The crucial prognostic signaling pathways of pancreatic ductal adenocarcinoma were identified by single-cell and bulk RNA sequencing data
© 2024. The Author(s)..
Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with poor prognosis and high mortality. Although a large number of studies have explored its potential prognostic markers using traditional RNA sequencing (RNA-Seq) data, they have not achieved good prediction effect. In order to explore the possible prognostic signaling pathways leading to the difference in prognosis, we identified differentially expressed genes from one scRNA-seq cohort and four GEO cohorts, respectively. Then Cox and Lasso regression analysis showed that 12 genes were independent prognostic factors for PDAC. AUC and calibration curve analysis showed that the prognostic model had good discrimination and calibration. Compared with the low-risk group, the high-risk group had a higher proportion of gene mutations than the low-risk group. Immune infiltration analysis revealed differences in macrophages and monocytes between the two groups. Prognosis related genes were mainly distributed in fibroblasts, macrophages and type 2 ducts. The results of cell communication analysis showed that there was a strong communication between cancer-associated fibroblasts (CAF) and type 2 ductal cells, and collagen formation was the main interaction pathway.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - year:2024 |
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Enthalten in: |
Human genetics - (2024) vom: 25. März |
Sprache: |
Englisch |
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Beteiligte Personen: |
Wang, Wenwen [VerfasserIn] |
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Date Revised 25.03.2024 published: Print-Electronic Citation Status Publisher |
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doi: |
10.1007/s00439-024-02663-4 |
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PPN (Katalog-ID): |
NLM370163109 |
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520 | |a Pancreatic ductal adenocarcinoma (PDAC) is a malignant tumor with poor prognosis and high mortality. Although a large number of studies have explored its potential prognostic markers using traditional RNA sequencing (RNA-Seq) data, they have not achieved good prediction effect. In order to explore the possible prognostic signaling pathways leading to the difference in prognosis, we identified differentially expressed genes from one scRNA-seq cohort and four GEO cohorts, respectively. Then Cox and Lasso regression analysis showed that 12 genes were independent prognostic factors for PDAC. AUC and calibration curve analysis showed that the prognostic model had good discrimination and calibration. Compared with the low-risk group, the high-risk group had a higher proportion of gene mutations than the low-risk group. Immune infiltration analysis revealed differences in macrophages and monocytes between the two groups. Prognosis related genes were mainly distributed in fibroblasts, macrophages and type 2 ducts. The results of cell communication analysis showed that there was a strong communication between cancer-associated fibroblasts (CAF) and type 2 ductal cells, and collagen formation was the main interaction pathway | ||
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700 | 1 | |a Zhang, Wenli |e verfasserin |4 aut | |
700 | 1 | |a Zhang, Xihua |e verfasserin |4 aut | |
700 | 1 | |a Huang, Manli |e verfasserin |4 aut | |
700 | 1 | |a Li, Chen |e verfasserin |4 aut | |
700 | 1 | |a Wang, Ling |e verfasserin |4 aut | |
700 | 1 | |a Lu, Zifan |e verfasserin |4 aut | |
700 | 1 | |a Xia, Jielai |e verfasserin |4 aut | |
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