1242P - Implementing functional precision oncology in real-world patients: Translating extensive in vitro data into personalized treatment combining genetics and functional assays

Background

Predictive and prognostic biomarkers for personalising cancer therapy are now widely used, but their application is still far from standard of care. Focusing exclusively on DNA alterations leads to a clinically relevant outcome in 40-60 % of patients; clinical benefit is another matter. Comprehensive tumor profiling could be a tool to improve treatment efficiency, revealing more actionable characteristics for combining appropriate therapies.

Methods

37 real world patients with progressive metastatic solid tumors were treated based on comprehensive tumor profilings (Exacta). The test method comprised genetics, expression profiling, IHC, immunocytochemistry, pharmacogenomics, and chemosensitivity using tissue or blood analyses. Therefore therapy options are found for the majority of patients (>99%),not only related to NGS. Data were collected over four years. Intrapatient analysis was applied, comparing PFS1 of the last guideline therapy with PFS2 of the matched treatment (ratio). Imaging data, side effects and quality of life were constantly recorded during the course. Individual analyses provide therapy options that are not apparent at first glance and applied drug combinations were discussed in a digital molecular tumor board.

Results

In 78% of patients, comprehensive tumour testing improved their PFS compared to the previous standard of care treatment (PFS2/PFS1>1). In 24% of patients, we observed a doubling of progression-free survival. The median PFS2/PFS1 ratio was 1.25. Worth mentioning that 54% had a PFS2 of more than 6 months (range 5-159 weeks), and eight patients still did not reach PFS2 endpoint. 46% had also a PFS1 >6months. In the univariate analyses of the ratio, significant results were found in two scenarios that had a negative impact on prognosis: a higher total number of oncogenes (p=0.04) and the presence of a p53 mutation caused a lower ratio (p=0.013). ECOG did not change significantly.

Conclusions

Combining genomic and transcriptional profiling is useful to improve personalized treatment. If possible not only targets might be considered for choice of therapy but also the context of the whole pathway network together with biomarkers.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Dörthe Schaffrin-Nabe.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.