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Nose-on-Chip Nanobiosensors for Early Detection of Lung Cancer Breath Biomarkers
ACS Sensors ( IF 8.2 ) Pub Date : 2024-09-09 , DOI: 10.1021/acssensors.4c01524 Vishal Chaudhary 1, 2 , Bakr Ahmed Taha 3 , Lucky 4 , Sarvesh Rustagi 5 , Ajit Khosla 6 , Pagona Papakonstantinou 7 , Nikhil Bhalla 7, 8
ACS Sensors ( IF 8.2 ) Pub Date : 2024-09-09 , DOI: 10.1021/acssensors.4c01524 Vishal Chaudhary 1, 2 , Bakr Ahmed Taha 3 , Lucky 4 , Sarvesh Rustagi 5 , Ajit Khosla 6 , Pagona Papakonstantinou 7 , Nikhil Bhalla 7, 8
Affiliation
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Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as a promising noninvasive nose-on-chip technique for the early detection of lung cancer through monitoring diversified biomarkers such as volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes the state-of-the-art breath-based lung cancer diagnosis employing chemiresistive-module nanobiosensors supported by theoretical findings. It unveils the fundamental mechanisms and biological basis of breath biomarker generation associated with lung cancer, technological advancements, and clinical implementation of nanobiosensor-based breath analysis. It explores the merits, challenges, and potential alternate solutions in implementing these nanobiosensors in clinical settings, including standardization, biocompatibility/toxicity analysis, green and sustainable technologies, life-cycle assessment, and scheming regulatory modalities. It highlights nanobiosensors’ role in facilitating precise, real-time, and on-site detection of lung cancer through breath analysis, leading to improved patient outcomes, enhanced clinical management, and remote personalized monitoring. Additionally, integrating these biosensors with artificial intelligence, machine learning, Internet-of-things, bioinformatics, and omics technologies is discussed, providing insights into the prospects of intelligent nose-on-chip lung cancer sniffing nanobiosensors. Overall, this review consolidates knowledge on breathomic biosensor-based lung cancer screening, shedding light on its significance and potential applications in advancing state-of-the-art medical diagnostics to reduce the burden on hospitals and save human lives.
中文翻译：
用于早期检测肺癌呼吸生物标志物的鼻片纳米生物传感器
肺癌仍然是一个全球健康问题，需要开发无创、及时、选择性和即时诊断工具。相应地，使用纳米生物传感器进行呼吸分析已成为一种有前途的无创鼻片技术，通过监测呼出气中的挥发性有机化合物/气体等多种生物标志物来早期检测肺癌。这篇全面的综述总结了采用化学电阻模块纳米生物传感器进行最先进的基于呼吸的肺癌诊断，并得到理论结果的支持。它揭示了与肺癌相关的呼吸生物标志物生成的基本机制和生物学基础、技术进步以及基于纳米生物传感器的呼吸分析的临床实施。它探讨了在临床环境中实施这些纳米生物传感器的优点、挑战和潜在的替代解决方案，包括标准化、生物相容性/毒性分析、绿色和可持续技术、生命周期评估和策划监管模式。它强调了纳米生物传感器在通过呼吸分析促进肺癌的精确、实时和现场检测方面的作用，从而改善患者的治疗结果、增强临床管理和远程个性化监测。此外，还讨论了将这些生物传感器与人工智能、机器学习、物联网、生物信息学和组学技术相结合，为智能鼻片肺癌嗅探纳米生物传感器的前景提供了见解。 总的来说，这篇综述巩固了基于呼吸生物传感器的肺癌筛查知识，阐明了其在推进最先进的医疗诊断以减轻医院负担和拯救人类生命方面的重要性和潜在应用。
更新日期：2024-09-09
中文翻译：
用于早期检测肺癌呼吸生物标志物的鼻片纳米生物传感器
肺癌仍然是一个全球健康问题，需要开发无创、及时、选择性和即时诊断工具。相应地，使用纳米生物传感器进行呼吸分析已成为一种有前途的无创鼻片技术，通过监测呼出气中的挥发性有机化合物/气体等多种生物标志物来早期检测肺癌。这篇全面的综述总结了采用化学电阻模块纳米生物传感器进行最先进的基于呼吸的肺癌诊断，并得到理论结果的支持。它揭示了与肺癌相关的呼吸生物标志物生成的基本机制和生物学基础、技术进步以及基于纳米生物传感器的呼吸分析的临床实施。它探讨了在临床环境中实施这些纳米生物传感器的优点、挑战和潜在的替代解决方案，包括标准化、生物相容性/毒性分析、绿色和可持续技术、生命周期评估和策划监管模式。它强调了纳米生物传感器在通过呼吸分析促进肺癌的精确、实时和现场检测方面的作用，从而改善患者的治疗结果、增强临床管理和远程个性化监测。此外，还讨论了将这些生物传感器与人工智能、机器学习、物联网、生物信息学和组学技术相结合，为智能鼻片肺癌嗅探纳米生物传感器的前景提供了见解。 总的来说，这篇综述巩固了基于呼吸生物传感器的肺癌筛查知识，阐明了其在推进最先进的医疗诊断以减轻医院负担和拯救人类生命方面的重要性和潜在应用。
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