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Patients with myelodysplastic syndromes (MDS) or acute myeloid leukemia (AML) are generally older and have more comorbidities. Therefore, identifying personalized treatment options for each patient early and accurately is essential. To address this, we developed a computational biology modeling (CBM) and digital drug simulation platform that relies on somatic gene mutations and gene CNVs found in malignant cells of individual patients. Drug treatment simulations based on unique patient-specific disease networks were used to generate treatment predictions. To evaluate the accuracy of the genomics-informed computational platform, we conducted a pilot prospective clinical study (NCT02435550) enrolling confirmed MDS and AML patients. Blinded to the empirically prescribed treatment regimen for each patient, genomic data from 50 evaluable patients were analyzed by CBM to predict patient-specific treatment responses. CBM accurately predicted treatment responses in 55 of 61 (90%) simulations, with 33 of 61 true positives, 22 of 61 true negatives, 3 of 61 false positives, and 3 of 61 false negatives, resulting in a sensitivity of 94%, a specificity of 88%, and an accuracy of 90%. Laboratory validation further confirmed the accuracy of CBM-predicted activated protein networks in 17 of 19 (89%) samples from 11 patients. Somatic mutations in the TET2, IDH1/2, ASXL1, and EZH2 genes were discovered to be highly informative of MDS response to hypomethylating agents. In sum, analyses of patient cancer genomics using the CBM platform can be used to predict precision treatment responses in MDS and AML patients.

Droplet digital PCR (ddPCR) is a highly sensitive and rapid method for detecting mutant allele frequency (MAF). In preliminary work, our lower limit of detection for common myeloid gene mutations was 0.001% in peripheral blood and bone marrow compared to 0.1% with flow cytometry and 0.01% with real-time quantitative PCR, and turnaround time is 1 day. Furthermore, we detected leukemic mutant alleles in peripheral blood (PB), introducing the possibility of sparing painful bone marrow biopsy procedures to determine treatment response. Thus, we hypothesized that ddPCR is a feasible and accurate method for monitoring leukemic disease burden in PB for the prospective care of patients (pts) with AML. Eighteen patients (pts) with de novo, relapse/refractory, and secondary AML were recruited to an IRB-approved study (NCT02435550) and bone marrow (BM), peripheral blood (PB), and saliva were collected at standard clinical visits. Gene mutations were identified by whole-exome sequencing (WES) of BM specimens at study entry. For ddPCR interrogation, genomic DNA was isolated (Qiagen), and select primers and probes (Bio-Rad/IDT) were developed based on variants identified in WES data. Case-specific primers and probes were validated on archived specimens obtained at study entry. 12/18 pt mutanomes met criteria for primer/probe design. 8 pts are in the primer/probe design and validation stage and 4 have completed validation and serial analyses. WES identified, and ddPCR confirmed, at least 1 mutation per patient at the study entry timepoint. The mutations included NRAS G13R, NRAS G12A, CSF3R T618I, and IDH2 R172K. In 2 cases, we observed a reduction in both PB and saliva MAF that were consistent with the reduction in both BM and PB blasts after treatment, resulting in complete remissions. Although PB blasts were reduced in a third pt receiving ruxolitinib, the persistence of their CSF3R MAF in PB indicated a resistant AML clone. WES revealed the presence of NRAS G13R variant in a secondary AML pt; however, WES did not detect this NRAS G13R variant in a cryopreserved BM specimen obtained at the pts MDS diagnosis. Interestingly, ddPCR was able to detect NRAS G13R variant at 0.1% MAF in a PB sample obtained at MDS diagnosis, demonstrating the ultrasensitive detection of rare variants within a sample, and highlighting the subclonal evolution of this pt's malignancy. Rapid detection of myeloid-related somatic mutations in a variety of tissue sources (i.e., saliva, PB) will allow for noninvasive monitoring of AML tumor burden. ddPCR may be used to observe molecular response to treatment and to detect molecular residual disease and relapse prior to clinically indicated BM biopsies. Citation Format: Kimberly E. Hawkins, Cesia Salan, Madeleine Turcotte, Lauren T. Vaughn, Mei Zhang, Yanping Zhang, Barry Sawicki, Glenda G. Anderson, Nosha Farhadfar, Hemant S. Murthy, Biljana N. Horn, Helen L. Leather, Paul Castillo, Maxim Norkin, John W. Hiemenz, Randy A. Brown, William Slayton, Jack W. Hsu, John R. Wingard, Christopher R. Cogle, Leylah M. Drusbosky. Droplet digital PCR is a sensitive method for detecting refractory acute myeloid leukemia (AML) clones in peripheral blood and saliva [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 3253.