Evidence map›Paper›PMID 41018623›Full record

ReviewACS omega2025

Application of Gene Editing Technology Based on Targeted Delivery Materials in TNBC.

Peng Qu, Xue Li, Jun Liu, Xiaohan Su, Shiqi Han, Yali Wang, Yunbo Luo, Jinsui Li, Cui Ma, Shishan Deng and 3 more

Abstract readReview
In one paragraph

Review in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. AMarine drugs · 2025
    Article
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

13 authors.

Peng QuDepartment of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, People's Republic of China.
Xue LiDepartment of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, People's Republic of China.
Jun LiuAffiliated Hospital of Southwest Medical University, Luzhou 646000, People's Republic of China.
Xiaohan SuDepartment of Breast Surgery, Mianyang 404 hospital, Mianyang 621000, P R China.
Shiqi HanDepartment of Academician (expert) Workstation, Biological Targeting Laboratory of Breast Cancer, Breast and Thyroid Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan 637000, P R China.
Yali WangDepartment of Academician (expert) Workstation, Biological Targeting Laboratory of Breast Cancer, Breast and Thyroid Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan 637000, P R China.
Yunbo LuoDepartment of Academician (expert) Workstation, Biological Targeting Laboratory of Breast Cancer, Breast and Thyroid Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan 637000, P R China.
Jinsui LiDepartment of Academician (expert) Workstation, Biological Targeting Laboratory of Breast Cancer, Breast and Thyroid Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan 637000, P R China.
Cui MaDepartment of Mathematics, Army Medical University, Chongqing 400038, PR China.
Shishan DengDepartment of Academician (expert) Workstation, Biological Targeting Laboratory of Breast Cancer, Breast and Thyroid Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan 637000, P R China.
Lingmi HouDepartment of Breast Surgery, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China.ORCID https://orcid.org/0000-0002-9164-6346
Qi LiangDepartment of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, People's Republic of China.
Panke ChengInstitute of Cardiovascular Diseases & Department of Cardiology, Sichuan Provincial People's Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, PR China.ORCID https://orcid.org/0000-0002-1900-8358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer, lacking the expression of estrogen receptor, progesterone receptor, and HER2, which leads to poor prognosis and limited treatment options. Despite advances in targeted therapies, TNBC patients often fail to benefit due to its heterogeneity, drug resistance, and immune evasion. Gene editing technologies such as CRISPR/Cas9 and RNA interference offer promising strategies for precise gene modulation, yet their clinical translation is challenged by delivery efficiency, off-target effects, and safety concerns. This review systematically summarizes key regulatory genes implicated in TNBC progression, including those involved in invasion, proliferation, and chemoresistance, such as BRCA1/2, TP53, MUC1, EGFR, MYC, and others. We further discuss advances in gene editing tools and their combination with targeted delivery materialsranging from viral vectors (AAV, lentivirus) to nonviral platforms (lipid nanoparticles, polymer-based systems, and bioderived vesicles)highlighting their potential to enhance editing specificity, minimize immune response, and overcome tumor microenvironment barriers. Finally, we address biosafety, ethical concerns, and mitigation strategies such as high-fidelity Cas9 variants and AI-assisted off-target prediction. Collectively, this review provides a comprehensive framework for future research and clinical application of targeted gene editing in TNBC, aiming to develop safer, more effective, and personalized treatment strategies.

Identifiers

PMID41018623
PMCPMC12461336

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.