Targeting hypoxia in combination with paclitaxel to enhance therapeutic efficacy in breast and ovarian cancer.

Acriflavine (PubChem CID: 443101) Cobalt (II) chloride (CoCl(2), PubChem CID: 24288) Combination therapy Hypoxia targeted therapy Metastasis Migration Paclitaxel (PubChem CID: 36314) Rolipram (PubChem CID: 5092) Tumor hypoxia

Journal

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
ISSN: 1950-6007
Titre abrégé: Biomed Pharmacother
Pays: France
ID NLM: 8213295

Informations de publication

Date de publication:
29 Oct 2024
Historique:
received: 11 07 2024
revised: 11 10 2024
accepted: 21 10 2024
medline: 31 10 2024
pubmed: 31 10 2024
entrez: 30 10 2024
Statut: aheadofprint

Résumé

The poor vascularization of solid tumors results in oxygen-deprived areas within the tumor mass. This phenomenon is defined as tumor hypoxia and is considered to be a major contributor to tumor progression in breast and ovarian cancers due to hypoxia-cascade-promoted increased metastasizing capacity. Hence, targeting hypoxia is a strategic cancer treatment approach, however, the hypoxia-modulating drugs face several limitations in monotherapies. Here, we investigated the impact of the potent hypoxia-inducible factor inhibitory compound acriflavine on tumor cell proliferation, migration, and metabolism under hypoxic conditions. We identified that acriflavine inhibited the proliferation of breast and ovarian tumor cells. To model the potential benefits of additional hypoxia response inhibition next to standard chemotherapy, we combined acriflavine with a frequently used chemotherapeutic agent, paclitaxel. In most breast and ovarian cancer cell lines used, we identified additive effects between the two drugs. The most significant findings were detected in triple-negative breast cancer cell lines, where we observed synergism. The drug combination effectively impeded tumor growth and metastasis formation in an in vivo orthotopic triple-negative breast cancer model as well. Additionally, we demonstrated that an epithelial-mesenchymal transition inhibitory drug, rolipram, combined with acriflavine and paclitaxel, notably reduced the motility of hypoxic triple-negative breast cancer cells. In conclusion, we identified novel drug combinations that can potentially combat triple-negative breast cancer by inhibiting hypoxia signaling and hindering cell migration and metastasis formation.

Identifiants

pubmed: 39476764
pii: S0753-3322(24)01487-2
doi: 10.1016/j.biopha.2024.117601
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

117601

Informations de copyright

Copyright © 2024 The Authors. Published by Elsevier Masson SAS.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Laura Svajda (L)

Department of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest, Hungary; Doctoral School of Semmelweis University, Budapest, Hungary. Electronic address: svajda.laura@ext.oncol.hu.

Ivan Ranđelović (I)

Department of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest, Hungary.

Sára Eszter Surguta (SE)

Department of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest, Hungary.

Marcell Baranyi (M)

Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, Budapest, Hungary.

Mihály Cserepes (M)

Department of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest, Hungary; Doctoral School of Semmelweis University, Budapest, Hungary.

József Tóvári (J)

Department of Experimental Pharmacology and the National Tumor Biology Laboratory, National Institute of Oncology, Budapest, Hungary; Doctoral School of Semmelweis University, Budapest, Hungary.

Classifications MeSH