2. Academic Validation
  3. Unbiased Drug Target Prediction Reveals Sensitivity to Ferroptosis Inducers, HDAC and RTK Inhibitors in Melanoma Subtypes

Unbiased Drug Target Prediction Reveals Sensitivity to Ferroptosis Inducers, HDAC and RTK Inhibitors in Melanoma Subtypes

  • Int J Dermatol. 2024 Dec 25. doi: 10.1111/ijd.17586.
Indira Pla # 1 2,  Botond L Szabolcs # 3 4 5 6,  Petra Nikolett Péter # 3 4 5 7,  Zsuzsanna Ujfaludi 8 9,  Yonghyo Kim 10,  Peter Horvatovich 11,  Aniel Sanchez 12,  Krzysztof Pawlowski 12 13 14,  Elisabet Wieslander 12,  Magdalena Kuras 1 2,  Jimmy Rodriguez Murillo 15,  Jéssica Guedes 2 16 17,  Dorottya M P Pál 3 4 5,  Anna A Ascsillán 3 4 5,  Lazaro Hiram Betancourt 2 16,  István Balázs Németh 7,  Jeovanis Gil 2 18,  Natália Pinto de Almeida 2 16 17,  Beáta Szeitz 19,  Leticia Szadai 7,  Viktória Doma 7,  Nicole Woldmar 2 15 16,  Áron Bartha 20 21,  Zoltan Pahi 6 22,  Tibor Pankotai 8 9 22,  Balázs Győrffy 19 21,  A Marcell Szasz 19,  Gilberto Domont 17,  Fábio Nogueira 23,  Ho Jeong Kwon 24,  Roger Appelqvist 2 16,  Sarolta Kárpáti 5,  David Fenyö 25 26,  Johan Malm 12,  György Marko-Varga # 2 16,  Lajos V Kemény # 3 4 5 6
Affiliations

Affiliations

  • 1 Department of Biomedical Engineering, Faculty of Engineering, LTH, Lund University, Lund, Sweden.
  • 2 European Cancer Moonshot Lund Center, Lund, Sweden.
  • 3 HCEMM-SU Translational Dermatology Research Group, Semmelweis University, Budapest, Hungary.
  • 4 Department of Physiology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
  • 5 Department of Dermatology, Venereology and Dermatooncology, Faculty of Medicine, Semmelweis University, Budapest, Hungary.
  • 6 MTA-SE Lendület "Momentum" Dermatology Research Group, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary.
  • 7 Department of Dermatology and Allergology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary.
  • 8 Department of Pathology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary.
  • 9 Competence Centre of the Life Sciences Cluster of the Centre of Excellence for Interdisciplinary Research, Development and Innovation, University of Szeged, Szeged, Hungary.
  • 10 Drug Discovery Platform Research Center, Therapeutics and Biotechnology Division, Korea Research Institute of Chemical Technology, Daejeon, Republic of Korea.
  • 11 Groningen Research Institute of Pharmacy, Analytical Biochemistry, University of Groningen, Groningen, The Netherlands.
  • 12 Section for Clinical Chemistry, Department of Translational Medicine, Skåne University Hospital Malmö, Malmö, Sweden.
  • 13 Department of Biochemistry and Microbiology, Warsaw University of Life Sciences, Warszawa, Poland.
  • 14 Department of Molecular Biology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • 15 Thermo Fisher Scientific, Waltham, MA, USA.
  • 16 Clinical Protein Science & Imaging, Biomedical Centre, Department of Biomedical Engineering, Lund University, Lund, Sweden.
  • 17 Chemistry Institute Federal, University of Rio de Janeiro, Rio de Janeiro, Brazil.
  • 18 Department of Translational Medicine, Lund University, Lund, Sweden.
  • 19 Division of Oncology, Department of Internal Medicine and Oncology, Semmelweis University, Budapest, Hungary.
  • 20 Department of Bioinformatics, Semmelweis University, Budapest, Hungary.
  • 21 Research Centre for Natural Sciences, Institute of Molecular Life Sciences, Budapest, Hungary.
  • 22 Hungarian Centre of Excellence for Molecular Medicine (HCEMM), Genome Integrity and DNA Repair Core Group, University of Szeged, Szeged, Hungary.
  • 23 Proteomics Unit, Institute of Chemistry and Research Center for Precision Medicine, Institute of Biophysics Carlos Chagas Filho, Federal Univesity of Rio de Janeiro, Rio de Janeiro, Brazil.
  • 24 Chemical Genomics Leader Research Laboratory, Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
  • 25 Institute for Systems Genetics, NYU Grossman School of Medicine, New York, NY, USA.
  • 26 Department of Biochemistry and Molecular Pharmacology, NYU Grossman School of Medicine, New York, NY, USA.
  • # Contributed equally.
PMID: 39722169 DOI: 10.1111/ijd.17586
Abstract

Background: The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies still poses a significant problem.

Objective: Here, we mine large-scale MM proteogenomic data to identify druggable targets and forecast treatment efficacy and resistance.

Methods: Leveraging protein profiles from established MM subtypes and molecular structures of 82 Cancer treatment drugs, we identified nine candidate hub proteins, mTOR, Fyn, PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, Src, and Akt1, across five distinct MM subtypes. These proteins are potential drug targets applicable to one or multiple MM subtypes. Additionally, by integrating proteogenomic profiles obtained from MM subtypes with MM cell line dependency and drug sensitivity data, we identified a total of 162 potentially targetable genes. Lastly, we identified 20 compounds exhibiting potential drug impact in at least one melanoma subtype.

Results: Employing these unbiased approaches, we have uncovered compounds targeting Ferroptosis demonstrating a striking 30× fold difference in sensitivity among different subtypes.

Conclusions: Our results suggest innovative and novel therapeutic strategies by stratifying melanoma samples through proteomic profiling, offering a spectrum of novel therapeutic interventions and prospects for combination therapy.

Keywords

HDAC; RTK inhibitor; drug target prediction; ferroptosis; malignant melanoma; skin cancer.

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