Evidence map›Paper›PMID 42724341›Full record

ReviewAmerican journal of cancer research2026

Metabolic reprogramming in diabetes and cancer: the role of PI3K/AKT/mTOR and beyond.

Nahed S Alharthi

Abstract readReview
In one paragraph

Review in American journal of cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nahed S AlharthiDepartment of Medical Laboratory, College of Applied Medical Sciences in Al-Kharj, Prince Sattam Bin Abdulaziz University Al-Kharj 11942, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus and cancer are among the most prevalent chronic diseases worldwide, and accumulating evidence suggests a significant association between these conditions. The metabolic disturbances characteristic of diabetes, including hyperglycemia, hyperinsulinemia, insulin resistance, and chronic inflammation, create a favorable environment for tumor initiation and progression. These alterations contribute to cellular metabolic reprogramming, enhanced proliferative signaling, and resistance to apoptosis. Key molecular pathways such as PI3K/AKT/mTOR, along with dysregulated glucose, lipid, and amino acid metabolism, play central roles in linking diabetic and oncogenic processes. In addition to metabolic alterations, genetic and epigenetic modifications, including mutations in oncogenes and tumor suppressor genes, as well as the involvement of non-coding RNAs, further strengthen this association. Emerging evidence also highlights the gut microbiome's role in modulating inflammation, metabolic homeostasis, and cancer susceptibility in diabetic conditions. Therapeutically, antidiabetic agents such as metformin, GLP-1 receptor agonists, and SGLT2 inhibitors have shown potential in modulating cancer-related pathways, although clinical evidence remains variable and requires further validation. This review provides a comprehensive overview of the shared metabolic and molecular mechanisms underlying the diabetes-cancer link, emphasizing the interplay between metabolic dysregulation, genetic alterations, and microbiome dynamics. A better understanding of these interconnected pathways may support the development of targeted therapeutic strategies and improve clinical outcomes. However, further well-designed studies are necessary to establish causal relationships and translate these findings into effective clinical interventions.

Indexed as

Diabetesepigenesishyperglycemiainsulin resistanceneoplasms

Identifiers

PMID42724341
PMCPMC13559360

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.