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Overview of Cancer Metabolism
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Dr. Arnaud Blomme
Laboratory of Metabolic Regulation, GIGA-Research Institute, University of Liège, 4000 Liege, Belgium
Pole of Pharmacology and Therapeutics (FATH), Institut de Recherche Expérimentale et Clinique, UCLouvain, 1200 Brussels, Belgium
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Overview of Cancer Metabolism

Abstract submission deadline
31 December 2025
Manuscript submission deadline
31 March 2026
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Topic Information

Dear Colleagues,

Cancers are characterized by a high metabolic heterogeneity, allowing cancer cells to survive and proliferate in harsh microenvironmental conditions, including hypoxia, acidosis, and limited availability of metabolic resources. In recent years, a growing body of experimental and clinical evidence has been obtained, suggesting that the metabolic plasticity of malignant cells plays a key role in cancer progression. Indeed, metabolic activities of cancer cells directly influence (epi)genetic modifications, intra- and inter-cellular signaling, metastatic processes, immune escape, and response of tumors to different anticancer therapies. Recent technical developments have allowed us to reveal the spatially and temporally resolved complexity of the metabolic networks within tumors and their role in tumor initiation and progression.

The aim of this Topic is to present new reports that advance our knowledge on tumor metabolism. We welcome the submissions of original research articles and reviews that focus on all aspects of cancer cell metabolism, with a special focus on the interactions between cancer cells and their microenvironment, as well as on the alterations of the various hallmarks of cancer. Apart from the contributions of conference participants, manuscripts are welcome from other interested research groups. All manuscripts will be peer-reviewed.

Dr. Arnaud Blomme
Dr. Cyril Corbet
Topic Editors

Keywords

  • immunometabolism
  • lipid metabolism and ferroptosis
  • metabolism and therapy resistance
  • tumor microenvironment and disease progression
  • epigenetics, circadian clock, and cancer metabolism
  • tumor acidosis and imaging

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Cells
cells 		5.2 10.5 2012 16 Days CHF 2700 Submit
Organoids
organoids 		- - 2022 25.6 Days CHF 1000 Submit
Cancers
cancers 		4.4 8.8 2009 20.3 Days CHF 2900 Submit
Metabolites
metabolites 		3.7 6.9 2011 14.4 Days CHF 2700 Submit
Pathophysiology
pathophysiology 		2.6 4.6 1994 24.7 Days CHF 1400 Submit

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Published Papers (1 paper)

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Article
Metabolomic Profiling and Bioanalysis of Chronic Myeloid Leukemia: Identifying Biomarkers for Treatment Response and Disease Monitoring
by Selim Sayın, Murat Yıldırım, Batuhan Erdoğdu, Ozan Kaplan, Emine Koç, Tuba Bulduk, Melda Cömert, Mustafa Güney, Mustafa Çelebier and Meltem Aylı
Metabolites 2025, 15(6), 376; https://doi.org/10.3390/metabo15060376 - 6 Jun 2025
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Abstract
Background: Including Chronic Myeloid Leukemia (CML) patients with deep molecular responses (MR4.5) and those with suboptimal responses provides valuable insights into treatment-associated metabolic changes. This study aimed to characterize the metabolomic alterations associated with CML and identify potential biomarkers for treatment response, particularly [...] Read more.
Background: Including Chronic Myeloid Leukemia (CML) patients with deep molecular responses (MR4.5) and those with suboptimal responses provides valuable insights into treatment-associated metabolic changes. This study aimed to characterize the metabolomic alterations associated with CML and identify potential biomarkers for treatment response, particularly in patients achieving a deeper molecular response versus those with poorer responses. Methods: Plasma samples were collected from 51 chronic-phase CML patients and 24 healthy controls. CML patients were classified into two groups based on molecular responses: T1 (BCR-ABL1 IS ≤ 0.0032%) and T2 (BCR-ABL1 IS > 0.0032%, <1%). Metabolomic profiling was conducted using quadrupole time-of-flight liquid chromatography/mass spectrometry. The data analysis involved a partial least squares discriminant analysis, variable importance in projection (VIP) scores, and a pathway enrichment analysis. Significant metabolites were identified. Results: The PLS-DA revealed distinct metabolomic profiles between CML patients and healthy controls as well as between the T1 and T2 groups. Key differentiating metabolites with VIP scores > 1.5 included glutamate, hypoxanthine, and D-galactonic acid. In the T2 group, significant increases in malate and 5-aminoimidazole-4-carboxamide ribonucleotide were observed, reflecting disruptions in purine metabolism, the tricarboxylic acid cycle, and amino acid metabolism. The pathway enrichment analysis highlighted significant alterations in CML energy metabolism, nucleotide synthesis, and amino acid biosynthesis. Conclusions: CML patients exhibit pronounced metabolic changes, particularly in energy and nucleotide metabolism, which are linked to treatment response. These findings provide novel insights into CML biology and suggest potential biomarkers for monitoring treatment efficacy and predicting outcomes and therapeutic targets for improving treatment outcomes and overcoming tyrosine kinase inhibitor resistance. Full article
(This article belongs to the Topic Overview of Cancer Metabolism)
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