Mxene@PEG Hybrid Molecularly Imprinted Electrochemical Interface for Ultrasensitive Detection of Mucin-1
Microchemical Journal, cilt.230, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 230
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.microc.2026.119877
- Dergi Adı: Microchemical Journal
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, Chemical Abstracts Core, Chimica, Index Islamicus, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO)
- Anahtar Kelimeler: Breast cancer, Electrochemistry, Molecularly imprinted polymers, Mucin-1, MXene
- Ankara Üniversitesi Adresli: Evet
Özet
Breast cancer is among the most prevalent cancers in women and poses significant global health challenges. In various types of cancer, such as those affecting especially the breast, pancreas, and lung, the cells that constitute the tumor tissues have been observed to produce a transmembrane glycoprotein known as Mucin-1 (MUC-1). This study presents an electrochemical sensor with great selectivity and sensitivity for MUC-1 detection, characterized by the exceptional properties of a hybrid system comprising MXene and molecularly imprinted polymer (MIP). The surface of a screen printed carbon electrode (SPCE) was modified using a solution of MXene and polyethylene glycol (PEG), followed by the formation of a MIP layer through electrochemical polymerization utilizing pyrrole as the functional monomer. Under optimal settings, the MIP-based nanosensor MUC-1 exhibited a linear response within the concentration range of 5–100 fg/mL. The performance of the assay was characterized by a sensitivity of 0.17 fg/mL, as demonstrated in standard solutions. The LOD of the assay was established at 1.47 fg/mL when applied to commercial serum samples, thereby providing quantitative sensitivity to detect low-abundance analytes. The selectivity of the sensor was analyzed in the presence of diverse interfering agents, and the computations of the selectivity coefficient (k) were conducted using biomarkers with analogous protein structures. Consequently, upon examination of additional validation parameters, the findings demonstrated high reproducibility, excellent selectivity, and stability. This study demonstrates the potential for MUC-1 detection in clinical and point-of-care settings, and also provides as a framework for the identification of other biomarkers.