Evidence map›Paper›PMID 39799471›Full record

ArticleJournal of cellular and molecular medicine2025

Comparative Analysis of Acquired Resistance to Bortezomib in Prostate Cancer Cells Using Proteomic and Bioinformatic Tools.

Semih Seker, Betul Sahin, Azmi Yerlikaya

Abstract readComparative Study
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Semih SekerDepartment of Medical Biology, Faculty of Medicine, Kutahya Health Sciences University, Kutahya, Turkey.ORCID 0000-0002-8957-2050
Betul SahinAcibadem Labmed Clinical Laboratories, Istanbul, Turkey.ORCID 0000-0001-8663-5741
Azmi YerlikayaDepartment of Medical Biology, Faculty of Medicine, Kutahya Health Sciences University, Kutahya, Turkey.ORCID 0000-0002-0678-0701

Funding

Kutahya Health Sciences University TSA-2022-103
6 · The paper itself

Abstract

Chemotherapy is a potent tool against cancer, but drug resistance remains a major obstacle. To combat this, understanding the molecular mechanisms behind resistance in cancer cells and the protein expression changes driving these mechanisms is crucial. Targeting the Ubiquitin-Proteasome System (UPS) has proven effective in treating multiple myeloma and shows promise for solid tumours. Despite initial success with the proteasome inhibitor bortezomib, acquired resistance soon after treatment poses a significant challenge to its efficacy. In this study, we explored proteins potentially involved in acquired resistance to bortezomib using label-free nLC-MS/MS proteomic analysis. The investigation revealed 299 proteins with notable differences in expression levels in the bortezomib-resistant PC3 prostate cancer cell line. Using bioinformatics tools, we illustrated the top 10 gene ontology (GO) processes [e.g., translational initiation (p = 5.964E-10), CRD-mediated mRNA stabilisation (p = 1.636E-5), and hydrogen ion transmembrane transport (p = 6.46E-5)] and the top 20 KEGG [e.g., metabolic pathways (p = 7.601E-13), biosynthesis of amino acids (p = 3.834E-12), and chemical carcinogenesis-reactive oxygen species (p = 1.891E-4)] and REACTOME [e.g., metabolism (p = 4.182E-21), translation (p = 9.484E-18), and Nonsense-Mediated Decay (NMD) (p = 1.829E-8)] pathways in the PC3-resistant cells. We further refined our results by comparing them with globally validated TCGA datasets. We correlated the 299 proteins identified through proteomic analysis with tumour aggressiveness and resistance by comparing them with the TCGA nodal metastasis N0 vs. N1 datasets using the UALCAN portal and identified 37 proteins consistent with our results. We believe that a combination of bortezomib with chemotherapeutics targeting these proteins could be effective in overcoming the resistance developed against bortezomib.

Indexed as

BortezomibComputational BiologyDrug Resistance, NeoplasmProstatic NeoplasmsProteomicsAntineoplastic AgentsCell Line, TumorGene Expression Regulation, NeoplasticGene OntologyHumansMaleProteomeAntineoplastic AgentsBortezomibProteomebioinformaticsbortezomibdrug resistanceprostate cancerproteomics

Identifiers

PMID39799471
PMCPMC11725179

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.