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Prospective prediction of clinical drug response in high-grade gliomas using an ex vivo 3D cell culture assay.


ABSTRACT:

Background

Clinical outcomes in high-grade glioma (HGG) have remained relatively unchanged over the last 3 decades with only modest increases in overall survival. Despite the validation of biomarkers to classify treatment response, most newly diagnosed (ND) patients receive the same treatment regimen. This study aimed to determine whether a prospective functional assay that provides a direct, live tumor cell-based drug response prediction specific for each patient could accurately predict clinical drug response prior to treatment.

Methods

A modified 3D cell culture assay was validated to establish baseline parameters including drug concentrations, timing, and reproducibility. Live tumor tissue from HGG patients were tested in the assay to establish response parameters. Clinical correlation was determined between prospective ex vivo response and clinical response in ND HGG patients enrolled in 3D-PREDICT (ClinicalTrials.gov Identifier: NCT03561207). Clinical case studies were examined for relapsed HGG patients enrolled on 3D-PREDICT, prospectively assayed for ex vivo drug response, and monitored for follow-up.

Results

Absent biomarker stratification, the test accurately predicted clinical response/nonresponse to temozolomide in 17/20 (85%, P = .007) ND patients within 7 days of their surgery, prior to treatment initiation. Test-predicted responders had a median overall survival post-surgery of 11.6 months compared to 5.9 months for test-predicted nonresponders (P = .0376). Case studies provided examples of the clinical utility of the assay predictions and their impact upon treatment decisions resulting in positive clinical outcomes.

Conclusion

This study both validates the developed assay analytically and clinically and provides case studies of its implementation in clinical practice.

SUBMITTER: Shuford S 

PROVIDER: S-EPMC8207705 | biostudies-literature |

REPOSITORIES: biostudies-literature

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