TY - JOUR
T1 - Discovery of Pancreatic Ductal Adenocarcinoma-Related Aberrant Glycosylations
T2 - A Multilateral Approach of Lectin Microarray-Based Tissue Glycomic Profiling With Public Transcriptomic Datasets
AU - Wagatsuma, Takanori
AU - Nagai-Okatani, Chiaki
AU - Matsuda, Atsushi
AU - Masugi, Yohei
AU - Imaoka, Masako
AU - Yamazaki, Ken
AU - Sakamoto, Michiie
AU - Kuno, Atsushi
N1 - Funding Information:
We are grateful to Dr. Yukio Hattori (JBA) for helpful discussion. We thank Ms. Maki Iwata (Keio University) for prepared pathological sections. We thank Mr. Shuichi Kakuda (JBA) for prepared anti-basigin antibody labeled with biotin. We would like to thank Editage (www.editage.com) for English language editing. Funding. This research was supported by the Project for Utilizing Glycans in the Development of Innovative Drug Discovery Technologies (grant number JP19ae0101020, JP19ae0101021, and JP19ae0101023) from the Japan Agency for Medical Research and Development (AMED).
Funding Information:
This research was supported by the Project for Utilizing Glycans in the Development of Innovative Drug Discovery Technologies (grant number JP19ae0101020, JP19ae0101021, and JP19ae0101023) from the Japan Agency for Medical Research and Development (AMED).
Publisher Copyright:
© Copyright © 2020 Wagatsuma, Nagai-Okatani, Matsuda, Masugi, Imaoka, Yamazaki, Sakamoto and Kuno.
PY - 2020/3/13
Y1 - 2020/3/13
N2 - Aberrant protein glycosylation is one of the most notable features in cancerous tissues, and thereby glycoproteins with disease-relevant glycosylation alterations are fascinating targets for the development of biomarkers and therapeutic agents. For this purpose, a reliable strategy is needed for the analysis of glycosylation alterations occurring on specific glycoproteins during the progression of cancer. Here, we propose a bilateral approach combining lectin microarray-based tissue glycomic profiling and database-derived transcriptomic datasets. First, lectin microarray was used to perform differential glycomic profiling of crude extracts derived from non-tumor and tumor regions of frozen tissue sections from pancreatic ductal adenocarcinoma (PDAC). This analysis revealed two notable tissue glycome alterations in PDAC samples: increases in sialylated glycans and bisecting N-acetylglucosamine and a decrease in ABO blood group antigens. To examine aberrations in the glycosylation machinery related to these glycomic alterations, we next employed public datasets of gene expression profiles in cancerous and normal pancreases provided by The Cancer Genome Atlas and the Genotype-Tissue Expression projects, respectively. In this analysis, glycosyltransferases responsible for the glycosylation alterations showed aberrant gene expression in the cancerous tissues, consistent with the tissue glycomic profiles. The correlated alterations in glycosyltransferase expression and tissue glycomics were then evaluated by differential glycan profiling of a membrane N-glycoprotein, basigin, expressed in tumor and non-tumor pancreatic cells. The focused differential glycomic profiling for endogenous basigin derived from non-tumor and cancerous regions of PDAC tissue sections demonstrated that PDAC-relevant glycan alterations of basigin closely reflected the notable features in the disease-specific alterations in the tissue glycomes. In conclusion, the present multi-omics strategy using public transcriptomic datasets and experimental glycomic profiling using a tiny amount of clinical specimens successfully demonstrated that basigin is a representative N-glycoprotein that reflects PDAC-related aberrant glycosylations. This study indicates the usefulness of large public data sets such as the gene expression profiles of glycosylation-related genes for evaluation of the highly sensitive tissue glycomic profiling results. This strategy is expected to be useful for the discovery of novel glyco-biomarkers and glyco-therapeutic targets.
AB - Aberrant protein glycosylation is one of the most notable features in cancerous tissues, and thereby glycoproteins with disease-relevant glycosylation alterations are fascinating targets for the development of biomarkers and therapeutic agents. For this purpose, a reliable strategy is needed for the analysis of glycosylation alterations occurring on specific glycoproteins during the progression of cancer. Here, we propose a bilateral approach combining lectin microarray-based tissue glycomic profiling and database-derived transcriptomic datasets. First, lectin microarray was used to perform differential glycomic profiling of crude extracts derived from non-tumor and tumor regions of frozen tissue sections from pancreatic ductal adenocarcinoma (PDAC). This analysis revealed two notable tissue glycome alterations in PDAC samples: increases in sialylated glycans and bisecting N-acetylglucosamine and a decrease in ABO blood group antigens. To examine aberrations in the glycosylation machinery related to these glycomic alterations, we next employed public datasets of gene expression profiles in cancerous and normal pancreases provided by The Cancer Genome Atlas and the Genotype-Tissue Expression projects, respectively. In this analysis, glycosyltransferases responsible for the glycosylation alterations showed aberrant gene expression in the cancerous tissues, consistent with the tissue glycomic profiles. The correlated alterations in glycosyltransferase expression and tissue glycomics were then evaluated by differential glycan profiling of a membrane N-glycoprotein, basigin, expressed in tumor and non-tumor pancreatic cells. The focused differential glycomic profiling for endogenous basigin derived from non-tumor and cancerous regions of PDAC tissue sections demonstrated that PDAC-relevant glycan alterations of basigin closely reflected the notable features in the disease-specific alterations in the tissue glycomes. In conclusion, the present multi-omics strategy using public transcriptomic datasets and experimental glycomic profiling using a tiny amount of clinical specimens successfully demonstrated that basigin is a representative N-glycoprotein that reflects PDAC-related aberrant glycosylations. This study indicates the usefulness of large public data sets such as the gene expression profiles of glycosylation-related genes for evaluation of the highly sensitive tissue glycomic profiling results. This strategy is expected to be useful for the discovery of novel glyco-biomarkers and glyco-therapeutic targets.
KW - ABO blood group antigen
KW - Genotype-Tissue Expression (GTEx)
KW - The Cancer Genome Atlas (TCGA)
KW - basigin/CD147
KW - glycosylation
KW - glycosyltransferase
KW - lectin microarray
KW - multi-omics
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U2 - 10.3389/fonc.2020.00338
DO - 10.3389/fonc.2020.00338
M3 - Article
AN - SCOPUS:85082713965
SN - 2234-943X
VL - 10
JO - Frontiers in Oncology
JF - Frontiers in Oncology
M1 - 338
ER -