Melanoma: who works on it

One card per institution. Filter by target, by country, or show only institutions in EU-13 (Horizon Europe widening) countries.

• All targets
• PD-1 55
• BRAF 18
• PD-L1 22
• MEK 7
• TP53 0
• CTLA-4 10
• MAPK 2
• NRAS 8
• STING 0
• STAT3 0
• PRAME 3
• AKT 0
• PI3K 0
• BAP1 2
• VEGF 4
• mTOR 0
• ERK 0
• LAG-3 2
• RAS 2
• CTNNB1 0
• CD40 0
• CDKN2A 3
• TNF 0
• YAP 0
• PTEN 1
• JAK 0
• KIT 3
• KRAS 1
• JNK 0
• PPAR 0
• TIGIT 0
• ALK 0
• B7-H3 3
• BCL-2 0
• EZH2 0
• HIF-1 0
• IL-15 1
• NF1 2
• NLRP3 0
• NRF2 0
• AMPK 0
• HSP90 0
• CD47 0
• MYC 0
• PKM2 0
• AXL 1
• COX-2 0
• EGFR 0
• GPX4 0
• MET 1
• HDAC 1
• IDH 1
• IL-17 1
• MMP-9 0
• CDK4/6 0
• CXCR4 0
• FGFR 0
• HER2 3
• IGF1R 0
• PSMA 3

EU-13 is a filter, not a ranking: it only narrows the list.

23 of 23+ institutions, ordered by recent publications and open trials. This is not a ranking of quality.

Terminated, withdrawn and suspended trials with the reason the sponsor gave in the registry, quoted word for word.

• Suspended

  JSI-1187-01 Monotherapy and in Combination With Dabrafenib for Advanced Solid Tumors With MAPK Pathway Mutations

  NCT04418167· JS InnoPharm, LLC· Updated 3 Sept 2025

  “Sponsor decision”Registry text, quoted unchanged. Source

• Terminated

  A Phase Ib Study of LXH254-centric Combinations in NSCLC or Melanoma

  NCT02974725· Novartis Pharmaceuticals· Updated 13 Apr 2025

  “Business reasons”Registry text, quoted unchanged. Source

• Suspended

  MEK Inhibitor FCN-159 To Treat Advanced Melanoma With NRAS-aberrant (Ia) and NRAS-mutant (Ib)or NF1-mutant(1b)

  NCT03932253· Shanghai Fosun Pharmaceutical Industrial Development Co. Ltd.· Updated 27 Mar 2024

  “Sponsor R\&D strategy adjustment”Registry text, quoted unchanged. Source

Trials whose registry record says individual participant data (IPD) will be shared.

• A Study to Evaluate the Safety and Activity of Belvarafenib as a Single Agent and in Combination With Either Cobimetinib or Cobimetinib Plus Nivolumab in Patients With NRAS-mutant Advanced Melanoma.

  NCT04835805· Genentech, Inc.· Source

• Study of Efficacy and Safety of LXH254 Combinations in Patients With Previously Treated Unresectable or Metastatic Melanoma

  NCT04417621· Novartis Pharmaceuticals· Source

Find publications on this disease by a MeSH method term, for example a sequencing or imaging method.

• Single-Cell Analysis 51
• Organoids 8
• Mendelian Randomization Analysis 12
• CRISPR-Cas Systems 21
• Gene Expression Profiling 116
• Sequence Analysis, RNA 9
• Whole Genome Sequencing 6
• Exome Sequencing 7
• Proteomics 46
• Metabolomics 20
• Mass Spectrometry 9
• Flow Cytometry 65
• Immunohistochemistry 106
• Liquid Biopsy 12
• Circulating Tumor DNA 37
• Xenograft Model Antitumor Assays 121
• Positron-Emission Tomography 31
• Magnetic Resonance Imaging 56
• Machine Learning 49
• Deep Learning 44
• Cohort Studies 77
• Genome-Wide Association Study 22

• Explainable machine learning predictive models for treatment response after SBRT in melanoma brain metastases.

  J Neurooncol, Nov 2026

• Pre-treatment machine learning prediction of local failure and time to local failure after Gamma Knife radiosurgery for radioresistant brain metastases.

  J Neurooncol, Nov 2026

• Burden of malignant melanoma among the elderly population in East Asia from 1990 to 2023 and machine learning projection to 2040.

  PLoS One, Sept 2026

• Predicting Targeted and Immunotherapeutic Response Outcomes in Melanoma With Single-Cell Raman Spectroscopy and Artificial Intelligence.

  JCO Precis Oncol, Sept 2026

• Explainable AI-Assisted Label-Free Raman Biosensing Reveals Therapy-Associated Spectral Signatures in Melanoma Tumors.

  Biosensors (Basel), Sept 2026

• A multiscale geospatial analysis integrating explainable machine learning to characterize spatial disparities in melanoma mortality associated with environmental justice and healthcare access in the contiguous United States.

  Front Public Health, Aug 2026

• Development of a novel RNA modification-based risk model to predict prognosis and immunotherapy response in melanoma using machine learning.

  J Cancer Res Clin Oncol, Aug 2026

• Automated model-based lesion tracking in CT: colorectal liver metastases as a use case for development and performance analysis.

  Eur Radiol Exp, Jul 2026

• FFixR: a machine learning framework for accurate somatic mutation calling from FFPE RNA-seq data in cancer.

  Bioinformatics, Jul 2026

• Identification of cell pyroptosis-related gene signature for prognosis in skin cutaneous melanoma.

  Comput Biol Chem, Jun 2026

See which targets of this disease your abstract mentions, and go to the people working on them.