Identification of Cancer Associated Fibroblasts Related Genes Signature to Facilitate Improved Prediction of Prognosis and Responses to Therapy in Patients with Pancreatic Cancer
Abstract
1. Introduction
2. Results
2.1. Higher CAF Infiltrations Are Related to Worse Overall Survival in Pancreatic Cancer
2.2. Intersection Genes Enrichment Related to ECM
2.3. Establishing the Prognostic Risk Model Genes from the Stromal CAF-Based
2.4. High CAF Infiltrations and Markers Can Be Shown from CAF Signature Genes
2.5. Chemo-Immuno-Therapy Sensitivity Prediction and Molecular Docking
2.6. High CAF Risk Is Correlated with Tumor Mutation Burden
2.7. GSEA and ssGSEA of the Six Genes of the CAF Signature
2.8. Validation of Key Genes in CCLE and HPA Databases
3. Discussion
4. Materials and Methods
4.1. Accumulating and Processing Data
4.2. Quantification of Cancer-Associated Fibroblasts (CAFs)
4.3. CAF and Stromal Co-Expression Network Module
4.4. Kaplan–Meier Curve and Log-Rank Analysis
4.5. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Analysis
4.6. CAF-Associated Model Construction and Validation
4.7. Sensitivity Drugs Prediction and Molecular Docking
4.8. Gathering and Analyzing Data on Somatic Changes
4.9. GSEA and ssGSEA Enrichment Analyses
4.10. Validation Via Cancer Cell Line Encyclopedia (CCLE) and Human Protein Atlas (HPA) Databases
4.11. Statistical Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
PC | Pancreatic cancer |
CAFs | Cancer associated fibroblasts |
GEO | Gene Expression Omnibus |
TCGA | the Cancer Genome Atlas |
WGCNA | weighted gene co-expression network analysis |
TMB | tumor mutation burden |
GSEA | Gene set enrichment analysis |
OS | overall survival |
TME | tumor microenvironment |
PSCs | pancreatic stellate cells |
ECM | extracellular matrix |
TGF-β | transforming growth factor-β |
IL-6 | interleukin-6 |
CCL2 | CC-chemokine ligand 2 |
ROS | reactive oxygen species |
EBV | Epstein–Barr virus |
LASSO | Least Absolute Shrinkage and Selection Operator |
DEGs | differentially expressed genes |
GS | gene significance |
MM | module membership |
GO | gene ontology |
BP | biological process |
CC | cell component |
MF | molecular function |
KEGG | kyoto encyclopedia of genes and genomes |
GSEA | Gene Set Enrichment Analysis |
ssGSEA | single-sample gene set enrichment analysis |
ADM | acinar-ductal metaplasia |
FPKM | per million mapped reads |
MAF | Mutation Annotation Format |
TPM | transcripts per million |
EPIC | Estimating the Proportion of Immune and Cancer cells |
MCP-counter | Microenvironment Cell Populations-counter |
TIDE | Tumor Immune Dysfunction and Exclusion |
MAD | median absolute deviation |
TOM | topological overlap matrix |
MEs | Module eigengenes |
GDSC | the Genomics of Drug Sensitivity in Cancer |
ICB | immune checkpoint blockade |
AUC | area under the curve |
CCLE | Cancer Cell Line Encyclopedias |
HPA | Human Protein Atlas |
ROC | receiver operating characteristic |
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Target | PDB ID | Drug | PubChem ID | Binding Energy (kcal/mol) |
---|---|---|---|---|
MMP2 | 1RTG | Staurosporine | 44259 | −7 |
Dasatinib | 3062316 | −8.2 | ||
OTX015 | 9936746 | −8.4 | ||
BMS-536924 | 135440466 | −8 | ||
Luminespib | 135539077 | −8.1 | ||
FSTL1 | 6JZA | Staurosporine | 44259 | −7.4 |
Dasatinib | 3062316 | −7.3 | ||
OTX015 | 9936746 | −7.6 | ||
BMS-536924 | 135440466 | −7 | ||
Luminespib | 135539077 | −7 | ||
GFPT2 | 7NUT | Staurosporine | 44259 | −8 |
Dasatinib | 3062316 | −8.5 | ||
OTX015 | 9936746 | −8.5 | ||
BMS-536924 | 135440466 | −9 | ||
Luminespib | 135539077 | −9.1 | ||
CTSK | 8V57 | Staurosporine | 44259 | −9 |
Dasatinib | 3062316 | −7.6 | ||
OTX015 | 9936746 | −8.5 | ||
BMS-536924 | 135440466 | −7.9 | ||
Luminespib | 135539077 | −7.5 |
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Zhou, Y.; Lu, Y.; Czubayko, F.; Chen, J.; Zheng, S.; Mo, H.; Liu, R.; Weber, G.F.; Grützmann, R.; Pilarsky, C.; et al. Identification of Cancer Associated Fibroblasts Related Genes Signature to Facilitate Improved Prediction of Prognosis and Responses to Therapy in Patients with Pancreatic Cancer. Int. J. Mol. Sci. 2025, 26, 4876. https://doi.org/10.3390/ijms26104876
Zhou Y, Lu Y, Czubayko F, Chen J, Zheng S, Mo H, Liu R, Weber GF, Grützmann R, Pilarsky C, et al. Identification of Cancer Associated Fibroblasts Related Genes Signature to Facilitate Improved Prediction of Prognosis and Responses to Therapy in Patients with Pancreatic Cancer. International Journal of Molecular Sciences. 2025; 26(10):4876. https://doi.org/10.3390/ijms26104876
Chicago/Turabian StyleZhou, Yong, Yanxi Lu, Franziska Czubayko, Jisheng Chen, Shuwen Zheng, Huaqing Mo, Rui Liu, Georg F. Weber, Robert Grützmann, Christian Pilarsky, and et al. 2025. "Identification of Cancer Associated Fibroblasts Related Genes Signature to Facilitate Improved Prediction of Prognosis and Responses to Therapy in Patients with Pancreatic Cancer" International Journal of Molecular Sciences 26, no. 10: 4876. https://doi.org/10.3390/ijms26104876
APA StyleZhou, Y., Lu, Y., Czubayko, F., Chen, J., Zheng, S., Mo, H., Liu, R., Weber, G. F., Grützmann, R., Pilarsky, C., & David, P. (2025). Identification of Cancer Associated Fibroblasts Related Genes Signature to Facilitate Improved Prediction of Prognosis and Responses to Therapy in Patients with Pancreatic Cancer. International Journal of Molecular Sciences, 26(10), 4876. https://doi.org/10.3390/ijms26104876