Evidence map›Paper›PMID 41386827›Full record

ArticleJournal, genetic engineering & biotechnology2025

Gene editing using gamma modified PNA: HBB gene as a model.

Noha Eltaweel, Ghada Elkamah, Nesma Elaraby, Iman Hassan, Ahmed Wassel, Nahla Abdel-Aziz, Khalda Amr

Abstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

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

7 authors.

Noha EltaweelMedical Molecular Genetics Department, Human Genetics and Genome Project Institute, NRC, Egypt. Electronic address: nohaeltaweel10@gmail.com.
Ghada ElkamahClinical Genetics Department, Human Genetics and Genome Project Institute, NRC, Egypt.
Nesma ElarabyMedical Molecular Genetics Department, Human Genetics and Genome Project Institute, NRC, Egypt.
Iman HassanBiochemistry Department, Faculty of Pharmacy (Girls), Al-Azhar University, Egypt.
Ahmed WasselThin Films & Electron Microscope Department, NRC, Egypt.
Nahla Abdel-AzizMedical Molecular Genetics Department, Human Genetics and Genome Project Institute, NRC, Egypt.
Khalda AmrMedical Molecular Genetics Department, Human Genetics and Genome Project Institute, NRC, Egypt. Electronic address: khalda_nrc@yahoo.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PNAs have emerged as a powerful tool in gene editing, particularly for correcting monogenic disorders by enhancing targeted recombination and genomic modifications. This study aimed to establish a gene editing technique using Peptide Nucleic Acid (PNA)/donor DNA-loaded poly lactic-co-glycolic acid (PLGA) nanoparticles at our genomic facilities, with the ultimate goal of correcting disease-causing mutations. Methods involved culturing skin fibroblasts from a healthy Egyptian volunteer without HBB gene mutations in two separate 12-well plates. Oligonucleotides were designed, and nanoparticles were formulated and characterized before being used to treat the cultured fibroblasts. DNA and RNA were extracted from treated cells, followed by molecular analyses to confirm the edits. Results indicated successful encapsulation of nanoparticles and modest, sustained introduction of the desired mutation, accompanied by functional impairment in HBB gene expression. The study successfully established PNA gene editing technology, potentially paving the way for future treatment studies of single-gene disorders.

Indexed as

Gene editingPNAThalassemiaTreatment

Identifiers

PMID41386827
PMCPMC12509102

What OpenQuestion holds

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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.