ReviewCurrent medicinal chemistry2024
Targeting Cervical Cancer Stem Cells by Phytochemicals.
Review in Current medicinal chemistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
6 citing papers in PubMed.
- Psoralidin inhibits stemness-associated characteristics in cervical cancer cells via modulation of Oct4/Sox2 expression.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- A three-gene radioresistance signature predicts tumor progression in cervical cancer.Translational cancer research · 2026Article
- Fenbendazole Exhibits Antitumor Activity Against Cervical Cancer Through Dual Targeting of Cancer Cells and Cancer Stem Cells: Evidence from In Vitro and In Vivo Models.Molecules (Basel, Switzerland) · 2025Article
- Phytochemicals as Therapeutic Agents against Cancer.Current medicinal chemistry · 2024Article
- Sulforaphane regulates cell proliferation and induces apoptotic cell death mediated by ROS-cell cycle arrest in pancreatic cancer cells.Frontiers in oncology · 2024Article
- (Nano)biotechnological approaches in the treatment of cervical cancer: integration of engineering and biology.Frontiers in immunology · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cervical cancer (CaCx) poses a significant global health challenge, ranking as the fourth most common cancer among women worldwide. Despite the emergence of advanced treatment strategies, recurrence remains a bottleneck in favorable treatment outcomes and contributes to poor prognosis. The chemo- or radio-therapy resistance coupled with frequent relapse of more aggressive tumors are some key components that contribute to CaCx-related mortality. The onset of therapy resistance and relapse are attributed to a small subset of, slow-proliferating Cancer Stem Cells (CSC). These CSCs possess the properties of tumorigenesis, self-renewal, and multi-lineage differentiation potential. Because of slow cycling, these cells maintain themselves in a semi-quiescent stage and protect themselves from different anti-proliferative anti-cancer drugs. Keeping in view recent advances in their phenotypic and functional characterization, the feasibility of targeting CSC and associated stem cell signaling bears a strong translational value. The presence of CSC has been reported in CaCx (CCSC) which remains a forefront area of research. However, we have yet to identify clinically useful leads that can target CCSC. There is compelling evidence that phytochemicals, because of their advantages over synthetic anticancer drugs, could emerge as potential therapeutic leads to target these CCSCs. The present article examined the potential of phytochemicals with reported anti-CSC properties and evaluated their future in preclinical and clinical applications against CaCx.
Indexed as
Identifiers
38288813What OpenQuestion holds
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.