High-performance indium-gallium-zinc-oxide thin-film transistor with Al-induced crystallization for ultra-sensitive detection of gastric cancer exosome microRNA-106a

Gastric cancer is a prevalent and lethal malignancy, largely due to the absence of specific symptoms in its early stages. The emerging biomarker, exosomal microRNA-106a (miR-106a), is closely associated with the progression of gastric cancer and positively correlates with the cancer cell metastasis. However, current diagnostic methods for microRNA, such as qRT-PCR, are effective but limited by the extremely low abundance, rendering detection without amplification challenging. In this work, we present a label-free detection method for miR-106a using a performance-enhanced IGZO thin-film transistor (TFT) biosensor, specifically an aluminum (Al)-induced crystallization (AIC) IGZO TFT biosensor (Bio-AIC IGZO TFT). The introduction of Al on IGZO film induced crystallization at high temperatures on the top channel, resulting in covalent bonding between the top channel and the Al layer, which significantly enhanced the TFT's electrical and sensing characteristics. When applied to miR-106a detection, the AlO_x/Al/AlO_x layer created a floating gate structure that can effectively transmit the weak electrical signals generated by biochemical reactions at the sensing interface to the channel layer of the device via the tunneling effect. This design prevented performance degradation typically caused by direct contact between the channel layer and liquid in conventional TFT biosensors. The prepared Bio-AIC IGZO TFT demonstrated a wide linear detection range between 1 fM and 1 μM, and exhibited high sensitivity of 4.04 dec⁻¹ with a detection limit as low as 0.23 fM (1.65 fg/mL) compared to the conventional Bio-IGZO TFT. Furthermore, the optimized biosensor had excellent reproducibility and selectivity for target RNA, demonstrating the potential for trace detection of biomarkers in early gastric cancer. In addition, the biosensor is scalable for detecting a wide range of biomarkers, providing a simple, high-performance strategy for achieving rapid RNA detection.