2D vanadium disulfide nanosheets assisted ultrasensitive, rapid, and label-free electrochemical quantification of cancer biomarker (MMP-2)

Nanotechnology(2023)

引用 0|浏览0
暂无评分
摘要
Cancer is one of the most tormenting global health burdens reporting high mortality and morbidity worldwide. Matrix metalloproteinase 2 (MMP-2) protein has elevated expression for most types of cancers, including prostate and breast cancer. Therefore, accurate and specific detection of MMP-2 biomarker is crucial for screening, treatment, and prognosis of related cancer. In this work, we have proposed a label-free electrochemical biosensor for the detection of MMP-2 protein. This biosensor was fabricated using hydrothermally synthesized vanadium disulfide (VS2) nanosheets with monoclonal anti-MMP2 antibodies biofunctionalized using a suitable linker. The VS2 nanomaterials were synthesized hydrothermally at different reaction temperatures (140 & DEG;C, 160 & DEG;C, 180 & DEG;C and 200 & DEG;C) generating different morphologies from a 3D bulk cubic structure at 140 & DEG;C to 2D nanosheets at 200 & DEG;C. Owing to the advantages of 2D VS2 nanosheets with high surface-to-volume ratio, excellent electrochemical response and high antibody loading possibility, it was selected for fabricating an MMP-2 specific biosensor. The antibody-antigen binding event is analyzed by recording electrochemical impedance spectroscopy signals for different target MMP-2 protein concentrations. The sensitivity and lower limit of detection were 7.272 (& UDelta;R/R)(ng ml)(-1) cm(-2) and 0.138 fg ml(-1), respectively in 10 mM phosphate buffer saline for this proposed sensor. Further, interference studies were also performed which demonstrates the sensor to be highly selective against non-specific target proteins. This 2D VS2 nanosheet-based electrochemical biosensor is a sensitive, cost-effective, accurate, and selective solution for cancer diagnosis.
更多
查看译文
关键词
matrix metalloproteinase-2, 2D nanosheets, vanadium disulfide, electrochemical biosensors, cancer biomarker
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要