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Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics.

ABSTRACT: The most widely used cancer animal model is the human-murine tumor xenograft. Unbiased molecular dissection of tumor parenchyma versus stroma in human-murine xenografts is critical for elucidating dysregulated protein networks/pathways and developing therapeutics that may target these two functionally codependent compartments. Although antibody-reliant technologies (e.g., immunohistochemistry, imaging mass cytometry) are capable of distinguishing tumor-proper versus stromal proteins, the breadth or extent of targets is limited. Here, we report an antibody-free targeted cross-species glycoproteomic (TCSG) approach that enables direct dissection of human tumor parenchyma from murine tumor stroma at the molecular/protein level in tumor xenografts at a selectivity rate presently unattainable by other means. This approach was used to segment/dissect and obtain the protein complement phenotype of the tumor stroma and parenchyma of the metastatic human lung adenocarcinoma A549 xenograft, with no need for tissue microdissection prior to mass-spectrometry analysis. An extensive molecular map of the tumor proper and the associated microenvironment was generated along with the top functional N-glycosylated protein networks enriched in each compartment. Importantly, immunohistochemistry-based cross-validation of selected parenchymal and stromal targets applied on human tissue samples of lung adenocarcinoma and normal adjacent tissue is indicative of a noteworthy translational capacity for this unique approach that may facilitate identifications of novel targets for next generation antibody therapies and development of real time preclinical tumor models.

SUBMITTER: Ye X

PROVIDER: S-EPMC5995176 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics.

Ye Xiaoying X Luke Brian T BT Wei Bih-Rong BR Kaczmarczyk Jan A JA Loncarek Jadranka J Dwyer Jennifer E JE Johann Donald J DJ Saul Richard G RG Nissley Dwight V DV McCormick Frank F Whiteley Gordon R GR Blonder Josip J

Oncotarget 20180529 41

The most widely used cancer animal model is the human-murine tumor xenograft. Unbiased molecular dissection of tumor parenchyma versus stroma in human-murine xenografts is critical for elucidating dysregulated protein networks/pathways and developing therapeutics that may target these two functionally codependent compartments. Although antibody-reliant technologies (e.g., immunohistochemistry, imaging mass cytometry) are capable of distinguishing tumor-proper versus stromal proteins, the breadth ...[more]

PMID: 29899869

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Project description:Glycosylation is among the most abundant and diverse protein post-translational modifications (PTMs) identified to date. The structural analysis of this PTM is challenging because of the diverse monosaccharides which are not conserved among organisms, the branched nature of glycans, their isomeric structures, and heterogeneity in the glycan distribution at a given site. Glycoproteomics experiments have adopted the traditional high-throughput LC-MSn proteomics workflow to analyze site-specific glycosylation. However, comprehensive computational platforms for data analyses are scarce. To address this limitation, we present a comprehensive, open-source, modular software for glycoproteomics data analysis called GlycoPAT (GlycoProteomics Analysis Toolbox; freely available from www.VirtualGlycome.org/glycopat). The program includes three major advances: (1) "SmallGlyPep," a minimal linear representation of glycopeptides for MSn data analysis. This format allows facile serial fragmentation of both the peptide backbone and PTM at one or more locations. (2) A novel scoring scheme based on calculation of the "Ensemble Score (ES)," a measure that scores and rank-orders MS/MS spectrum for N- and O-linked glycopeptides using cross-correlation and probability based analyses. (3) A false discovery rate (FDR) calculation scheme where decoy glycopeptides are created by simultaneously scrambling the amino acid sequence and by introducing artificial monosaccharides by perturbing the original sugar mass. Parallel computing facilities and user-friendly GUIs (Graphical User Interfaces) are also provided. GlycoPAT is used to catalogue site-specific glycosylation on simple glycoproteins, standard protein mixtures and human plasma cryoprecipitate samples in three common MS/MS fragmentation modes: CID, HCD and ETD. It is also used to identify 960 unique glycopeptides in cell lysates from prostate cancer cells. The results show that the simultaneous consideration of peptide and glycan fragmentation is necessary for high quality MSn spectrum annotation in CID and HCD fragmentation modes. Additionally, they confirm the suitability of GlycoPAT to analyze shotgun glycoproteomics data.

Dataset Information

Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics.

Publications

Direct molecular dissection of tumor parenchyma from tumor stroma in tumor xenograft using mass spectrometry-based glycoproteomics.

Similar Datasets

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