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Identification of a ΔNp63-Dependent Basal-Like A Subtype-Specific Transcribed Enhancer Program (B-STEP) in Aggressive Pancreatic Ductal Adenocarcinoma.

Xin WangAna Patricia KutschatJoana Aggrey-FynnFeda H HamdanRondell P GrahamAlexander Q WixomYara SoutoSwetlana Ladigan-BaduraJennifer A YonkusAmro M AbdelrahmanRoberto Alva-RuizJochen GaedckePhilipp StroebelRobyn Laura KosinskyFlorian WegwitzPatrick C HermannMark J TrutyJens Thomas SivekeStephan A HahnElisabeth HessmannSteven A JohnsenZeynab Najafova
Published in: Molecular cancer research : MCR (2023)
A major hurdle to the application of precision oncology in pancreatic cancer is the lack of molecular stratification approaches and targeted therapy for defined molecular subtypes. In this work, we sought to gain further insight and identify molecular and epigenetic signatures of the basal-like A pancreatic ductal adenocarcinoma (PDAC) subgroup that can be applied to clinical samples for patient stratification and/or therapy monitoring. We generated and integrated global gene expression and epigenome mapping data from patient-derived xenograft (PDX) models to identify subtype-specific enhancer regions that were validated in patient-derived samples. In addition, complementary nascent transcription and chromatin topology (HiChIP) analyses revealed a basal-like A subtype-specific transcribed enhancer program (B-STEP) in PDAC characterized by enhancer RNA (eRNA) production that is associated with more frequent chromatin interactions and subtype-specific gene activation. Importantly, we successfully confirmed the validity of eRNA detection as a possible histological approach for PDAC patient stratification by performing RNA in situ hybridization analyses for subtype-specific eRNAs on pathological tissue samples. Thus, this study provides proof-of-concept that subtype-specific epigenetic changes relevant for PDAC progression can be detected at a single cell level in complex, heterogeneous, primary tumor material. Implications: Subtype-specific enhancer activity analysis via detection of eRNAs on a single cell level in patient material can be used as a potential tool for treatment stratification.
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