Spatial proteome profiling by immunohistochemistry-based laser capture microdissection and data-independent acquisition proteomics.
Anal Chim Acta
; 1127: 140-148, 2020 Aug 29.
Article
em En
| MEDLINE
| ID: mdl-32800117
Understanding the tumor heterogeneity through spatially resolved proteome profiling is important for biomedical research and clinical application. Laser capture microdissection (LCM) is a powerful technology for exploring local cell populations without losing spatial information. Conventionally, tissue sections are stained with hematoxylin and eosin (H&E) for cell-type identification before LCM. However, it generally requires experienced pathologists to distinguish different cell types, which limits the application of LCM to broad cancer research field. Here, we designed an immunohistochemistry (IHC)-based workflow for cell type-resolved proteome analysis of tissue samples. Firstly, targeted cell type was marked by IHC using antibody targeting cell-type specific marker to improve accuracy and efficiency of LCM. Secondly, to increase protein recovery from chemically crosslinked IHC tissues, we optimized a decrosslinking procedure to seamlessly combine with the integrated spintip-based sample preparation technology SISPROT. This newly developed approach, termed IHC-SISPROT, has comparable performance as H&E staining-based proteomic analysis. High sensitivity and reproducibility of IHC-SISPROT were achieved by combining with data independent acquisition proteomics. More than 3500 proteins were identified from only 0.2â¯mm2 and 12⯵m thickness of hepatocellular carcinoma (HCC) tissue section. Furthermore, using 5â¯mm2 and 12⯵m thickness of HCC tissue section, 6660 and 6052 protein groups were quantified from cancer cells and cancer-associated fibroblasts (CAFs) by the IHC-SISPROT workflow. Bioinformatic analysis revealed the enrichment of cell type-specific ligands and receptors and potentially new communications between cancer cells and CAFs by these signaling proteins. Therefore, IHC-SISPROT is a sensitive and accurate proteomic approach for spatial profiling of cell type-specific proteome from tissues.
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Base de dados:
MEDLINE
Assunto principal:
Carcinoma Hepatocelular
/
Neoplasias Hepáticas
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article