ReviewInternational journal of nanomedicine2026
Unraveling Diabetes Mellitus-Driven Tumorigenesis: From Pathophysiological Mechanisms, Therapeutic Drugs to Tailor-Made Nanosystems.
Review in International journal of nanomedicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
5 authors.
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Abstract
Diabetes mellitus (DM) and cancer are two major global public health challenges. Growing evidence shows that the core features of DM, including hyperactivated insulin/IGF-1 signaling axis, chronic hyperglycemia, and a persistent inflammatory microenvironment, are important factors driving tumorigenesis and progression. Currently available clinical antidiabetic drugs, such as chemically synthesized drugs, biological and natural products, have been proven to achieve a dual therapeutic effect of controlling blood glucose and regulating the tumor microenvironment (TME). However, these drugs face practical difficulties such as poor oral bioavailability, off-target side effects, and low drug accumulation at tumor sites in clinical application. To overcome these challenges, nanotechnology offers a highly promising solution. Thus, this review elucidates the mechanisms of DM-driven cancer development and the anti-tumor therapeutic mechanisms of current anti-diabetic drugs. Then, we highlight how tailor-made nanosystems overcome traditional delivery barriers, offering unique advantages in targeted delivery, integrated diagnostics, and the oral administration of fragile biologics. Finally, the clinical translatability, disadvantages, and future prospects of these nanosystems will be briefly discussed.
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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 Socratic graph.