ReviewMedicina (Kaunas, Lithuania)2022
Glutathione Transferase P1: Potential Therapeutic Target in Ovarian Cancer.
Review in Medicina (Kaunas, Lithuania), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 15 citations in OpenAlex.
- Transcriptional activation of GSTP1 by ANXA3 is associated with cisplatin sensitivity in colorectal cancer cells.Oncology letters · 2026Article
- The role of glutathione S-transferases in human disease pathogenesis and their current inhibitors.Genes & diseases · 2025Review
- Therapeutic Chemoresistance in Ovarian Cancer: Emerging Hallmarks, Signaling Mechanisms and Alternative Pathways.Current medicinal chemistry · 2025Review
- The Cancer Antioxidant Regulation System in Therapeutic Resistance.Antioxidants (Basel, Switzerland) · 2024Review
- The Role of Glutathione Transferase Omega-Class Variant Alleles in Individual Susceptibility to Ovarian Cancer.International journal of molecular sciences · 2024Article
- Peroxiredoxin-1 as a molecular chaperone that regulates glutathione S-transferase P1 activity and drives mutidrug resistance in ovarian cancer cells.Biochemistry and biophysics reports · 2024Article
- Cell plasticity modulation by flavonoids in resistant breast carcinoma targeting the nuclear factor kappa B signaling.Cancer metastasis reviews · 2024Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chemotherapy resistance of ovarian cancer, regarded as the most lethal malignant gynecological disease, can be explained by several mechanisms, including increased activity of efflux transporters leading to decreased intracellular drug accumulation, increased efflux of the therapeutic agents from the cell by multidrug-resistance-associated protein (MRP1), enhanced DNA repair, altered apoptotic pathways, silencing of a number of genes, as well as drug inactivation, especially by glutathione transferase P1 (GSTP1). Indeed, GSTP1 has been recognized as the major enzyme responsible for the conversion of drugs most commonly used to treat metastatic ovarian cancer into less effective forms. Furthermore, GSTP1 may even be responsible for chemoresistance of non-GST substrate drugs by mechanisms such as interaction with efflux transporters or different signaling molecules involved in regulation of apoptosis. Recently, microRNAs (miRNAs) have been identified as important gene regulators in ovarian cancer, which are able to target GST-mediated drug metabolism in order to regulate drug resistance. So far, miR-186 and miR-133b have been associated with reduced ovarian cancer drug resistance by silencing the expression of the drug-resistance-related proteins, GSTP1 and MDR1. Unfortunately, sometimes miRNAs might even enhance the drug resistance in ovarian cancer, as shown for miR-130b. Therefore, chemoresistance in ovarian cancer treatment represents a very complex process, but strategies that influence GSTP1 expression in ovarian cancer as a therapeutic target, as well as miRNAs affecting GSTP1 expression, seem to represent promising predictors of chemotherapeutic response in ovarian cancer, while at the same time represent potential targets to overcome chemoresistance in the future.
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Registered trials
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.