Georg Feldmann1, Sherri Rauenzahn, Anirban Maitra. 1. Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Abstract
BACKGROUND: Pancreatic cancer is a disease of near uniform fatality and the overwhelming majority of patients succumb to their advanced malignancy within a few months of diagnosis. Despite considerable advances in our understanding of molecular mechanisms underlying pancreatic carcinogenesis, this knowledge has not yet been fully translated into clinically available treatment strategies that yield significant improvements in disease free or overall survival. OBJECTIVE: Cell line-based in vitro model systems provide powerful tools to identify potential molecular targets for therapeutic intervention as well as for initial pre-clinical evaluation of novel drug candidates. Here we provide a brief overview of recent literature on cell line-based model systems of pancreatic cancer and their application in the search for novel therapeutics against this vicious disease. CONCLUSION: While in vitro models of pancreatic cancer are of tremendous value for genetic studies and initial functional screenings in drug discovery, they carry several imanent drawbacks and are often poor in predicting therapeutic response in humans. Therefore, in most instances they are successfully exploited to generate hypothesis and identify molecular targets for novel therapeutics, which are subsequently subject to further in-depth characterization using more advanced in vivo model systems and clinical trials.
BACKGROUND:Pancreatic cancer is a disease of near uniform fatality and the overwhelming majority of patients succumb to their advanced malignancy within a few months of diagnosis. Despite considerable advances in our understanding of molecular mechanisms underlying pancreatic carcinogenesis, this knowledge has not yet been fully translated into clinically available treatment strategies that yield significant improvements in disease free or overall survival. OBJECTIVE: Cell line-based in vitro model systems provide powerful tools to identify potential molecular targets for therapeutic intervention as well as for initial pre-clinical evaluation of novel drug candidates. Here we provide a brief overview of recent literature on cell line-based model systems of pancreatic cancer and their application in the search for novel therapeutics against this vicious disease. CONCLUSION: While in vitro models of pancreatic cancer are of tremendous value for genetic studies and initial functional screenings in drug discovery, they carry several imanent drawbacks and are often poor in predicting therapeutic response in humans. Therefore, in most instances they are successfully exploited to generate hypothesis and identify molecular targets for novel therapeutics, which are subsequently subject to further in-depth characterization using more advanced in vivo model systems and clinical trials.
Authors: Koichi Fukino; Lei Shen; Satoshi Matsumoto; Carl D Morrison; George L Mutter; Charis Eng Journal: Cancer Res Date: 2004-10-15 Impact factor: 12.701
Authors: Andrew J Aguirre; Nabeel Bardeesy; Manisha Sinha; Lyle Lopez; David A Tuveson; James Horner; Mark S Redston; Ronald A DePinho Journal: Genes Dev Date: 2003-12-17 Impact factor: 11.361
Authors: H Hahn; C Wicking; P G Zaphiropoulous; M R Gailani; S Shanley; A Chidambaram; I Vorechovsky; E Holmberg; A B Unden; S Gillies; K Negus; I Smyth; C Pressman; D J Leffell; B Gerrard; A M Goldstein; M Dean; R Toftgard; G Chenevix-Trench; B Wainwright; A E Bale Journal: Cell Date: 1996-06-14 Impact factor: 41.582
Authors: Kayleigh C Ross; Andrew J Andrews; Christopher D Marion; Timothy J Yen; Vikram Bhattacharjee Journal: Mol Cancer Ther Date: 2017-05-12 Impact factor: 6.261
Authors: Leslie A Parsels; Qiang Zhang; David Karnak; Joshua D Parsels; Kwok Lam; Henning Willers; Michael D Green; Alnawaz Rehemtulla; Theodore S Lawrence; Meredith A Morgan Journal: Int J Radiat Oncol Biol Phys Date: 2021-08-01 Impact factor: 7.038
Authors: Aleksandra Buha; David Wallace; Vesna Matovic; Amie Schweitzer; Branislav Oluic; Dusan Micic; Vladimir Djordjevic Journal: Biomed Res Int Date: 2017-11-16 Impact factor: 3.411