Journal of proteome research · 2026
Integrative Transcriptomic and Proteomic Profiling Defines Secretory and Immune Related Subtypes in Pancreatic Ductal Adenocarcinoma.
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Lin Shizhao, Yao Xiangqing, Guo Pengfei, Shi Han, Luo Haoteng, Ke Kun, Teng Tianhong, Weng Shangeng
Аннотация
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is characterized by extreme molecular heterogeneity and poor prognosis. Understanding its multiomics molecular heterogeneity may facilitate precise classification and individualized treatment.
METHODS: Transcriptomic and proteomic profiles from 140 PDAC patients were integrated using Similarity Network Fusion (SNF) to identify robust molecular subtypes. Sparse partial least-squares discriminant analysis (sPLS-DA), differential expression analysis, and network-based functional enrichment were employed to characterize subtype-specific features. Associations between molecular subtypes, clinicopathological variables, and patient survival were further assessed.
RESULTS: Three PDAC subtypes were identified with distinct molecular and clinical profiles. The basic subtype (SNF-1) showed no significant transcriptomic or proteomic distinction. The pancreatic secretory subtype (SNF-2) exhibited highly active endocrine and exocrine secretion pathways, suggesting strong dependence on pancreatic secretory function. The glycolytic-immune suppressive subtype (SNF-3) displayed prominent immune-evasion features and activation of multiple drug-resistance pathways, consistent with its poorest prognosis. These findings reveal distinct molecular programs underlying PDAC heterogeneity and its clinical manifestations.
CONCLUSION: This integrative multiomics analysis delineates three biologically and clinically distinct PDAC subtypes. The results highlight metabolic and functional diversity underlying tumor heterogeneity, offering new insights for precision stratification and the development of targeted therapeutic strategies.
METHODS: Transcriptomic and proteomic profiles from 140 PDAC patients were integrated using Similarity Network Fusion (SNF) to identify robust molecular subtypes. Sparse partial least-squares discriminant analysis (sPLS-DA), differential expression analysis, and network-based functional enrichment were employed to characterize subtype-specific features. Associations between molecular subtypes, clinicopathological variables, and patient survival were further assessed.
RESULTS: Three PDAC subtypes were identified with distinct molecular and clinical profiles. The basic subtype (SNF-1) showed no significant transcriptomic or proteomic distinction. The pancreatic secretory subtype (SNF-2) exhibited highly active endocrine and exocrine secretion pathways, suggesting strong dependence on pancreatic secretory function. The glycolytic-immune suppressive subtype (SNF-3) displayed prominent immune-evasion features and activation of multiple drug-resistance pathways, consistent with its poorest prognosis. These findings reveal distinct molecular programs underlying PDAC heterogeneity and its clinical manifestations.
CONCLUSION: This integrative multiomics analysis delineates three biologically and clinically distinct PDAC subtypes. The results highlight metabolic and functional diversity underlying tumor heterogeneity, offering new insights for precision stratification and the development of targeted therapeutic strategies.