Insulin resistance as a modifiable contributor to breast cancer: mechanisms, biomarkers, and therapeutic implications

Insulin resistance (IR) has emerged as a metabolically relevant contributor to the development and progression of breast cancer (BC), with a case fatality of nearly 15%. IR mainly shows a relationship with obesity, type 2 diabetes mellitus (T2DM), and persistent low-intensity inflammation, and promotes a pro-tumorigenic environment through hyperinsulinemia, enhanced signaling through insulin, along with insulin-like growth factor (IGF), adipocytokine imbalance, and metabolic reprogramming. IR activates mitogenic phosphatidylinositol 3-kinase (PI3K)-protein kinase B (AKT) and mitogen-activated protein kinase (MAPK) routes, increases estrogen bioavailability, and supports survival of tumor cells alongside resistance to therapeutic interventions. IR markers, such as the triglyceride-glucose index (TyG) and homeostatic model assessment of insulin resistance (HOMA-IR), have been linked to higher BC risk, aggressive tumor phenotypes, and adverse clinical outcomes. Ongoing studies also show that IR-related adipocytokines, such as adipsin and visfatin, interact with metabolic dysfunction to increase BC risk independent of obesity (OR = 18.5, 95% CI: 2–159.5 and OR = 11.25, 95% CI: 1.3–98, respectively). With the accessibility of IR indices, their integration into BC risk stratification, prognostic assessment, and treatment planning offers a promising path for precision oncology. This review synthesizes preclinical, epidemiological, and clinical evidence to examine the mechanistic links between IR and BC and also highlights translational opportunities for prevention, prognosis prediction, and therapeutic opportunities in breast tumorigenesis, useful for both physicians and researchers. Current evidence appears supportive of a relationship between IR and BC development, progression, and treatment outcomes. However, the extent of this relationship and its clinical utility still needs further investigation. The inclusion of IR-linked parameters as indicators for BC risk assessment and prognosis may help identify patients who are likely to benefit from metabolic interventions.