Development of an explainable AI system using routine clinical parameters for rapid differentiation of inflammatory conditions.

Introduction: Inflammatory conditions in patients have various causes and require different treatments. Bacterial infections are treated with antibiotics, while these medications are ineffective against viral infections. Autoimmune diseases and graft-versus-host disease (GVHD) after allogeneic stem cell transplantation, require immunosuppressive therapies such as glucocorticoids, which may be contraindicated in other inflammatory states. In this study, we employ a combination of straightforward blood tests to devise an explainable artificial intelligence (XAI) for distinguishing between bacterial infections, viral infections, and autoimmune diseases/graft-versus-host disease. Patients and methods: We analysed peripheral blood from 80 patients with inflammatory conditions and 38 controls. Complete blood count, CRP analysis, and a rapid flow cytometric test for myeloid activation markers CD169, CD64, and HLA-DR were utilized. A two-step XAI distinguished firstly with C5.0 rules pruned by ABC analysis between controls and inflammatory conditions and secondly between the types of inflammatory conditions with a new bivariate decision tree using the Simpson impurity function. Results: Inflammatory conditions were distinguished using an XAI, achieving an overall accuracy of 81.0% (95%CI 72 - 87%). Bacterial infection (N = 30), viral infection (N = 26), and autoimmune diseases/GVHD (N = 24) were differentiated with accuracies of 90.3%, 80.0%, and 79.0%, respectively. The most critical parameter for distinguishing between controls and inflammatory conditions was the expression of CD64 on neutrophils. Monocyte count and expression of CD169 were most crucial for the classification within the inflammatory conditions. Conclusion: Treatment decisions for inflammatory conditions can be effectively guided by XAI rules, straightforward to implement and based on promptly acquired blood parameters.

Prediction of Clinical Outcomes with Explainable Artificial Intelligence in Patients with Chronic Lymphocytic Leukemia.

BACKGROUND: The International Prognostic Index (IPI) is applied to predict the outcome of chronic lymphocytic leukemia (CLL) with five prognostic factors, including genetic analysis. We investigated whether multiparameter flow cytometry (MPFC) data of CLL samples could predict the outcome by methods of explainable artificial intelligence (XAI). Further, XAI should explain the results based on distinctive cell populations in MPFC dot plots. METHODS: We analyzed MPFC data from the peripheral blood of 157 patients with CLL. The ALPODS XAI algorithm was used to identify cell populations that were predictive of inferior outcomes (death, failure of first-line treatment). The diagnostic ability of each XAI population was evaluated with receiver operating characteristic (ROC) curves. RESULTS: ALPODS defined 17 populations with higher ability than the CLL-IPI to classify clinical outcomes (ROC: area under curve (AUC) 0.95 vs. 0.78). The best single classifier was an XAI population consisting of CD4+ T cells (AUC 0.78; 95% CI 0.70-0.86; p < 0.0001). Patients with low CD4+ T cells had an inferior outcome. The addition of the CD4+ T-cell population enhanced the predictive ability of the CLL-IPI (AUC 0.83; 95% CI 0.77-0.90; p < 0.0001). CONCLUSIONS: The ALPODS XAI algorithm detected highly predictive cell populations in CLL that may be able to refine conventional prognostic scores such as IPI.

Identification of critical hemodilution by artificial intelligence in bone marrow assessed for minimal residual disease analysis in acute myeloid leukemia: The Cinderella method.

Minimal residual disease (MRD) detection is a strong predictor for survival and relapse in acute myeloid leukemia (AML). MRD can be either determined by molecular assessment strategies or via multiparameter flow cytometry. The degree of bone marrow (BM) dilution with peripheral blood (PB) increases with aspiration volume causing consecutive underestimation of the residual AML blast amount. In order to prevent false-negative MRD results, we developed Cinderella, a simple automated method for one-tube simultaneous measurement of hemodilution in BM samples and MRD level. The explainable artificial intelligence (XAI) Cinderella was trained and validated with the digital raw data of a flow cytometric "8-color" AML-MRD antibody panel in 126 BM and 23 PB samples from 35 patients. Cinderella predicted PB dilution with high accordance compared to the results of the Holdrinet formula (Pearson's correlation coefficient r = 0.94, R2  = 0.89, p < 0.001). Unlike conventional neuronal networks Cinderella calculated the distributions of 12 different cell populations that were assigned to true hematopoietic counterparts as a human in the loop (HIL) approach. Besides characteristic BM cells such as myelocytes and myeloid progenitor cells the XAI identified discriminating populations, which were not specific for BM or PB (e.g., T cell/NK cell subpopulations and CD45 negative cells) and considered their frequency differences. Thus, Cinderella represents a HIL-XAI algorithm capable to calculate the degree of hemodilution in BM samples with an AML MRD immunophenotype panel. It is explicable, transparent, and paves a simple way to prevent false negative MRD reports.

A Bioinformatics View on Acute Myeloid Leukemia Surface Molecules by Combined Bayesian and ABC Analysis.

"Big omics data" provoke the challenge of extracting meaningful information with clinical benefit. Here, we propose a two-step approach, an initial unsupervised inspection of the structure of the high dimensional data followed by supervised analysis of gene expression levels, to reconstruct the surface patterns on different subtypes of acute myeloid leukemia (AML). First, Bayesian methodology was used, focusing on surface molecules encoded by cluster of differentiation (CD) genes to assess whether AML is a homogeneous group or segregates into clusters. Gene expressions of 390 patient samples measured using microarray technology and 150 samples measured via RNA-Seq were compared. Beyond acute promyelocytic leukemia (APL), a well-known AML subentity, the remaining AML samples were separated into two distinct subgroups. Next, we investigated which CD molecules would best distinguish each AML subgroup against APL, and validated discriminative molecules of both datasets by searching the scientific literature. Surprisingly, a comparison of both omics analyses revealed that CD339 was the only overlapping gene differentially regulated in APL and other AML subtypes. In summary, our two-step approach for gene expression analysis revealed two previously unknown subgroup distinctions in AML based on surface molecule expression, which may guide the differentiation of subentities in a given clinical-diagnostic context.

The Low Expression of Fc-Gamma Receptor III (CD16) and High Expression of Fc-Gamma Receptor I (CD64) on Neutrophil Granulocytes Mark Severe COVID-19 Pneumonia.

Hyperinflammation through neutrophil granulocytes contributes to disease severity in COVID-19 pneumonia and promotes acute lung failure. Understanding the mechanisms of the dysregulations within the myeloid cell compartment may help to improve therapies for severe COVID-19 infection. Here, we investigated the immunopathological characteristics of circulating neutrophil granulocytes and monocytes in 16 patients with COVID-19 pneumonia by multiparameter flow cytometry in comparison to 9 patients with pulmonary infiltrates but without COVID-19. We correlated the immunophenotypes with the scores of the severity-of-disease classification system, APACHE-II. We found that the mean fluorescence intensity (MFI) of CD15, which is important for the transendothelial migration, was significantly reduced in the patients with COVID-19 (difference ± SD; 295.70 ± 117.50 MFI; p = 0.02). In addition, the granularity was significantly lower in the neutrophil granulocytes of patients with COVID-19 (difference ± SD; 1.11 ± 0.43 side-scatter ratio; p = 0.02). Moreover, the Fc-gamma receptor III (CD16) and Fc-gamma receptor I (CD64) on the neutrophil granulocytes were expressed discordantly with COVID-19 severity. CD16 correlated as inversely proportional (ρ = (-)0.72; 95% CI (-)0.92-(-)0.23; p = 0.01) and CD64 as proportional (ρ = 0.76; 95% CI 0.31-0.93; p = 0.01) with the APACHE-II scores of the patients. We conclude that the deviant expression of the Fc-gamma receptors might play role in a dysregulated antibody-mediated phagocytosis in severe cases of COVID-19 pneumonia.

Flow cytometry datasets consisting of peripheral blood and bone marrow samples for the evaluation of explainable artificial intelligence methods.

Three different Flow Cytometry datasets consisting of diagnostic samples of either peripheral blood (pB) or bone marrow (BM) from patients without any sign of bone marrow disease at two different health care centers are provided. In Flow Cytometry, each cell rapidly passes through a laser beam one by one, and two light scatter, and eight surface parameters of more than 100.000 cells are measured per sample of each patient. The technology swiftly characterizes cells of the immune system at the single-cell level based on antigens presented on the cell surface that are targeted by a set of fluorochrome-conjugated antibodies. The first dataset consists of N=14 sample files measured in Marburg and the second dataset of N=44 data files measured in Dresden, of which half are BM samples and half are pB samples. The third dataset contains N=25 healthy bone marrow samples and N=25 leukemia bone marrow samples measured in Marburg. The data has been scaled to log between zero and six and used to identify cell populations that are simultaneously meaningful to the clinician and relevant to the distinction of pB vs BM, and BM vs leukemia. Explainable artificial intelligence methods should distinguish these samples and provide meaningful explanations for the classification without taking more than several hours to compute their results. The data described in this article are available in Mendeley Data [1].

Monitoring multiple myeloma in the peripheral blood based on cell-free DNA and circulating plasma cells.

With the advent of novel, highly effective therapies for multiple myeloma (MM), classical serologic monitoring appears insufficient for response assessment and prediction of relapse. Moreover, serologic studies in MM are hampered by interference of therapeutic antibodies. The detection of malignant plasma cell clones by next generation sequencing (NGS) or multiparameter flow cytometry (MFC) circumvents these difficulties and can be performed in the peripheral blood (pB) by targeting circulating cell-free DNA (cfDNA) or circulating plasma cells (CPCs), thus also avoiding an invasive sampling procedure. Here, we applied NGS of VJ light chain (LC) rearrangements in cfDNA and MFC of magnetically-enriched CD138-positive CPCs (me-MFC) to investigate disease burden in unselected MM patients. Sequencing was successful for 114/130 (87.7%) cfDNA samples and me-MFC results were analyzable for 196/205 (95.6%) samples. MM clones were detectable in 38.9% of samples taken at initial diagnosis or relapse (ID/RD), but only in 11.8% of samples taken during complete remission (CR). Circulating MM plasma cells were present in 83.3% of ID/RD samples and 9.9% of CR samples. Residual disease assessment by NGS or me-MFC in samples taken during very good partial remission or CR was 80% concordant. Notably, 4/4 (NGS) and 5/8 (me-MFC) positive CR samples were from patients with oligo- or non-secretory myeloma. The time to progression was shorter if there was evidence of residual myeloma in the pB. Together, our findings indicate that our two novel analytical approaches accurately indicate the course of MM and may be particularly valuable for monitoring patients with serologically non-trackable disease.

Superior Overall Survival in Patients with Colorectal Cancer, Regular Aspirin Use, and Combined Wild-Type PIK3CA and KRAS-Mutated Tumors.

The impact of aspirin use after the diagnosis of colorectal cancer is unknown. Among others, PIK3CA (phosphatidylinositol-4,5-bisphosphate 3-kinase, catalytic subunit alpha) mutational status was proposed as a molecular biomarker for the response to adjuvant aspirin therapy. However, prognostic data on aspirin use after a colorectal cancer diagnosis in relation to KRAS mutational status is limited. In a single-center retrospective study, we obtained KRAS and PIK3CA mutational status in a cohort of 153 patients with a first diagnosis of colorectal cancer receiving tumor surgery with curative intent. PIK3CA mutational status was determined by pyrosequencing, and KRAS mutational status was determined by next-generation sequencing. Clinicopathological data and survival data were assessed using patient records and reporting registers. We observed a significant 10-year overall survival benefit in patients with aspirin use and combined wild-type PIK3CA and mutated-KRAS tumors (HR = 0.38; 95% CI = 0.17-0.87; p = 0.02), but not in patients without aspirin use. Our data indicate a benefit of aspirin usage particularly for patients with combined wild-type PIK3CA and mutated-KRAS tumor characteristics.

Expression of ß-1,4-galactosyltransferases during Aging in Caenorhabditis elegans.

BACKGROUND: Altered plasma activity of ß-1,4-galac-tosyl-transferases (B4GALTs) is a novel candidate biomarker of human aging. B4GALT1 is assumed to be largely responsible for this activity increase, but how it modulates the aging process is unclear at present. OBJECTIVES: To determine how expression of B4GALT1 and other B4GALT enzymes changes during aging of an experimentally tractable model organism, Caenorhabditis elegans. METHODS: Targeted analysis of mRNA levels of all 3 C. elegans B4GALT family members was performed by qPCR in wild-type and in long-lived daf-2 (insulin/IGF1-like receptor)-deficient or germline-deficient animals. RESULTS: bre-4 (B4GALT1/2/3/4) is the only B4GALT whose expression increases during aging in wild-type worms. In addition, bre-4 levels also rise during aging in long-lived daf-2-deficient worms, but not in animals that are long-lived due to the lack of germline stem cells. On the other hand, expression of sqv-3 (B4GALT7) and of W02B12.11 (B4GALT5/6) appears decreased or constant, respectively, in all backgrounds during aging. CONCLUSIONS: The age-dependent bre-4 mRNA increase in C. elegans parallels the age-dependent B4GALT activity increase in humans and is consistent with C. elegans being a suitable experimental organism to define potentially conserved roles of B4GALT1 during aging.

The Oncoprotein SKI Acts as A Suppressor of NK Cell-Mediated Immunosurveillance in PDAC.

Drugs targeting epigenetic mechanisms such as histone deacetylase inhibitors (HDACi) suppress tumor growth. HDACi also induce the expression of ligands for the cytotoxicity receptor NKG2D rendering tumors more susceptible to natural killer (NK) cell-dependent killing. The major acetylases responsible for the expression of NKG2D ligands (NKG2D-L) are CBP and p300. The role of the oncogene and transcriptional repressor SKI, an essential part of an HDAC-recruiting co-repressor complex, which competes with CBP/p300 for binding to SMAD3 in TGFß signaling, is unknown. Here we show that the siRNA-mediated downregulation of SKI in the pancreatic cancer cell lines Panc-1 and Patu8988t leads to an increased target cell killing by primary NK cells. However, the higher cytotoxicity of NK cells did not correlate with the induction of NKG2D-L. Of note, the expression of NKG2D-L and consequently NK cell-dependent killing could be induced upon LBH589 (LBH, panobinostat) or valproic acid (VPA) treatment irrespective of the SKI expression level but was significantly higher in pancreatic cancer cells upon genetic ablation of SKI. These data suggest that SKI represses the inducible expression of NKG2D-L. The combination of HDACi with NK cell-based immunotherapy is an attractive treatment option for pancreatic tumors, specifically for patients with high SKI protein levels.

Determination of CD43 and CD200 surface expression improves accuracy of B-cell lymphoma immunophenotyping.

BACKGROUND: The Matutes score (MS) was proposed to differentiate chronic lymphocytic leukemia (CLL) from other B-cell non-Hodgkin lymphomas (B-NHLs). However, ambiguous immunophenotypes are common and remain a diagnostic challenge. Therefore, we evaluated the diagnostic benefit of measuring CD200 and CD43 expression together with the standard MS antigens. METHODS: 138 lymphoma patient samples and a validation cohort of 138 additive samples were classified according to the standard MS and further assigned with one or two additional points, for high CD200 and/or CD43 expression levels. The "classical" MS and the "Matutes score-extended" (MS-e) were categorized as high (4-5/6-7), intermediate (2-3/4-5), and low (0-1/0-3). Samples were reclassified into the MS-e with focus on ambiguous cases with an intermediate "classical" MS. RESULTS: A total of 35 of 138 (25.4%) patient samples were assigned to the intermediate MS group and confirmed by histopathological reports as CLL (14/40.0%) and B-NHLs other than CLL (21/60%). MS-e analysis identified 13 of 14 (92.9%) of CLL cases (MS-e 4-5) and 18/21 (85.7%) non-CLL cases (MS-e ≤ 3) correctly. Overall, the sensitivity of the CLL diagnosis was significantly increased by application of MS-e compared to the "classical" MS (98.8% vs. 82.7%; p = 0.0009), while specificity of both methods was almost equal (94.7% vs. 98.3%; p = 0.4795). Of note, sole measurement of CD43 and CD200 on B-cells sufficiently differentiated CLL from non-CLL with a test accuracy superior to the "classical" MS (F1 score 96.2 vs. 93.6). CONCLUSION: CD200 and CD43 have a high informative value in diagnostic immunophenotyping and facilitate the separation of CLL from other B-NHLs particularly in ambiguous cases.

Aberrant CD3-Positive, CD8-Low, CD7-Negative Lymphocytes May Appear During Viral Infections and Mimic Peripheral T-Cell Lymphoma.

Flow cytometry (FC) facilitates diagnosis of peripheral T-cell non-Hodgkin lymphoma (T-NHL), but overlapping features between reactive and neoplastic T-cell proliferations often hamper a rapid assessment. One hundred forty peripheral blood samples submitted to diagnostic FC for T-cell immunophenotyping were retrospectively analyzed. A T-cell population with a conspicuous aberrant surface epitope expression pattern was observed in 18 cases and diagnostic follow up was performed. The aberrant T-cell population exhibited a low scatter profile, a CD7-negative/low, CD8-low and CD3-positive immunophenotype, and monoclonal T-cell receptor expansion. T-NHL was ruled out by follow up in all cases. Epstein-Barr virus infection was diagnosed in 12 cases, cytomegalovirus infection in three cases; one patient had been vaccinated. The irregular subpopulation disappeared spontaneously within days or weeks. We describe a novel peripheral blood T-cell subpopulation with a low light scatter and CD8-low, CD7-negative/low and CD3-positive marker expression profile, which indicates reactive T-cell expansion in patients who present with peripheral lymphadenopathy and/or B symptoms.

Correction to: Optimizing conditions for labeling of mesenchymal stromal cells (MSCs) with gold nanoparticles: a prerequisite for in vivo tracking of MSCs.

The authors apologized for the unfortunate error in figure during publication of the article and they also explained that some of the solid grey graphs in Fig. 5 are intentionally based on the same data. For 8 different surface makers (CD14, CD73, CD34, CD105, CD19, CD90, CD45, HA-DR) in accordance to the guidelines of the manufacturer a panel of 4 different isotype controls were used, corresponding to 4 different fluorescence channels.

Outcome of non-mold effective anti-fungal prophylaxis in patients at high-risk for invasive fungal infections after allogenic stem cell transplantation.

Patients who develop severe graft-versus-host disease (GvHD) after allogeneic stem cell transplantation (alloSCT) have a higher risk for invasive fungal infection (IFI). At our center, fluconazole prophylaxis is standard and upfront mold-effective prophylaxis performed only in patients with specific risk constellations. A total of 290 patients undergoing alloSCT between May 2002 and August 2011 were analyzed. Patients were regarded as high-risk if they suffered from acute GvHD II-IV° or extensive chronic GvHD. The 2-year incidence of an IFI after alloSCT was 8.97% (26/290) in the entire cohort and 7.78% (7/90) in the high-risk group. Mortality due to IFI was 3.85% (1/26) without including a high-risk patient. In the multivariate analysis a pre-transplant fungal infection was the only significant risk factor for developing an IFI after alloSCT (HR = 5.298; p = .001). A fluconazole prophylaxis in patients with GvHD after alloSCT is feasible in facilities with HEPA filtration and high awareness of clinical signs for IFI.

Comprehensive genetic diagnosis of acute myeloid leukemia by next-generation sequencing.

Differential induction therapy of all subtypes of acute myeloid leukemia other than acute promyelocytic leukemia is impeded by the long time required to complete complex and diverse cytogenetic and molecular genetic analyses for risk stratification or targeted treatment decisions. Here, we describe a reliable, rapid and sensitive diagnostic approach that combines karyotyping and mutational screening in a single, integrated, next-generation sequencing assay. Numerical karyotyping was performed by low coverage whole genome sequencing followed by copy number variation analysis using a novel algorithm based on in silico-generated reference karyotypes. Translocations and DNA variants were examined by targeted resequencing of fusion transcripts and mutational hotspot regions using commercially available kits and analysis pipelines. For the identification of FLT3 internal tandem duplications and KMT2A partial tandem duplications, we adapted previously described tools. In a validation cohort including 22 primary patients' samples, 9/9 numerically normal karyotypes were classified correctly and 30/31 (97%) copy number variations reported by classical cytogenetics and fluorescence in situ hybridization analysis were uncovered by our next-generation sequencing karyotyping approach. Predesigned fusion and mutation panels were validated exemplarily on leukemia cell lines and a subset of patients' samples and identified all expected genomic alterations. Finally, blinded analysis of eight additional patients' samples using our comprehensive assay accurately reproduced reference results. Therefore, calculated karyotyping by low coverage whole genome sequencing enables fast and reliable detection of numerical chromosomal changes and, in combination with panel-based fusion-and mutation screening, will greatly facilitate implementation of subtype-specific induction therapies in acute myeloid leukemia.

Development, Function, and Clinical Significance of Plasmacytoid Dendritic Cells in Chronic Myeloid Leukemia.

Plasmacytoid dendritic cells (pDC) are the main producers of a key T-cell-stimulatory cytokine, IFNα, and critical regulators of antiviral immunity. Chronic myeloid leukemia (CML) is caused by BCR-ABL, which is an oncogenic tyrosine kinase that can be effectively inhibited with ABL-selective tyrosine kinase inhibitors (TKI). BCR-ABL-induced suppression of the transcription factor interferon regulatory factor 8 was previously proposed to block pDC development and compromise immune surveillance in CML. Here, we demonstrate that pDCs in newly diagnosed CML (CML-pDC) develop quantitatively normal and are frequently positive for the costimulatory antigen CD86. They originate from low-level BCR-ABL-expressing precursors. CML-pDCs also retain their competence to maturate and to secrete IFN. RNA sequencing reveals a strong inflammatory gene expression signature in CML-pDCs. Patients with high CML-pDC counts at diagnosis achieve inferior rates of deep molecular remission (MR) under nilotinib, unless nilotinib therapy is combined with IFN, which strongly suppresses circulating pDC counts. Although most pDCs are BCR-ABL-negative in MR, a substantial proportion of BCR-ABL + CML-pDCs persists under TKI treatment. This could be of relevance, because CML-pDCs elicit CD8+ T cells, which protect wild-type mice from CML. Together, pDCs are identified as novel functional DC population in CML, regulating antileukemic immunity and treatment outcome in CML.Significance: CML-pDC originates from low-level BCR-ABL expressing stem cells into a functional immunogenic DC-population regulating antileukemic immunity and treatment outcome in CML. Cancer Res; 78(21); 6223-34. ©2018 AACR.

High ß-1,4-Galactosyltransferase-I expression in peripheral T-lymphocytes is associated with a low risk of relapse in germ-cell cancer patients receiving high-dose chemotherapy with autologous stem cell reinfusion.

Survival of patients with germ-cell cancer (GCC) and primary progression or relapse after cisplatin-based first-line chemotherapy is highly heterogeneous, ranging from close to zero to more than 70%. We investigated ß-1,4-Galactosyltransferase-I (B4GALT1) expression levels in peripheral lymphocytes in a cohort of 46 testicular cancer patients. B4GALT1 enhances immune cell crosstalk via glycosylation of surface molecules. A high expression level of B4GALT1 in T-lymphocytes, but not in monocytes, was associated with a lower risk of relapse with a hazard ratio (HR) of 0.66 (95% confidence interval (CI) of HR: 0.45-0.97; p = 0.02) upon multivariate Cox regression analysis. Correspondingly, interleukin 10 (IL10), a cytokine released by cytotoxic T-cells, was likewise significantly elevated in T-lymphocytes of non-relapse GCC patients (HR: 0.3; 95% CI of HR: 0.14-0.65; p = 0.002). Our data indicate that glycosylation and activation of T-lymphocytes may play a pivotal role in disease control in GCC patients with primary progressive or relapsed disease.

Maintenance of cellular respiration indicates drug resistance in acute myeloid leukemia.

Primary resistance to induction therapy is an unsolved clinical problem in acute myeloid leukemia (AML). Here we investigated drug resistance in AML at the level of cellular metabolism in order to identify early predictors of therapeutic response. Using extracellular flux analysis, we compared metabolic drug responses in AML cell lines sensitive or resistant to cytarabine or sorafenib after 24h of drug treatment to a small cell lung cancer (SCLC) cell line exposed to etoposide. Only drug-resistant AML cells maintained oxidative metabolism upon drug exposure while SCLC cells displayed an overall metabolic shift towards glycolysis, i.e. a Warburg effect to escape drug toxicity. Moreover, primary AML blasts displayed very low glycolytic activity, while oxygen consumption was readily detectable, indicating an essential role of oxidative pathways in the bioenergetics of AML blasts. In line with these observations, analysis of the mitochondrial membrane potential using tetramethylrhodamine ethyl ester staining and flow cytometry allowed for clear discrimination between drug sensitive and resistant AML cell line clones and primary blasts after 24h of treatment with cytarabine or sorafenib. Our data reveal a distinct metabolic phenotype of resistant AML cells and suggest that disrupting oxidative metabolism rather than glycolysis may enhance the cytotoxic effects of chemotherapy in AML.