Journal
NAR CANCER
Volume 4, Issue 4, Pages -Publisher
OXFORD UNIV PRESS
DOI: 10.1093/narcan/zcac030
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Funding
- European Union [777111]
- DFG (German Research foundation) [329628492, SFB1321]
- SATURN3 program - German Federal Ministry of Education and Research (BMBF)
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Molecular signatures for classifying pancreatic ductal adenocarcinoma (PDAC) into subtypes show inconsistency and instability across different datasets, due to technical biases and sample preparation issues.
Molecular signatures have been suggested as biomarkers to classify pancreatic ductal adenocarcinoma (PDAC) into two, three, four or five subtypes. Since the robustness of existing signatures is controversial, we performed a systematic evaluation of four established signatures for PDAC stratification across nine publicly available datasets. Clustering revealed inconsistency of subtypes across independent datasets and in some cases a different number of PDAC subgroups than in the original study, casting doubt on the actual number of existing subtypes. Next, we built sixteen classification models to investigate the ability of the signatures for tumor subtype prediction. The overall classification performance ranged from similar to 35% to similar to 90% accuracy, suggesting instability of the signatures. Notably, permuted subtypes and random gene sets achieved very similar performance. Cellular decomposition and functional pathway enrichment analysis revealed strong tissue-specificity of the predicted classes. Our study highlights severe limitations and inconsistencies that can be attributed to technical biases in sample preparation and tumor purity, suggesting that PDAC molecular signatures do not generalize across datasets. How stromal heterogeneity and immune compartment interplay in the diverging development of PDAC is still unclear. Therefore, a more mechanistic or a cross-platform multi-omic approach seems necessary to extract more robust and clinically exploitable insights.
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