Analysis of the Evolving MDS/AML Clones to Identify Resistance Mechanisms and Predict New Therapy Options at Relapse Using Computational Biology Modeling: Case-Studies from iCare1 Clinical Study

Background: Relapse is a major challenge in treating patients with MDS and AML. In this study we used a genomics-informed computational biology modeling (CBM) technique to understand the mechanisms of relapse after chemotherapy treatment and to postulate new re-induction treatment options. Methods:...

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Veröffentlicht in:Blood 2018-11, Vol.132 (Supplement 1), p.3086-3086
Hauptverfasser: Vali, Shireen, Abbasi, Taher, Singh, Neeraj Kumar, Usmani, Shahabuddin, Lala, Deepak Anil, G, Poornachandra, Radhakrishnan, Saumya, Birajdar, Shivgonda C, Naga, Ganesh, Drusbosky, Leylah M., Cogle, Christopher R.
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Sprache:eng
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Zusammenfassung:Background: Relapse is a major challenge in treating patients with MDS and AML. In this study we used a genomics-informed computational biology modeling (CBM) technique to understand the mechanisms of relapse after chemotherapy treatment and to postulate new re-induction treatment options. Methods: 120 patients with AML or MDS were recruited in the iCare1 prospective clinical study (NCT02435550), designed to assess predictive accuracy of CBM prediction by comparing computer predictions of treatment response to actual clinical outcomes. WES, CNV, and cytogenetics were obtained for 96 patients (Table). Genomic profiling was conducted by conventional cytogenetics, whole exome sequencing (SureSelectXT Clinical Research Exome, Agilent), and array CGH (Agilent). Somatic genomic mutations were inputted into CBM technology to create disease-specific protein network maps for each patient. A digital drug library of FDA-approved drugs was created for CBM by programming each agent's mechanism of action determined from published literature. Digital drug simulations of the patient's choice of therapy were tested at varying doses and predicted efficacy of the drugs were measured as a function of a disease inhibition score (DIS), defined as the degree to which disease pathways and phenotypes (cell proliferation and viability) were returned to a mutation-free state. Treating physicians were masked to the results of CBM predictions and the clinical outcomes were prospectively recorded. Clinical response for MDS patients was defined as CR+PR+HI (IWG 2006). Clinical response for AML patients was defined as CR+PR by IWG 2003 criteria. Results: 50 patients were eligible for evaluation based on length of follow-up. In 50 patients, 61 treatments were administered. CBM maps of relapsed samples from iCare 1 patients accurately matched the patient's nonresponse of treatment at relapse in 90% of patients and identified mechanisms for chemoresistance in these patients (Table 1). An example case-study is presented (CASE I: UFH-00012): AML patient, relapsed after 7+3 induction therapy. CBM predicted response to azacitidine (AZA) at first relapse and clinically was evaluated to be a responder with a blast reduction to 2%, normal CBC, and normal cytogenetics. After 9 months of AZA, the disease relapsed and was genetically profiled. CBM analysis and digital drug simulation of the relapsed disease genomics confirmed a non-response to AZA. A GOF mutation in EZH2 present in pre-AZA was a key
ISSN:0006-4971
1528-0020
DOI:10.1182/blood-2018-99-115821