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CancersCancers
  • Article
  • Open Access

5 August 2020

Profound Reprogramming towards Stemness in Pancreatic Cancer Cells as Adaptation to AKT Inhibition

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1
Oncoimmunology, Navarrabiomed-UPNA, Navarra Institute for Health Research (IdiSNA), Irunlarrea 3, 31008 Pamplona, Spain
2
Medical Oncology Unit, Complejo Hospitalario de Navarra (CHN), IdISNA, Irunlarrea 3, 31008 Pamplona, Spain
3
Proteored-ISCIII, Proteomics Platform, Navarrabiomed, Complejo Hospitalario de Navarra (CHN), Universidad Pública de Navarra (UPNA), IdISNA, Irunlarrea 3, 31008 Pamplona, Spain
4
Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), CIMA, Universidad de Navarra, IdISNA, Irunlarrea 3, 31008 Pamplona, Spain
This article belongs to the Special Issue Pancreatic Ductal Adenocarcinoma

Abstract

Cancer cells acquire resistance to cytotoxic therapies targeting major survival pathways by adapting their metabolism. The AKT pathway is a major regulator of human pancreatic adenocarcinoma progression and a key pharmacological target. The mechanisms of adaptation to long-term silencing of AKT isoforms of human and mouse pancreatic adenocarcinoma cancer cells were studied. Following silencing, cancer cells remained quiescent for long periods of time, after which they recovered proliferative capacities. Adaptation caused profound proteomic changes largely affecting mitochondrial biogenesis, energy metabolism and acquisition of a number of distinct cancer stem cell (CSC) characteristics depending on the AKT isoform that was silenced. The adaptation to AKT1 silencing drove most de-differentiation and acquisition of stemness through C-MYC down-modulation and NANOG upregulation, which were required for survival of adapted CSCs. The changes associated to adaptation sensitized cancer cells to inhibitors targeting regulators of oxidative respiration and mitochondrial biogenesis. In vivo pharmacological co-inhibition of AKT and mitochondrial metabolism effectively controlled pancreatic adenocarcinoma growth in pre-clinical models.

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