Prospective clinical trial of the Oncobox

Interrogating gene expression in tumor can identify up- and downregulated molecular targets of cancer drugs. Here we report the results of prospective clinical investigation NCT03724097 of using RNA sequencing analysis for personalized cancer therapy. Transcriptomic profiles were analyzed using computational algorithm Oncobox that identifies altered expression of drug target genes and molecular pathways and builds a personalized rating of targeted therapeutics. Oncobox reports were provided to oncologists, and treatment outcomes were assessed. Totally, 239 adult solid cancer patients were enrolled: 135 received cancer drug therapy, others received palliative treatment or radiotherapy, or died before therapy started. Oncobox recommended drugs were prescribed in 59% of the cases receiving therapy. Otherwise, patients received non-targeted therapy or targeted therapy predicted as inefficient by Oncobox (controls). Patients in the Oncobox group were significantly pre-treated compared to controls (mean number of previous lines therapy 2 vs 1.2, respectively), but we observed a longer progression-free survival (PFS) trend in the Oncobox group. Furthermore, post-hoc analysis revealed that time between biopsy collection and tumor molecular profiling significantly impacts Oncobox predictive capacity. Excluding patient cases with biopsy obtained more than 7 months before RNA sequencing lead to a statistically significant difference in PFS between Oncobox and control groups with hazard ratio of 0.45 (95% CI: 0.23-0.9, p-value = 0.023). These results suggest that transcriptomic profiling provides clinically relevant therapeutic match and can improve disease control rate in recurrent and/or metastatic solid cancers.