In Vitro Drug Profiling to Guide Treatment for Relapse/Refractory AML
Authors: Lam Stephen , Poon Andrew Chung-Hin , Chan Koon C. , Singh Navrose Kaur , Lam Wing , Wong Ching-Man , Fung Chi Yeung , Lai Wing-Hei , Ng Ka Lam Nelson K. L. , Leung Anskar Y.H. 
Published: December 2024

Background

AML is a group of heterogeneous diseases. The one-size-fit all approach of chemotherapy and allogeneic stem cell transplantation could only achieve long term survival in 30-40%. There is an unmet need to identify novel treatment. In vitro drug profiling of primary leukemia cells allows high-throughput and patient-specific functional interrogation and was shown to correlate with disease biology (1-3). However, translation into clinical outcome has not been achieved.

Methods

Mononuclear cells from bone marrow aspirate (BM) or peripheral blood (PB) from AML patients were cultured in vitro and treated with 54 drugs at various doses for 72 hours, either singly or in combination with azacitidine. Fifty-two were FDA-approved and clinically accessible, including inhibitors of tyrosine kinases, protein synthesis and degradation, DNA damage repair, cell cycle checkpoint, anti-apoptotic machinery, DNA methylation and histone modification. Readout was cell viability measured by resazurin-based fluorometric assay and number of Annexin V negative blast population by flow cytometry. Area under dose-response curves represented patient-specific drug sensitivity and were correlated with genomic mutational profile. Predicted patient-specific effective drugs were tested in NSG mice transplanted with primary leukemia cells.

Results

Two hundred and two primary samples were screened and 51 (25%) were excluded due to poor growth in vitro. Excellent correlation was observed between technical replicates (r=0.972), paired BM and PB (r=0.947), and paired fresh and frozen samples (r=0.909), attesting to robustness of the platform. Significant correlation was observed among drugs of the same classes, for example between inhibitors of PARP (e.g. niraparib-talazoparib, r=0.78, p=1.3e-22), proteasome (e.g. bortezomib-ixazomib, r=0.90, p=4.2e-36), JAK (ruxolitinib-tofacitinib, r=0.91, p=8.3e-35), MEK (cobimetinib-trametinib, p=0.93, p=8.8e-47) and CDK (abemaciclib-palbociclib, p=0.56, p=2.7e-10), confirming that the readout is biologically meaningful. Intriguingly, there were unexpected correlations between specific pairs of drugs of different classes, for instance homoharringtonine (protein translation inhibitor)-abemaciclib (CDK inhibitor) (r=0.65, p=4.3e-17) and between specific gene mutations and drug sensitivity was observed, e.g. sensitivity of CEBPAbZIP mutated samples to PARP inhibitors (p=0.00156), and of AML with inv(16) to MEK inhibitors (p=0.0016). Synergistic anti-leukemia effect (excess over bliss additivism ≥ 10%) was observed in As2O3 or venetoclax when combined with azacitidine in 68% and 59% samples respectively. Drug response to daunorubicin showed good prediction of chemo-resistance in patients who had non-remission after “7+3” (ROC curve AUC = 0.9). Importantly, in vitro drug sensitivities of AML samples were correlated with in vivo anti-leukaemia effect in respective patient-derived xenogarafts e.g. entrectinib, venetoclax, alectinib and ponatinib in combination with azacitidine. More such correlations including those of transcriptomics and genetics will be reported at the presentation.

Conclusions

A biologically meaningful and clinically relevant in vitro drug screening platform with high throughput capacity and short turnover time showed potential of clinical application to guide treatment in relapse/refractory AML at real-time. It also provided insights to the development of novel therapeutic targets in certain AML subtypes.

Reference

1. Lam SS, Ho ES, He BL, Wong WW, Cher CY, Ng NK, et al. Homoharringtonine (omacetaxine mepesuccinate) as an adjunct for FLT3-ITD acute myeloid leukemia. Sci Transl Med. 2016;8(359):359ra129.

2. Heinemann T, Kornauth C, Severin Y, Vladimer GI, Pemovska T, Hadzijusufovic E, et al. Deep Morphology Learning Enhances Ex Vivo Drug Profiling-Based Precision Medicine. Blood Cancer Discov. 2022;3(6):502-15.

3. Bottomly D, Long N, Schultz AR, Kurtz SE, Tognon CE, Johnson K, et al. Integrative analysis of drug response and clinical outcome in acute myeloid leukemia. Cancer Cell. 2022;40(8):850-64 e9.