Genome Sequencing as an Alternative to Cytogenetic Analysis in Myeloid Cancers

Abstract

Background: Genomic analysis is essential for risk stratification in patients with acute myeloid leukemia (AML) or myelodysplastic syndromes (MDS). Whole-genome sequencing is a potential replacement for conventional cytogenetic and sequencing approaches, but its accuracy, feasibility, and clinical utility have not been demonstrated.

Methods: We used a streamlined whole-genome sequencing approach to obtain genomic profiles for 263 patients with myeloid cancers, including 235 patients who had undergone successful cytogenetic analysis. We adapted sample preparation, sequencing, and analysis to detect mutations for risk stratification using existing European Leukemia Network (ELN) guidelines and to minimize turnaround time. We analyzed the performance of whole-genome sequencing by comparing our results with findings from cytogenetic analysis and targeted sequencing.

Results: Whole-genome sequencing detected all 40 recurrent translocations and 91 copy-number alterations that had been identified by cytogenetic analysis. In addition, we identified new clinically reportable genomic events in 40 of 235 patients (17.0%). Prospective sequencing of samples obtained from 117 consecutive patients was performed in a median of 5 days and provided new genetic information in 29 patients (24.8%), which changed the risk category for 19 patients (16.2%). Standard AML risk groups, as defined by sequencing results instead of cytogenetic analysis, correlated with clinical outcomes. Whole-genome sequencing was also used to stratify patients who had inconclusive results by cytogenetic analysis into risk groups in which clinical outcomes were measurably different.

Conclusions: In our study, we found that whole-genome sequencing provided rapid and accurate genomic profiling in patients with AML or MDS. Such sequencing also provided a greater diagnostic yield than conventional cytogenetic analysis and more efficient risk stratification on the basis of standard risk categories. (Funded by the Siteman Cancer Research Fund and others.).

Figure 1.. Timeline of Whole-Genome Sequencing (WGS) Process and Study Design.

Panel A shows the workflow and approximate processing time for each step of the rapid WGS method used for samples obtained from the study patients. As the first step in library construction, unfragmented DNA is cleaved and tagged for analysis in a process called tag-mentation. Examples of the reports that were generated by this process are provided in Figures S1A and S1B in the Supplementary Appendix. Panel B shows the design of the study involving both retrospective and prospective cohorts of patients with acute myeloid leukemia (AML) or myelodysplastic syndromes (MDS). The retrospective cohort included 146 samples obtained from individual patients selected to represent a broad range of cytogenetic and molecular features of AML and MDS. The prospective cohort included 117 unselected, consecutive samples obtained from patients with a known or suspected myeloid cancer for whom cytogenetic testing was requested at the study center. Seven of these patients ultimately received a diagnosis other than AML or MDS. QC denotes quality control.

Figure 2.. A Comparison of WGS with Conventional Cytogenetic Analysis and Targeted Gene Sequencing.

Panel A shows the sensitivity of WGS for the detection of recurrent structural variants (SVs) and copy-number alterations (CNAs) as compared with conventional cytogenetic analysis and for the detection of single-nucleotide variants (SNVs) and insertion–deletions (INDELs) as compared with high-coverage targeted gene sequencing. I bars denote 95% confidence intervals. Panel B shows the identification and confirmation by WGS of 13 new recurrent SVs that were not detected by conventional cytogenetic analysis, as supported by orthogonal methods, including fluorescence in situ hybridization (FISH), polymerase chain reaction (PCR) with sequencing of SV breakpoints, or detection of fusion transcripts in RNA-sequence (RNA-seq) data. Panel C shows the identification of 21 new CNAs in 14 patients; 12 of these alterations were confirmed by chromosomal microarray (CMA), FISH, or sequence-defined breakpoints. An additional 9 CNAs were identified by WGS only and could not be confirmed by CMA (in 6 patients) or confirmation was not attempted because of the size or abundance of the CNA event (in 3 patients). CNAs were also identified in 13 patients with ambiguous or inconclusive results on cytogenetic analysis. Additional details regarding these comparisons are provided in Tables S4 and S5 and Figure S2C in the Supplementary Appendix.

Figure 3 (facing page).. Clinical Feasibility and Diagnostic Yield of WGS-Based Genomic Profiling in 117 Consecutive Patients.

Panel A shows the time it took to process samples obtained from 117 consecutive patients with AML or MDS by means of WGS from April 2019 through February 2020. The median processing time for all study patients is indicated by the dashed horizontal black line. The height of each bar shows the total time in days for processing, starting from construction of the sequencing library and ending with completion of the automated final report for an individual patient sample. The duration of each individual step (as obtained from time stamps recorded in the information management system of the clinical laboratory) is indicated by the shaded bar segments and includes the duration of library generation and quality assessment, sequencing, and analysis and reporting. These times reflect the processing time plus waiting time before the next step. Longer turnaround times occurred because of delays between steps, rather than longer processing times. The dashed horizontal red lines show the recommended maximum turnaround time for FISH testing and conventional cytogenetic analysis, according to published recommendations, although shorter turnaround times occur in many laboratories. Panel B shows the yield of new WGS findings in samples obtained from 68 unselected, consecutive patients with AML. The top panel shows the cumulative number of patients with new genomic findings that were identified by WGS, as compared with conventional cytogenetic analysis or FISH, performed at the time of diagnosis, along with the cumulative number of patients with new events that changed the category of genetic risk group on the basis of established European Leukemia Network (ELN) guidelines. FISH testing included assays for PML–RARA, CBFB–MYH11, RUNX1–RUNX1T1, del(5q), and chromosome 7 deletion, according to recommendations^,; all testing was performed in samples obtained from 60 of 68 patients (88%), and subgroups of these assays were performed for the remaining patients. The results of ELN assignments to a genetic risk group by WGS, conventional cytogenetic analysis with FISH, and cytogenetic analysis alone are shown in the middle panel. The red asterisk indicates that the patient’s risk group was reclassified according to the WGS results, and the red arrow indicates that the conventional risk-group assignment was based on FISH results alone. Genomic events that were detected by WGS are shown in the bottom panel and are labeled as concordant with cytogenetic analysis, FISH, or target sequencing (in black), new findings made by WGS (in blue), and new findings that resulted in a change in the ELN genetic risk group (in red). The status regarding internal tandem duplication in FLT3 (FLT3-ITD) and the allele ratio as determined by PCR were used for both conventional and WGS-based risk stratifications.

Figure 4.. Risk Assessment by WGS in Patients with AML, According to Existing Genetic Risk Groups.

Panel A shows overall survival for 71 patients with AML who were treated with chemotherapy alone after remission, as stratified into established ELN genetic risk groups on the basis of a combination of conventional cytogenetic analysis, FISH, and targeted gene sequencing. Panel B shows the same cohort as in Panel A with risk stratification according to WGS results. The ratio of the mutated FLT3-ITD allele to the wild-type allele, as determined by PCR, was used for both the conventional and WGS classifications; the presence or absence of the mutation was used when allele ratios were not available. Panel C shows the clinical outcomes for 27 patients for whom genetic risk could not be determined because of inconclusive, unsuccessful, or unknown results on cytogenetic analysis. The median survival in this cohort was 11.2 months (95% confidence interval [CI], 5.6 to 38.8). Panel D shows the stratification of the cohort in Panel C into established genetic risk groups with the use of WGS results, which predicted shorter overall survival for patients at adverse risk than for those at intermediate or favorable risk (not adverse) (age-adjusted hazard ratio for death for intermediate or favorable risk versus adverse risk, 0.29; 95% CI, 0.09 to 0.94). All P values were calculated with the use of a log-rank test for equal survival among the groups and were adjusted for multiple comparisons.