Minjoong Kim (Department of Medical Informatics and Statistics, BK21 project, University of Ulsan College of Medicine, Seoul 05505, Korea)

Minjoong Kim (Department of Medical Informatics and Statistics, BK21 project, University of Ulsan College of Medicine, Seoul 05505, Korea)

Bokyung Kim (Department of Medical Informatics and Statistics, BK21 project, University of Ulsan College of Medicine, Seoul 05505, Korea)

Lee Yelin (Department of Medical Informatics and Statistics, BK21 project, University of Ulsan College of Medicine, Seoul 05505, Korea)

Jihyeon Kim (Department of Medical Informatics and Statistics, BK21 project, University of Ulsan College of Medicine, Seoul 05505, Korea)

Jiyoung Yu (Convergence Medicine Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, 05505, Korea)

Kyunggon Kim (Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Brain Korea 21 Project, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Korea)

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with limited effective targeted therapies. Mass spectrometry (MS)-based proteomics enables comprehensive profiling of clinical tissues and critical insights into tumor biology. In this study, we performed quantitative MS analysis to compare the proteomes of FFPE samples from two PDAC patient cohorts: those treated with neoadjuvant chemotherapy (NACT, n=34) and those undergoing upfront surgery (n=30). Proteins were extracted using adaptive focused acoustics (AFA, Covaris S220) and digested via S-Trap microcolumns for optimal recovery. Peptides were analyzed by high-resolution liquid chromatography-tandem MS (LC-MS/MS) on a Thermo Scientific Eclipse Tribrid Orbitrap system, allowing deep proteome coverage and sensitive quantification. Data were processed using MaxQuant, resulting in 3,870 quantified proteins after normalization and missing value imputation. Multivariate analyses, including partial least squares-discriminant analysis (PLS-DA) and volcano plots, revealed clear separation between NACT and upfront surgery groups. Gene ontology analysis indicated NACT-treated tumors were enriched in apoptosis-related proteins and showed reduced expression of metastatic markers, while upfront surgery samples upregulated pathways involved in cell adhesion, migration, and proliferation. Furthermore, normal tissues from both groups displayed distinct proteomic patterns, suggesting systemic chemotherapy effects. Our findings underscore the value of advanced MS-based proteomics for elucidating therapy-induced molecular changes and for identifying clinically relevant biomarkers in PDAC.

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