Mouse models in squamous cell lung cancer: impact for drug discovery

Aditi P. Singh, Diego Adrianzen Herrera, Yifei Zhang, Roman Perez-Soler, Haiying Cheng

Research output: Contribution to journalReview articlepeer-review

12 Scopus citations

Abstract

Introduction: Squamous cell lung cancer (SQCLC) is the second most common subtype of non-small cell lung cancer (NSCLC) and has limited therapeutic options. Its development is likely a result of a multistep process in response to chronic tobacco exposure, involving sequential metaplasia, dysplasia and invasive carcinoma. Its complex genomic landscape has recently been revealed but no driver mutations have been validated that could lead to molecularly targeted therapy as have emerged in lung adenocarcinoma. Few preclinical murine models exist for testing and developing novel therapeutics in SQCLC. Areas covered: This review discusses the pathophysiology and molecular underpinnings of SQCLC that have limited the development of animal models. It then explores the advantages and limitations of a variety of existing mouse models and illustrates their potential application in drug discovery and chemoprevention. Expert opinion: There are several challenges in the development of mouse models for SQCLC, such as lack of validated driver genetic alterations, unclear cell of origin, and difficulty in reproducing the sophisticated tumor microenvironment of human disease. Nevertheless, several successful SQCLC murine models have emerged, especially Patient Derived Xenografts (PDXs) and Genetically Engineered Mouse Models (GEMMs). Continued efforts are needed to generate more SQCLC animal models to better understand its carcinogenesis and metastasis and to further test novel therapeutic strategies.

Original languageEnglish (US)
Pages (from-to)347-358
Number of pages12
JournalExpert Opinion on Drug Discovery
Volume13
Issue number4
DOIs
StatePublished - Apr 3 2018

Keywords

  • Squamous cell lung cancer
  • mouse models
  • murine models
  • xenografts

ASJC Scopus subject areas

  • Drug Discovery

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