Published June 21, 2025
| Version v1.1
Dataset
Open
Targeting ARPC1B+ Cancer Stem Cells to Sensitize Pancreatic Cancer to Gemcitabine Treatment
Authors/Creators
Authors/Creators
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Wu, Yang
(Data manager)1
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Zhang, Jianpeng
(Data curator)2
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zhu, weixiong
(Data collector)3
- Zhu, Xinrui (Data collector)4
- Liu, Yi (Researcher)5
- Wang, Xin (Researcher)6
- Zhao, Tianyu (Researcher)7
- Zhang, Chun8
- Zhang, Zili (Researcher)9
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shi, wenjie
(Contact person)10
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Shi, Run
(Contact person)11, 12
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zhou, zhaokai
(Contact person)13
- Xu, Shaohui (Contact person)14
- 1. Pancreas Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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2.
First Affiliated Hospital of Guangzhou Medical University
- 3. The Second Clinical Medical College, Lanzhou University, Lanzhou, China
- 4. Department of Hepatobiliary and Pancreatic Surgery, The Third Affiliated Hospital of Suzhou University
- 5. Department of Oncology, The Second Hospital of Dalian Medical University
- 6. Department of Oncology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research
- 7. Institute of Social Medicine and Epidemiology, Medical University of Graz
- 8. Department of Gastroenterology, Affiliated Hospital of Nanjing University of Chinese Medicine
- 9. State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture, Nanjing University of Chinese Medicine
- 10. Molecular and Experimental Surgery, Clinic for General-, Visceral -, Vascular- and Transplantation Surgery, Medical Faculty and University Hospital Magdeburg, Otto-von-Guericke University, Magdeburg, Germany
-
11.
Jiangsu Province Hospital
- 12. The First Affiliated Hospital of Nanjing Medical University
- 13. Department of Urology, The Second Xiangya Hospital of Central South University, Changsha, China
- 14. Institute of Functional Nano & Soft Materials (FUNSOM), Soochow University
Description
Pancreatic cancer is a highly aggressive malignancy and poses significant therapeutic challenges due to resistance to conventional therapies. Cancer stem cells (CSCs) act as key contributors to this resistance with their self-renewal capacity. In this study, we identified the ARPC1B+ CSC subpopulation specifically resistant to gemcitabine through integrated analysis of scRNA-seq and bulk RNA-seq data from pancreatic cancer samples. Additionally, ARPC1B expression was significantly elevated in gemcitabine-resistant CSCs and correlated with higher mutation burden and intra-tumor heterogeneity. Molecular docking analysis identified CK-636 as a potential ARPC1B-targeting agent with high affinity. Ex vivo and in vivo experiments demonstrated that combinational therapy of gemcitabine along with CK-636 could significantly inhibit tumor growth compared to gemcitabine alone, indicating that targeting ARPC1B+ CSCs can sensitize pancreatic cancer to gemcitabine treatment. These findings highlight ARPC1B+ CSCs as a promising therapeutic target for overcoming gemcitabine resistance in pancreatic cancer.
Notes (English)
- We collected six scRNA-seq datasets of pancreatic ductal adenocarcinoma (PDAC), including GSE263733, GSE197177, GSE212966, GSE155698, GSE141017, and GSE154778. These datasets comprise 15 adjacent normal tissue samples, 58 primary tumors, 16 liver metastases, and 20 peripheral blood mononuclear cell (PBMC) samples. PDACs displayed intratumoral heterogeneity, categorized into 11 clusters based on marker genes. Clusters C1 and C6 were identified as cancer stem cell-like clusters and showed a strong correlation with gemcitabine resistance scores.
- We collected nine microarray and sequencing datasets: GSE84219, GSE62452, GSE71729, TCGA-PDAC, GSE78229, GSE57495, GSE79668, GSE85916, and GSE28735. Each dataset underwent preprocessing individually, followed by batch effect correction using the ComBat function. The datasets were then integrated into a meta-cohort for survival analysis. The stemness score was calculated as the average of enrichment scores derived from GSVA deconvolution of 27 previously published stem cell-related gene sets. ARPC1B expression levels and the Stemness index were each divided into high and low expression groups based on their respective median values.
Other (English)
Files
Meta_bulk_cli.csv
Additional details
Funding
- National Natural Science Foundation of China
- No.82304902
Dates
- Updated
-
2025-06-22
Software
- Repository URL
- https://github.com/LuckyRaphael/PDAC_CSC
- Programming language
- R
References
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