Abstract 3910
Background
Cancer immunotherapy based on immune checkpoint inhibitors (ICIs) is approved in several indications, in most of them independently of biomarker status. Yet, in the era of precision oncology, detailed tumor molecular profiling is a prerequisite of informed therapeutic decisions.
Methods
Tumor molecular profiles of 159 patients were analyzed by NGS (595 cancer-associated genes), PD-L1 IHC and MSI assays. Molecular alterations and targeted therapy drugs were classified and ranked by relevance based on scientific evidence by our in-house developed algorithm, the Realtime Oncology Molecular Treatment Calculator.
Results
Of the 159 samples 20 (13%) originated from tumors where at least one ICI is approved without biomarker status. 10 (50%) of these were positive to at least one immunotherapy-related biomarker (TMB-H, MSI-H or PD-L1 positive). In the remaining samples biomarker positivity was detected in 38 cases (27%). Directly targetable driver mutations were detected in 60% of the biomarker-positive and 49% of the biomarker-negative samples. Directly targetable mutations were detected in 60% of the biomarker-independently ICI-approved tumors, and in 51% of the other tumor types. JAK1/2 and STK11 mutations are known to lead to resistance to ICI treatments. Deleterious JAK1/2 mutations were detected in 9 patients, 1 in the biomarker-independent ICI group, while both two detected STK11 mutations were present in this group.
Conclusions
We found that ICI-biomarkers are more common in tumor types where ICIs are approved irrespectively of biomarker status, suggesting that these tumor types are more prone to immune evasion. However, in line with the increased mutational burden, biomarker positive tumors also tend to harbor somewhat more directly targetable driver mutations. We computationally ranked driver-drug relations according to the relevant evidence database and found that in 8 of the 29 ICI-biomarker and actionable driver double positive cases targeting the drivers was ranked with higher evidence scores than ICI therapy. These results highlight that strong drivers may favor targeted inhibition, and the importance of use of an evidence-based standardized algorithm to support driver versus ICI therapy decisions in precision oncology.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
R. Dóczi: Full / Part-time employment: Oncompass Medicine Hungary Ltd. D. Tihanyi: Full / Part-time employment: Oncompass Medicine Hungary Ltd. P. Filotas: Full / Part-time employment: Oncompass Medicine Hungary Ltd. A. Dirner: Full / Part-time employment: Oncompass Medicine Hungary Ltd. B. Pálházi: Full / Part-time employment: Oncompass Medicine Hungary Ltd. E. Várkondi: Full / Part-time employment: Oncompass Medicine Hungary Ltd. Z. Farkas: Full / Part-time employment: Oncompass Medicine Hungary Ltd. J. Deri: Full / Part-time employment: Oncompass Medicine Hungary Ltd. C. Hegedus: Full / Part-time employment: Oncompass Medicine Hungary Ltd. I. Petak: Leadership role, ownership: Oncompass Medicine Hungary Ltd. All other authors have declared no conflicts of interest.
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