Author

Maxime Vanmechelen

KU LeuvenORCID 0000-0002-8342-3150Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:experimental assay· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Frederik De SmetiD· 3 shared Pouya NazariiD· 3 shared Asier AntoranziD· 2 shared Brecht DecraeneiD· 2 shared Francesca Maria BosisioiD· 2 shared Abhishek Dinkarnath GargiD· 1 shared Alexandre ArnouldiD· 1 shared Ann HoebeniD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersCancer Biology

Frederik De SmetORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Longitudinal tumor ecosystem mapping defines glioblastoma treatment trajectories

Maxime Vanmechelen, Pouya Nazari, Jan C. Beckervordersandforth, Chiara Caprioli, Daphne J. G. Leunissen, Basiel Cole, Carmen Bravo González‐Blas, Brecht Decraene, Yanti De Visser, G Shankar, Maikel Verduin, daniele Pantano, Sien Bevers, Tom Moors, Shanna Zielinski, , Frederik De Smet

This study maps glioblastoma tumor ecosystems over time using spatial single-cell profiling to identify prognostic subgroups and treatment responses.

bioRxiv · Mar 7, 2026 · PreprintCancer Biology

Distinct tumor immune microenvironmental (TIME) landscapes drive divergent immunotherapy responses in glioblastoma

Linqian Weng, Krish Skandha Gopalan, Mélanie Guyot, Maxime Vanmechelen, Pouya Nazari, Marie Duhamel, Clelia Donisi, Carla Pallarés-Moratalla, Abhishek Dinkarnath Garg, Kieron White, Annette T. Byrne, Diether Lambrechts, Frederik De Smet, Gabriele Bergers

This study identifies three distinct tumor immune microenvironment (TIME) subtypes in glioblastoma (GBM) with divergent responses to immunotherapy, supporting personalized treatment strategies.

Neuro-Oncology · Jan 27, 2026Peer-reviewedCancer Biology

QUAL-IF-AI: Quality Control of Immunofluorescence Images using Artificial Intelligence

Madhavi Dipak Andhari, Giulia Rinaldi, Pouya Nazari, Gautam Shankar, Nikolina Dubroja, Johanna Vets, Tessa Ostyn, Maxime Vanmechelen, Brecht Decraene, Alexandre Arnould, Willem Mestdagh, Bart De Moor, Frederik De Smet, Francesca Maria Bosisio, Asier Antoranz

QUAL-IF-AI is a deep learning tool that detects and manages artifacts in multiplex immunofluorescence images, achieving high accuracy and IoU across common artifact types.

bioRxiv · Jan 26, 2024 · PreprintBioinformatics