Whole urine-based multiple cancer diagnosis and metabolite profiling using 3D evolutionary gold nanoarchitecture combined with machine learning-assisted SERS

• DOI: 10.1016/j.snb.2024.135828
• Publication Date: 2024-04-15T15:44:10Z
• Authors: Muhammad Shalahud...; Vo Thi Nhat Linh; Jun-Yeong Yang; Chaewon Mun; Seunghun Lee; Sung-Gyu Park; In Woong Han; Samjin Choi; Min-Young Lee; Dong-Ho Kim; Ho Sang Jung
• Keywords: Nanoporous

To develop onsite applicable cancer diagnosis technologies, a noninvasive human biofluid detection method with high sensitivity and specificity is required, available for classifying from the normal group. Herein, three-dimensional evolutionary gold nanoarchitecture (3D-EGN) developed by forming Au nanosponge (AuS) on 96-well plate, followed decoration of nanoparticles (AuNPs) evolved nanolamination (AuNL) high-throughput urine sensing in liquid phase. The 3D-EGN exhibits not only strong electromagnetic field generated numerous hotspot regions between AuNPs further enhanced light scattering multigrain boundaries after lamination process, but also highly volumetric due to nanoporous structure AuS, which advantageous sensitive liquid-phase SERS detection. activity platform characterized using malachite green, showing limit 1.23 × 10-9 M phase, excellent uniformities both within single well well-to-well relative standard deviation (RSD) values about 10%. has been demonstrated whole clinical samples, proving effective molecular presence Brownian motion medium. Subsequently, metabolite candidates are investigated verify metabolic alternation multicancer, including pancreatic, prostate, lung, colorectal cancers, simultaneously them into five different groups, an accuracy 95.6%, machine-learning methods. integration nanomaterials conventional provides rapid multicancer diagnostic system opens new era diseases biofluids.