Literature DB >> 29641186

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.

Ruilian Xu1, Jun Tang1,2, Quantong Deng1, Wan He1, Xiujie Sun2, Ligang Xia1, Zhiqiang Cheng1, Lisheng He1, Shuyuan You1, Jintao Hu1, Yuxiang Fu1, Jian Zhu1, Yixin Chen1, Weina Gao2, An He2, Zhengyu Guo2, Lin Lin2, Hua Li2, Chaofeng Hu, Ruijun Tian2,3.   

Abstract

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.

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Year:  2018        PMID: 29641186     DOI: 10.1021/acs.analchem.8b00596

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  8 in total

1.  Laser capture microdissection-capillary zone electrophoresis-tandem mass spectrometry (LCM-CZE-MS/MS) for spatially resolved top-down proteomics: a pilot study of zebrafish brain.

Authors:  Rachele A Lubeckyj; Liangliang Sun
Journal:  Mol Omics       Date:  2022-02-21

2.  Mutual regulation of JAG2 and PRAF2 promotes migration and invasion of colorectal cancer cells uncoupled from epithelial-mesenchymal transition.

Authors:  Wan He; Jun Tang; Wenwen Li; Yong Li; Yi Mei; Lisheng He; Keli Zhong; Ruilian Xu
Journal:  Cancer Cell Int       Date:  2019-06-11       Impact factor: 5.722

Review 3.  Proteomic Profiling and Artificial Intelligence for Hepatocellular Carcinoma Translational Medicine.

Authors:  Nurbubu T Moldogazieva; Innokenty M Mokhosoev; Sergey P Zavadskiy; Alexander A Terentiev
Journal:  Biomedicines       Date:  2021-02-06

4.  Three-dimensional spatial transcriptomics uncovers cell type localizations in the human rheumatoid arthritis synovium.

Authors:  Denis Schapiro; Konstantin Carlberg; Britta Lötstedt; Ludvig Larsson; Sanja Vickovic; Franziska Hildebrandt; Marina Korotkova; Aase H Hensvold; Anca I Catrina; Peter K Sorger; Vivianne Malmström; Aviv Regev; Patrik L Ståhl
Journal:  Commun Biol       Date:  2022-02-11

5.  Hanging drop sample preparation improves sensitivity of spatial proteomics.

Authors:  Yumi Kwon; Paul D Piehowski; Rui Zhao; Ryan L Sontag; Ronald J Moore; Kristin E Burnum-Johnson; Richard D Smith; Wei-Jun Qian; Ryan T Kelly; Ying Zhu
Journal:  Lab Chip       Date:  2022-07-26       Impact factor: 7.517

6.  Dissecting the multi-omics atlas of the exosomes released by human lung adenocarcinoma stem-like cells.

Authors:  Hai-Tao Luo; Yuan-Yuan Zheng; Jun Tang; Li-Juan Shao; Yi-Heng Mao; Wei Yang; Xiao-Fei Yang; Yang Li; Rui-Jun Tian; Fu-Rong Li
Journal:  NPJ Genom Med       Date:  2021-06-14       Impact factor: 8.617

7.  Fast quantitative urinary proteomic profiling workflow for biomarker discovery in kidney cancer.

Authors:  Lin Lin; Quan Yu; Jiaxin Zheng; Zonglong Cai; Ruijun Tian
Journal:  Clin Proteomics       Date:  2018-12-22       Impact factor: 3.988

8.  Spatially resolved proteomics identify biomarkers from endometrial sentinel lymph nodes.

Authors:  Renliang Li; Shengtao Zhou
Journal:  Cell Rep Med       Date:  2021-06-15
  8 in total

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