Juan Eduardo Megías-Vericat1, David Martínez-Cuadrón1,2, Joaquín Martínez López3, Juan Miguel Bergua4, Mar Tormo5, Josefina Serrano6, Ataulfo González7, Jaime Pérez de Oteyza8, Susana Vives9, Belén Vidriales10, Pilar Herrera11, Juan Antonio Vera12, Aurelio López Martínez13, Adolfo de la Fuente14, Mª Lourdes Amador15, José-Ángel Hernández-Rivas16, Mª Ángeles Fernández17, Carlos Javier Cerveró18, Daniel Morillo19, Pilar Hernández Campo20, Julián Gorrochategui20, Daniel Primo20, José Luis Rojas20, Margarita Guenova21, Joan Ballesteros20, Miguel Sanz1,2 and Pau Montesinos1,2 on behalf of the Spanish PETHEMA group.
1 Hospital Universitari i Politècnic La Fe, Valencia, Spain.
2 CIBERONC, Instituto Carlos III, Madrid, Spain.
3 Hospital Universitario 12 de Octubre, UCM, CNIO, CIBERONC, Madrid, Spain.
4 Hospital San Pedro de Alcántara, Cáceres, Spain.
5 Hospital Clínico Universitario, Valencia, Spain.
6 Hospital Universitario Reina Sofía, Córdoba, Spain.
7 Hospital Universitario Clínico San Carlos, Madrid, Spain.
8 Hospital de Madrid Norte Sanchinarro, Madrid, Spain.
9 ICO-Hospital Germans Trias i Pujol, Josep Carreras Leukemia Research Institute, Universitat Autònoma de Barcelona, Badalona, Spain.
10 Complejo Asistencial Universitario de Salamanca, Salamanca, Spain.
11 Hospital Universitario Ramón y Cajal, Madrid, Spain.
12 Hospital Universitario Virgen Macarena, Sevilla, Spain.
13 Hospital Arnau de Vilanova, Valencia, Spain.
14 MD Anderson Cancer Center, Madrid, Spain.
15 Hospital de Montecelo, Pontevedra, Spain.
16 Hospital Universitario Infanta Leonor, Universidad Complutense de Madrid, Madrid, Spain.
17 Hospital Xeral Cies, Vigo, Spain.
18 Hospital Virgen de la Luz, Cuenca, Spain.
19 Fundación Jiménez Díaz, Madrid, Spain.
20 Vivia Biotech, Tres Cantos, Madrid, Spain.
21 Specialized Hospital for Active Treatment of Hematological Diseases, Sofía, Bulgaria.
Received: October 10, 2018
Accepted: January 12, 2019
Mediterr J Hematol Infect Dis 2019, 11(1): e2019016 DOI 10.4084/MJHID.2019.016
| This is an Open Access article distributed
under the terms of the Creative Commons Attribution License
(https://creativecommons.org/licenses/by-nc/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Induction schedules in acute myeloid leukemia (AML) are based on
combinations of cytarabine and anthracyclines. The choice of the
anthracycline employed has been widely studied in multiple clinical
trials showing similar complete remission rates.
Different ex vivo tests have been employed to select the most effective drug combination from the individualized sensitivity and resistance assays, but none of them have been recommended in clinical practice. We are developing a Precision Medicine (PM) test based on an actionable native environment method (PharmaFlow platform), which showed excellent correlations with clinical responses in AML, avoiding some limitations of other ex vivo assays.
The objective of this non-interventional study is to explore whether a significant percentage of patients AML samples may show different ex-vivo sensitivity to IDA vs DNR vs MIT combined with CYT.
Patients and Methods
Vivia’s PharmaFlow PM Test.
• Native environment whole bone marrow sample
Ex vivo drug sensitivity analysis was made using the PharmaFlow platform (previously termed ExviTech®) maintaining the bone marrow (BM) microenvironment. A minimum BM sample volume between 1 and 2 ml was collected by aspiration at AML diagnosis, before starting induction chemotherapy, and was processed by an automated method in Vivia Biotech laboratories 24 hours after extraction. Samples were incubated for 48 hours in 96 well plates, each well containing different drugs or drug combinations at different concentrations, enabling calculation of dose-response curves for every single drug (CYT, IDA, DNR, MIT) and combination used in treatments (CYT-IDA, CYT-DNR, CYT-MIT). The number of BM samples analyzed were 289 with IDA, 333 with DNR and 274 with MIT. A more detailed description of the procedure has been published elsewhere. The concentrations assayed for each anthracycline were:
- Concentrations for IDA (µM): > 0.0002 ; 0.001 ; 0.002 ; 0.006 ; 0.01 ; 0.018 ; 0.02 ; 0.04 ; 0.05 ; 0.055 ; 0.08 ; 0.13 ; 0.16 ; 0.2 ; 0.26 ; 0.4 ; 0.5 ; 0.6 ; 1.5.
- Concentrations for DNR (µM): > 0.001; 0.05 ; 0.075 ; 0.093 ; 0.15 ; 0.18 ; 0.25 ; 0.3 ; 0.37 ; 0.45 ; 0.75 ; 0.85 ; 1.25 ; 1.5 ; 2.7 ; 3.
- Concentrations for MIT (µM): > 0.001 ; 0.0016 ; 0.008 ; 0.01 ; 0.04 ; 0.08 ; 0.2 ; 0.38 ; 0.6 ; 0.8 ; 1 ; 2.33 ; 3.5 ; 7.
• Modeling of ex vivo activity of CYT, IDA, DNR, MIT
Evaluation of drug response was done by counting the number of live pathological cells (LPC) remaining after incubation at increasing drug concentrations. Dying cells (apoptosis) were excluded using Annexin V-FITC. Pharmacological responses were estimated using pharmacodynamic (PD) population-based models which essentially perform the fitting of the dependent variable (natural log of LPC) in a non-linear mixed-effects model to derive typical population values (fixed effects) and the magnitude of inter-patient and residual variability (random effects). Model development was performed with the first-order conditional estimation method using interaction option with the software NONMEM (v7.2), according to the following equation:
For data presentation, the survival index was computed, with the number of LPC in control wells that were not exposed to any drugs being set as 100%. The number of live cells in each drug-treated well was compared with this control value, and the survival index for each drug at each concentration was determined as the percentage of LPC at every tested concentration.
Interpatient variability (IPV) associated with all parameters was described using an exponential model of the components of variance. An additive error structure was used for the residual variability. Population PD models were built with BM samples from 227 patients that were incubated with IDA, 271 with DNR, and 212 with MIT. Bayesian estimation methods were then used to retrieve individual patient parameters based on their available exposure-response measurements in conjunction with the PD population parameters. After several trials with different modeling strategies, we could conclude that optimal approach, in terms of correlation with clinical output, was achieved by forcing typical parameters to values obtained in a different model using a dataset from samples tested at 72h. Therefore, the typical parameter value for the maximum fractional effect (Emax) was set to 1 for both drugs. For γ, the typical parameter value was calculated but limited to the range 0-3. IPV for both parameters could not be determined with this dataset.
For interaction analysis, a Surface Interaction model was used to estimate the degree of synergy, referred as α parameter, between both drugs (R environment (v3.3.1) for statistical computing). In this analysis, a value equal to 0 is an additive effect, a value > 0 indicates a synergistic effect, and a value < 0 reflects an antagonistic effect.
Study endpoints. The primary end-point was the comparison between the selective sensitivities of the different anthracyclines individually using the AUCs in the dose-response curve. For the comparisons between the combinations of anthracyclines with CYT, we employed the volume under the surface (VUS) of the dose-response curves. Besides, the differences in either drug potency or synergism ex vivo were also calculated according to the observed and predicted response after induction.
|Table 1. Baseline characteristics of the 198 analyzed patients.|
Ex vivo PharmaFlow Test characterization of IDA, DNR and MIT models. Dose-response graphs were generated for the single drugs (IDA, DNR, and MIT) using PD models (Figure 1). Most of the observations were contained within the simulation-based 95% confidence intervals of the 5-95th population percentiles proving good predictability of the selected models. Pharmacological population parameters, as well as variability and error values, are shown in Table 2.
The average dose-responses of the three anthracyclines were similar, with a slight decrease in EC50 values with IDA (p-value=1.462E-06; Table 2), reproducing the results of the clinical trials.[4,6-8,12] However, the interpatient variability of either drug is quite large (Table 2, Figure 1), which could explain why some patients could show very differential sensitivities to these three drugs. As an example, Figure 2 illustrates a patient sample that is resistant to IDA and DNR (right shifted dose-response curve) but sensitive to MIT (left shifted dose-response curve).
To identify these cases of selective sensitivity to anthracyclines, we compared the potency, regarding AUC, between IDA vs. DNR, IDA vs. MIT, and DNR vs. MIT (Figure 3, Table 3). Most dots tend to line up, but red dots represent patient samples with a difference in potency between these drugs >30%. Red dots from 3 pairwise comparisons identify 28.3% of patient samples with >30% different potency among IDA-DNR-MIT (Figure 4).
|Table 3. Differences in Area Under the Dose-Response Curve between anthracyclines.|
|Figure 4. Differences in Area Under the Dose-Response Curve between anthracyclines. A 28.3% of patients samples showed >30% different potency among Idarubicin-Daunorubicin-Mitoxantrone Area Under the Dose-Response Curve (AUC).|
Ex vivo PharmaFlow Test characterization of CYT-IDA, CYT-DNR, and CYT-MIT combinations and their synergism. The pairwise comparison of the combination treatments CYT-IDA, CYT-DNR, and CYT-MIT obtained differential sensitivity to these anthracyclines (red dots of Figure 5). In this case, the red dots represent patient samples with a difference in CYT + anthracyclines synergy differences >30%, and red dots from 3 pairwise comparisons identified an 8.2% of patient samples (Figure 6, Table 4).
Furthermore, the values for the alpha parameters of the interaction models of CYT-IDA, CYT-MIT, CYT-DNR were 0.72, 0.59 and 0.25, indicating synergistic response in the ex vivo combination experiments.
|Table 4. Differences in Volume Under the Surface (VUS) between the combinations of cytarabine and different anthracyclines.|
The first line induction therapy recommended by ELN and NCCN clinical guidelines includes seven days of a standard dose of CYT plus three days of an anthracycline, especially IDA (12 mg/m2) or DNR (60-90 mg/m2). The combination of CYT-MIT was not considered standard therapy, although it has been widely employed.
The influence of the anthracycline´s selection in the efficacy of induction therapy was analyzed in some RCTs.[3-22] The comparison between CYT-DNR and CYT-IDA has been studied in 13 different trials,[3-15] but only five studies reported differences in CR rates in favor of CYT-IDA.[4,6-8,12] A meta-analysis confirmed the superiority of CYT-IDA against CYT-DNR, obtaining higher overall survival (OS), disease-free survival (DFS), CR, lower relapse rate, although this scheme increased induction death and mucositis. Regarding the employment of CYT-DNR or CYT-MIT, a clinical trial reported similar CR, length of duration of CR, OS, and toxicity. No evidence of differences between CYT-IDA and CYT-MIT in CR, survival rates, and toxicity was observed in 6 RCTs[9,11,17-20] and one meta-analysis. Combinations of CYT-doxorubicin showed worse outcomes than CYT-DNR and CYT-IDA. According to clinical trials, in our study the average dose-responses of IDA, DNR, and MIT were similar, with a slight decrease in EC50 with IDA, indicating a probable higher potency with IDA than DNR and MIT. However, the anthracycline dosage of induction protocols assumed a cumulative doses proportion of 4:1 for DNR: IDA and DNR: MIT, but these proportions are not based in well-designed trials. In our cohort, according to this proportion and EC50 of DNR (0.458), the estimated EC50 of IDA and MIT was 0.115, a proportion 1.6 fold higher than IDA EC50 and three fold lower than MIT EC50 measured with ex vivo test.
Other studies analyzed the role of different anthracyclines in the AML induction with CYT and a third component, but CR and survival rates were similar for DNR, MIT, and aclarubicin.[32,33] Besides the selection of the anthracycline, the dose intensity is crucial in the therapy success. An RCT reported significant improvements in CR, OS and event-free survival (EFS) using DNR doses of 90 mg/m2 compared to doses of 45 mg/m2. The response-oriented individualized induction therapy is another approach tested with IDA+CYT scheme without any advantage over the standard scheme. In addition, some specific AML characteristics could modify the anthracycline response, such as FLT3-ITD mutated patients which showed higher CR and survival with high-dose DNR compared to standard-dose DNR or IDA.[36,37] These findings were reproduced in vitro in FLT3-ITD-mutated cell lines. Unfortunately, we have not enough data to analyze the impact of this mutation in our cohort.
Despite the previous experiences of ex vivo drug testing with limited sensitivity[38-44], the PharmaFlow PM test aims to solve technical limitations including some novelties:
a) the use of whole BM sample, maintaining the native environment, which has been hypothesized that it can influence the emergence of resistance;[45-48]
b) the increase of the accuracy obtained modeling ex vivo activity with PD population models in one single step;
c) the improvements in the measures performed by automated flow cytometry platform (PharmaFlow).
The correlation between in vitro and in vivo therapy sensitivity of PharmaFlow PM test has been recently demonstrated in a cohort of 123 AML patients after induction therapy with CYT-IDA (most of these patients were also included in this study). This study achieved an 81% of overall accuracy in the correlations between test predictions and hematological response, identifying with success responders (CR/CR with incomplete recovery) in 93% of cases and non-responders (partial remission/resistance) in 60% of cases. The present study generates a theoretical role of PM tests in individual anthracycline selection but does not provide enough data and critical analyses to allow to translate their use in the routine clinical practice.
Regarding the synergism between anthracyclines and CYT, we observed a synergistic response with the three combinations, especially with CYT-IDA and CYT-MIT. In a previous study, we also reported a higher synergy with CYT-IDA and CYT-MIT combination and a trend to an additive effect with CYT-DAU. Curiously, a novel approach in AML therapy is the use of the liposomal formulation of CYT and DNR in a molar ratio concentration of 5:1, based on a probable higher synergistic effect.[51,52] Furthermore, the pairwise comparisons between combinations of CYT-IDA, CYT-DNR, and CYT-MIT found in an 8.2% of patients synergy differences >30%, probably associated to the interpatient variability in drug sensibility observed in dose-response graphs.
Some limitations should be addressed in this study. First, this study analyzes the differences between ex vivo sensitivities to three different anthracyclines combined with CYT in BM samples of AML patients at diagnosis, but the correlation between ex vivo responses and clinical response was not analyzed. Second, although the incubation time was relatively short, additional transportation and processing time could lead, in several patients, to a non-affordable delay to start induction chemotherapy while receiving the test report. Third, associations of the different in vitro response of each anthracycline and specific characteristics of AML (age, WBC, cytogenetic risk, FLT3-ITD, and NPM1 status, etc.) were not analyzed. Finally, the findings reported are not yet validated in an independent cohort.
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