High-Sensitive Spatial Proteomics for Pancreatic Cancer Progression Analysis

Area of Science:

• Oncology
• Proteomics
• Biochemistry

Background:

• Pancreatic cancer diagnosis and treatment are challenging due to late symptom onset and limited early detection methods.
• Intraductal papillary mucinous neoplasms (IPMNs) are noninvasive precursors to invasive pancreatic ductal adenocarcinoma (PDAC).
• Understanding protein expression changes during progression from normal ductal (ND) cells to IPMN and PDAC is crucial for early detection.

Purpose of the Study:

• To present an optimized spatial tissue proteomics workflow, SP-Max (Spatial Proteomics Optimized for Maximum Sensitivity and Reproducibility in Minimal Sample).
• To maximize protein recovery and quantification from limited laser microdissected (LMD) samples of pancreatic tissues.
• To identify molecular differences and potential markers associated with pancreatic cancer progression.

Main Methods:

• Development and optimization of the SP-Max workflow for spatial proteomics.
• Application of SP-Max to Formalin-Fixed Paraffin-Embedded (FFPE) pancreatic tissue samples.
• Comparative proteomic analysis across normal ductal (ND), IPMN, and PDAC tissues.

Main Results:

• SP-Max workflow enabled identification of over 6000 proteins and quantification of over 5200 protein groups.
• Comparative analysis revealed critical molecular differences in protein pathways between ND, IPMN, and PDAC.
• Identified potential protein markers associated with the progression of pancreatic lesions.

Conclusions:

• SP-Max provides a systematic and reproducible approach for high-resolution proteomic analysis of pancreatic tissues.
• The workflow enhances the study of precancerous lesions and cancer progression.
• Findings contribute to understanding molecular changes in pancreatic cancer development and may inform early detection strategies.