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An Ex Vivo Platform for the Prediction of Clinical Response in Multiple Myeloma.

ABSTRACT: Multiple myeloma remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, Ex vivo Mathematical Myeloma Advisor (EMMA), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from multiple myeloma patients, allowing us to predict clinical response to up to 31 drugs within 5 days after bone marrow biopsy. From a cohort of 52 multiple myeloma patients, EMMA correctly classified 96% as responders/nonresponders and correctly classified 79% according to International Myeloma Working Group stratification of level of response. We also observed a significant correlation between predicted and actual tumor burden measurements (Pearson r = 0.5658, P < 0.0001). Preliminary estimates indicate that, among the patients enrolled in this study, 60% were treated with at least one ineffective agent from their therapy combination regimen, whereas 30% would have responded better if treated with another available drug or combination. Two in silico clinical trials with experimental agents ricolinostat and venetoclax, in a cohort of 19 multiple myeloma patient samples, yielded consistent results with recent phase I/II trials, suggesting that EMMA is a feasible platform for estimating clinical efficacy of drugs and inclusion criteria screening. This unique platform, specifically designed to predict therapeutic response in multiple myeloma patients within a clinically actionable time frame, has shown high predictive accuracy in patients treated with combinations of different classes of drugs. The accuracy, reproducibility, short turnaround time, and high-throughput potential of this platform demonstrate EMMA's promise as a decision support system for therapeutic management of multiple myeloma. Cancer Res; 77(12); 3336-51. ©2017 AACR.

SUBMITTER: Silva A

PROVIDER: S-EPMC7819642 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature

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An Ex Vivo Platform for the Prediction of Clinical Response in Multiple Myeloma.

Silva Ariosto A Silva Maria C MC Sudalagunta Praneeth P Distler Allison A Jacobson Timothy T Collins Aunshka A Nguyen Tuan T Song Jinming J Chen Dung-Tsa DT Chen Lu L Cubitt Christopher C Baz Rachid R Perez Lia L Rebatchouk Dmitri D Dalton William W Greene James J Gatenby Robert R Gillies Robert R Sontag Eduardo E Meads Mark B MB Shain Kenneth H KH

Cancer research 20170411 12

Multiple myeloma remains treatable but incurable. Despite a growing armamentarium of effective agents, choice of therapy, especially in relapse, still relies almost exclusively on clinical acumen. We have developed a system, Ex vivo Mathematical Myeloma Advisor (EMMA), consisting of patient-specific mathematical models parameterized by an ex vivo assay that reverse engineers the intensity and heterogeneity of chemosensitivity of primary cells from multiple myeloma patients, allowin ...[more]

PMID: 28400475

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Project description:UnlabelledVery-late-antigen-4 (VLA-4, α4β1 integrin, CD49d/CD29) is a transmembrane adhesion receptor that plays an important role in cancer and immune responses. Enhanced VLA-4 expression has been observed in multiple myeloma (MM) cells and surrounding stroma. VLA-4 conformational activation has been associated with MM pathogenesis. VLA-4 is a promising MM imaging and therapeutic biomarker.MethodsSpecificity of (64)Cu-LLP2A ((64)Cu-CB-TE1A1P-PEG4-LLP2A), a high-affinity VLA-4 peptidomimetic-based radiopharmaceutical, was evaluated in α4 knock-out mice and by competitive blocking in wild-type tumor-bearing mice. (64)Cu-LLP2A PET/CT (static and dynamic) imaging was conducted in C57BL6/KaLwRij mice bearing murine 5TGM1-GFP syngeneic tumors generated after intravenous injection via the tail. Blood samples were collected for serum protein electrophoresis. Bone marrow and splenic cells extracted from tumor-bearing and control mice (n= 3/group) were coincubated with the optical analog LLP2A-Cy5 and mouse B220, CD4, Gr1, and Mac1 antibodies and analyzed by fluorescence-activated cell sorting. Human radiation dose estimates for (64)Cu-LLP2A were extrapolated from mouse biodistribution data (6 time points, 0.78 MBq/animal, n= 4/group). Ten formalin-fixed paraffin-embedded bone marrow samples from deceased MM patients were stained with LLP2A-Cy5.Results(64)Cu-LLP2A and LLP2A-Cy5 demonstrated high specificity for VLA-4-positive mouse 5TGM1-GFP myeloma and nonmalignant inflammatory host cells such as T cells and myeloid/monocytic cells. Ex vivo flow cytometric analysis supported a direct effect of myeloma on increased VLA-4 expression in host hematopoietic microenvironmental elements. SUVs and the number of medullar lesions detected by (64)Cu-LLP2A PET corresponded with increased monoclonal (M) protein (g/dL) in tumor-bearing mice over time (3.29 ± 0.58 at week 0 and 9.97 ± 1.52 at week 3). Dynamic PET with (64)Cu-LLP2A and (18)F-FDG demonstrated comparable SUV in the prominent lesions in the femur. Human radiation dose estimates indicated urinary bladder wall as the dose-limiting organ (0.200 mGy/MBq), whereas the dose to the red marrow was 0.006 mGy/MBq. The effective dose was estimated to be 0.017 mSv/MBq. Seven of the ten human samples displayed a high proportion of cells intensely labeled with LLP2A-Cy5 probe.Conclusion(64)Cu-LLP2A and LLP2A-Cy5 demonstrated binding specificity for VLA-4 in an immune-competent murine MM model. (64)Cu-LLP2A displayed favorable dosimetry for human studies and is a potential imaging candidate for overexpressed VLA-4.

Dataset Information

An Ex Vivo Platform for the Prediction of Clinical Response in Multiple Myeloma.

Publications

An <i>Ex Vivo</i> Platform for the Prediction of Clinical Response in Multiple Myeloma.

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