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  4. EMT, Stemness, and Drug Resistance in Biological Context: A 3D Tumor Tissue/In Silico Platform for Analysis of Combinatorial Treatment in NSCLC with Aggressive KRAS-Biomarker Signatures
 
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May 1, 2022
Journal Article
Title

EMT, Stemness, and Drug Resistance in Biological Context: A 3D Tumor Tissue/In Silico Platform for Analysis of Combinatorial Treatment in NSCLC with Aggressive KRAS-Biomarker Signatures

Abstract
Epithelial-to-mesenchymal transition (EMT) is discussed to be centrally involved in invasion, stemness, and drug resistance. Experimental models to evaluate this process in its biological complexity are limited. To shed light on EMT impact and test drug response more reliably, we use a lung tumor test system based on a decellularized intestinal matrix showing more in vivo-like proliferation levels and enhanced expression of clinical markers and carcinogenesis-related genes. In our models, we found evidence for a correlation of EMT with drug resistance in primary and secondary resistant cells harboring KRASG12C or EGFR mutations, which was simulated in silico based on an optimized signaling network topology. Notably, drug resistance did not correlate with EMT status in KRAS-mutated patient-derived xenograft (PDX) cell lines, and drug efficacy was not affected by EMT induction via TGF-β. To investigate further determinants of drug response, we tested several drugs in combination with a KRASG12C inhibitor in KRASG12C mutant HCC44 models, which, besides EMT, display mutations in P53, LKB1, KEAP1, and high c-MYC expression. We identified an aurora-kinase A (AURKA) inhibitor as the most promising candidate. In our network, AURKA is a centrally linked hub to EMT, proliferation, apoptosis, LKB1, and c-MYC. This exemplifies our systemic analysis approach for clinical translation of biomarker signatures.
Author(s)
Peindl, Matthias
Göttlich, Claudia
Crouch, Samantha
Hoff, Niklas
Lüttgens, Tamara
Schmitt, Franziska
Nieves Pereira, Jesús Guillermo
May, Celina
Schliermann, Anna
Kronenthaler, Corinna
Cheufou, Danjouma
Reu-Hofer, Simone
Rosenwald, Andreas
Weigl, Elena
Walles, Thorsten
Schüler, Julia
Dandekar, Thomas
Nietzer, Sarah  
Fraunhofer-Institut für Silicatforschung ISC  
Dandekar, Gudrun  
Fraunhofer-Institut für Silicatforschung ISC  
Journal
Cancers  
Open Access
DOI
10.3390/cancers14092176
Additional full text version
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Language
English
Fraunhofer-Institut für Silicatforschung ISC  
Keyword(s)
  • 3D lung tumor tissue models

  • boolean in silico models

  • drug resistance

  • EMT

  • invasion

  • KRAS biomarker signatures

  • stemness

  • targeted combination therapy

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