In vitro assays as a tool to personalize treatment in central nervous system tumors: a systematic literature review

Martina Offi1,2, Mariachiara Buccarelli3, Silvia Chiesa4

  • 1Department of Neuroscience, Catholic University School of Medicine, Rome, Italy.

PubMed

Insights

In vitro drug screening using patient-derived models shows promise for predicting brain tumor treatment outcomes, potentially overcoming limitations of molecular profiling in neuro-oncology.

Area of Science:

  • Neuro-oncology
  • Translational Cancer Research
  • Genomics and Precision Medicine

Background:

  • Personalized neuro-oncology treatments traditionally depend on molecular profiling, but clinical benefits have been limited.
  • In vitro drug sensitivity testing with patient-derived models (organoids, cell lines) is an emerging strategy.
  • Molecular profiling faces challenges in glioblastoma due to absent driver mutations and evolving profiles at recurrence.

Purpose of the Study:

  • To systematically review the evidence on the efficacy of in vitro drug screening in predicting treatment outcomes for brain tumors.
  • To assess the potential of patient-derived models to enhance personalized neuro-oncology.
  • To evaluate the quality of evidence supporting in vitro drug screening for brain tumor treatment prediction.

Main Methods:

  • Systematic literature review following PRISMA guidelines.
  • Inclusion of 15 studies encompassing 300 patients, predominantly cohort studies.
  • Analysis of evidence from in vitro assays utilizing patient-derived stem cells, standardized assays (e.g., ChemoID), and tumor-derived organoids.

Main Results:

  • In vitro assays using patient-derived models demonstrated reliable prediction of treatment outcomes.
  • Patient-derived models may offer advantages over molecular profiling, particularly for glioblastoma.
  • The overall quality of evidence supporting these methods was limited, with only one randomized clinical trial identified.

Conclusions:

  • In vitro drug screening with patient-derived models is a promising strategy for personalized neuro-oncology.
  • These models show potential to overcome limitations of molecular profiling in brain tumor treatment selection.
  • Further clinical validation is required before widespread implementation in patient care.