Artificially Intelligent Nanoarray Detects Various Cancers by Liquid Biopsy of Volatile Markers. Issue 17 (14th July 2022)

• Record Type: Journal Article
• Authors: Einoch Amor, Reef; Zinger, Assaf; Broza, Yoav Y.; Schroeder, Avi; Haick, Hossam
• Is Part Of: Advanced healthcare materials. Volume 11:Issue 17(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-07-14
• Subjects: breast cancer -- liquid biopsies -- machine‐ learning -- nanotechnology -- ovarian cancer -- pancreatic cancer -- sensors; Biomedical materials -- Periodicals; 610.28
• DOI: 10.1002/adhm.202200356
• Languages: English
• ISSNs: 2192-2640

Abstract

Abstract: Cancer is usually not symptomatic in its early stages. However, early detection can vastly improve prognosis. Liquid biopsy holds great promise for early detection, although it still suffers from many disadvantages, mainly searching for specific cancer biomarkers. Here, a new approach for liquid biopsies is proposed, based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray based on a varied set of chemi‐sensitive nano‐based structured films is developed and used to detect and stage cancer. As a proof‐of‐concept, three cancer models are tested showing high incidence and mortality rates in the population: breast cancer, ovarian cancer, and pancreatic cancer. The nanoarray has >84% accuracy, >81% sensitivity, and >80% specificity for early detection and >97% accuracy, 100% sensitivity, and >88% specificity for metastasis detection. Complementary mass spectrometry analysis validates these results. The ability to analyze such a complex biological fluid as blood, while considering data of many VOCs at a time using the artificially intelligent nanoarray, increases the sensitivity of predictive models and leads to a potential efficient early diagnosis and disease‐monitoring tool for cancer. Abstract : Early cancer detection can immensely improve prognosis. Here, a potential early diagnosis and disease‐monitoring tool is proposed based on volatile organic compound (VOC) patterns in the blood headspace. An artificial intelligence nanoarray in combination with machine learning models gives high performances for early cancer (>84% accuracy) and metastasis (>97% accuracy) detection.