Establishment of PD3D models of sarcomas: A promising preclinical tool for improvement of sarcoma treatment.

Abstract

e23538 Background: Compared to the progress in understanding and treating carcinomas in the past decade, the options and related clinical benefit in terms of response rates and overall survival for sarcoma patients lacks behind. Increasing incidence, low 5-year-survival rates and nearly endless heterogeneity of sarcomas are challenging oncologists every day. The necessity of so far missing representative preclinical models is obvious. PD3D cell culture models have already proven to be a useful tool to reverse clinical engineer patient outcome in carcinomas. Here we report the establishing and refining of PD3D models for the plethora of sarcoma entities. Methods: We obtained viable sarcoma tissue samples from incisional biopsies or tumor resections. We continuously optimized media conditions. For quality control and pathological evaluation, we embedded the cells in FFPE, stained patient-specific models according to original tumor samples and evaluated them pathologically. Upon histopathological evaluation, we performed semi-automated drug response assays on patient-specific models with up to 12 drugs and drug combinations, including standard of care drugs plus a selection of additional drugs. In the fashion of a prospective observatory study, we compared the results from the in vitro screen with the actual clinical outcome. Results: More than 25 patient derived 3D-cell culture models have been established from various subtypes of sarcomas. Optimized media conditions and sampling operation improved the take rates from ca. 10 to 80% irrespective of the tumor subtype. Pathological examination of the models confirmed original diagnoses and revealed that the patient-specific models recapitulate the key properties of the original tumor. Negative predictive value of drug sensitivity testing was close to 100 %, while the positive predictive value was > 80 %. These results in a limited number of cases puts the predictive value en par with recently published data about the predictive value of patient-derived organoids in carcinomas. Conclusions: Patient derived 3D-cell culture models of sarcomas can be routinely established, irrespective of subtype Models can be used for multi-omics analyses including drug sensitivity screenings Pretherapeutic drug sensitivity screenings could support clinical decision making Findings need to be confirmed in a prospective observatory trial.