Mapping the current research landscape of metformin in cancer based on bibliometric analysis

Metformin, a widely prescribed first-line treatment for type 2 diabetes, has attracted significant attention for its potential anticancer effects. However, despite the rapid expansion of literature over the past two decades, research on the relationship between metformin and cancer remains highly fragmented, making it difficult to achieve a cohesive understanding of its mechanisms and therapeutic relevance across diverse cancer types. To address this gap, we integrated a bibliometric framework with bioinformatics analyses to systematically map the research landscape and uncover underlying molecular insights. Our findings reveal gene targets such as TP53, SIRT1, and HIF1A, key signaling pathways including AMPK/mTOR and p53, and cancer types like breast and colorectal cancer that are frequently associated with metformin, offering an integrative perspective to inform future cancer research.

Authors

Institutions

Publication Details

Journal
Discover Oncology
Published
2025-08-11
DOI
https://doi.org/10.1007/s12672-025-03327-z
Citations
1
Primary Topic
Metabolism, Diabetes, and Cancer
Type
article
Field-Weighted Citation Impact
0.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mapping the current research landscape of metformin in cancer based on bibliometric analysis

Sike He, Nan Jiang, Guangxi Sun, Yuan Wang et al.
1 citations
Discover Oncology
Metabolism, Diabetes, and Cancer
0.81
article

Mapping the current research landscape of metformin in cancer based on bibliometric analysis

Sike He, Nan Jiang, Guangxi Sun, Yuan Wang, Zhi Li
article en
1 citations

Abstract

Metformin, a widely prescribed first-line treatment for type 2 diabetes, has attracted significant attention for its potential anticancer effects. However, despite the rapid expansion of literature over the past two decades, research on the relationship between metformin and cancer remains highly fragmented, making it difficult to achieve a cohesive understanding of its mechanisms and therapeutic relevance across diverse cancer types. To address this gap, we integrated a bibliometric framework with bioinformatics analyses to systematically map the research landscape and uncover underlying molecular insights. Our findings reveal gene targets such as TP53, SIRT1, and HIF1A, key signaling pathways including AMPK/mTOR and p53, and cancer types like breast and colorectal cancer that are frequently associated with metformin, offering an integrative perspective to inform future cancer research.

Discover OncologyVol. 16(1)
Sichuan University (CN), Chengdu University of Information Technology (CN), Chengdu University of Technology (CN), West China Hospital of Sichuan University (CN)
Good health and well-being
Openalex Percentile: Top 25%
Metabolism, Diabetes, and Cancer
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.