Impact of the Updated IPSS-Molecular Prognostic Scoring System for Myelodysplastic Syndrome in 10,283 Real World Samples

Introduction The International Prognostic Scoring System-Molecular (IPSS-M) is a validated prognostic method that incorporates molecular information to improve risk stratification for patients with myelodysplastic syndromes (MDS). It is a weighted sum of prognostic variables consisting of clinical, cytogenetic, and somatic mutation information (up to 31 genes), used to generate a patient-specific risk score and associated risk category assignment. To assess the impact of combining additional molecular data into MDS prognosis, we retrospectively analyzed 10,283 real world samples from patients who had been sequenced with a commercially available targeted next-generation sequencing (NGS) panel to determine the number of patients whose risk stratification could potentially be altered by IPSS-M.

Methods Next-generation sequencing was performed using a panel capable of detecting and reporting single nucleotide variants and small indels across 50 genes. IPSS-M uses 19 binary molecular features incorporating somatic mutation information from 31 genes, 27 of which are targeted by the NGS panel used. Whole blood or bone marrow samples from patients with cause-for-testing for MDS or peripheral blood cytopenias were submitted for analysis by a clinician. DNA was extracted and assayed by the targeted, NGS panel and sequenced on Illumina DNA sequencers (Illumina, San Diego, CA). Results were reviewed, orthogonally confirmed unless previously validated, and reported by clinical laboratory directors. Disease status or symptoms were abstracted from test requisitions for each patient. TP53 loss of heterozygosity and KMT2A partial tandem duplications (MLL^PTD) are molecular features in the IPSS-M but could not be assessed in this study.

Results A total 10283 samples were analyzed including 4437 with an indication for MDS. 46.0% (4728/10283) of samples had at least one of 17 IPSS-M molecular features. The mean number of features observed was 0.83 with a range 0-6. In the IPSS-M, multiple mutations in TP53 have the strongest negative effect and this feature was observed in 2.3% of patients (236/10283). SF3B1-α, which provides the strongest positive effect, was observed in 6.5% (666/10283) of patients. The most common features were ASXL1 (15.3%, 1571/10283), DNMT3A (11.7%, 1204/10283) and SRSF2 (10.0%, 1030/10283).

629 MDS or peripheral blood cytopenia patients had serial testing performed allowing us to observe possible changes in IPSS-M risk scores over time. Patients with serial testing had a mean of 2.16 tests performed with a range of 2-5 tests. The mean interval between tests was 225 days (median = 177 days, range 0-1211 days). 63.4% (399/629) of patients with serial tests had at least one molecular feature in at least one sample. Furthermore, a change in IPSS-M molecular features was observed between tests in 44.1% (176/399) of cases potentially leading to a change of IPSS-M risk score and clinical management in these patients. Gains of features between tests were observed in 30.1% (120/399) while losses were observed in 22.1% (88/399). These changes in mutation status may be result of tumor evolution, response to therapeutic intervention, or a combination thereof. A small number of patients (n=23) showed both losses and gains of molecular features over the course of testing revealing insights into the biological evolution of MDS. Efforts are ongoing to gather clinical and cytogenetic data associated with these samples to fully assess changes in IPSS-M scores over time.

Conclusion A large proportion (50.1%, 2257/4437) of MDS patients analyzed have molecular findings that allow for further clinical risk stratification. These findings show the benefit of targeting a broad panel of genes using NGS for MDS prognosis and patient risk stratification.

Hogg:Labcorp: Current Employment. Zeng:Labcorp: Current Employment, Current equity holder in publicly-traded company. Hoffman:Labcorp: Current Employment, Current equity holder in publicly-traded company. Severson:Labcorp: Current Employment, Current equity holder in publicly-traded company. Cai:Labcorp: Current Employment. Chen:Labcorp: Current Employment, Current equity holder in publicly-traded company. Gardner:Labcorp: Current Employment, Current equity holder in publicly-traded company. Holden:Labcorp: Current Employment, Current equity holder in publicly-traded company. Iyer:Labcorp: Current Employment, Current equity holder in publicly-traded company. Leo Kenyon:Labcorp: Current Employment, Current equity holder in publicly-traded company. Boles:Labcorp: Current Employment, Current equity holder in publicly-traded company. Parker:Labcorp: Current Employment. Letovsky:Labcorp: Current Employment, Current equity holder in publicly-traded company. Dong:Labcorp: Current Employment, Current equity holder in publicly-traded company. Nagan:Labcorp: Current Employment, Current equity holder in publicly-traded company. Ramkissoon:Labcorp: Current Employment, Current equity holder in publicly-traded company. Eisenberg:Labcorp: Current Employment, Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees. Chenn:Labcorp: Current Employment, Current equity holder in publicly-traded company; Qiagen: Honoraria. Jensen:Labcorp: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties; PetDx: Consultancy.