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Published on: February 11, 2019
Master Regulators of Oncogenic KRAS Response in Pancreatic Cancer: An Integrative Network Biology Analysis
Shivan Sivakumar1, Ines de Santiago1, Leon Chlon1,2
1Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom.
Background:
KRAS is the most frequently mutated gene in pancreatic ductal adenocarcinoma (PDAC), but the mechanisms underlying the transcriptional response to oncogenic KRAS are still not fully understood. We aimed to uncover transcription factors that regulate the transcriptional response of oncogenic KRAS in pancreatic cancer and to understand their clinical relevance.
Methods And Findings:
We applied a well-established network biology approach (master regulator analysis) to combine a transcriptional signature for oncogenic KRAS derived from a murine isogenic cell line with a coexpression network derived by integrating 560 human pancreatic cancer cases across seven studies. The datasets included the ICGC cohort (n = 242), the TCGA cohort (n = 178), and five smaller studies (n = 17, 25, 26, 36, and 36). 55 transcription factors were coexpressed with a significant number of genes in the transcriptional signature (gene set enrichment analysis [GSEA] p < 0.01). Community detection in the coexpression network identified 27 of the 55 transcription factors contributing to three major biological processes: Notch pathway, down-regulated Hedgehog/Wnt pathway, and cell cycle. The activities of these processes define three distinct subtypes of PDAC, which demonstrate differences in survival and mutational load as well as stromal and immune cell composition. The Hedgehog subgroup showed worst survival (hazard ratio 1.73, 95% CI 1.1 to 2.72, coxPH test p = 0.018) and the Notch subgroup the best (hazard ratio 0.62, 95% CI 0.42 to 0.93, coxPH test p = 0.019). The cell cycle subtype showed highest mutational burden (ANOVA p < 0.01) and the smallest amount of stromal admixture (ANOVA p < 2.2e-16). This study is limited by the information provided in published datasets, not all of which provide mutational profiles, survival data, or the specifics of treatment history.
Conclusions:
Our results characterize the regulatory mechanisms underlying the transcriptional response to oncogenic KRAS and provide a framework to develop strategies for specific subtypes of this disease using current therapeutics and by identifying targets for new groups.
Insights
Oncogenic KRAS drives pancreatic cancer subtypes with distinct survival and molecular features. Identifying key transcription factors reveals therapeutic strategies for pancreatic ductal adenocarcinoma (PDAC).
Area of Science:
- Oncology
- Genetics
- Bioinformatics
Background:
- KRAS is frequently mutated in pancreatic ductal adenocarcinoma (PDAC).
- Mechanisms of KRAS-driven transcriptional response in PDAC remain unclear.
- Understanding these mechanisms is crucial for developing targeted therapies.
Purpose of the Study:
- To identify transcription factors regulating oncogenic KRAS transcriptional response in pancreatic cancer.
- To investigate the clinical relevance of these transcription factors.
- To define PDAC subtypes based on regulatory mechanisms.
Main Methods:
- Network biology approach (master regulator analysis) was employed.
- Integrated transcriptional signature of oncogenic KRAS with coexpression networks from 560 human PDAC cases.
- Gene set enrichment analysis (GSEA) and community detection identified key transcription factors and biological processes.
Main Results:
- Identified 55 coexpressed transcription factors, with 27 contributing to three major biological processes: Notch pathway, Hedgehog/Wnt pathway, and cell cycle.
- These processes define three distinct PDAC subtypes with varying survival, mutational load, and stromal/immune composition.
- The Hedgehog subgroup exhibited the worst survival, while the Notch subgroup showed the best survival.
Conclusions:
- Characterized regulatory mechanisms of oncogenic KRAS transcriptional response.
- Provided a framework for developing subtype-specific therapeutic strategies for PDAC.
- Highlighted the potential for targeting identified pathways and transcription factors.
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