Proteogenomic landscape of human pancreatic ductal adenocarcinoma in an Asian population reveals tumor cell-enriched and immune-rich subtypes.
Do Young HyeonDowoon NamYoungmin HanDuk Ki KimGibeom KimDaeun KimJingi BaeSeunghoon BackDong-Gi MunInamul Hasan MadarHangyeore LeeSu-Jin KimHokeun KimSangyeop HyunChang Rok KimSeon Ah ChoiYong Ryoul KimJuhee JeongSuwan JeonYeon Woong ChooKyung Bun LeeWooil KwonSeunghyuk ChoiTaewan GooTaesung ParkYoung-Ah SuhHongbeom KimJa-Lok KuMin-Sik KimEunok PaekDeachan ParkKeehoon JungSung Hee BaekJin-Young JangDaehee HwangSang-Won LeePublished in: Nature cancer (2022)
We report a proteogenomic analysis of pancreatic ductal adenocarcinoma (PDAC). Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. Messenger RNA-protein abundance correlations revealed potential prognostic biomarkers correlated with patient survival. Integrated clustering of mRNA, protein and phosphorylation data identified six PDAC subtypes. Cellular pathways represented by mRNA and protein signatures, defining the subtypes and compositions of cell types in the subtypes, characterized them as classical progenitor (TS1), squamous (TS2-4), immunogenic progenitor (IS1) and exocrine-like (IS2) subtypes. Compared with the mRNA data, protein and phosphorylation data further classified the squamous subtypes into activated stroma-enriched (TS2), invasive (TS3) and invasive-proliferative (TS4) squamous subtypes. Orthotopic mouse PDAC models revealed a higher number of pro-tumorigenic immune cells in TS4, inhibiting T cell proliferation. Our proteogenomic analysis provides significantly mutated genes/biomarkers, cellular pathways and cell types as potential therapeutic targets to improve stratification of patients with PDAC.
Keyphrases
- single cell
- binding protein
- cell proliferation
- cell therapy
- rna seq
- high grade
- protein protein
- electronic health record
- signaling pathway
- amino acid
- big data
- genome wide
- endothelial cells
- stem cells
- small molecule
- protein kinase
- oxidative stress
- pi k akt
- machine learning
- epithelial mesenchymal transition
- deep learning
- climate change
- artificial intelligence
- transcription factor
- cell fate
- genome wide identification
- pluripotent stem cells