Serum Metabolomics Coupling With Clinical Laboratory Indicators Reveal Taxonomic Features of Leukemia

Modulation of Tumor Metabolism in Acute Leukemia by Plant-Derived Polymolecular Drugs and Their Effects on Mitochondrial Function

The analysis of tumor metabolism offers promising opportunities for developing new therapeutic strategies. Plant-derived polymolecular drugs can regulate cellular metabolism, making them potential candidates for treatment. This study examined the metabolic effects of plant-derived polymolecular drugs-P2Et, Anamu-SC, and Esperanza-on leukemic cell lines (lymphoid and myeloid types) and primary leukemic blasts. The metabolic analysis included oxidative status, glucose consumption, extracellular acidification, oxygen consumption, mitochondrial dynamics, and untargeted metabolomics. Additionally, the effect of co-treatment with conventional chemotherapeutic drugs was investigated. Results showed that P2Et and Anamu-SC reduced the viability and proliferation of all tumor cell lines, exhibiting antioxidant effects. Anamu-SC decreased reactive oxygen species levels in lymphoid tumor cells. Mitochondrial activity was selectively affected by the plant-derived polymolecular drugs, with Anamu-SC and Esperanza causing more significant, potentially reversible damage compared to P2Et. Anamu-SC and Esperanza increased levels of phosphatidylcholines and carnitines. The co-administration of plant-derived polymolecular drugs with chemotherapeutics improved the cytostatic efficacy of cytarabine. In conclusion, this research highlights the promising pharmacological activity of Anamu-SC and Esperanza as mitocans for the treatment of acute leukemia. The study emphasizes the practical significance of combining plant-derived polymolecular drugs with conventional chemotherapeutics to enhance their cytostatic efficacy.

Metabolomics for hematologic malignancies: Advances and perspective

With the use of advanced technology, metabolomics allows for a thorough examination of metabolites and other small molecules found in biological specimens, blood, and tissues. In recent years, metabolomics has been recognized that is closely related to the development of malignancies in the hematological system. Alterations in metabolomic pathways and networks are important in the pathogenesis of hematologic malignancies and can also provide a theoretical basis for early diagnosis, efficacy evaluation, accurate staging, and individualized targeted therapy. In this review, we summarize the progress of metabolomics, including glucose metabolism, amino acid metabolism, and lipid metabolism in lymphoma, myeloma, and leukemia through specific mechanisms and pathways. The research of metabolomics gives a new insight and provides therapeutic targets for the treatment of patients with hematologic malignancies.

Artificial intelligence reveals the predictions of hematological indexes in children with acute leukemia

Childhood leukemia is a prevalent form of pediatric cancer, with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) being the primary manifestations. Timely treatment has significantly enhanced survival rates for children with acute leukemia. This study aimed to develop an early and comprehensive predictor for hematologic malignancies in children by analyzing nutritional biomarkers, key leukemia indicators, and granulocytes in their blood. Using a machine learning algorithm and ten indices, the blood samples of 826 children with ALL and 255 children with AML were compared to a control group of 200 healthy children. The study revealed notable differences, including higher indicators in boys compared to girls and significant variations in most biochemical indicators between leukemia patients and healthy children. Employing a random forest model resulted in an area under the curve (AUC) of 0.950 for predicting leukemia subtypes and an AUC of 0.909 for forecasting AML. This research introduces an efficient diagnostic tool for early screening of childhood blood cancers and underscores the potential of artificial intelligence in modern healthcare.

Profiling of serum metabolome of breast cancer: multi-cancer features discriminate between healthy women and patients with breast cancer

Introduction

The progression of solid cancers is manifested at the systemic level as molecular changes in the metabolome of body fluids, an emerging source of cancer biomarkers.

Methods

We analyzed quantitatively the serum metabolite profile using high-resolution mass spectrometry. Metabolic profiles were compared between breast cancer patients (n=112) and two groups of healthy women (from Poland and Norway; n=95 and n=112, respectively) with similar age distributions.

Results

Despite differences between both cohorts of controls, a set of 43 metabolites and lipids uniformly discriminated against breast cancer patients and healthy women. Moreover, smaller groups of female patients with other types of solid cancers (colorectal, head and neck, and lung cancers) were analyzed, which revealed a set of 42 metabolites and lipids that uniformly differentiated all three cancer types from both cohorts of healthy women. A common part of both sets, which could be called a multi-cancer signature, contained 23 compounds, which included reduced levels of a few amino acids (alanine, aspartate, glutamine, histidine, phenylalanine, and leucine/isoleucine), lysophosphatidylcholines (exemplified by LPC(18:0)), and diglycerides. Interestingly, a reduced concentration of the most abundant cholesteryl ester (CE(18:2)) typical for other cancers was the least significant in the serum of breast cancer patients. Components present in a multi-cancer signature enabled the establishment of a well-performing breast cancer classifier, which predicted cancer with a very high precision in independent groups of women (AUC>0.95).

Discussion

In conclusion, metabolites critical for discriminating breast cancer patients from controls included components of hypothetical multi-cancer signature, which indicated wider potential applicability of a general serum metabolome cancer biomarker.

Untargeted metabolomic and lipidomic analyses reveal lipid dysregulation in the plasma of acute leukemia patients

Acute leukemias (AL) are aggressive neoplasms with high mortality rates. Metabolomics and oxidative status have emerged as important tools to identify new biomarkers with clinical utility. To identify the metabolic differences between healthy individuals (HI) and patients with AL, a multiplatform untargeted metabolomic and lipidomic approach was conducted using liquid and gas chromatography coupled with quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS or GC-QTOF-MS). Additionally, the total antioxidant capacity (TAC) was measured. A total of 20 peripheral blood plasma samples were obtained from patients with AL and 18 samples from HI. Our analysis revealed 135 differentially altered metabolites in the patients belonging to 12 chemical classes; likewise, the metabolic pathways of glycerolipids and sphingolipids were the most affected in the patients. A decrease in the TAC of the patients with respect to the HI was evident. This study conducted with a cohort of Colombian patients is consistent with observations from other research studies that suggest dysregulation of lipid compounds. Furthermore, metabolic differences between patients and HI appear to be independent of lifestyle, race, or geographic location, providing valuable information for future advancements in understanding the disease and developing more global therapies.

miRNA-1 promotes acute myeloid leukemia cell pathogenesis through metabolic regulation

Acute myeloid leukemia (AML) is a heterogeneous and deadly disease characterized by uncontrolled expansion of malignant blasts. Altered metabolism and dysregulated microRNA (miRNA) expression profiles are both characteristic of AML. However, there is a paucity of studies exploring how changes in the metabolic state of the leukemic cells regulate miRNA expression leading to altered cellular behavior. Here, we blocked pyruvate entry into mitochondria by deleting the Mitochondria Pyruvate Carrier (MPC1) gene in human AML cell lines, which decreased Oxidative Phosphorylation (OXPHOS). This metabolic shift also led to increased expression of miR-1 in the human AML cell lines tested. AML patient sample datasets showed that higher miR-1 expression correlates with reduced survival. Transcriptional and metabolic profiling of miR-1 overexpressing AML cells revealed that miR-1 increased OXPHOS, along with key metabolites that fuel the TCA cycle such as glutamine and fumaric acid. Inhibition of glutaminolysis decreased OXPHOS in miR-1 overexpressing MV4-11 cells, highlighting that miR-1 promotes OXPHOS through glutaminolysis. Finally, overexpression of miR-1 in AML cells exacerbated disease in a mouse xenograft model. Together, our work expands current knowledge within the field by uncovering novel connections between AML cell metabolism and miRNA expression that facilitates disease progression. Further, our work points to miR-1 as a potential new therapeutic target that may be used to disrupt AML cell metabolism and thus pathogenesis in the clinic.