Dataset Information

A Micro-Quantitative and FFPE-compatible Workflow for Im- 2 munohistochemistry-Guided Spatial Proteomic Analysis of 3 Cellular Subpopulations within the Tumor Microenvironment

ABSTRACT: Understanding the spatial proteomic landscape of human tumors is essential for dissecting cellular heterogeneity and microenvironmental interactions in cancer biology. Traditional bulk proteomic approaches, however, obscure spatial information and average out signals from distinct cell populations. Here, we present a detailed and reproducible micro-quantitative protocol for spatially resolved proteomic analysis of specific cellular subpopulations isolated from immunohistochemistry (IHC)–labeled formalin-fixed paraffin-embedded (FFPE) tissue sections using laser microdissection (LMD). By combining IHC staining to visually define phenotypically distinct cells within preserved tissue architecture and precise LMD capture, approximately 2000 target cells can be isolated per sample for downstream proteomic quantification. Despite the ultra-low input, optimized lysis and digestion steps ensure consistent peptide recovery and highly reproducible label-free LC–MS/MS data across replicates. Integrating immunohistochemistry staining-guided spatial sampling with ultrasensitive quantitative proteomics, this workflow enables reliable cell-type-specific profiling directly within human tumor tissues. The protocol bridges histopathology and proteomics, offering a practical framework for translational research exploring spatial protein signatures and tumor microenvironmental heterogeneity.

ORGANISM(S): Homo Sapiens

SUBMITTER: Yang Chen

PROVIDER: PXD078338 | iProX | Thu May 14 00:00:00 GMT+01:00 2026

REPOSITORIES: iProX

ACCESS DATA

Similar Datasets

Project description:Aims: Steroid-induced osteonecrosis of the femoral head (SIONFH) is a debilitating condition often accompanied by cystic change in the affected bone. Previous studies and our clinical observation have suggested the potential for tissue repair within the cystic change, but the underlying cellular mechanisms remain unclear. This study aims to investigate the heterogeneity of cells in the cystic change region, focusing on chondrocytes and endothelial cells, using single-cell RNA sequencing (scRNA-seq) and subsequent histological validation. Method: Cystic change tissues were obtained from patients undergoing total hip arthroplasty. Single-cell RNA sequencing was performed to identify distinct cell populations, particularly chondrocytes and endothelial cells. Alcian blue staining was employed to detect chondrocytes, while immunohistochemistry (IHC) was used to verify the presence of repair-associated chondrocytes. Additionally, HE staining was performed to further analyze tissue architecture like blood vessels. Results: ScRNA-seq analysis identified two major cell types in the cystic change region: endothelial cells involved in angiogenesis and chondrocytes, which included subpopulations associated with cartilage repair. Alcian blue staining showed strong cartilage matrix staining within the cystic change. Immunohistochemistry further validated the expression of repair-associated markers in the chondrocyte population, suggesting active cartilage repair. Cellular communication analysis revealed intercellular interactions between reparative chondrocyte via matrix proteins (FN1, COL1A1) and integrin receptors on angiogenic endothelial cell, suggesting their potential collaboration in the repair process. Conclusion: This study highlights the positive effects of cystic change region of SIONFH in the process of repair based on clinical observations and single-cell RNA sequencing technology. The presence of functionally distinct cell populations, including angiogenic endothelial cells and repair-associated chondrocytes, within cystic change region of SIONFH. The findings suggest a biological basis for repair in the cystic change tissue, providing insights that may inform future therapeutic strategies targeting bone and cartilage regeneration in osteonecrosis.

Dataset Information

A Micro-Quantitative and FFPE-compatible Workflow for Im- 2 munohistochemistry-Guided Spatial Proteomic Analysis of 3 Cellular Subpopulations within the Tumor Microenvironment

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets