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

Pla, Indira LU orcid ; Szabolcs, Botond L. ; Péter, Petra Nikolett ; Ujfaludi, Zsuzsanna ; Kim, Yonghyo ; Horvatovich, Peter LU ; Sanchez, Aniel LU ; Pawlowski, Krzysztof LU ; Wieslander, Elisabet and Kuras, Magdalena LU orcid , et al. (2025) In International Journal of Dermatology 64(5). p.870-881
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... (More)

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.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
drug target prediction, ferroptosis, HDAC, malignant melanoma, RTK inhibitor, skin cancer
in
International Journal of Dermatology
volume
64
issue
5
pages
12 pages
publisher
Wiley-Blackwell
external identifiers
  • scopus:85215807075
  • pmid:39722169
ISSN
0011-9059
DOI
10.1111/ijd.17586
language
English
LU publication?
yes
id
2820d9c3-2f7c-4de9-ac9f-bec261f966c8
date added to LUP
2025-06-03 09:01:22
date last changed
2025-07-01 12:01:25
@article{2820d9c3-2f7c-4de9-ac9f-bec261f966c8,
  abstract     = {{<p>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.</p>}},
  author       = {{Pla, Indira and Szabolcs, Botond L. and Péter, Petra Nikolett and Ujfaludi, Zsuzsanna and Kim, Yonghyo and Horvatovich, Peter and Sanchez, Aniel and Pawlowski, Krzysztof and Wieslander, Elisabet and Kuras, Magdalena and Murillo, Jimmy Rodriguez and Guedes, Jéssica and Pál, Dorottya M.P. and Ascsillán, Anna A. and Betancourt, Lazaro Hiram and Németh, István Balázs and Gil, Jeovanis and de Almeida, Natália Pinto and Szeitz, Beáta and Szadai, Leticia and Doma, Viktória and Woldmar, Nicole and Bartha, Áron and Pahi, Zoltan and Pankotai, Tibor and Győrffy, Balázs and Szasz, A. Marcell and Domont, Gilberto and Nogueira, Fábio and Kwon, Ho Jeong and Appelqvist, Roger and Kárpáti, Sarolta and Fenyö, David and Malm, Johan and Marko-Varga, György and Kemény, Lajos V.}},
  issn         = {{0011-9059}},
  keywords     = {{drug target prediction; ferroptosis; HDAC; malignant melanoma; RTK inhibitor; skin cancer}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{870--881}},
  publisher    = {{Wiley-Blackwell}},
  series       = {{International Journal of Dermatology}},
  title        = {{Unbiased Drug Target Prediction Reveals Sensitivity to Ferroptosis Inducers, HDAC and RTK Inhibitors in Melanoma Subtypes}},
  url          = {{http://dx.doi.org/10.1111/ijd.17586}},
  doi          = {{10.1111/ijd.17586}},
  volume       = {{64}},
  year         = {{2025}},
}