임은경 (한국생명공학연구원)

한빛사논문

조회191

한국생명공학연구원

CV File 342 kb

Biosens. Bioelectron., May 01 2024, 258 S0956-5663(24)00352-X | https://doi.org/10.1016/j.bios.2024.116347 Deep learning-assisted monitoring of trastuzumab efficacy in HER2-Overexpressing breast cancer via SERS immunoassays of tumor-derived urinary exosomal biomarkers

Jinyoung Kim ^a, Hye Young Son ^b,c,d,e, Sojeong Lee ^a, Hyun Wook Rho^b, Ryunhyung Kim^a, Hyein Jeong ^a, Chaewon Park ^a, Byeonggeol Mun ^a, Yesol Moon^a, Eunji Jeong ^a, Eun-Kyung Lim ^f,g,h, Seungjoo Haam ^a

^aDepartment of Chemical and Biomolecular Engineering, Yonsei University, Yonsei-ro 50, Seoul, 120-749, Republic of Korea

^bDepartment of Radiology, Yonsei University, Seoul, 03772, Republic of Korea

^cSeverance Biomedical Science Institute, Yonsei University, Seoul, 03772, Republic of Korea

^dYUHS-KRIBB Medical Convergence Research Institute, Yonsei University, Seoul, 03772, Republic of Korea

^eDepartment of Biochemistry & Molecular Biology, College of Medicine, Yonsei University, Seoul, 03722, Republic of Korea

^fBionanotechnology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141, Republic of Korea

^gDepartment of Nanobiotechnology, KRIBB School of Biotechnology, University of Science and Technology (UST), Daejeon, 34113, Republic of Korea

^hSchool of Pharmacy, Sungkyunkwan University, Suwon, 16419, Republic of Korea

Corresponding authors: Eun-Kyung Lim, Seungjoo Haam

Abstract

Monitoring drug efficacy is significant in the current concept of companion diagnostics in metastatic breast cancer. Trastuzumab, a drug targeting human epidermal growth factor receptor 2 (HER2), is an effective treatment for metastatic breast cancer. However, some patients develop resistance to this therapy; therefore, monitoring its efficacy is essential. Here, we describe a deep learning-assisted monitoring of trastuzumab efficacy based on a surface-enhanced Raman spectroscopy (SERS) immunoassay against HER2-overexpressing mouse urinary exosomes. Individual Raman reporters bearing the desired SERS tag and exosome capture substrate were prepared for the SERS immunoassay; SERS tag signals were collected to prepare deep learning training data. Using this deep learning algorithm, various complicated mixtures of SERS tags were successfully quantified and classified. Exosomal antigen levels of five types of cell-derived exosomes were determined using SERS-deep learning analysis and compared with those obtained via quantitative reverse transcription polymerase chain reaction and western blot analysis. Finally, drug efficacy was monitored via SERS-deep learning analysis using urinary exosomes from trastuzumab-treated mice. Use of this monitoring system should allow proactive responses to any treatment-resistant issues.

논문정보

형식Research article
게재일2024년 05월 (BRIC 등록일 2024-05-13)
연구진국내(교신)+국외 연구진
분야 바이오·의료융합 > 바이오센싱 및 나노바이오물질

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