Abstract 1668P
Background
Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with specific genomic and pathological characteristics. Although some 30 anti-neoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed. Several patient-derived tumor models have been proposed to serve as therapeutic prediction tools. However, the lack of tumor microenvironment considerations and time-consuming procedures make their clinical utility limited.
Methods
Cells were recovered from newly resected breast tumors as whole-tumor cell cultures (WTCs). Immunohistochemistry, flow cytometry, DNA- and RNA- sequencing were performed to ensure the WTCs recapitulate the biology of original tumors. A broad range of clinically relevant drugs was tested on the WTCs. Cell viability assay, real-time imaging tool, transcriptomic analysis, and panel gene-expression analysis were carried out to investigate the model's predictive value and clinical relevance. A separate validation study was also carried out to compare WTC-based test results and patients’ clinical responses in neoadjuvant treatment settings.
Results
We generated WTCs with a high success rate (±90%) for all subtypes of breast tumors. The hormone receptors, Ki67, HER2 status, tumor microenvironment interactions, mutational signatures, and gene-expression profiles were well-retained in the WTCs. We observed strong clinical relevance and predictive values in WTCs from the drug-profiling data by calculating drug sensitivity scores (DSS) in combination with gene-expression analyses. The WTC-based testing results and patient clinical responses toward standard neoadjuvant therapies also showed good concordance for the first 15 enrolled BC patients in the validation study.
Conclusions
The WTC represents the original tumor characteristics to a large extent and allows us to accomplish personalized drug testing within 10-days, highlighting its potential for individualized BC therapy. Coupled with genomic and transcriptomic analyses, WTC-based testing can also help stratify specific BC patient groups for assignment into appropriate clinical trials and validate potential biomarkers.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Swedish Society of Medicine, Swedish Society for Medical Research, Swedish Cancer Society, Swedish Research Council, Cancer Society in Stockholm, Region Stockholm, MedTechLabs, Swedish Breast Cancer Association.
Disclosure
T. Foukakis: Financial Interests, Institutional, Research Grant: Roche, Pfizer; Financial Interests, Personal, Speaker’s Bureau: Novartis, Pfizer, Roche, UpToDate. J. Hartman: Financial Interests, Personal, Speaker’s Bureau: Roche, Novartis, AstraZeneca, Eli Lilly, MSD; Financial Interests, Institutional, Research Grant: Cepheid, Novartis; Financial Interests, Institutional, Funding: Roche; Financial Interests, Personal, Ownership Interest: Stratipath. All other authors have declared no conflicts of interest.