<p>Unopposed estrogen refers to prolonged estrogenic stimulation in the absence of adequate progesterone-mediated counter-regulation. Unopposed estrogen is strongly implicated in endometrial hyperplasia and type I endometrial carcinogenesis, and it is also biologically relevant to estrogen receptor-positive breast cancer. Evidence linking estrogen exposure to ovarian cancer is more heterogeneous and appears to vary by menopausal status, hormone therapy formulation, duration of exposure, and histologic subtype; therefore, ovarian cancer risk should be interpreted as an association rather than a definitive causal consequence of unopposed estrogen. Ongoing estrogen signaling can drive cell proliferation, oxidative DNA damage, and chronic inflammation in estrogen target tissues. Until now, conventional hormone assays, such as enzyme-linked immunosorbent assay (ELISA) have only been able to measure the amount of hormones in the circulation, but may not effectively detect dynamic, tissue-specific, or early-stage estrogenic activity. This review is unique in focusing on unopposed estrogen as a clinically significant biosensing target and critically reviewing estrogen receptor functionalized nanoprobe platforms for the detection of unopposed estrogen and the diagnosis of cancer, unlike other reviews, which have broadly discussed estrogen biosensors or nanoprobe-formatted cancer diagnostics. It focuses on platforms using estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ) as well as strategies for receptor immobilization, nanomaterials design, signal transduction, and applications in biofluids, cells, and tissues. The review also discusses a translational aspect by considering obstacles to clinical implementation, such as probe stability, specificity of chemical analysis in complex biological matrices, required assay standardization, validation, and compatibility with use in a portable or point-of-care system. Newer trends like multiplex hormone profiling, smart devices integration, and signal interpretation with the help of machine learning (ML) are also discussed. This review aims to place unopposed estrogen biology in the context of ER-functionalized nanobiosensing and clinical translation problems, establishing a focused framework for future precision diagnostic tool development for cancer risk assessment and early detection by estrogen.</p> Graphical abstract <p></p>