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A Network-Based Approach for Identification of Subtype-Specific Master Regulators in Pancreatic Ductal Adenocarcinoma

by Yuchen Zhang 1,†, Lina Zhu 1,† and Xin Wang 1,2,*
1
Department of Biomedical Sciences, City University of Hong Kong, Hong Kong SAR, China
2
Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
*
Author to whom correspondence should be addressed.
These authors equally contribute to this manuscript.
Genes 2020, 11(2), 155; https://doi.org/10.3390/genes11020155
Received: 28 December 2019 / Revised: 26 January 2020 / Accepted: 29 January 2020 / Published: 1 February 2020
(This article belongs to the Special Issue Current Advances in Network Biology for Disease Understanding)
Pancreatic ductal adenocarcinoma (PDAC), the predominant subtype of pancreatic cancer, has been reported with equal mortality and incidence for decades. The lethality of PDAC is largely due to its late presentation, when surgical resection is no longer an option. Similar to other major malignancies, it is now clear that PDAC is not a single disease, posing a great challenge to precise selection of patients for optimized adjuvant therapy. A representative study found that PDAC comprises four distinct molecular subtypes: squamous, pancreatic progenitor, immunogenic, and aberrantly differentiated endocrine exocrine (ADEX). However, little is known about the molecular mechanisms underlying specific PDAC subtypes, hampering the design of novel targeted agents. In this study we performed network inference that integrates miRNA expression and gene expression profiles to dissect the miRNA regulatory mechanism specific to the most aggressive squamous subtype of PDAC. Master regulatory analysis revealed that the particular subtype of PDAC is predominantly influenced by miR-29c and miR-192. Further integrative analysis found miR-29c target genes LOXL2, ADAM12 and SERPINH1, which all showed strong association with prognosis. Furthermore, we have preliminarily revealed that the PDAC cell lines with high expression of these miRNA target genes showed significantly lower sensitivities to multiple anti-tumor drugs. Together, our integrative analysis elucidated the squamous subtype-specific regulatory mechanism, and identified master regulatory miRNAs and their downstream genes, which are potential prognostic and predictive biomarkers.
Keywords: miRNA; regulatory network inference; pancreatic ductal adenocarcinoma; subtype miRNA; regulatory network inference; pancreatic ductal adenocarcinoma; subtype
MDPI and ACS Style

Zhang, Y.; Zhu, L.; Wang, X. A Network-Based Approach for Identification of Subtype-Specific Master Regulators in Pancreatic Ductal Adenocarcinoma. Genes 2020, 11, 155.

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