Master Regulators of Oncogenic KRAS Response in Pancreatic Cancer: An Integrative Network Biology Analysis

Abstract

BackgroundKRAS 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 FindingsWe 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.ConclusionsOur 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.

Immunophenotypes of pancreatic ductal adenocarcinoma: Meta‐analysis of transcriptional subtypes

“…Several recent studies have described the transcriptomic landscape of PDAC and identified different subtypes with different clinical outcomes and drug sensitivities . Table summarises several notable studies.…”

“…This had identified three subtypes: classical, quasimesenchymal and exocrine‐like, which have different prognoses and different responses to treatment. This classification has subsequently been challenged and revised, with newer classifications being put forward . Moffitt et al .…”

“…Sivakumar et al . used a master regulator approach based on the transcriptional effects of oncogenic KRAS to determine 3 subtypes that showed different prognoses, characteristics and treatment strategies …”

Novel Targets in Pancreatic Cancer Therapy - Current Status and Ongoing Translational Efforts

“…Likewise, Notch signaling has now long been found to be altered and pathophysiologically involved in pancreatic carcinogenesis. Various approaches to pharmacologically target oncogenic Notch signaling in different cancers including pancreatic cancer have been developed, including the application of γ-secretase inhibitors and antagonists against Notch ligands [73,74,75], and some of these endeavors are still underway at various stages of preclinical as well as early clinical evaluation [76,77,78,79,80,81,82]. …”

Opportunities and Resistance to Signal-Targeted Therapies in Pancreatic Cancer: What Can we Learn from Proteomic Studies?

“…The heterogeneity within tumor is thus a critical component of resistance mechanisms [21]. Technological progress and big data have led to a characterisation of pancreatic cancer's molecular identity (of mostly resected tumors) [22][23][24][25]. However, in contrast to other cancers such in lung cancer with EGFR mutations, these global approaches failed to identify simple therapeutic strategies based on a stratification of PDAC patients.…”