Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.
IF: 8.008
Cited by: 29


Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm2 and 10 μm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm2 and 10 μm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.



MeSH terms

Colonic Neoplasms


Xu, Ruilian
Tang, Jun
Deng, Quantong
He, Wan
Sun, Xiujie
Xia, Ligang
Cheng, Zhiqiang
He, Lisheng
You, Shuyuan
Hu, Jintao
Fu, Yuxiang
Zhu, Jian
Chen, Yixin
Gao, Weina
He, An
Guo, Zhengyu
Lin, Lin
Li, Hua
Hu, Chaofeng
Tian, Ruijun

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