Evidence map›Paper›PMID 41869637›Full record

ArticleDrugs and drug candidates2026

Cancer Metabolism and Its Historical & Molecular Foundations: An Overview.

Rami A Al-Horani

Abstract read
In one paragraph

Article in Drugs and drug candidates, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Rami A Al-HoraniDivision of Basic Pharmaceutical Sciences, College of Pharmacy, Xavier University of Louisiana, New Orleans, LA 70125, USA.ORCID 0000-0001-9146-2662

Funding

Inhibitors of Human Factor XIIIa as New AnticoagulantsR16GM149412 · NIGMS · XAVIER UNIVERSITY OF LOUISIANA · PI Rami A Al-Horani · 2023 to 2026
$599k
NIGMS NIH HHS R16 GM149412
6 · The paper itself

Abstract

Cancer metabolism is a cornerstone of tumor biology, characterized by profound alterations in cellular energy production and biosynthetic pathways that drive malignancy. The seminal discovery of the "Warburg effect", the preference of cancer cells for aerobic glycolysis even under oxygen-rich conditions, provided the first major insight into this field. Historically, this observation was attributed to defective mitochondria, but modern research has revealed a far more complex picture of metabolic reprogramming that is actively driven by oncogenes, tumor suppressor genes, and the tumor microenvironment (TME). This review advances a unifying framework for understanding cancer metabolism as a dynamic ecosystem defined by three interconnected adaptations: metabolic plasticity, oncometabolite-driven epigenetic remodeling, and immune-metabolic crosstalk. These adaptations extend beyond glycolysis to encompass glutamine metabolism, lipid synthesis, amino acid utilization, and mitochondrial dynamics, all coordinated to fuel rapid proliferation, promote survival, and enable metastasis. By examining the drivers, consequences, and therapeutic barriers within this framework, we highlight emerging strategies for precision intervention. Although understanding the mechanistic basis of these pathways has unveiled new therapeutic avenues, clinical translation has been limited by metabolic redundancy, microenvironmental buffering, and patient heterogeneity. Strategies such as metabolic inhibitors, dietary interventions, and immuno-metabolic combinations offer promising prospects for disrupting tumor growth when guided by biomarker-driven patient selection and emerging technologies, including spatial metabolomics and AI-driven network modeling.

Indexed as

aerobic glycolysisepigenetic regulationmetabolic reprogrammingmitochondrial dynamicstargeted therapyTMEWarburg effect

Identifiers

PMID41869637
PMCPMC13002032

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.