Molecular precision oncology faces two major challenges: first, to identify relevant and actionable molecular variants in a rapidly changing field and second, to provide access to a broad patient population. Here, we report a four-year experience of the Molecular Tumor Board (MTB) of the Comprehensive Cancer Center Freiburg (Germany) including workflows and process optimizations. This retrospective single-center study includes data on 488 patients enrolled in the MTB from February 2015 through December 2018. Recommendations include individual molecular diagnostics, molecular stratified therapies, assessment of treatment adherence and patient outcomes including overall survival. The majority of MTB patients presented with stage IV oncologic malignancies (90.6%) and underwent an average of 2.1 previous lines of therapy. Individual diagnostic recommendations were given to 487 patients (99.8%). A treatment recommendation was given in 264 of all cases (54.1%) which included a molecularly matched treatment in 212 patients (43.4%). The 264 treatment recommendations were implemented in 76 patients (28.8%). Stable disease was observed in 19 patients (25.0%), 17 had partial response (22.4%) and five showed a complete remission (6.6%). An objective response was achieved in 28.9% of cases with implemented recommendations and for 4.5% of the total population (22 of 488 patients). By optimizing the MTB workflow, case-discussions per session increased significantly while treatment adherence and outcome remained stable over time. Our data demonstrate the feasibility and effectiveness of molecular-guided personalized therapy for cancer patients in a clinical routine setting showing a low but robust and durable disease control rate over time.

(1) Background: Next-generation sequencing (NGS) of patients with advanced tumors is becoming an established method in Molecular Tumor Boards. However, somatic variant detection, interpretation, and report generation, require in-depth knowledge of both bioinformatics and oncology. (2) Methods: MIRACUM-Pipe combines many individual tools into a seamless workflow for comprehensive analyses and annotation of NGS data including quality control, alignment, variant calling, copy number variation estimation, evaluation of complex biomarkers, and RNA fusion detection. (3) Results: MIRACUM-Pipe offers an easy-to-use, one-prompt standardized solution to analyze NGS data, including quality control, variant calling, copy number estimation, annotation, visualization, and report generation. (4) Conclusions: MIRACUM-Pipe, a versatile pipeline for NGS, can be customized according to bioinformatics and clinical needs and to support clinical decision-making with visual processing and interactive reporting.

Background: Given the poor prognosis of metastatic pancreatic adenocarcinoma (mPDAC), closer disease monitoring through liquid biopsy, most frequently based on serial measurements of cell-free mutated KRAS (KRAS^mut cfDNA), has become a highly active research focus, aimed at improving patients’ long-term outcomes. However, most of the available data show only a limited predictive and prognostic value of single-parameter-based methods. We hypothesized that a combined longitudinal analysis of KRAS^mut cfDNA and novel protein biomarkers could improve risk stratification and molecular monitoring of patients with mPDAC. Methods: We prospectively collected 160 plasma samples from 47 patients with mPDAC at our institution. Highly sensitive single-target ddPCR assays were employed to detect and quantify KRAS^mut cfDNA. Additionally, analysis of ten protein biomarkers was performed through Enzyme-linked Immunosorbent Assay (ELISA), and Carbohydrate-Antigen 19-9 (CA 19-9) dynamics were registered. Results: KRAS^mut cfDNA was detectable in 37/47 (78.7%) patients throughout the course of study, and CA 19-9 levels were elevated in 40 out of 47 (85.1%) patients. KRAS^mut cfDNA increase at the time of the first follow-up could predict inferior progression-free survival (PFS) (Hazard ratio (HR) = 3.40, p = 0.0003) and overall survival (OS) (HR = 4.91, p < 0.0001). In contrast to CA 19-9 kinetics, which were not predictive of outcome, integrated analysis of KRAS^mut cfDNA combined with six evaluated circulating protein biomarkers allowed basal risk stratification at the time of the first follow-up (HR = 10.2, p = 0.0014). Conclusions: A combined longitudinal analysis of KRAS^mut cfDNA with selected protein biomarkers offers significantly improved prognostic value for patients with mPDAC compared to single-parameter methods. This innovative approach is a step forward in the molecular monitoring of mPDAC and should be validated in further prospective studies.

Background: Given the poor prognosis of metastatic pancreatic adenocarcinoma (mPDAC), closer disease monitoring through liquid biopsy, most frequently based on serial measurements of cell-free mutated KRAS (KRASmut cfDNA), has become a highly active research focus, aiming to improve patients´ long-term outcome. However, most of the available data show only a limited predictive and prognostic value of single-parameter based methods. We hypothesized that a combined longitudinal analysis of KRASmut cfDNA and novel protein biomarkers could improve risk stratification and molecular monitoring of patients with mPDAC. Methods: We prospectively collected 160 plasma samples from 47 patients with mPDAC at our institution. Highly sensitive single-target ddPCR assays were employed to detect and quantify KRASmut cfDNA. Additionally, analysis of ten protein biomarkers was performed through Enzyme-linked Immunosorbent Assay (ELISA), and CA 19-9 dynamics were registered. Results: KRASmut cfDNA was detectable in 37/47 (78.7%) patients through course of study, and CA 19-9 levels were elevated in 40 out of 47 (85.1%) patients. KRASmut cfDNA increase at time of first follow-up could predict inferior PFS (Hazard ratio (HR) = 3.40, P = 0.0003) and OS (HR = 4.91, P < 0.0001). In contrast to CA 19-9 kinetics, not predictive of outcome, integrated analysis of KRASmut cfDNA combined with six evaluated circulating protein biomarkers, allowed basal risk stratification at time of first follow-up (HR = 10.2, P = 0.0014). Conclusion: A combined longitudinal analysis of KRASmut cfDNA with selected protein biomarkers offers significantly improved prognostic value for patients with mPDAC compared to single-parameter methods. This innovative approach is a step forward in the molecular monitoring of mPDAC and should be validated in further prospective studies.