{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Zhang D"],"funding":["Joint Funds for the Innovation of Science and Technology, Fujian Province","Science Fund Program for Excellent Young Scientists of Fujian","Guiding Projects of Fujian Province","National Natural Science Foundation of China"],"pubmed_abstract":["The presence of a micropapillary (MPP) component is a crucial determinant of surgical strategies for lung adenocarcinoma (LUAD), yet reliable blood biomarkers for predicting MPP⁺ LUAD remain elusive. Here, we integrate 4D label-free quantitative proteomics, a nanomixing-enhanced microfluidic surface-enhanced Raman spectroscopy (SERS) platform, and machine learning to sensitively identify and validate blood protein biomarkers associated with MPP⁺ LUAD. Comparative proteomics reveal 44 differentially expressed proteins (DEPs) between MPP⁺ and MPP⁻ LUADs, with bioinformatics uncovering their roles in MPP⁺ LUAD formation. To enable sensitive, multiplex detection of 4 upregulated DEPs, the nanomixing effect is leveraged to enhance target protein-SERS barcode interactions while minimizing nonspe"],"journal":["Advanced science (Weinheim, Baden-Wurttemberg, Germany)"],"pagination":["e2501336"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12224922"],"repository":["biostudies-literature"],"pubmed_title":["Proteomics-Empowered Microfluidic-SERS Immunoassay for Identifying and Detecting Biomarkers of Micropapillary Lung Adenocarcinoma."],"pmcid":["PMC12224922"],"funding_grant_id":["2021Y9228","2023Y0053","2024J09030","12074069"],"pubmed_authors":["Zhang D","Chen Y","Xu H","Wang J","Peng K"],"additional_accession":[]},"is_claimable":false,"name":"Proteomics-Empowered Microfluidic-SERS Immunoassay for Identifying and Detecting Biomarkers of Micropapillary Lung Adenocarcinoma.","description":"The presence of a micropapillary (MPP) component is a crucial determinant of surgical strategies for lung adenocarcinoma (LUAD), yet reliable blood biomarkers for predicting MPP⁺ LUAD remain elusive. Here, we integrate 4D label-free quantitative proteomics, a nanomixing-enhanced microfluidic surface-enhanced Raman spectroscopy (SERS) platform, and machine learning to sensitively identify and validate blood protein biomarkers associated with MPP⁺ LUAD. Comparative proteomics reveal 44 differentially expressed proteins (DEPs) between MPP⁺ and MPP⁻ LUADs, with bioinformatics uncovering their roles in MPP⁺ LUAD formation. To enable sensitive, multiplex detection of 4 upregulated DEPs, the nanomixing effect is leveraged to enhance target protein-SERS barcode interactions while minimizing nonspe","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 May","modification":"2025-07-28T03:03:43.031Z","creation":"2025-07-28T03:03:43.031Z"},"accession":"S-EPMC12224922","cross_references":{"pubmed":["40318161"],"doi":["10.1002/advs.202501336"]}}