Analytical and Potential Clinical Performance of Oncomine Myeloid Research Assay for Myeloid Neoplasms

Performance evaluation and clinical impact of the Oncomine Myeloid Research Assay for gene expression analysis in myeloid haematologic malignancies

AIM

Gene expression analysis facilitates the detection of diagnostic and prognostic biomarkers for myeloid haematological malignancies. The Oncomine Myeloid Research Assay (OMA; Thermo Fisher Scientific, Massachusetts, USA) provides a comprehensive analysis of gene expression of five target genes, along with gene alteration and fusion. Here, we present the performance of the OMA for gene expression analysis.

METHODS

In total, 53 RNA samples from patients diagnosed with acute myeloid leukaemia (AML) or myelodysplastic syndrome were included. Of these 53 samples, 3 were evaluated for reproducibility and 50 were evaluated for comparison with RNA-sequencing (RNA-seq). The prognostic impact of the gene expression profile produced by both OMA and RNA-seq in AML was investigated using follow-up data from 33 patients with AML.

RESULTS

The OMA showed good intrarun and interrun reproducibility. Compared with the RNA-seq results, high correlations were found in BAALC, MECOM and WT1 (all r>0.9), with moderate correlations in MYC (r=0.75, p<0.001) and SMC1A (r=0.42, p=0.002). The agreement between OMA and RNA-seq in classifying the dysregulated expression group was almost perfect, except for SMC1A (κ=0.175). Among these five genes, only BAALC showed a significant clinical impact in patients with AML. Patients with high BAALC expression showed significantly shorter overall survival based on both OMA (p=0.037) and RNA-seq (p=0.003).

CONCLUSIONS

OMA gene expression analysis offers reproducible and accurate gene expression data for most targeted genes and demonstrates the utility of BAALC expression as a prognostic marker in AML.

The role of next-generation sequencing in acute myeloid leukemia

PURPOSE OF REVIEW

The development of high-throughput techniques like next-generation sequencing (NGS) has unraveled the genetic profile of cancer. In this review, we discuss the role of NGS on the diagnostic, risk stratification, and follow-up of patients with acute myeloid leukemia (AML).

RECENT FINDINGS

NGS has become an essential tool in clinical practice for AML management. Therefore, efforts are being made to improve its applications, automation, and turnaround time. Other high-throughput techniques, such as whole genome sequencing or RNA-sequencing, can be also used to this end. However, not all institutions may be able to implement these approaches. NGS is being investigated for measurable residual disease (MRD) assessment, especially with the development of error-correction NGS. New data analysis approaches like machine learning are being investigated in order to integrate genomic and clinical data and develop comprehensive classifications and risk scores.

SUMMARY

NGS has proven to be a useful approach for the analysis of genomic alterations in patients with AML, which aids patient management. Current research is being directed at reducing turnaround time and simplifying processes so that these techniques can be universally integrated into clinical practice.

A retrospective comparison of salvage intensive chemotherapy versus venetoclax-combined regimen in patients with relapsed/refractory acute myeloid leukemia (AML)

Background:

Evidence that a venetoclax (VEN)-combined regimen is effective in relapsed/refractory acute myeloid leukemia (R/R AML) is emerging. However, it is unknown how VEN-combined low intensity treatment compares to intensive chemotherapy (IC) in medically fit patients with R/R AML.

Methods:

We compared AML patients who received IC (n = 89) to those who received a VEN in combination with hypomethylating agents or low dose cytarabine (VEN combination) (n = 54) as their first- or second-line salvage after failing anthracycline-containing intensive chemotherapy.

Results:

The median age was 49 years, and significantly more patients in the VEN combination group were in their second salvage and had received prior stem cell transplantation (SCT). Overall response rates including CR, CRi, and MLFS were comparable (44.0% for IC vs. 59.3% for VEN combination, p = 0.081), but VEN combination group compared to IC group tended to show lower treatment related mortality. The rate of bridging to SCT was the same (68.5%), but the percentage of SCT at blast clearance was significantly higher in the VEN-combined group (62.3% vs. 86.5%, p = 0.010). After median follow-up periods of 22.5 (IC) and 11.3 months (VEN combination), the median overall survival was 8.9 (95% CI, 5.4-12.4) and 12.4 months (95% CI, 9.5-15.2) (p = 0.724), respectively.

Conclusion:

VEN combination provides a comparable anti-leukemic response and survival to salvage IC, and provide a bridge to SCT with better disease control in medically-fit patients with R/R AML.

Validation, Implementation, and Clinical Impact of the Oncomine Myeloid Targeted-Amplicon DNA and RNA Ion Semiconductor Sequencing Assay

The identification of clinically significant genes recurrently mutated in myeloid malignancies necessitates expanding diagnostic testing with higher throughput, such as targeted next-generation sequencing. We present validation of the Thermo Fisher Oncomine Myeloid Next-Generation Sequencing Panel (OMP), targeting 40 genes and 29 fusion drivers recurrently mutated in myeloid malignancies. The study includes data from a sample exchange between two Canadian hospitals demonstrating high concordance for detection of DNA and RNA aberrations. Clinical validation demonstrates high accuracy, sensitivity, and specificity of the OMP, with a lower limit of detection of 5% for single-nucleotide variants and 10% for insertions/deletions. Prospective sequencing was performed for 187 samples from 168 unique patients presenting with suspected or confirmed myeloid malignancy and other hematological conditions to assess clinical impact of identifying variants. Of detected variants, 48% facilitated or clarified diagnoses, 29% affected prognoses, and 25% had the potential to influence clinical management. Of note, OMP was essential to identifying patients with premalignant clonal states likely contributing to cytopenias. We also found that the detection of even a single variant by the OMP assay, versus 0 variants, was predictive of overall survival, independent of age, sex, or diagnosis (P = 0.03). This study demonstrates that molecular profiling of myeloid malignancies with the OMP represents a promising strategy to advance molecular diagnostics.

Prognostic value of measurable residual disease monitoring by next-generation sequencing before and after allogeneic hematopoietic cell transplantation in acute myeloid leukemia

Given limited studies on next-generation sequencing-based measurable residual disease (NGS-MRD) in acute myeloid leukemia (AML) patients after allogeneic hematopoietic stem cell transplantation (allo-HSCT), we longitudinally collected samples before and after allo-HSCT from two independent prospective cohorts (n = 132) and investigated the prognostic impact of amplicon-based NGS assessment. Persistent mutations were detected pre-HSCT (43%) and 1 month after HSCT (post-HSCT-1m, 20%). All persistent mutations at both pre-HSCT and post-HSCT-1m were significantly associated with post-transplant relapse and worse overall survival. Changes in MRD status from pre-HSCT to post-HSCT-1m indicated a higher risk for relapse and death. Isolated detectable mutations in genes associated with clonal hematopoiesis were also significant predictors of post-transplant relapse. The optimal time point of NGS-MRD assessment depended on the conditioning intensity (pre-HSCT for myeloablative conditioning and post-HSCT-1m for reduced-intensity conditioning). Serial NGS-MRD monitoring revealed that most residual clones at both pre-HSCT and post-HSCT-1m in patients who never relapsed disappeared after allo-HSCT. Reappearance of mutant clones before overt relapse was detected by the NGS-MRD assay. Taken together, NGS-MRD detection has a prognostic value at both pre-HSCT and post-HSCT-1m, regardless of the mutation type, depending on the conditioning intensity. Serial NGS-MRD monitoring was feasible to compensate for the limited performance of the NGS-MRD assay.

Improved Variant Detection in Clinical Myeloid NGS Testing by Supplementing a Commercial Myeloid NGS Assay with Custom or Extended Data Filtering and Accessory Fragment Analysis

BACKGROUND

Commercial myeloid next-generation sequencing (NGS) panels may facilitate uniform generation of raw data between laboratories. However, different strategies for data filtering and variant annotation may contribute to differences in variant detection and reporting. Here, we present how custom data filtering or the use of Oncomine extended data filtering improve detection of clinically relevant mutations with the Oncomine Myeloid Research Assay.

METHODS

The study included all patient samples (n = 264) analyzed during the first-year, single-site, clinical use of the Ion Torrent Oncomine Myeloid Research Assay. In data analysis, the default analysis filter was supplemented with our own data filtering algorithm in order to detect additional clinically relevant mutations. In addition, we developed a sensitive supplementary test for the ASXL1 c.1934dupG p.Gly646fs mutation by fragment analysis.

RESULTS

Using our custom filter chain, we found 96 different reportable variants that were not detected by the default filter chain. Twenty-six of these were classified as variants of strong or potential clinical significance (tier I/tier II variants), and the custom filtering discovered otherwise undetected tier I/tier II variants in 25 of 132 patients with clinically relevant mutations (19%). The remaining 70 variants not detected by the default filter chain were classified as variants of unknown significance. Among these were several unique variants with possible pathogenic potential judged by bioinformatic predictions. The recently launched Oncomine 5.14 extended filter algorithm detects most but not all of the tier I/tier II variants that were not detected by the default filter. The supplementary fragment analysis for the ASXL1 c.1934dupG p.Gly646fs confidently detected a variant allele frequency of down to 4.8% (SD 0.83%). The assay also detected the ASXL1 c.1900_1922del23 mutation.

CONCLUSION

Detection of clinically relevant variants with the Oncomine Myeloid Research NGS assay can be significantly improved by supplementing the default filter chain with custom data filtering or the recently launched Oncomine 5.14 extended filter algorithm. Our accessory fragment analysis facilitates easy testing for frequent ASXL1 mutations that are poorly or not covered by the NGS assay.