Abstract 1548: Genetic biomarkers predict clinical response and survival in myelodysplasia

Abstract

Abstract Background: Hypomethylating agents (HMA) used in higher-risk myelodysplastic syndromes (MDS) improve survival but HMA-failure has a poor prognosis. Abnormal bone marrow (BM) colony-forming units (CFUs) persist in treated MDS patients despite achievement of complete remission, suggesting persistent abnormal stem cell function. We aim to identify genetic biomarkers following treatment with Azacitidine ± Thalidomide or Lenalidomide that predict clinical outcomes in MDS. Methods: BM cells from patients enrolled in ALLG MDS3 and MDS4 clinical trials at baseline and after 4 cycles of treatment (C4) were grown in Methocult for 14 days. CFUs were pooled at baseline; C4 macroscopically normal and abnormal colonies were harvested separately. mRNA expression was quantified using the Nanostring nCounter PanCancer Pathways panel. Clinical outcomes analysed were: (1) clinical benefit at 12 months (haematological improvement or better as per IWG criteria) (2) best response achieved. Genes expressed above background level in ≥25% of samples were included for statistical analyses, resulting in 516 genes across 56 samples from 23 different patients. R limma package was used for differential expression analysis. Patients were weighted using limma's voomWithQualityWeights function. Moderated t-tests with empirical Bayes were done to identify differentially expressed genes. For testing between colonies, a log-fold-change cut-off of 0.5 was used with limma's treat function. P-values were adjusted for multiple hypothesis testing. Results: 98 genes exhibited significantly different expression (p <0.05) when comparing C4 normal to baseline colonies and 118 genes were differentially expressed between C4 normal to C4 abnormal colonies. Key results are summarised: (1) Within C4 normal colonies - RFC3 (p=0.04) and LTBP1 (p=0.04) were upregulated in patients with clinical benefit at 12 months (2) Within C4 abnormal colonies - FN1 (p=0.03) was upregulated in those failing to achieve at least a partial response (PR) (3) Comparing C4 normal colonies to baseline: a. The top 5 differentially expressed genes: MAPK12, PLAU, FGFR1, IL10 and FLNA (p<0.001) were downregulated in the C4 normal group; b. In addition, for patients with clinical benefit, MYD88 and PIK3R5 were downregulated (p<0.001) while; c. In patients who achieved at least a PR as best response, NFKB1, SYK and TGFBR2 were downregulated (p<0.001). d. Gene ontology analysis revealed upregulated genes involved in plasma membrane and cytokine production were over-represented at baseline while; e. KEGG pathway analysis showed upregulated genes involved in the cytokine receptor, Notch and NF-kB signalling pathways. Conclusion: We identified changes in gene expression following treatment in MDS that predict outcomes in response and clinical benefit. These genetic biomarkers require further validation and could define early markers of resistance for investigation of novel therapies. Citation Format: Lynette Chee, David Ritchie, Jessica Chung, Daniel Park, Mandy Ludford-Menting, Jane Ripley, Melita Kenealy, Rachel Koldej. Genetic biomarkers predict clinical response and survival in myelodysplasia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 1548.