PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 8, 2026Molecular Aspects of Medicine2 citationsOpen Access

Dual-targeting strategies for cancer and diabetes: Converging pharmacological pathways and repurposed therapies

View Full Paper
GBGurjit Kaur BhattiIAIshtiaq AhmedASAbhishek Sehrawat

Key Points

  • This review examines dual-targeting strategies for cancer and diabetes, focusing on shared pathways and therapies.
  • Evaluated preclinical studies and clinical trial data on dual-targeting strategies.
  • Analyzed pharmacological agents like metformin and statins for their effects on both cancer and diabetes.
  • Explored the role of anti-inflammatory biologics and natural compounds in addressing both diseases.
  • Shared pathophysiological mechanisms link cancer and diabetes, including oxidative stress and metabolic reprogramming.
  • Repurposed agents like metformin show promise in improving outcomes for both conditions.
  • Biomarker-guided patient selection may enhance therapeutic efficacy in integrated treatments.

Abstract

The rising global burden of cancer and diabetes mellitus, particularly type 2 diabetes (T2DM), underscores a critical need for integrated therapeutic strategies. Epidemiological studies reveal a compelling bidirectional association between these diseases, with T2DM increasing cancer risk and adversely affecting cancer prognosis. Shared pathophysiological mechanisms including insulin/IGF-1 signaling, chronic low-grade inflammation, oxidative stress, and metabolic reprogramming serve as potential therapeutic convergence points. This review explores the mechanistic and clinical basis for dual-targeting strategies that address both malignancy and metabolic dysfunction simultaneously. Key molecular intersections include the PI3K/Akt/mTOR and AMPK pathways, which are central to cell proliferation, survival, and glucose metabolism. Pharmacological agents like metformin, SGLT2 inhibitors, and statins demonstrate promising anticancer effects in addition to glycemic control, while biologics such as canakinumab and tocilizumab modulate inflammatory processes relevant to both disease states. Natural compounds including curcumin, resveratrol, and berberine exhibit dual benefits via antioxidant, anti-inflammatory, and metabolic pathways. The review critically evaluates preclinical studies, retrospective cohort analyses, and clinical trial data supporting the repurposing of anti-diabetic agents for oncology indications. Despite mixed outcomes in large-scale trials, evidence suggests biomarker-based patient selection may enhance therapeutic efficacy. Moreover, emerging paradigms including immunometabolism, gut microbiota modulation, and gene-based interventions offer promising frontiers for integrated care. Ultimately, dual-targeting strategies represent an emerging and promising therapeutic framework for managing patients with overlapping cancer and metabolic disease, with potential to optimize outcomes, reduce therapy-related toxicities, improve long-term survival. Future research must prioritize biomarker-guided precision therapies, multidisciplinary management and the inclusion of metabolic parameters in oncology trial designs. • Overview of insulin/IGF-1, PI3K–Akt–mTOR, inflammation, adipokines, AMPK and microbiome linking diabetes and cancer. • Evidence for repurposing antidiabetic drugs (metformin, SGLT2 inhibitors, TZDs) as potential anticancer therapies. • Critical evaluation of clinical trials and safety signals of metabolic drugs used in oncology. • Anti-inflammatory biologics and nutraceuticals as potential dual-purpose therapies for diabetes and cancer. • Emerging immunometabolic and microbiome-targeted strategies to treat both metabolic and malignant disease. • Identification of translational gaps and roadmap for precision dual-target drug development. • Future vision for personalized dual-acting therapies integrating glycemic control with tumor suppression.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bhatti et al. (2026) studied this question.

synapsesocial.com/papers/69acc56732b0ef16a404f6f9https://doi.org/10.1016/j.mam.2026.101464
Ask AI
Helpful
Bookmark
Share
View Full Paper