, to be about $1,900, putting it in the range of other testing platforms. At high-throughput laboratories the cost could be about $1,300. As the cost of sequencing decreases, WGS will likely reach price parity with conventional testing platforms.
Acknowledging that WGS is not yet widely available, Spencer said one objective of the study was to stimulate interest in the technology and demonstrate the feasibility of streamlining the process. Additionally, limited data are available from direct comparisons with other platforms.
"Nobody's ever really done a head-to-head study of genome sequencing versus conventional testing for leukemia," he told 鶹ý. "The next step is to implement it in practice, and we're going to do that at [WUSTL] as part of a clinical study. We will track things like we did in our paper, like turnaround times and differences between sequencing results and conventional testing. We'll also return the results to oncologists and their patients so we can understand whether treatment decisions were changed and what the outcomes were."
WGS offers the potential to provide far more information than clinicians and patients receive from conventional testing, he added. Examples include HLA typing for transplantation and assessment of pharmacogenetic biomarkers to predict whether a patient will respond to a therapy or have adverse reactions to therapy.
"Because we are sequencing the whole genome, we can analyze it in different ways to provide clinically relevant information with just a single test," said Spencer.
Disclosures
The study was supported by NCI and the Alvin J. Siteman Cancer Center.
Spencer disclosed relevant relationships with Illumina and Wugen.
Primary Source
New England Journal of Medicine
Duncavage EJ, et al "Genome sequencing as an alternative to cytogenetic analysis in myeloid cancers" N Engl J Med 2021; DOI: 10.1056/NEJMoa2024534.