ReviewInternational journal of molecular sciences2023
First-Line Combination Treatment with Low-Dose Bipolar Drugs for ABCB1-Overexpressing Drug-Resistant Cancer Populations.
Review in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed, 3 citations in OpenAlex.
- Ginsenosides Rh2 and Rg3 in first-line combination therapy: Prospects for rapid clinical translation in drug-resistant triple-negative breast cancer.Journal of ginseng research · 2026Review
- From Psychiatry to Oncology: Exploring the Anti-Neoplastic Mechanisms of Aripiprazole and Its Potential Use in Cancer Treatment.Pharmacology research & perspectives · 2025Review
- Orphan nuclear receptor NR2E3 is a new molecular vulnerability in solid tumors by activating p53.Cell death & disease · 2025Article
- Low-Dose Perifosine, a Phase II Phospholipid Akt Inhibitor, Selectively Sensitizes Drug-Resistant ABCB1-Overexpressing Cancer Cells.Biomolecules & therapeutics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumors include a heterogeneous population, of which a small proportion includes drug-resistant cancer (stem) cells. In drug-sensitive cancer populations, first-line chemotherapy reduces tumor volume via apoptosis. However, it stimulates drug-resistant cancer populations and finally results in tumor recurrence. Recurrent tumors are unresponsive to chemotherapeutic drugs and are primarily drug-resistant cancers. Therefore, increased apoptosis in drug-resistant cancer cells in heterogeneous populations is important in first-line chemotherapeutic treatments. The overexpression of ABCB1 (or P-gp) on cell membranes is an important characteristic of drug-resistant cancer cells; therefore, first-line combination treatments with P-gp inhibitors could delay tumor recurrence. Low doses of bipolar drugs showed P-gp inhibitory activity, and their use as a combined therapy sensitized drug-resistant cancer cells. FDA-approved bipolar drugs have been used in clinics for a long period of time, and their toxicities are well reported. They can be easily applied as first-line combination treatments for targeting resistant cancer populations. To apply bipolar drugs faster in first-line combination treatments, knowledge of their complete information is crucial. This review discusses the use of low-dose bipolar drugs in sensitizing ABCB1-overexpressing, drug-resistant cancers. We believe that this review will contribute to facilitating first-line combination treatments with low-dose bipolar drugs for targeting drug-resistant cancer populations. In addition, our findings may aid further investigations into targeting drug-resistant cancer populations with low-dose bipolar drugs.
Indexed as
Identifiers
What 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.