Nicola Miglino, Nora C. Toussaint, Alexander Ring, Ximena Bonilla, Marina Tusup, Benedict Gosztonyi, Tarun Mehra, Gabriele Gut, Francis Jacob, Stephane Chevrier, Kjong-Van Lehmann, Ruben Casanova, Andrea Jacobs, Sujana Sivapatham, Laura 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 L. Frei, Marta Nowak, Anja Irmisch, Jack Kuipers, Monica-Andreea Baciu-Drăgan, Pedro F. Ferreira, Franziska Singer, Anne Bertolini, Michael Prummer, Ulrike Lischetti, Rudolf Aebersold, Marina Bacac, Gerd Maass, Holger Moch, Michael Weller, Alexandre P. A. Theocharides, Markus G. Manz, Niko Beerenwinkel, Christian Beisel, Lucas Pelkmans, Berend Snijder, Bernd Wollscheid, Viola Heinzelmann, Bernd Bodenmiller, Mitchell P. Levesque, Viktor H. Koelzer, Gunnar Rätsch, Reinhard Dummer, Andreas Wicki
{"title":"Feasibility of multiomics tumor profiling for guiding treatment of melanoma","authors":"Nicola Miglino, Nora C. Toussaint, Alexander Ring, Ximena Bonilla, Marina Tusup, Benedict Gosztonyi, Tarun Mehra, Gabriele Gut, Francis Jacob, Stephane Chevrier, Kjong-Van Lehmann, Ruben Casanova, Andrea Jacobs, Sujana Sivapatham, Laura 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 L. Frei, Marta Nowak, Anja Irmisch, Jack Kuipers, Monica-Andreea Baciu-Drăgan, Pedro F. Ferreira, Franziska Singer, Anne Bertolini, Michael Prummer, Ulrike Lischetti, Rudolf Aebersold, Marina Bacac, Gerd Maass, Holger Moch, Michael Weller, Alexandre P. A. Theocharides, Markus G. Manz, Niko Beerenwinkel, Christian Beisel, Lucas Pelkmans, Berend Snijder, Bernd Wollscheid, Viola Heinzelmann, Bernd Bodenmiller, Mitchell P. Levesque, Viktor H. Koelzer, Gunnar Rätsch, Reinhard Dummer, Andreas Wicki","doi":"10.1038/s41591-025-03715-6","DOIUrl":null,"url":null,"abstract":"<p>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 (<i>n</i> = 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.</p>","PeriodicalId":19037,"journal":{"name":"Nature Medicine","volume":"51 1","pages":""},"PeriodicalIF":58.7000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1038/s41591-025-03715-6","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
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.
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