Electrochemical biosensors for Calreticulin in lung Cancer.
1/5 보강
Electrochemical biosensors represent an advanced and novel technology for the sensitive and specific detection of clinically relevant biomarkers.
APA
Afzal O, Altharawi A, et al. (2026). Electrochemical biosensors for Calreticulin in lung Cancer.. Clinica chimica acta; international journal of clinical chemistry, 585, 120904. https://doi.org/10.1016/j.cca.2026.120904
MLA
Afzal O, et al.. "Electrochemical biosensors for Calreticulin in lung Cancer.." Clinica chimica acta; international journal of clinical chemistry, vol. 585, 2026, pp. 120904.
PMID
41692133 ↗
Abstract 한글 요약
Electrochemical biosensors represent an advanced and novel technology for the sensitive and specific detection of clinically relevant biomarkers. Of these, serum calreticulin (CRT), an indicator of immunogenic cell death (ICD), has great potential as a biomarker in lung cancer. Clinical studies have reported that soluble calreticulin is significantly higher in the serum of lung cancer patients than healthy control groups and is directly proportional to pathologic grade and histologic classification. Recent improvements in the design of electrochemical biosensors, including the use of aptamers as bioreceptors and nanomaterial-enhanced signal transduction pathways, have enabled the detection of femtomolar-to-attomolar levels of CRT in complex biomatrices without the need for labor-intensive sample preprocessing. This ICD pathway is defined by pre-apoptotic exposure of CRT on the cell membrane, which acts as an "eat-me" signal that leads to antigen-presenting cell recognition and activation of adaptive immune responses that are essential in host defense against tumors. In this review, we synthesized the current knowledge on the development of electrochemical biosensors, CRT biology in immunogenic cell death signaling, and serum-based principles of biomarker detection that can be applied in lung cancer diagnosis. In the future, it is possible to add microfluidic multiplexing platforms to perform multi-biomarker analysis simultaneously, develop point-of-care devices based on artificial intelligence-assisted data interpretation, and conduct clinical validation programs that determine diagnostic reference intervals in various patient groups. Such technological improvements will most likely support the early detection of cancer, better risk stratification of patients, and refinement of clinical laboratory workflows for accurate oncology practice.
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