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Background <p>Senescence-related transcriptional programs and epithelial-mesenchymal transition (EMT) are implicated in pancreatic ductal adenocarcinoma (PDAC) progression and therapy resistance. However, the single-cell distribution, functional heterogeneity, and clinical relevance of EMT-associated senescence-like programs remain incompletely defined.</p> Methods <p>We integrated single-cell RNA sequencing (scRNA-seq) data from 10 treatment-naive PDAC tumors with bulk transcriptomic profiles from TCGA-PAAD and an independent validation cohort. Senescence-related transcriptional activity was estimated using ssGSEA based on a curated CellAge gene set. EMT-like tumor cell subclusters were identified by unsupervised clustering after marker-based annotation, and differentiation trajectories were reconstructed using pseudotemporal analysis. A senescence-related gene signature was established for molecular subtyping and prognostic modeling. Drug sensitivity was explored using GDSC-based prediction and connectivity mapping.</p> Results <p>scRNA-seq analysis suggested that EMT-like tumor cells carried relatively high senescence-related transcriptional scores within the PDAC tumor microenvironment. Subclustering revealed five distinct EMT-like subsets, among which KRT19⁺ and UBE2C⁺ subsets showed high senescence-related scores, VMP1⁺ and NFE4⁺ subsets showed intermediate scores, and the MZB1⁺ subset showed low scores. Pseudotemporal ordering suggested an association between senescence-related transcriptional activity and EMT-like progression, but did not establish causality. Twelve senescence-related genes stratified patients into two subtypes (SubA and SubB). SubB patients exhibited poorer overall survival (median OS 17.0 vs. 34.8 months, log-rank <i>P</i> = 0.04) and an immune-excluded phenotype characterized by CD8 + T-cell depletion and reduced stromal/immune scores, despite evidence of altered tumor antigenicity. A refined 5-gene risk score (CDK1, FOXM1, NDRG1, PAK4, TPX2) showed moderate prognostic performance. Experimental validation supported up-regulation trends for the five model genes in PDAC, with statistically significant overexpression observed for NDRG1, PAK4, and TPX2 in the small validation cohort. TPX2 expression was positively associated with P16 expression. UMAP-based mapping revealed subcluster-specific enrichment of model genes. Drug-response prediction revealed distinct predicted IC₅₀ profiles between high- and low-risk patients, while CMap analysis nominated negatively connected compounds that may reverse the high-risk transcriptional signature.</p> Conclusions <p>EMT-like tumor subclusters with elevated senescence-related transcriptional activity may be associated with PDAC aggressiveness and therapy-related phenotypes. The molecular subtypes and 5-gene signature provide a hypothesis-generating framework for prognosis prediction and therapy selection. Prospective validation and functional experiments are required before clinical application or senescence-targeted treatment recommendations can be made.</p>

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Single-cell and bulk transcriptomics identify senescence-related EMT transcriptional programs and a prognostic framework in pancreatic ductal adenocarcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月8日

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  • Long-Jiang Chen,
  • Lun Wu,
  • Su-Hang Chen,
  • Xuan Pan,
  • Zheng-Chao Shen,
  • Jie Wang,
  • Shuo Zhang,
  • Lu-Lu Zhai,
  • Xiao-Ming Wang

摘要

Background

Senescence-related transcriptional programs and epithelial-mesenchymal transition (EMT) are implicated in pancreatic ductal adenocarcinoma (PDAC) progression and therapy resistance. However, the single-cell distribution, functional heterogeneity, and clinical relevance of EMT-associated senescence-like programs remain incompletely defined.

Methods

We integrated single-cell RNA sequencing (scRNA-seq) data from 10 treatment-naive PDAC tumors with bulk transcriptomic profiles from TCGA-PAAD and an independent validation cohort. Senescence-related transcriptional activity was estimated using ssGSEA based on a curated CellAge gene set. EMT-like tumor cell subclusters were identified by unsupervised clustering after marker-based annotation, and differentiation trajectories were reconstructed using pseudotemporal analysis. A senescence-related gene signature was established for molecular subtyping and prognostic modeling. Drug sensitivity was explored using GDSC-based prediction and connectivity mapping.

Results

scRNA-seq analysis suggested that EMT-like tumor cells carried relatively high senescence-related transcriptional scores within the PDAC tumor microenvironment. Subclustering revealed five distinct EMT-like subsets, among which KRT19⁺ and UBE2C⁺ subsets showed high senescence-related scores, VMP1⁺ and NFE4⁺ subsets showed intermediate scores, and the MZB1⁺ subset showed low scores. Pseudotemporal ordering suggested an association between senescence-related transcriptional activity and EMT-like progression, but did not establish causality. Twelve senescence-related genes stratified patients into two subtypes (SubA and SubB). SubB patients exhibited poorer overall survival (median OS 17.0 vs. 34.8 months, log-rank P = 0.04) and an immune-excluded phenotype characterized by CD8 + T-cell depletion and reduced stromal/immune scores, despite evidence of altered tumor antigenicity. A refined 5-gene risk score (CDK1, FOXM1, NDRG1, PAK4, TPX2) showed moderate prognostic performance. Experimental validation supported up-regulation trends for the five model genes in PDAC, with statistically significant overexpression observed for NDRG1, PAK4, and TPX2 in the small validation cohort. TPX2 expression was positively associated with P16 expression. UMAP-based mapping revealed subcluster-specific enrichment of model genes. Drug-response prediction revealed distinct predicted IC₅₀ profiles between high- and low-risk patients, while CMap analysis nominated negatively connected compounds that may reverse the high-risk transcriptional signature.

Conclusions

EMT-like tumor subclusters with elevated senescence-related transcriptional activity may be associated with PDAC aggressiveness and therapy-related phenotypes. The molecular subtypes and 5-gene signature provide a hypothesis-generating framework for prognosis prediction and therapy selection. Prospective validation and functional experiments are required before clinical application or senescence-targeted treatment recommendations can be made.