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. 2025 Mar 10;9(1):66.
doi: 10.1038/s41698-025-00858-0.

A nationwide comprehensive genomic profiling and molecular tumor board platform for patients with advanced cancer

Pieter-Jan Volders  1   2   3 , Philippe Aftimos  4 , Franceska Dedeurwaerdere  5 , Geert Martens  6 , Jean-Luc Canon  7 , Gabriela Beniuga  8 , Guy Froyen  1   2 , Jacques Van Huysse  9 , Rebecca De Pauw  10 , Hans Prenen  11   12 , Suzan Lambin  13 , Lore Decoster  14   15 , Freya Vaeyens  16 , Sylvie Rottey  17 , Pieter-Jan Van Dam  18 , Lynn Decoster  19 , Annemie Rutten  20 , Max Schreuer  21 , Siebe Loontiens  3   22   23 , Joni Van der Meulen  3   22   23 , Jeroen Mebis  2   24 , Kristof Cuppens  2   25 , Sabine Tejpar  26 , Isabelle Vanden Bempt  27 , Jacques De Grève  15   16 , David Schröder  7 , Cédric van Marcke  28   29 , Marc Van Den Bulcke  30 , Evandro de Azambuja  31 , Kevin Punie  20 , Brigitte Maes  32   33
Affiliations

A nationwide comprehensive genomic profiling and molecular tumor board platform for patients with advanced cancer

Pieter-Jan Volders et al. NPJ Precis Oncol. .

Abstract

The Belgian Approach for Local Laboratory Extensive Tumor Testing (BALLETT) study assessed the feasibility of using comprehensive genomic profiling (CGP) in clinical decision-making for patients with advanced cancers. This multi-center study enrolled 872 patients from 12 Belgian hospitals. CGP was performed on tumor tissues using a standardized CGP panel (523 genes) across nine laboratories with success in 93% of patients and a median turnaround time of 29 days. Actionable genomic markers were identified in 81% of patients, substantially higher than the 21% using nationally reimbursed, small panels. A national molecular tumor board (nMTB) recommended treatments for 69% of patients, with 23% receiving matched therapies. Reasons for non-compliance were highly variable across clinical sites. Overall, BALLETT demonstrates the feasibility of implementing decentralized CGP and its potential to identify actionable targets in most patients with advanced cancers. BALLETT reinforces CGP's utility and emphasizes the importance of collaboration, standardization, and addressing implementation challenges.

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Conflict of interest statement

Competing interests: Author P.A. declares a consultancy role with Boehringer Ingelheim, Roche, Novartis, Amcure, Servier, G1 Therapeutics, Radius, Deloitte, Daiichi Sankyo, Olema; honoraria from Synthon, Amgen, Novartis, Gilead, Lilly and Menarini; travel grants from Amgen, MSD, Pfizer, Roche, Daiichi Sankyo; research funding to his institution from Roche. Author K.P. declares speaker fees and/or honoraria for advisory/consultancy roles from Astra Zeneca, Eli Lilly, Exact Sciences, Focus Patient, Izidok, Medimix, Medscape, MSD, Mundi Pharma, Need Inc., Novartis, Pfizer, Hoffmann/La Roche, Sanofi and Seagen; travel grants from Astra Zeneca, Gilead Sciences, MSD, Novartis, Pfizer, PharmaMar and Hoffmann/La Roche. Author C.v.M. is a board member of BSMO but declares no personal financial competing interest. Author K.C. declares speaker fees and/or honoraria for advisory/consultancy roles from Amgen, Astra Zeneca, Bristol-Myers-Squibb, Daiichi Sankyo, Iteos therapeutics, Janssen, Merck Sharp Dohme, Pierre-Fabre Oncology. All other authors declare no financial or non-financial competing interests.

Figures

Fig. 1
Fig. 1. Patient characteristics and study flow.
a General overview of the BALLETT study recruitment, success rate, and recommendations. b Overview of the participants’ characteristics and tumor types.
Fig. 2
Fig. 2. CGP success rate, turnaround times, and timeline.
a CGP success rate across the different participating labs. The overall success rate was high (93%). b Turnaround time (TAT) at the participating sites. TAT is measured as the days between signing the informed consent form and delivering the report to the treating clinician. The median TAT was 29 days, yet differences between the sites are apparent. c Timeline of the patient trajectory indicating key milestones with median values in days as assessed for all patients.
Fig. 3
Fig. 3. Overview of actionable findings.
a Frequency of actionable genomic alterations and biomarkers across different tumor types in the BALLETT study. b Comparison of actionability using CGP versus standard-of-care gene panels in Belgium.
Fig. 4
Fig. 4. Treatment recommendations and uptake.
a Relative distribution of treatment recommendation types across tumor types. b Uptake rate of the nMTB recommendations and reasons for deviation from recommendations across participating hospitals in the BALLETT study. MNP medical need program.
Fig. 5
Fig. 5. BALLETT study workflow.
Workflow diagram, illustrating the process from patient recruitment to treatment recommendation.
See this image and copyright information in PMC

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