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Prognostic model establishment and immune microenvironment analysis based on transcriptomic data of long-term survivors of pancreatic ductal adenocarcinoma

Lin, Lizhi LU ; Norrsell, Ragnar LU ; Andersson, Roland LU ; Shen, Xian and Ansari, Daniel LU (2025) In Biochemistry and Biophysics Reports 44.
Abstract

Pancreatic cancer continues to be a major cause of cancer deaths worldwide. Characterizing the tumors of long-term survivors (≥5 years survival) would create opportunities in prognostic and therapeutic strategies. In this study, RNA sequencing data was used to identify differentially expressed genes (DEGs) in tumors of long-term survivors (LTS) vs short-term survivors (STS). Using LASSO-Cox regression, 4 prognostic DEGs, along with tumor stage, were utilized to develop a model for identifying high- and low-risk tumors. In Kaplan-Meier survival analysis, the high-risk group had significantly worse prognosis in both the training and validation cohorts. Using KEGG pathway gene signature sets, the high-risk group was found to have... (More)

Pancreatic cancer continues to be a major cause of cancer deaths worldwide. Characterizing the tumors of long-term survivors (≥5 years survival) would create opportunities in prognostic and therapeutic strategies. In this study, RNA sequencing data was used to identify differentially expressed genes (DEGs) in tumors of long-term survivors (LTS) vs short-term survivors (STS). Using LASSO-Cox regression, 4 prognostic DEGs, along with tumor stage, were utilized to develop a model for identifying high- and low-risk tumors. In Kaplan-Meier survival analysis, the high-risk group had significantly worse prognosis in both the training and validation cohorts. Using KEGG pathway gene signature sets, the high-risk group was found to have amplification of pathways, such as focal adhesion and ECM receptor interaction. The low-risk group, meanwhile, showed upregulation of specific metabolic pathways. Using ESTIMATE analysis, the high-risk group was found to have more stromal cell infiltration. Increased unpolarized macrophages and decreased inflammatory/anti-tumoral macrophages were also found in the high-risk group. Lastly, drug sensitivities were calculated and found to be generally higher in the high-risk group. This study reveals a model for predicting survival and drug sensitivity in pancreatic cancer. Genetic, molecular and tumor microenvironment characteristics of tumors from LTS and STS have been identified, highlighting opportunities for further research.

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author
; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Drug sensitivity, Long-term survivors, Pancreatic cancer, Prognostic model, Transcriptomics, Tumor microenvironment
in
Biochemistry and Biophysics Reports
volume
44
article number
102280
publisher
Elsevier
external identifiers
  • pmid:41080752
  • scopus:105016823613
ISSN
2405-5808
DOI
10.1016/j.bbrep.2025.102280
language
English
LU publication?
yes
id
98616cd4-11d5-40ec-bd85-d72b84ffef3a
date added to LUP
2025-11-21 15:55:40
date last changed
2025-11-22 03:00:05
@article{98616cd4-11d5-40ec-bd85-d72b84ffef3a,
  abstract     = {{<p>Pancreatic cancer continues to be a major cause of cancer deaths worldwide. Characterizing the tumors of long-term survivors (≥5 years survival) would create opportunities in prognostic and therapeutic strategies. In this study, RNA sequencing data was used to identify differentially expressed genes (DEGs) in tumors of long-term survivors (LTS) vs short-term survivors (STS). Using LASSO-Cox regression, 4 prognostic DEGs, along with tumor stage, were utilized to develop a model for identifying high- and low-risk tumors. In Kaplan-Meier survival analysis, the high-risk group had significantly worse prognosis in both the training and validation cohorts. Using KEGG pathway gene signature sets, the high-risk group was found to have amplification of pathways, such as focal adhesion and ECM receptor interaction. The low-risk group, meanwhile, showed upregulation of specific metabolic pathways. Using ESTIMATE analysis, the high-risk group was found to have more stromal cell infiltration. Increased unpolarized macrophages and decreased inflammatory/anti-tumoral macrophages were also found in the high-risk group. Lastly, drug sensitivities were calculated and found to be generally higher in the high-risk group. This study reveals a model for predicting survival and drug sensitivity in pancreatic cancer. Genetic, molecular and tumor microenvironment characteristics of tumors from LTS and STS have been identified, highlighting opportunities for further research.</p>}},
  author       = {{Lin, Lizhi and Norrsell, Ragnar and Andersson, Roland and Shen, Xian and Ansari, Daniel}},
  issn         = {{2405-5808}},
  keywords     = {{Drug sensitivity; Long-term survivors; Pancreatic cancer; Prognostic model; Transcriptomics; Tumor microenvironment}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Biochemistry and Biophysics Reports}},
  title        = {{Prognostic model establishment and immune microenvironment analysis based on transcriptomic data of long-term survivors of pancreatic ductal adenocarcinoma}},
  url          = {{http://dx.doi.org/10.1016/j.bbrep.2025.102280}},
  doi          = {{10.1016/j.bbrep.2025.102280}},
  volume       = {{44}},
  year         = {{2025}},
}