Advancing early cancer diagnosis requires tools capable of distinguishing cancer subtypes at the single-cell level with high sensitivity. In this project, we developed a nanoplatform based on IO/Au gap-enhanced Raman tags (GERTs) for multiplexed detection of surface protein biomarkers and machine learning–based classification of cancer cells. The core–shell–shell architecture integrates a magnetic iron oxide core for cell isolation and guidance, with a dual gold shell structure engineered to create intense electromagnetic "hot spots" for surface-enhanced Raman scattering (SERS) signal amplification. By targeting specific biomarkers with spectrally encoded Raman tags, we achieved high-throughput, label-free profiling of heterogeneous cancer cell populations. Read More ...

Figure illustrates the schematic workflow for biomarker detection and subtype classification using the IO/Au/GERT platform. This system supports accurate identification of cancer cell types such as SKBR3 and MM231, enabling potential applications in liquid biopsy and personalized oncology.

Flavonoids are plant-derived polyphenolic compounds widely recognized for their diverse biological activities, including potent anticancer effects. This project focuses on elucidating the structure–activity relationships (SAR) and mechanistic pathways through which flavonoids exert anticancer properties. Through comprehensive literature analysis, we examined how specific structural features—such as the C2=C3 double bond, oxo group at C4, and ring B positioning—influence their ability to inhibit cancer progression. Flavonoids interfere with tumor development through multiple biological mechanisms, including topoisomerase inhibition, protein kinase modulation, angiogenesis suppression, cell cycle arrest, and apoptosis induction. Read more ...