Integrative multi-omics and radiogenomic profiling decodes NNK-related tumor remodeling and prognostic stratification in pancreatic cancer.
Authors
Affiliations (7)
Affiliations (7)
- Department of Radiology, The First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
- Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai Institute of Medical Imaging, Shanghai, China.
- Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China.
- School of Instrument and Electronics, North University of China, Shanxi, China.
- CeyearTechnologies Co. Ltd., Shandong, China.
- Department of Radiology, Jiaxing Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medical University, Jiaxing, China.
- Department of Pancreatic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China. Cancer Center, Zhongshan Hospital, Fudan University, Shanghai, China.
Abstract
To elucidate how the tobacco-specific carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) relates to pancreatic cancer (PC) progression and to develop a CT-based radiomics model that non-invasively decodes NNK-related molecular alterations. NNK-related genes were identified by integrating toxicogenomic mining across multiple databases with multi-cohort transcriptomic analyses. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), a multi-algorithm machine-learning framework, and Cox proportional hazards modeling were applied to screen key regulators and prognosis-related factors. Single-cell RNA sequencing was performed to characterize cellular heterogeneity and tumor-stroma communication associated with ITGA3. Radiomic features were extracted from CT scans, and a radiomics signature was constructed. Prognostic value was evaluated in the cancer imaging archive (TCIA), and an independent surgical cohort. A total of 268 NNK-associated PC genes were identified, enriched in extracellular matrix (ECM) remodeling, focal adhesion, PI3K-AKT signaling, and DNA-damage response pathways. Machine-learning prioritization yielded 15 key candidates, among which ITGA3 remained an independent prognostic factor (P < 0.05). Single-cell analysis showed enrichment of basal/epithelial-mesenchymal transition (EMT)-high epithelial subsets and intensified epithelial-cancer-associated fibroblast-macrophage communication in ITGA3-high tumors. The NNK-related ITGA3-guided radiomics model predicted ITGA3 expression (AUC = 0.893 and 0.839) and achieved significant postoperative survival stratification. NNK is associated with a malignant transcriptional program characterized by epithelial remodeling, stromal interaction, and immune suppression. These molecular features can be captured non-invasively through CT-based radiomics. The NNK-related ITGA3-associated radiomics (NIR) score provides a practical tool for preoperative risk stratification in PC and offers a bridge linking environmental carcinogen exposure with tumor imaging phenotypes.