A genomics-informed computational biology platform prospectively predicts treatment responses in AML and MDS patients.

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.

Detection of Skeletal Lesions by Whole Body Multidetector Computed Tomography in Multiple Myeloma has no Impact on Long-Term Outcomes Post Autologous Hematopoietic Cell Transplantation.

BACKGROUND: Multiple myeloma (MM), a plasma cell malignancy, is the most common cancer to involve the skeleton. Skeletal related events such as pathologic fractures and lytic bone lesions have been associated with poor prognosis. Whole body multidetector computed tomography (WBCT) has been shown to be the most sensitive imaging modality in detecting small osteolytic lesions (< 5 mm) in the spine. The significance of lytic lesions detected only by CT is unknown as is their impact on overall survival of MM. The aim of this study was to evaluate the impact of lytic bone lesions seen only by WBCT on progression free survival (PFS) and overall survival (OS) in MM patients after hematopoietic cell transplantation (HCT). METHODS: We evaluated 72 patients who had WBCT and conventional radiographic skeletal survey (CSS) after initial or salvage chemotherapy prior to HCT. RESULTS: Forty-one patients (57%) had more findings on WBCT than CSS, 31 patients (43%) had no differences in the two imaging techniques, 9 patients had no bone lesions on either modality, and 5 patients had lesions only identified by WBCT and not on CSS. PFS and OS were similar in patients with lesions seen by CSS irrespective of whether additional lesions were noted by WBCT; similarly, in patients without lesions on CSS, OS and PFS were better than patients with lytic lesions, but detection of occult lesions by WBCT did not adversely affect PFS or OS. CONCLUSIONS: Our study shows that although WBCT is more sensitive in defining existing myelomatous bony disease in MM, these additional findings may not have any impact on PFS and OS of MM patients. Only patients without any bone lesions on conventional skeletal survey had significantly better PFS and OS. This suggests CSS remains the gold standard for evaluating myeloma bone disease.