Feasibility of multiomics tumor profiling for guiding treatment of melanoma
Nicola Miglino, Nora C. Toussaint, Alexander Ring, Ximena Bonilla, Marina Tusup, Benedict Gosztonyi, Tarun Mehra, Gabriele Gut, Francis Jacob, Stéphane Chevrier, Kjong-Van Lehmann, Ruben Casanova, Andrea Jacobs, Sujana Sivapatham, Laura Amanda Boos, Parisa Rahimzadeh, Manuel Schuerch, Bettina Sobottka, Natalia Chicherova, Shuqing Yu, Rebekka Wegmann, Julien Mena, Emanuela S. Milani, Sandra Goetze, Cinzia Esposito, Jacobo Sarabia del Castillo, Anja Frei, Marta Nowak, Anja Irmisch, Jack Kuipers, Monica-Andreea Baciu-Drăgan, Pedro Ferreira, Franziska Singer, Anne Bertolini, Michael Prummer, Ulrike Lischetti, Melike Ak, Faisal Alquaddoomi, Silvana I. Albert, Jonas Albinus, Ilaria Alborelli, Sonali Andani, Per-Olof Attinger, Monica-Andreea Baciu-Drăgan, Daniel Baumhoer, Beatrice Beck‐Schimmer, Lara Bernasconi, Lars Bosshard, Byron Calgua, Stéphane Chevrier, Ricardo Coelho, Maya D’Costa, Esther Danenberg, Natalie R. Davidson, Stefanie Engler, Martin Erkens, Katja Eschbach, André Fedier, Joanna Ficek-Pascual, Bruno S. Frey, Linda Grob, Detlef Günther, Pirmin Haeuptle, Viola Heinzelmann‐Schwarz, Sylvia Herter, René Holtackers, Tamara Huesser, Alexander Immer, Tim M. Jaeger, Alva Rani James, Philip Jermann, André Kahles, Abdullah Kahraman, Werner Kuebler, Christian P. Kunze, Christian Kurzeder, Mitchell P. Levesque, Flavio C. Lombardo, Sebastian Lugert, Philipp Markolin, Martin Mehnert, Julian M. Metzler, Simone Muenst, Riccardo Murri, Charlotte K.Y. Ng, Stefan Nicolet, Mónica Núñez López, Patrick G. A. Pedrioli, Salvatore Piscuoglio, Laurie Prélot, Natalie Rimmer, Mathilde Ritter, Christian Rommel, María L. Rosano-González, Natascha Santacroce, Ramona Schlenker, Petra Schwalie, Severin Schwan, Tobias Schär, Gabriela Senti
Abstract
There is limited evidence supporting the feasibility of using omics and functional technologies to inform treatment decisions. Here we present results from a cohort of 116 melanoma patients in the prospective, multicentric observational Tumor Profiler (TuPro) precision oncology project. Nine independent technologies, mostly at single-cell level, were used to analyze 126 patient samples, generating up to 500 Gb of data per sample (40,000 potential markers) within 4 weeks. Among established and experimental markers, the molecular tumor board selected 54 to inform its treatment recommendations. In 75% of cases, TuPro-based data were judged to be useful in informing recommendations. Patients received either standard of care (SOC) treatments or highly individualized, polybiomarker-driven treatments (beyond SOC). The objective response rate in difficult-to-treat palliative, beyond SOC patients (n = 37) was 38%, with a disease control rate of 54%. Progression-free survival of patients with TuPro-informed therapy decisions was 6.04 months, (95% confidence interval, 3.75-12.06) and 5.35 months (95% confidence interval, 2.89-12.06) in ≥third therapy lines. The proof-of-concept TuPro project demonstrated the feasibility and relevance of omics-based tumor profiling to support data-guided clinical decision-making. ClinicalTrials.gov identifier: NCT06463509 .