Clinical trials of targeted therapy (TT) and immunotherapy (IT) for highly aggressive advanced melanoma have shown marked improvements in response and survival rates. However, real-world data on treatment patterns and clinical outcomes for patients with advanced BRAF V600 mutant melanoma are ultimately scarce. The study was designed as an observational retrospective chart review study, which included 382 patients with advanced BRAF V600 mutant melanoma, who received TT in a real-world setting and were not involved in clinical trials. The data were collected from twelve medical centers in Russia. The objective response rates (ORRs) to combined BRAFi plus MEKi and to BRAFi mono-therapy were 57.4% and 39.8%, respectively. The median progression-free survival (PFS) and median overall survival (OS) were 9.2 months and 22.6 months, respectively, for the combined first-line therapy; 9.4 months and 16.1 months, respectively, for the combined second-line therapy; and 7.4 months and 17.1 months, respectively, for the combined third- or higher-line therapy. Analysis of treatment patterns demonstrated the effectiveness of the combined TT with BRAF plus MEK inhibitors in patients with brain metastases, rare types of BRAF mutations, and across lines of therapy, as well as a well-tolerated and manageable safety profile.

e23142 Background: Anticancer target drugs (ATDs) specifically bind and inhibit molecular targets that play important roles in tumorigenesis. More than 150 different ATDs have been approved for clinical use worldwide, and the clinicians are faced with the problem of choosing the best therapeutic solution for each patient. The problem of efficient ATD selection remains largely unsolved and personalized approaches are needed to select the best ATD candidates for individual patients. Methods: We propose a new approach termed OncoFinder. It is based on digesting gene expression profiles for the analysis of activation of intracellular signalling pathways as a marker for the selection of target therapies. The original bioinformatic algorithms were integrated with the databases featuring molecular drug targets, compositions of signalling pathways, including the functional role of each gene product, for more than 1700 pathways (Buzdin, Front.Genet 2014; Ozerov, Nature Communications 2016). Results: We showed that pathway activation strengths are more stable and reliable biomarkers of cancer than the expressions of individual genes. OncoFinder allows to detect changes at the level of pathway activation and to predict the effectiveness of drugs based on the knowledge of their molecular targets. We applied it to find new biomarkers of clinical response to the ATD cetuximab; for modelling the combined chemotherapy of acute myeloid leukemia and combined anti-VEGF/BRAF therapy of melanoma. For two unrelated datasets obtained for colon cancer patients before treatment with the ATD bevacizumab, we were able to distinguish between those who responded to treatment and not (p < 0.01). We next assayed biopsies for kidney cancer patients with known responses to the ATD sorafenib. The responders and non-responders showed a significant difference (p = 0.02). Finally, the OncoFinder platform was prospectively used for decision making support to patients with advanced metastatic solid tumors (n = 23). The efficiency of the ATD treatment was 61% (complete + partial response, RECIST). Conclusions: OncoFinder method may be effective for predicting response to ATD based on high throughput gene expression profiles.

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Background: Overall survival of advanced colorectal cancer (CRC) patients remains poor, and gene expression analysis could potentially complement detection of clinically relevant mutations to personalize CRC treatments. Methods: We performed RNA sequencing of formalin-fixed, paraffin-embedded (FFPE) cancer tissue samples of 23 CRC patients and interpreted the data obtained using bioinformatic method Oncobox for expression-based rating of targeted therapeutics. Oncobox ranks cancer drugs according to the efficiency score calculated using target genes expression and molecular pathway activation data. The patients had primary and metastatic CRC with metastases in liver, peritoneum, brain, adrenal gland, lymph nodes and ovary. Two patients had mutations in NRAS, seven others had mutated KRAS gene. Patients were treated by aflibercept, bevacizumab, bortezomib, cabozantinib, cetuximab, crizotinib, denosumab, panitumumab and regorafenib as monotherapy or in combination with chemotherapy, and information on the success of totally 39 lines of therapy was collected. Results: Oncobox drug efficiency score was effective biomarker that could predict treatment outcomes in the experimental cohort (AUC 0.77 for all lines of therapy and 0.91 for the first line after tumor sampling). Separately for bevacizumab, it was effective in the experimental cohort (AUC 0.87) and in 3 independent literature CRC datasets, n = 107 (AUC 0.84–0.94). It also predicted progression-free survival in univariate (Hazard ratio 0.14) and multivariate (Hazard ratio 0.066) analyses. Difference in AUC scores evidences importance of using recent biosamples for the prediction quality. Conclusion: Our results suggest that RNA sequencing analysis of tumor FFPE materials may be helpful for personalizing prescriptions of targeted therapeutics in CRC.

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