Here we present a protocol for the isolation of leukemic cells from leukemia patients bone marrow and analysis of their metabolic state. Assessment of the metabolic profile of primary leukemia cells could help to better characterize the demand of primary cells and could lead up to more personalized medicine.
The metabolic requirement of cancer cells can negatively influence survival and treatment efficacy. Nowadays, pharmaceutical targeting of metabolic pathways is tested in many types of tumors. Thus, characterization of cancer cell metabolic setup is inevitable in order to target the correct pathway to improve the overall outcome of patients. Unfortunately, in a majority of cancers, the malignant cells are quite difficult to obtain in higher numbers and the tissue biopsy is required. Leukemia is an exception, where a sufficient number of leukemic cells can be isolated from the bone marrow. Here, we provide a detailed protocol for the isolation of leukemic cells from leukemia patients bone marrow and subsequent analysis of their metabolic state using extracellular flux analyzer. Leukemic cells are isolated by the density gradient, which does not affect their viability. The next cultivation step helps them to regenerate, thus the metabolic state measured is the state of cells in optimal conditions. This protocol allows achieving consistent, well-standardized results, which could be used for the personalized therapy.
The metabolic profile is one of the main characteristics of cells and altered bioenergetics are now considered one of the hallmarks of cancer1,2,3. Moreover, changes in the metabolic setup could be used in the treatment of cancer by targeting signal transduction pathways or enzymatic machinery of cancer cells4,5,6. Knowing the metabolic predisposition of cancer cells is thus an advantage and can help improve the current therapy.
There are a plenty of already established methods which can assess the metabolic activity of cells in culture. Regarding glycolysis, glucose uptake can be measured by the radioactive labeling, using 2-NBDG (2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose) or extracellular lactate levels measured enzymatically7,8. Fatty acid oxidation rate is another metabolic parameter measured by isotopically labeled palmitate9,10. Oxygen consumption rate is a method widely-used for determining mitochondrial activity in cells11,12, together with the mitochondrial membrane potential evaluation13,14, ATP/ADP (adenosine 5′-triphosphate/Adenosine 5′-diphosphate) ratio measurement15 or total intracellular ATP measurement16. Signaling pathways known to regulate metabolic processes could be determined by protein quantifications and can improve the understanding of metabolic measurements17,18,19.
However, all these methods measure only one or, in the best scenario, a few metabolic parameters in one sample simultaneously. Importantly, simultaneous measurement of the oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) can be achieved by the extracellular flux analysis by, for example, Seahorse XFp Analyzer. OCR is an indicator of mitochondrial respiration and ECAR is mainly the result of glycolysis (we cannot ignore CO2 production possibly elevating ECAR of cells with high oxidative phosphorylation activity)20. So far, various cell types have been studied using these analyzers21,22,23.
Here we describe the protocol for the extracellular flux analysis of primary blasts (leukemia cells derived from the immature hematopoietic stage) from leukemia patients. To the best of our knowledge, a specific protocol for primary blasts is not available yet.
All samples were obtained with the informed consent of the children's parents or guardians and approval of Ethical committee of Charles University in Prague, Czech Republic, the study no. NV15-28848A.
1. Preparation of Reagents
2. Isolation of Mononuclear Cells from Bone Marrow
NOTE: Ideally, measurement of metabolic state of primary leukemia cells should start immediately after bone marrow collection and cell isolation. Nevertheless, relevant data could be also obtained from cells isolated after transportation from other hematology centers in the Czech Republic. Perform all sub-steps in a sterile tissue culture hood.
3. Overnight Cultivation of Mononuclear Cells
NOTE: Perform all sub-steps in a sterile tissue culture hood.
4. Preparation of Cell Adhesive-coated Plates
5. Hydration of Sensor Cartridge
NOTE: Hydrate two 8-well extracellular flux analyzer cartridges.
6. Seeding Cells in Cell Adhesive-coated Plates
NOTE: For Glycolysis stress test, use Glycolysis stress test medium. For Cell Mito stress test, use Cell Mito stress test medium with BSA.
7. Loading the Sensor Cartridge
8. Setting Up the Program
9. Evaluation and Interpretation of the Results
Figure 3 shows the curves after Glycolysis stress test and Cell Mito stress test measurements of leukemic blasts from the BCP-ALL (B-cell precursor acute lymphoblastic leukemia) and AML (acute myeloid leukemia) patients. The calculation of metabolic parameters from these measurements is also indicated. 500,000 cells per well were seeded and all measurements were done in hexaplicates.
In the Glycolysis stress test, the only basal medium is used, so that the cells are deprived of nutrients. The first parameter obtained is the Basal acidification, which should reflect the amount of glucose stored in cells. After the first injection, ECAR is increased since cells utilize glucose and can ferment it to lactate. Oligomycin A in the second injection inhibits ATP-synthase and thus directs the cells to produce ATP mainly via glycolysis. This should cause further elevation of ECAR. Injection of 2-DG completely inhibits glycolysis and ECAR drops.
In the Cell Mito stress test, a medium supplemented with glutamine and glucose are used, so that the cells are not deprived of all nutrients and the Basal respiration parameter reflects their basal metabolic state. After first injection with Oligomycin A, cells inhibit mitochondrial respiration and switch to glycolysis which is represented as a decrease of OCR. FCCP (the second and third injection), on the other hand, uncouples ATP production from respiration, so that the cells now consume oxygen at a maximal rate and OCR rise to its highest value. The last injection of Rotenone and Antimycin A mixture completely inhibits mitochondrial respiration and OCR is decreased close to zero.
Figure 1: Density gradient centrifugation of the bone marrow sample. Mononuclear cells enriched for leukemic cells are separated by density gradient medium. Please click here to view a larger version of this figure.
Figure 2: Outline of Glycolysis stress test and Cell Mito stress test. (A) Exemplary result of Glycolysis stress test. (B) Exemplary result of Cell Mito stress test. Parameters are indicated within the curves. Please click here to view a larger version of this figure.
Figure 3: Extracellular flux analysis of leukemic blasts from BCP-ALL (A, B) and AML (B, C) patient. (A and C) Glycolysis stress test results. Please note that the first measurement point can significantly differ from the rest and should be excluded from the analysis in that case. (B and D) Cell Mito stress test results. Parameters are indicated within the curves. Please click here to view a larger version of this figure.
Port | Glycolysis stress test | Cell mito stress test | ||
Load to the port | Final concentration in the wells | Load to the port | Final concentration in the wells | |
A | 20 μL of 100 mM glucose | 10 mM glucose | 20 μL of 20 μM Oligomycin A | 2 μM Oligomycin A |
B | 22 μL of 20 μM Oligomycin A | 2 μM Oligomycin A | 22 μL of 15 μM FCCP | 1.5 μM FCCP |
C | 25 μL of 1 M 2-DG | 100 mM 2-DG | 25 μL of 30 μM FCCP | 4.5 μM FCCP |
D | X | 25 μL of 10 μM Rotenone and 10 μg/ml Antimycin A | 1 μM Rotenone and 1 μg/ml Antimycin A |
Table 1: Compound volumes.
Step | Settings |
Calibration | Automatic |
Equilibration | Automatic |
Baseline measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port A | Injection |
Measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port B | Injection |
Measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port C | Injection |
Measurement | Four times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Table 2: Program for Glycolysis stress test.
Step | Settings |
Calibration | Automatic |
Equilibration | Automatic |
Baseline measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port A | Injection |
Measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port B | Injection |
Measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port C | Injection |
Measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Injection of the port D | Injection |
Measurement | Three times: Mix – 3 min, Wait – 0 min, Measure – 3 min |
Table 3: Program for Cell Mito stress test.
The above-described protocol allows for the measurement of the metabolic activity assessed by OCR and ECAR values in primary leukemic blasts derived from patients with acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML). The advantage of measurement using an extracellular flux analyzer is that it enables the detection of metabolic profile in the real time in the live cells. Essentially, every step in the provided protocol could be adjusted depending on the cell type one plans to study. Here, we will discuss the most important parameters which could affect the results and could provide less than optimal values.
The first step towards optimization was a comparison of data obtained from fresh material vs frozen material. The ability to measure the metabolic activity from the frozen material would allow for retrospective studies of patients' samples stored in liquid nitrogen bank. In case of ALL samples, we were able to detect consistent metabolic activity only from the fresh material whereas AML cells were measured also after de-freezing with optimal results.
The second step towards optimization is the cultivation of primary leukemic blasts. We have tested the metabolic activity of the cells straight after the density gradient separation (without culturing) or after culturing overnight. Even if the cells after the density gradient separation looked viable and vital under a microscope, their metabolic activity was impaired. Overall ECAR and OCR values were lower and also, after injection, OCR or ECAR values did not respond optimally as they did in cultivated cells.
Cultivation under different conditions can also influence the results. Using insulin transferrin sodium selenite supplement (ITS) is considered a good practice when cultivating primary blasts8, but this supplement interferes with the metabolic activity of the cells. During Cell Mito stress test, leukemic blasts cultivated with ITS did not respond to Oligomycin A (OCR should decrease in order to calculate ATP-linked respiration). We also tried to co-cultivate the cells with mesenchymal stem cells (MSC), but in this case, OCR and ECAR values have been lower compared to the cells cultivated without MSCs. In summary, cultivating primary blasts from leukemia patients in RPMI medium with 10 % FBS is the best option.
Patients suitable for the characterization of their metabolic profile must meet certain criteria which on one hand limit the number of tested samples but on the other will yield relevant results. We measured the metabolic function of patients with high cellularity (for one measurement we seeded 500,000 cells/per wells in hexaplicate) and only samples with 80 and a higher percentage of leukemic blasts could be measured to avoid detection of unspecific metabolic activity of other cell types present in the suspension.
One of the crucial steps in data analysis is the normalization, so that metabolic parameters between different leukemic samples could be compared. According to our previous experiments performed with leukemic cell lines, we found that normalization to the number of the cells gives the best results. The specific number of cells per well needs to be determined by the researcher and depends on the size and metabolic activity of tested cells.
The authors have nothing to disclose.
We would like to thank the Czech Pediatric Hematology Centers. This work was supported by the Grant of Ministry of Health (NV15-28848A), by Ministry of Health of Czech Republic, University Hospital Motol, Prague, Czech Republic 00064203 and by Ministry of Education, Youth and Sports NPU I nr.LO1604.
RPMI 1640 Medium, GlutaMAX Supplement | Gibco, ThermoFisher Scientific | 61870-010 | |
Fetal Bovine Serum | Biosera | FB-1001/100 | |
Antibiotic-Antimycotic (100X) | Gibco, ThermoFisher Scientific | 15240-062 | |
Sodium bicarbonate | Sigma-Aldrich | S5761-500G | |
D-(+) Glucose | Sigma-Aldrich | G7021-100G | |
Oligomycin A | Sigma-Aldrich | 75351-5MG | |
2-Deoxy-D-glucose | Sigma-Aldrich | D8375-1G | |
FCCP | Sigma-Aldrich | C2920-10MG | |
DMSO | Sigma-Aldrich | D8418-100ML | |
Rotenone | Sigma-Aldrich | R8875-1G | |
Antimycin A from Streptomyces sp. | Sigma-Aldrich | A8674-25MG | |
Seahorse XF Base Medium, 100 mL | Agilent Technologies | 103193-100 | |
L-glutamine solution, 200 mM | Sigma-Aldrich | G7513-100ML | |
HEPES solution, 1 M, pH 7.0-7.6 | Sigma-Aldrich | H0887-100ML | |
Sodium pyruvate | Sigma-Aldrich | P5280-25G | |
Bovine Serum Albumin | Sigma-Aldrich | A2153-10G | |
Ficoll-Paque Plus | Sigma-Aldrich | GE17-1440-02 | Density gradient medium |
Seahorse XFp FluxPak | Agilent Technologies | 103022-100 | |
Corning™ Cell-Tak Cell and Tissue Adhesive | ThermoFisher Scientific | CB40240 | |
Seahorse Analyzer XFp | Agilent Technologies | S7802A | |
Seahorse XFp Cell Culture Miniplate | Agilent Technologies | 103025-100 |