Spatial proteomics dataset of single cells with translation activity (pS6) in tumour microenvironment

This dataset contains single-cell spatial proteomics measurements from three pleural mesothelioma (PM) tumour specimens (PM10, PM31, PM5), generated using MACSima Imaging Cyclic Staining (MICS) technology (Miltenyi Biotec). The dataset is provided as a Microsoft Excel file (.xlsx) containing three sheets, one per tumour specimen. Each sheet reports data organized by marker, cell type classification, and region of interest (ROI; minimum n=2 ROIs per specimen). Each row represents a single segmented cell, annotated with spatial coordinates (centroid x/y), ROI identity, and cell subtype classification. Cell types were assigned by applying pre-defined mean fluorescence intensity (MFI) thresholds with mutual exclusion rules. Protein expression levels were quantified using a panel of antibody-derived markers covering major tumour microenvironment compartments, including immune cell identity markers, tumour cell markers, translation activity and mitochondrial content Translation activity was inferred from pS6 antibody intensity and used to stratify CD4⁺FoxP3⁺ Treg cells into pS6-high and pS6-low subsets in downstream spatial analyses. Tissue metabolic states were defined based on TOMM22 expression, distinguishing TOMM22⁺ (metabolically active) from TOMM22⁻ (low-metabolic) regions. This dataset supports the analysis of spatial organisation, cell-cell proximity, and translational heterogeneity within the pleural mesothelioma tumour microenvironment,