Experimental in vitro, ex vivo and in vivo models in prostate cancer research

Verena Sailer1, Gunhild von Amsberg2, Stefan Duensing3

  • 1Institute for Pathology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany.

Nature Reviews. Urology
|November 30, 2022
PubMed

Insights

Androgen deprivation therapy is key for advanced prostate cancer, but resistance necessitates better preclinical models. Current models must address tumor heterogeneity and microenvironment interactions for effective drug development.

Area of Science:

  • Oncology
  • Translational Medicine
  • Drug Discovery

Background:

  • Androgen deprivation therapy (ADT) is a cornerstone in advanced prostate cancer treatment, inducing initial remission but often followed by resistance and disease progression.
  • The development of novel therapeutic strategies is critical due to the increasing challenge of treatment resistance.
  • A significant gap exists between promising laboratory drug candidates and clinical approval, underscoring the need for improved preclinical evaluation.

Purpose of the Study:

  • To critically assess current preclinical models used in advanced prostate cancer research.
  • To highlight the limitations of existing models in recapitulating disease complexity.
  • To emphasize the requirements for preclinical models that can accurately predict clinical efficacy.

Main Methods:

  • Review of various preclinical models, including cell lines, organoids, xenografts, and genetically engineered mouse models.
  • Analysis of model capabilities in representing inter-patient and intra-patient heterogeneity.
  • Evaluation of models' capacity to incorporate tumor microenvironment interactions and 3D tissue effects.

Main Results:

  • A wide array of preclinical models are available, each with specific strengths and weaknesses.
  • Current models often fail to adequately capture critical aspects like tumor heterogeneity, resistance mechanisms, and microenvironment dynamics.
  • The 3D architecture of tumors significantly impacts drug penetration, bioavailability, and efficacy, a factor not fully represented in all models.

Conclusions:

  • There is an urgent need for advanced preclinical models that more accurately mimic the complexity of advanced prostate cancer.
  • Models must integrate tumor heterogeneity, microenvironment interactions, and 3D tissue properties to improve the translation of drug candidates to clinical success.
  • Enhanced preclinical models are essential for accelerating the development of effective novel treatments for advanced prostate cancer.