Home Journals Articles Updates About
CN
image
收藏切换
GBCDB: Gallbladder cancer transcriptome/single-cell sequencing data analysis and drug resistance prediction platform
收藏切换
Zheng LU1, 2, Fang-ming SONG3, Jing FU4, Chun-liang LIU4, *, Xiao-fei CHEN2, *
Acta Pharmaceutica Sinica | 2026, 61(7) : 2668 - 2674
Less
收藏切换
Acta Pharmaceutica Sinica | 2026, 61(7): 2668-2674
• Original Articles •
GBCDB: Gallbladder cancer transcriptome/single-cell sequencing data analysis and drug resistance prediction platform
Full
Zheng LU1, 2, Fang-ming SONG3, Jing FU4, Chun-liang LIU4, *, Xiao-fei CHEN2, *
Affiliations
  • 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2School of Pharmacy, Naval Medical University, Shanghai 200433, China
  • 3School of Life Sciences and Medical Engineering, Guangxi Medical University, Nanning 530021, China
  • 4National Center for Liver Cancer, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
Published: 2026-07-12 doi: 10.16438/j.0513-4870.2026-0179
Outline
收藏切换

Gallbladder cancer (GBC) is a highly invasive malignant tumor of the digestive system. Chemotherapy plays a crucial role in its advanced treatment, yet significant interpatient variability in drug response and prominent drug resistance issues persist. Currently, there is a lack of systematic transcriptomic databases and drug response prediction tools specifically tailored for GBC. To address this gap, we developed the Gallbladder Cancer Database (GBCDB, http://www.gbcdb.com/). This platform integrates five bulk-transcriptome datasets (126 samples) and one single-cell dataset (24 samples, encompassing 140 870 cells across eight major cell lineages), comprehensively covering neoplastic tissues, adjacent normal tissues, and cholecystitis tissues. GBCDB offers a user-friendly interface supporting flexible query modes for single-gene, dual-gene, and multi-gene analyses. The platform enables comprehensive comparative analysis through multiple visualization tools: Box plots display expression distributions across sample types, correlation scatter plots reveal gene associations, heatmaps visualize gene expression patterns, and Unified Manifold Approximation and Projection (UMAP) is applied to single-cell transcriptomic data. Additionally, the RefDNN model predicts resistance to five commonly used gallbladder cancer chemotherapeutics — gemcitabine, cisplatin, 5-fluorouracil, mitomycin C, and paclitaxel. GBCDB provides systematic data resources and analytical tools for molecular mechanism research and chemotherapy resistance assessment in gallbladder cancer, offering scientific foundations for developing personalized treatment strategies.

gallbladder cancer  /  database  /  transcriptomics  /  single-cell transcriptomics  /  drug resistance prediction
路峥, 宋方茗, 付静, 刘春良, 陈啸飞. GBCDB: 胆囊癌转录组/单细胞测序数据分析及耐药性预测平台. 药学学报, 2026 , 61 (7) : 2668 -2674 . DOI: 10.16438/j.0513-4870.2026-0179
Zheng LU, Fang-ming SONG, Jing FU, Chun-liang LIU, Xiao-fei CHEN. GBCDB: Gallbladder cancer transcriptome/single-cell sequencing data analysis and drug resistance prediction platform[J]. Acta Pharmaceutica Sinica, 2026 , 61 (7) : 2668 -2674 . DOI: 10.16438/j.0513-4870.2026-0179
Appendix
Less
Year 2026 volume 61 Issue 7
243
119
Cite this Article
BibTeX
Article Info
doi: 10.16438/j.0513-4870.2026-0179
  • Receive Date：2026-02-10
  • Online Date：2026-09-21
  • Published：2026-07-12
Article Data
Affiliations
History
  • Received：2026-02-10
  • Revised：2026-04-09
Affiliations
    1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
    2School of Pharmacy, Naval Medical University, Shanghai 200433, China
    3School of Life Sciences and Medical Engineering, Guangxi Medical University, Nanning 530021, China
    4National Center for Liver Cancer, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China
References
Share
https://castjournals.cast.org.cn/joweb/yxxb/EN/10.16438/j.0513-4870.2026-0179
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House