ArticleCells2022
Reverting
Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 20 citations in OpenAlex.
- CRISPR in clinical oncology: translational advances from molecular diagnostics to therapeutics.Nature reviews. Clinical oncology · 2026Review
- Designing nucleic acid-based therapeutics for cancer treatment: Updates on the state of the art.Molecular therapy : the journal of the American Society of Gene Therapy · 2026Review
- Hybrid Dihydropyrimidinones Targeting AKT Signaling: Antitumor Activity in Hormone-Dependent 2D and 3D Cancer Models.Pharmaceutics · 2025Article
- Exploring treatment options in cancer: Tumor treatment strategies.Signal transduction and targeted therapy · 2024Review
- Application of prime editing system to introduce TP53 R248Q hotspot mutation in acute lymphoblastic leukemia cell line.Cancer science · 2024Article
- Article
- Article
- Genome editing and cancer therapy: handling the hypoxia-responsive pathway as a promising strategy.Cellular and molecular life sciences : CMLS · 2023Review
- Review
- Advances of Epigenetic Biomarkers and Epigenome Editing for Early Diagnosis in Breast Cancer.International journal of molecular sciences · 2022Review
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 at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is the leading cause of cancer-related deaths in women. The aggressive breast cancer subtype is commonly linked to the genetic alterations in the TP53 tumor suppressor gene, predominantly the missense mutations. Robust experimental models are needed to gain better insights into these mutations’ molecular properties and implications in tumorigenesis. The generation of such models harboring the alterations is feasible with the CRISPR-based gene editing technology. Moreover, the development of new CRISPR applications, particularly DNA base and prime editing, has considerably improved the precision and versatility of gene editing. Here, we employed the prime editing tool to revert a TP53 missense C > T mutation (L194F) in a T47D luminal A breast cancer cell line. In parallel, this prime editing tool was also utilized to introduce the L194F mutation in HEK293T cells. To assess the prime editing efficiency in both cell lines, we first performed Sanger sequencing in the prime-edited cells pool and single cell-derived clones. However, the Sanger sequencing approach did not detect any base substitution in these cell lines. Next, by employing the more sensitive amplicon target sequencing, we managed to identify the expected substitution in these T47D and HEK293T cells, albeit the editing efficiency was low. In light of these findings, we discussed the technical aspects and provided suggestions for improve the prime editing workflow and efficiency for future experiments.
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.