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In this study, we systematically evaluated the nanoLC-Zeno TOF platform using data-independent acquisition (DIA) and identified 3,142 to 7,059 protein groups from 1 to 200 ng of standard K562 digest. Additionally, a targeted acquisition strategy detected 184 peptides with enhanced signals using Zeno activation. To achieve cell type-resolved spatial proteomics, we developed a workflow integrating image-guided laser capture microdissection for the analysis of gastric cancer tissue. A 30-minute nanoLC gradient facilitated the quantification of 2,514 proteins from 0.2 mm 2 regions representing cancer cells, cancer-associated fibroblasts (CAFs), and immune cells, as defined by multiplex immunohistochemistry (mIHC). This spatial proteomics approach revealed cellular heterogeneity within the tumor microenvironment of a clinical gastric cancer sample, and targeted validation identified the differential expression of 12 cancer-associated proteins comprising 103 peptides between cancer cell-enriched and CAF-enriched regions. This workflow offers a practical strategy for spatial proteomic analysis of clinical tissue samples.
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Zhang et al. (2026) studied this question.
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