Metabolic heterogeneity in DLBCL cells reveals an innovative antimetabolic combination strategy

doi:10.21203/rs.3.rs-5241406/v1

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Metabolic heterogeneity in DLBCL cells reveals an innovative antimetabolic combination strategy

https://doi.org/10.21203/rs.3.rs-5241406/v1

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Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma, characterized by aggressive and heterogeneous tumors originating from B-cells. Especially in patients with relapsed or refractory (R/R) disease, DLBCL remains a challenging cancer to treat. Metabolic reprogramming is a hallmark of malignant cells. Our research focuses on developing strategies to enhance the clinical outcomes for R/R DLBCL patients by targeting metabolic vulnerabilities. Here we report that the combination of metformin and L-asparaginase, two FDA-approved antimetabolic drugs, strongly sensitizes DLBCL cells to apoptosis, independently of their OxPhos or BCR/glycolytic status. The combination of metformin with L-asparaginase strongly impacts various metabolic liabilities, including glutaminolysis, lipid metabolism, TCA cycle and redox responses. In addition, this combination of antimetabolic drugs interferes with two critical pathways involved in cancer survival, namely the mTOR and MAPK oncogenic pathways. Most importantly, we obtained the proof of principle of the beneficial effect of the metformin and L-asparaginase combination in DLBCL patients. Taken together, our findings establish that combining metformin and L-asparaginase affects DLBCL cell survival by targeting multiple metabolic pathways and hence may represent a new approach for the treatment of R/R DLBCL patients.

*Leonardo Lordello, Stéphanie Nuan-Aliman, and Karoline Kielbassa-Elkadi are co-first authors.

Biological sciences/Cancer/Cancer metabolism

Biological sciences/Cancer/Haematological cancer/Lymphoma/Non-hodgkin lymphoma/B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma in adults^1,2. Even though cure rates have significantly improved since the introduction of anti-CD20 immunochemotherapy, refractory/relapsed (R/R) DLBCL patients reach up to 40%³. While cutting-edge immunotherapies by CAR-T cells have improved outcomes, around 60% of R/R DLBCL patients will not be cured with such therapy^4,5. DLBCL is a highly heterogeneous disease, and investigation of new therapeutic strategies is an urgent need to guide clinical practice.

Cancer cells exhibit bioenergetic alterations in order to meet their high-energy requirements, and deregulation of cellular energetics has been recognized as one of the hallmarks of cancer⁶. Therefore, cancer cell metabolism has opened up new avenues for cancer treatment. High glucose consumption through aerobic glycolysis is well known as the “Warburg effect”, but it is now realized that deregulated mitochondrial oxidative phosphorylation, amino acid, and lipid metabolism are also critical metabolic hallmarks^7–9. Therefore, the concept of combining molecular-targeted drugs with antimetabolic cooperativity has emerged.

Genetic and functional genomic studies have captured DLBCL heterogeneity and revealed oncogenic drivers in DLBCL^10–18. More recently, metabolic signatures have uncovered distinct metabolic DLBCL subsets, including the OxPhos DLBCL subset characterized by a non-functional BCR and increased mitochondrial metabolism¹⁹, along with the BCR subset that presents an up-regulation of genes encoding BCR signaling components and enzymes associated with glycolysis^19,20. Due to the emerging complexity of the metabolic landscape of DLBCL, and the high capability of cancer cells to reprogram their metabolism, one can hypothesize that the inhibition of multiple metabolic pathways using a combination of drugs is necessary for curative potential.

In the study presented here, we reveal that combining the two FDA-approved antimetabolic drugs, metformin and L-asparaginase, induces massive DLBCL cell apoptosis that was not seen upon treatment with each drug alone, both in OxPhos and BCR/glycolytic DLBCL cells. Furthermore, we uncovered that the combination of metformin and L-asparaginase induces multiple strong metabolic disturbances, including lipid metabolism, glutaminolysis, TCA cycle, and redox response. In addition, we show that mTOR and MAPK kinase pathways are targeted by this combination of antimetabolic drugs. Ultimately, we established in the clinic that the combination of metformin with L-asparaginase has a beneficial impact on R/R DLBCL patients. Altogether, our data highlight a previously unrecognized beneficial effect of combining metformin and L-asparaginase to induce DLBCL cell apoptosis, regardless of their cell of origin and metabolic classification, and provide the framework for the use of these two drugs together to overcome resistance in R/R DLBCL patients.

Human DLBCL cell lines and culture conditions

MD-901, OCI-LY19, and SU-DHL4 DLBCL cell lines were obtained from José Angel Martinez-Climent (Centro de Investigación Médica Aplicada, Pamplona, Spain). Cells were grown in RPMI-1640 GlutaMAX medium (Gibco) supplemented with 10% heat-inactivated fetal bovine serum (FBS) (Hyclone), 100 U/mL penicillin, and 100 µg/mL streptomycin (Gibco) at 37°C with 5% CO2.

For glutamine or glucose deprivation experiments, DLBCL cells were grown in RPMI-1640 medium supplemented as above without either glutamine or glucose.

Antibodies and reagents

Metformin (PHR1084) and 2-deoxy-D-glucose (2-DG, D8375) were purchased from Merck (Darmstadt, Germany), and L-asparaginase (®Kidrolase) was a kind gift from Isabelle Madelaine-Chambrin and Nathalie Jourdan (Service de Pharmacie Centrale Hôpital Saint-Louis). The antibodies were purchased from Santa Cruz Biotechnology (p70 S6 kinase sc-8418; 4EBP1 sc-9977; p38alpha/beta MAPK sc-7972; ERK1/2 sc-514302; β-actin sc-47798; GAPDH sc-32233), Cell Signaling Technology (Phospho-p70 S6 kinase (Thr389) #9234; Phospho-4E-BP1 (Ser65) #9451; Phospho-p38 MAPK (Thr180/Tyr182) #4511; Phospho-p44/42 MAPK (Erk1/2) (Thr202/Tyr204) #4370; 4EBP1 #9452), and Merck (β-actin, A5441).

Measurement of intracellular ATP content

Intracellular ATP content was measured using an ATP luminescence detection kit (CellTiter-Glo® Luminescent Cell Viability Assay, Promega, Madison, WI, USA) according to the manufacturer's instructions. Briefly, 4 x 10⁵ cells were seeded in 100 µL of complete medium. Cells were treated for 1 h with or without 20 mM 2-deoxy-D-glucose (2-DG) at 37°C followed by 30 min at room temperature to inhibit glycolysis. At the end of the incubation time, 100 µL of CellTiter-Glo solution was added, and cells were incubated for 10 min at room temperature. The luminescence signal (relative luminescence units (RLU)) was recorded with a microplate reader (Centro LB 960 microplate luminometer, Berthold Technologies, Bad Wildbach, Germany). The difference between total ATP content and ATP produced under 2-DG treatment results in glycolytic ATP.

Apoptosis Assays

DLBCL cells were harvested and washed twice with cold PBS. Cells were resuspended in 1X binding buffer containing Annexin V/PE (BD Biosciences Pharmingen, San Diego, CA, USA) and 4’,6-diamidino-2-phenylindole (DAPI, Molecular Probes, Life Technologies, Carlsbad, CA, USA) for 15 min at room temperature. The samples were then subjected to cytometric analysis with a MACSQuant Analyzer 10 Flow Cytometer (Miltenyi Biotec, Bergisch Gladbach, Germany), and the data were analyzed using the Flowjo v10.2 software (Ashland, OR, USA).

Measurement of Mitochondrial Transmembrane Potential

For the determination of mitochondrial transmembrane potential (ΔΨm), cells were stained with 100 nM of tetramethylrhodamine, methyl ester (TMRM) (Molecular Probes, Life Technologies, Carlsbad, CA, USA) in RPMI-1640 GlutaMAX medium for 30 min at room temperature. Cells were evaluated by cytometric analysis as above.

Cell viability assay

Cell viability was assessed using trypan blue dye exclusion.

Immunoblotting

Immunoblots were performed as previously described²¹.

NMR-based metabolomics

Exponentially growing DLBCL cells were seeded at a density of 2x10⁵-2,5x10⁵/ml in a total volume of 25 ml in 75 cm2 flasks at the time of treatment with antimetabolic drugs (total 5x10⁶ cells/condition) and harvested 24 h later. Decaplicates of either extracellular medium or dry cell pellet samples were prepared for each condition: Extracellular media were added to the deuterated buffer with 3.57 mM of trimethylsilylpropanoic acid (TSP) concentration to obtain a final concentration of 1 mM of the TSP sample in the NMR tube, following standard protocols²². Dry cell pellets were treated with 400 µL of ice-cold methanol and 65 µL of ice-cold water. A volume of 200 µL of ice-cold chloroform, then 200 µL of ice-cold water and finally 200 µL of ice-cold chloroform were further added. The samples were then left on ice for 15 min, and centrifugated at 2000 rpm for 15 min. The upper methanol/water phase (containing polar metabolites) and the lower chloroform phase (containing lipophilic compounds), were transferred into separate glass vials. Solvents were removed under a stream of nitrogen for 30 min. The water phases were put in the freeze dryer one night. The dry water phase samples were resuspended in 580 µL of NMR buffer (100 mM sodium phosphate buffer pH 7.4, in D₂O, with 3.57 mM TSP and 6 mM NaN₃) to obtain the polar phase extract. The lipophilic phases were resuspended in 600 µL of deuterated NMR solvent (2:1 mixture of pure CDCl₃ and CDCl₃ containing 0.03% of TMS, to obtain a final solution of 0.01% of TMS) and then vortexed. After centrifugation (5 min), 580 µL of the supernatant was directly transferred into an NMR tube to prepare the organic phase extract.

All samples were measured on a 500 MHz Bruker Avance III spectrometer equipped with a SampleXpress automation sample changer and a cryogenic 5 mm ¹³C/¹H dual probe with Z-gradient. The exometabolome sample spectra were acquired using a classical 1D ¹H experiment used for the metabolomics analysis of biofluids by NMR (1D-NOESY pulse sequence with presaturation for water suppression). The endometabolome samples were acquired using the classical experiment used for the metabolomic analysis of tissue extracts by NMR (1D-CPMG pulse sequence with presaturation for water suppression)²². The operating software was TopSpin 3.1 1 (Bruker BioSpin, France).

Metabolite Identification. For each NMR spectrum, the standard processing protocol was applied, including Fourier transform, phase correction, baseline correction, and calibration. Spectra were aligned to a reference signal using TSP as a chemical shift standard (0.016 ppm). For metabolite identification, ¹H NMR spectra were analyzed using Chenomx NMR Suite 8.0 (Chenomx Inc.). Metabolite identification was performed using the spectral reference library and fitting peak intensity and location to the observed signals.

Statistical Analysis. The processing of raw data was carried out using NMRProcflow, including baseline correction, chemical shift calibration, data alignment, and variable-sized bucketing²³. For all datasets, a threshold corresponding to a signal-to-noise ratio of 3 was applied. For normalization, we chose to calculate for each sample the intensity variation between the spectrum of this sample and the reference spectrum recorded on the growing medium (RPMI-1640 left under the same experimental conditions as the sample). In the second step, we normalized this intensity variation with the integration of the number of cells over the duration of the treatment. Subsequently, we used SIMCA 15 software (Umetrics) to perform principal component analysis (PCA) or orthogonal projections to latent structure discriminant analysis (OPLSDA) in order to discriminate cancer cell line classes. Pareto scaling was used in both analyses. MetaboAnalyst 6.0²⁴ was used to perform t-tests and determine p-values with FDR correction and to generate box plots (https://www.metaboanalyst.ca/).

Antimetabolic therapy

Three patients followed at the Hôpital Saint-Louis, with a confirmed diagnosis of R/R DLBCL, were treated after consent with an optimized antimetabolic drug combination, including the sequential administration of L-asparaginase and metformin followed by temsirolimus, based on our previous work and our novel preclinical data included in the present study²⁵. This combination was discussed and approved on June 26, 2018, by the scientific committee of the Lymphoma Study Association (LYSA). Treatment consisted of L-asparaginase (K, ®Kidrolase, Jazz Pharmaceuticals, 10 000 UI/m²) over 60 min on days 1, 3, 5, 7, 9, 11, and 13, metformin (M, Mylan, 1000 mg/day) once a day continuously from day 1 to day 14, and temsirolimus (T, ® Torisel, Pfizer, 75 mg/week) administered on day 1 of week 3 and week 4. Response assessment was scheduled at month 1 and month 3 based on Lugano criteria²⁶.

Tissue processing and hematoxylin and eosin staining of DLBCL patient biopsies

Core biopsies obtained from patients with DLBCL were fixed in buffered formalin for 24 h and then transferred to 70% ethanol for 6 h. Subsequently, tissues were dehydrated using increasing concentrations of ethanol (70%, 95%, 100%) in an automated processor (Logos One, Microm France), followed by a final incubation in isopropanol. After dehydration, tissues were impregnated with paraffin and embedded using a tissue embedding system (Tissue tek), followed by sectioning on a microtome (Autosection, Sakura) with a thickness of 4µm. Slides were stained with hematoxylin and eosin at the department of Anatomic Pathology at Hospital Saint Louis, Paris, France, following standard protocols.

Statistics

Statistical significance was assessed using unpaired t-test (Prism 8.0, GraphPad Software, San Diego, CA, USA). A p-value of < 0.05 was considered statistically significant, with the following degrees: * p < 0.05; ** p < 0.01; *** p < 0.001; **** p < 0.0001.

Combining metformin and L-asparaginase strongly enhances apoptosis in DLBCL cell lines irrespective of their OxPhos or BCR/glycolytic subtypes

To explore the optimal treatment strategy to target metabolism in DLBCL cells, we evaluated the impact of combining metformin and L-asparaginase, two FDA-approved antimetabolic drugs, on DLBCL cell survival. Using a quantitative measure of apoptosis, we tested each drug individually and in combination. In two GCB models (OCI-LY19 and SU-DHL4) and one ABC model (MD-901), combining metformin and L-asparaginase markedly increased apoptosis compared to each individual drug (Fig. 1A). Thus, while individual DLBCL models respond differentially to metformin and L-asparaginase, the combination of the two drugs overcame this functional heterogeneity. This effect was associated with greater loss of mitochondrial transmembrane potential (ΔΨm) (Fig. 1B), along with higher levels of caspase 3 and poly(ADP-ribose) polymerase 1 (PARP1) cleavage (Fig. 1C,D and Supplemental Material). Moreover, metformin and L-asparaginase co-treated cells exhibited a higher level of the DNA-damage marker γH2AX (Fig. 1E and Supplemental Material).

The metabolic status of DLBCL cell lines has been reported to play an important role in drug response²⁷. Therefore, we compared the level of glycolytic ATP among the three DLBCL cell lines. The two OxPhos OCI-LY19 and MD-901 DLBCL cell lines presented only a low level of glycolytic ATP (25% and 30%, respectively) as compared to what was seen with the BCR SU-DHL4 DLBCL cell line (~ 55%) (Fig. 1F). This observation is fully in line with their reported sensitivity to the SYK inhibitor R406 that only induces apoptosis in DLBCL cell lines having an active BCR signaling, whereas OxPhos DLBCLs that do not display functional BCR signaling are insensitive to this inhibitor^28,29.

Altogether, these data indicate that combining metformin and L-asparaginase induces stronger DNA damage and subsequent apoptosis of DLBCL cells, independently of their GCB, ABC, BCR/glycolytic, and OxPhos subtypes.

Metabolic alteration landscape of metformin and L-asparaginase combination in DLBCL cells

Using an untargeted NMR-based metabolomics approach, we monitored the metabolic changes occurring in the three DLBCL cell models (two OxPhos and one BCR/glycolytic, see above Fig. 1F) following treatment with metformin, L-asparaginase, and their combination for 24 h. Treatment of all three DLBCL cell lines with the E.coli L-asparaginase led to a massive depletion not only of asparagine but also of glutamine in the extracellular medium that paralleled the increased levels of aspartate and glutamate, respectively (Fig. 2A). These observations indicate that in DLBCL cells, E. coli L-asparaginase exerts strong dual asparaginase and glutaminase activities. Most importantly, both glutamine and glutamate were massively depleted from the intracellular medium, indicating that the E. coli L-asparaginase strongly impacts glutaminolysis in DLBCL cells (Fig. 2B).

To probe the prosurvival benefit of glutamine in DLBCL cells, we then assessed how glutamine depletion impacts DLBCL cell survival. Remarkably, glutamine deprivation was accompanied by significant DLBCL cell death, in both OxPhos and BCR/glycolytic subtypes (Fig. 2C). Notably, treatment of DLBCL cells with the E. coli L-asparaginase in the absence of glutamine led to a more pronounced DLBCL cell death compared to what was seen upon glutamine deprivation alone (Fig. 2D), suggesting that L-asparaginase treatment targets DLBCL cell survival via additional metabolic pathways (see § below).

Glutamine is metabolized through glutaminolysis to produce glutamate and α-ketoglutarate, with the latter being used to replenish the tricarboxylic acid (TCA) cycle^7,30. While limited TCA intermediates could be detected by ¹H NMR spectroscopy, a significant decrease in fumarate was seen upon L-asparaginase treatment (Fig. 2E). Most importantly, co-treatment of L-asparaginase with metformin led to a more pronounced decrease in fumarate as compared to what was seen upon treatment with either L-asparaginase or metformin alone (Fig. 2E), indicating that combining metformin with L-asparaginase more strongly impacts the TCA cycle compared to each drug alone. In line, a marked reduction of GSH, a critical antioxidant linked to OxPhos DLBCL cell survival²⁰, was observed upon co-treatment with metformin and L-asparaginase in the two OxPhos DLBCL cell lines (Fig. 2E).

Finally, since lipid metabolism has emerged as critical for cancer cell survival, we also explored the impact of combining metformin and L-asparaginase on lipid levels, analyzing the DLBCL cellular organic phase by ¹H NMR. A massive decrease in phospholipids, total cholesterol, and glycerophosphocholine levels was observed only when metformin and L-asparaginase were combined (Fig. 2F), thus again illustrating the broader metabolic impact of combining these two FDA-approved antimetabolic drugs.

Altogether, these observations indicate that combining metformin with L-asparaginase is beneficial to strongly impact glutaminolysis, lipid metabolism, TCA cycle, and redox responses in DLBCL cells (Fig. 2G).

Combination of metformin and L-asparaginase strongly inhibits glycolysis

Both increased glucose uptake and glycolysis pathway that converts glucose into lactate under aerobic conditions (also known as the “Warburg effect”) have been reported in DLBCL cells³¹. To better understand the beneficial effect of combining metformin and L-asparaginase on DLBCL cells, we thus evaluated by ¹H NMR how each drug alone or in combination impacts glycolysis by measuring glucose and lactate levels. Metformin treatment resulted in decreased glucose and increased lactate levels in the extracellular medium, what could be expected for an anti-diabetic drug (Fig. 3A). In contrast, surprisingly, L-asparaginase inhibited glycolysis as indicated by a marked increase in glucose and a decrease in lactate levels in the extracellular medium (Fig. 3A). Importantly, combining L-asparaginase with metformin nullifies the pro-glycolytic effect of metformin treatment alone, highlighting the beneficial antimetabolic effect of the combination of metformin with L-asparaginase (Fig. 3A).

Glucose depletion sensitized all three DLBCL cell models (two OxPhos and one glycolytic) to the cytotoxic effect of metformin (Fig. 3B), indicating that metformin-induced glycolysis provides a survival signal to DLBCL cells. Most importantly, the combination of L-asparaginase with metformin counteracted the glucose-dependent pro-survival effect of metformin treatment alone (Fig. 3B, C).

Collectively, our findings demonstrate that combining metformin with L-asparaginase enhances their pro-apoptotic efficacy on DLBCL cells, both OxPhos and glycolytic, by cooperatively targeting multiple metabolic pathways (Figs. 2G and 3D).

Metformin cooperates with L-asparaginase to modulate mTOR and MAPK signaling pathways

Since the combination of metformin with L-asparaginase induces massive DLBCL cell apoptosis, and is deleterious to a variety of pro-survival metabolic pathways, including glutamine metabolism, lipid metabolism, and mitochondrial activity, we next investigated how these two anti-metabolic drugs impacted critical oncogenic pathways involved in metabolic stress response and survival. The mammalian target of rapamycin complex 1 (mTORC1) is a central actor in the control of energy homeostasis and cell survival ³². Metformin and L-asparaginase together markedly decreased mTORC1 activity, as evidenced by reduced phosphorylation of p70-S6K on threonine 389 and 4EBP1 on serine 65 (Fig. 4A and Supplemental Material). Interestingly, the combination of metformin and L-asparaginase impacts mTORC1 in the two OxPhos DLBCL cell lines (MD-901 and OCI-LY19) and the glycolytic one (SU-DHL4).

To further elucidate mechanisms underlying the action of metformin and L-asparaginase, we also investigated the impact of the two anti-metabolic drugs on p38 and ERK MAP kinases that play a critical role in cell survival upon various stress conditions and are also involved in regulating cellular metabolism³³. Treatment with L-asparaginase and metformin strongly increased p38 activity, as was seen by increased phosphorylation on threonine 180 and tyrosine 182, whereas it had no or little effect on ERK activity (Fig. 4B and Supplemental Material).

Combination of metformin and L-asparaginase has a clinical benefit in refractory/relapsed DLBCL patients

Since currently available mouse models do not fully recapitulate human DLBCL disease and lack key features of human DLBCL (such as markers of mature B cells), it was important to validate the benefit of combining metformin and L-asparaginase in human DLBCL patients. Therefore, we set up a combined antimetabolic therapy as described in Fig. 5A. The combination was not administered longer than 14 days to limit L-asparaginase toxicities. Thus, in the last two weeks of each antimetabolic treatment cycle, patients received temsirolimus (Torisel) that targets mTOR, a pathway that was impacted by the combination of L-asparaginase and metformin (Fig. 4A). The three treated patients were refractory to R-CHOP and immunotherapy, including CAR-T cell therapy, for one patient. All three patients exhibited reduced serum levels of glucose and glutamine and increased serum levels of glutamate four hours after the administration of metformin and L-asparaginase (Fig. 5B). Notably, one patient showed apoptosis in about 50% of the core tumor biopsy that was performed 24 hours post-administration of metformin and L-asparaginase (Fig. 5C). This patient had a 69% reduction of total metabolic tumor volume (TMTV) at positron emission tomography (PET) scan analysis after 56 days of treatment (Fig. 5D). This patient completed two cycles, which led to the extension of the treatment for a total of 121 days (Fig. 5E) with a duration of response of 68 days. Altogether, although a small number of patients were treated, these data established the proof of principle that patients refractory to immunochemotherapy or cell immunotherapy, such as CAR-T cells, can benefit out of an optimized anti-metabolic targeting strategy.

Reprogramming of cancer cell metabolism is now recognized as a hallmark of cancer⁶. Furthermore, cancer cells have a high capacity to adapt their metabolism to their environmental conditions⁹. Thus, one interesting therapeutic strategy in cancer could be the combination of antimetabolic drugs able to create an antimetabolic cooperativity to promote cell death³⁴. In the study presented here, we conducted the first comprehensive analysis of how the combination of the two FDA-approved drugs, metformin and L-asparaginase, impacts on DLBCL cell metabolism and survival, both in cellulo and in vivo. Remarkably, we found that the combination of metformin with L-asparaginase induces a much broader spectrum of metabolic disturbances than that observed with each drug alone. First, we have shown that combining L-asparaginase with metformin strongly impacts lipid metabolism. Second, L-asparaginase is able to nullify the pro-glycolytic effect of metformin, with the combination of the two leading to a massive decrease in glycolysis. Third, L-asparaginase in the presence of metformin optimally reduces glutaminolysis. Fourth, the TCA cycle and antioxidant response are strongly impacted by the combination of L-asparaginase and metformin. Fifth, the combination of L-asparaginase with metformin impacts the mTORC1 and MAPK pathways. The impact of treatment with metformin and L-asparaginase on levels of phospholipids, cholesterol, and fatty acids was somewhat unexpected, even though metformin alone is known to affect lipid metabolism³⁵. Nonetheless, it is of great importance since lipid metabolism is one of the most altered metabolic pathway in multiple cancer types^8,36. Further, recent studies have implicated fatty acid metabolism as a major energetic source in aggressive B-cell lymphoma, including DLBCL^20,37–39. Still, the exact molecular mechanisms underlying these metabolic alterations and their relation to the inferior clinical outcome of patients have remained largely elusive, which is worth further investigation.

We demonstrated that the combination of metformin with L-asparaginase triggers massive DLBCL cell apoptosis and DNA damage as compared to what was seen with each antimetabolic drug alone. The beneficial combinatory effect was seen in both OxPhos and BCR/glycolytic DLBCL cell lines, thus highlighting the benefit of inducing a wide spectrum of metabolic disturbances to promote DLBCL cell apoptosis. Importantly, massive induction of apoptosis was also seen in DLBCL patient tumor biopsies after the co-administration of L-asparaginase with metformin. Recently, mechanisms of compensatory energy acquisition pathways in glycolysis-suppressed DLBCL cells have been explored. Silencing of Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), a critical enzyme regulating glycolysis, in Eµ-Myc-GAPDH^high cells isolated from mouse primary B lymphomas (used as a model of aggressive non-Hodgkin B cell lymphomas) led to a metabolic switch towards glutamine and OxPhos metabolism. Conversely, overexpression of GAPDH in Eµ-Myc-GAPDH^low cells was sufficient to induce a metabolic switch towards glycolysis²⁵. Moreover, the GAPDH-dependent metabolic reprogramming strongly limited the capacity of either phenformin or L-asparaginase to induce apoptosis of Eµ-Myc murine lymphoma cells²⁵. Therefore, these observations are fully consistent with our study that reveals that targeting various metabolic pathways is required for optimal induction of DLBCL cell death in OxPhos and BCR/glycolytic human DLBCL cells.

Altogether, our data point to metformin and L-asparaginase as a promising combinatory strategy to induce massive DLBCL cell apoptosis. Our study reinforces the concept that combining antimetabolic drugs will be necessary to avoid cancer cell resistance through energy metabolism reprogramming and ensure a long-term anticancer response.

Many clinical trials using individual metabolic inhibitors have failed to improve the outcome of DLBCL patients^40–47. This is likely not due to poor efficacy of the drug, but rather to the ability of cancer cells to find a metabolic path to reprogram and bypass the targeted metabolic pathway. The use of metformin led to inconclusive results regarding its beneficial impact on DLBCL patient outcome^44–47. L-asparaginase alone was not evaluated in DLBCL patients. A previous study revealed a beneficial impact of administering L-asparaginase combined with an mTOR inhibitor, Temserolimus, followed by the administration of metformin in four R/R DLBCL patients exhibiting an OxPhos profiles (GAPDH^low)²⁵. In our combined antimetabolic therapy, the sequence of administration was optimized based on our preclinical study with L-asparaginase being co-administered with metformin, followed by the administration of the mTOR inhibitor. Remarkably, one of the patients presented a 69% reduction of TMTV after two cycles of treatment, even though this patient was R/R to nine prior lines of treatment, including CAR-T cells. Our data indicate that administering an optimized combination of antimetabolic drugs based on a deeper understanding of DLBCL cell metabolism may open new avenues for R/R DLBCL patients.

In summary, we established that combining metformin with L-asparaginase induces a large spectrum of metabolic disturbances, including lipid, glutamine and mitochondrial metabolism as well as glycolysis. Further, it induces massive DLBCL cell apoptosis both in vitro and in vivo in DLBCL patients. Our data are of great functional importance because they constitute a significant advance in understanding the metabolic vulnerabilities of DLBCL cells. It provides a strong rationale for combinatory therapeutic interventions that include optimized combinations of antimetabolic drugs in R/R DLBCL patients.

Acknowledgments

The authors thank the Centre d’Imagerie Cellulaire et de Cytométrie, Centre de Recherche des Cordeliers UMRS 1138, Paris for FACS analysis.

This work was supported by grants from Fondation Nelia et Amadeo Barletta, Switzerland, the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement no. 766214, Institut National du Cancer, Fondation ARC pour la Recherche sur le Cancer, 12 Rounds contre le Cancer, the integrated cancer research center "SiRIC InsiTu : Insights into cancer: From inflammation to tumor" (grant number INCa-DGOS-INSERM-ITMO Cancer_18008), INSERM, and Université Paris Cité (to V.B.), and doctoral fundings from Fondation Nelia et Amadeo Barletta, Switzerland (S.N.-A. and A.M.), the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement no. 766214, Universitée Paris Cité (L.L.), and Société Française d’Hématologie (A.M.). J.A.M.-C. is supported by Instituto de Salud Carlos III–FIS–CIBERONC (CB16/12/00489) and Arnal Planelles Foundation. GK is supported by the Ligue contre le Cancer (équipe labellisée); Agence Nationale de la Recherche (ANR-22-CE14-0066 VIVORUSH, ANR-23-CE44-0030 COPPERMAC, ANR-23-R4HC-0006 Ener-LIGHT); Association pour la recherche sur le cancer (ARC); Cancéropôle Ile-de-France; Fondation pour la Recherche Médicale (FRM); a donation by Elior; European Joint Programme on Rare Diseases (EJPRD) Wilsonmed; European Research Council Advanced Investigator Award (ERC-2021-ADG, Grant No. 101052444; project acronym: ICD-Cancer, project title: Immunogenic cell death (ICD) in the cancer-immune dialogue); The ERA4 Health Cardinoff Grant Ener-LIGHT; European Union Horizon 2020 research and innovation programmes Oncobiome (grant agreement number: 825410, Project Acronym: ONCOBIOME, Project title: Gut OncoMicrobiome Signatures [GOMS] associated with cancer incidence, prognosis and prediction of treatment response, Prevalung (grant agreement number 101095604, Project Acronym: PREVALUNG EU, project title: Biomarkers affecting the transition from cardiovascular disease to lung cancer: towards stratified interception), Neutrocure (grant agreement number 861878 : Project Acronym: Neutrocure ; project title: Development of “smart” amplifiers of reactive oxygen species specific to aberrant polymorphonuclear neutrophils for treatment of inflammatory and autoimmune diseases, cancer and myeloablation); National support managed by the Agence Nationale de la Recherche under the France 2030 programme (reference number 21-ESRE-0028, ESR/Equipex+ Onco-Pheno-Screen); Hevolution Network on Senescence in Aging (reference HF-E Einstein Network); Institut National du Cancer (INCa); Institut Universitaire de France; LabEx Immuno-Oncology ANR-18-IDEX-0001; a Cancer Research ASPIRE Award from the Mark Foundation; PAIR-Obésité INCa_1873, the RHUs Immunolife and LUCA-pi (ANR-21-RHUS-0017 and ANR-23-RHUS-0010, both dedicated to France Relance 2030); Seerave Foundation; SIRIC Cancer Research and Personalized Medicine (CARPEM, SIRIC CARPEM INCa-DGOS-Inserm-ITMO Cancer_18006 supported by Institut National du Cancer, Ministère des Solidarités et de la Santé and INSERM). This study contributes to the IdEx Université de Paris Cité ANR-18-IDEX-0001. Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union, the European Research Council or any other granting authority. Neither the European Union nor any other granting authority can be held responsible for them.

Authorship

Contribution: V.B.: conceptualization, methodology, supervision, project administration; L.L., S.N.-A., K.K.E, A.M., K.K., I.M., E.P., C.C., J. L-C., V.M., G.B: investigation; V.B., L.L, S.N-A.,K.K.E, A.M., K.K., I.M., G.B., C.C.: formal analysis; J.A.M.-C., J.L.-C., C.T., N.G., G.K.: ressources (reagents, materials, patients and analysis tools); V.B., L.L.: writing; S.N.-A., K. K.-E.: visualization; K.K.-E., A.M., C.T. G.K., critical reading of the manuscript.

Conflict-of-interest disclosure

J.A.M.-C. declares research funding (unrelated to the present work) from Roche/Genentech, Jannsen, AstraZeneca, Regeneron, Palleon, Priothera and K36-Therapeutics; and holds stock options, patents rights, and royalties in MIMO Biosciences. IM is a consultant for Osasuna Therapeutics. GK has been holding research contracts with Daiichi Sankyo, Eleor, Kaleido, Lytix Pharma, PharmaMar, Osasuna Therapeutics, Samsara Therapeutics, Sanofi, Sutro, Tollys, and Vascage. GK is on the Board of Directors of the Bristol Myers Squibb Foundation France. GK is a scientific co-founder of everImmune, Osasuna Therapeutics, Samsara Therapeutics and Therafast Bio. GK is in the scientific advisory boards of Hevolution, Institut Servier, Longevity Vision Funds and Rejuveron Life Sciences. GK is the inventor of patents covering therapeutic targeting of aging, cancer, cystic fibrosis and metabolic disorders. GK’s wife, Laurence Zitvogel, has held research contracts with Glaxo Smyth Kline, Incyte, Lytix, Kaleido, Innovate Pharma, Daiichi Sankyo, Pilege, Merus, Transgene, 9 m, Tusk and Roche, was on the on the Board of Directors of Transgene, is a cofounder of everImmune, and holds patents covering the treatment of cancer and the therapeutic manipulation of the microbiota. GK’s brother, Romano Kroemer, was an employee of Sanofi and now consults for Boehringer-Ingelheim. The funders had no role in the design of the study; in the writing of the manuscript, or in the decision to publish the results. The other authors declare no competing financial interests.

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Metabolic heterogeneity in DLBCL cells reveals an innovative antimetabolic combination strategy

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Abstract

Figures

INTRODUCTION

METHODS

Human DLBCL cell lines and culture conditions

Antibodies and reagents

Measurement of intracellular ATP content

Apoptosis Assays

Measurement of Mitochondrial Transmembrane Potential

Cell viability assay

Immunoblotting

NMR-based metabolomics

Antimetabolic therapy

Tissue processing and hematoxylin and eosin staining of DLBCL patient biopsies

Statistics

RESULTS

Metabolic alteration landscape of metformin and L-asparaginase combination in DLBCL cells

Combination of metformin and L-asparaginase strongly inhibits glycolysis

Metformin cooperates with L-asparaginase to modulate mTOR and MAPK signaling pathways

Combination of metformin and L-asparaginase has a clinical benefit in refractory/relapsed DLBCL patients

DISCUSSION

Declarations

References

Additional Declarations

Supplementary Files

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