Clinicopathological and prognostic significance of GPC3 in human breast cancer and its 3D structure prediction

被引:0
作者
Utpal Dev Barman
Subbroto Kumar Saha
Md. Ashraful Kader
Mohammad Abu Hena Mostofa Jamal
Satya Priya Sharma
Abdus Samad
Md. Shahedur Rahman
机构
[1] Jashore University of Science and Technology,Department of Genetic Engineering and Biotechnology
[2] Konkuk University,Department of Stem Cell and Regenerative Biotechnology
[3] Islamic University,Department of Biotechnology and Genetic Engineering
[4] Chonbuk National University Medical School,Department of Biomedical Sciences
[5] Chonbuk National University,Department of Gynecology and Obstetrics
[6] Johns Hopkins School of Medicine,undefined
来源
Network Modeling Analysis in Health Informatics and Bioinformatics | 2020年 / 9卷
关键词
GPC3; Breast cancer; Prognostic significance; 3D structure;
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摘要
Glypican-3 (GPC3) is a heparan sulfate proteoglycan that may function as a tumor suppressor in breast cancer (BC). To evaluate the prognostic value of GPC3 in BC, systematic analysis was performed in this study. To evaluate gene alteration during breast carcinogenesis, GPC3 expression was analyzed using the Oncomine, GENT, UALCAN, bcGenExMiner, and UCSC Xena databases. The prognostic role of GPC3 in BC was investigated using KM Plotter and PrognoScan databases. Promoter methylation status and heat map of GPC3 were determined using UALCAN and UCSC Xena. GPC3 expression was significantly downregulated in BC compared to that in normal tissues and was correlated with prognosis. However, estrogen receptor and progesterone receptor status were positively correlated with GPC3 expression, whereas basal-like status, triple-negative breast cancer status, and Scarff, Bloom, and Richardson grade criteria were negatively correlated with GPC3 expression. Further analysis indicated that GPC3 was correlated with Ras-association domain family 6 (RASSF6) expression in BC tissues. GPC3 may thus be considered a significant marker for predicting BC prognosis along with RASSF6. Comparative protein modeling of GPC3 was performed using a FASTA formatted sequence from NCBI, in Swiss model, and GPC3 was visualized using PyMOL tools. The GPC3 active site was identified with CASTp server. The Ramachandran plot in PROCHECK showed significant scores for the protein model in its most favored regions. ProSA server indicated the high accuracy of the protein model. However, large-scale and comprehensive studies are needed to clarify these results.
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