Evidence map›Paper›PMID 40425842›Full record

Observational studyNature medicine2025

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, Stephane Chevrier and 46 more

Erratum issued Registry-linked trialAbstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT06463509 (Establishment and Standardization of a Platform for In-depth Tumour Profiling), which is not on this map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06463509 completednot on this map

Establishment and Standardization of a Platform for In-depth Tumour Profiling (TUPRO) in Patients With Advanced Melanoma - a Prospective, Multicentric HFV Research Project/Category A

TypeobservationalSponsorReinhard DummerRan2019 to 2023Enrolled116ConditionsMelanomaArmsEstablishment of an in-deepth tumor profiling platform
3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
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  7. Target discovery and drug design in the era of artificial intelligence.Medicinal chemistry research : an international journal for rapid communications on design and mechanisms of action of biologically active agents · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

56 authors.

Nicola Miglino *Department of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Nora C Toussaint *NEXUS Personalized Health Technologies, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-7911-7647
Alexander Ring *Department of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Ximena Bonilla *Department of Computer Science, Institute of Machine Learning, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-4950-6825
Marina Tusup *Department of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Benedict GosztonyiDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Tarun MehraDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.ORCID http://orcid.org/0009-0005-8429-5110
Gabriele GutDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Francis JacobDepartment of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland.ORCID http://orcid.org/0000-0002-0446-1942
Stephane ChevrierDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Kjong-Van LehmannDepartment of Computer Science, Institute of Machine Learning, ETH Zurich, Zurich, Switzerland.
Ruben CasanovaDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Andrea JacobsDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Sujana SivapathamDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.
Laura BoosDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Parisa RahimzadehDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-7192-9795
Manuel SchuerchDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Bettina SobottkaDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital, Zurich, Switzerland.
Natalia ChicherovaNEXUS Personalized Health Technologies, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-7899-0348
Shuqing YuNEXUS Personalized Health Technologies, ETH Zurich, Zurich, Switzerland.
Rebekka WegmannDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-9616-3303
Julien MenaDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-8040-810X
Emanuela S MilaniDepartment of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Sandra GoetzeDepartment of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-6880-8020
Cinzia EspositoDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Jacobo Sarabia Del CastilloDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Anja L FreiDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital, Zurich, Switzerland.
Marta NowakDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital, Zurich, Switzerland.
Anja IrmischRoche Pharmaceutical Research and Early Development, Roche Innovation Center, Zurich, Switzerland.
Jack KuipersSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Monica-Andreea Baciu-DrăganSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Pedro F FerreiraSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Franziska SingerNEXUS Personalized Health Technologies, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-6017-1595
Anne BertoliniNEXUS Personalized Health Technologies, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-0691-0489
Michael PrummerNEXUS Personalized Health Technologies, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-9896-3929
Ulrike LischettiDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Tumor Profiler Consortium
Rudolf AebersoldDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-9576-3267
Marina BacacRoche Pharmaceutical Research and Early Development, Roche Innovation Center, Zurich, Switzerland.
Gerd MaassRoche Diagnostics GmbH, MWG, Penzberg, Germany.
Holger MochDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-7986-2839
Michael WellerDepartment of Neurology, University Hospital and University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-1748-174X
Alexandre P A TheocharidesDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.
Markus G ManzDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-4676-7931
Niko BeerenwinkelSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.ORCID http://orcid.org/0000-0002-0573-6119
Christian BeiselDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID http://orcid.org/0000-0001-5360-2193
Lucas PelkmansDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.
Berend SnijderDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Bernd WollscheidDepartment of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Viola HeinzelmannDepartment of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland.
Bernd BodenmillerDepartment of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-6325-7861
Mitchell P LevesqueDepartment of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-5902-9420
Viktor H KoelzerDepartment of Pathology and Molecular Pathology, University of Zurich and University Hospital, Zurich, Switzerland.ORCID http://orcid.org/0000-0001-9206-4885
Gunnar RätschSIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Reinhard DummerDepartment of Dermatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-2279-6906
Andreas WickiDepartment of Medical Oncology and Hematology, University of Zurich and University Hospital, Zurich, Switzerland. andreas.wicki@usz.ch.ORCID http://orcid.org/0000-0002-2924-8080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 .

Indexed as

Biomarkers, TumorMelanomaSkin NeoplasmsAdultAgedAged, 80 and overFeasibility StudiesFemaleGenomicsHumansMaleMiddle AgedMultiomicsPrecision MedicineProgression-Free SurvivalProspective StudiesBiomarkers, Tumor

Identifiers

PMID40425842
PMCPMC12283375

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.