Evidence map›Paper›PMID 40658288›Full record

ReviewDiscover nano2025

Advances in nanoparticle-based doxorubicin delivery: precision strategies for targeted treatment of triple-negative breast cancer.

Navakanth Raju Ramayanam, Sarad Pawar Naik Bukke, Murali Krishna Moka, Himanshu Dehingia, Aditya Bordoloi, Riya Debbarma, Purushothama Reddy Kudumula, Balakrishna Vuyyala, P Dharani Prasad, Akugizibwe Catherine

Abstract readReview
In one paragraph

Review in Discover nano, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
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

10 authors.

Navakanth Raju RamayanamDepartment of Pharmacy Practice, Faculty of Pharmacy, Dr. M.G.R Educational and Research Institution, Chennai, Tamil Nadu, 600077, India. drnavakanthraju@gmail.com.
Sarad Pawar Naik BukkeDepartment of Pharmaceutics and Pharmaceutical Technology, Kampala International University, Western Campus, P.O. Box 71, Ishaka, Bushenyi, Uganda. drsaradpawar@kiu.ac.ug.ORCID http://orcid.org/0000-0002-5693-2953
Murali Krishna MokaDepartment of Clinical Research, Hindu Mission Hospital, Tambaram, Chennai, Tamil Nadu, 600045, India.
Himanshu DehingiaDepartment of Pharmacy Practice, School of Pharmacy, The Assam Kaziranga University, Jorhat, Assam, India.
Aditya BordoloiDepartment of Pharmacy Practice, School of Pharmacy, The Assam Kaziranga University, Jorhat, Assam, India.
Riya DebbarmaDepartment of Pharmacy Practice, School of Pharmacy, The Assam Kaziranga University, Jorhat, Assam, India.
Purushothama Reddy KudumulaDepartment of Pharmacy Practice, Sanjo College of Pharmaceutical Studies, Palakkad, Kerala, 678702, India.
Balakrishna VuyyalaDepartment of Pharmacology, Gurunanak Institutions Technical Campus, Hyderabad, Telangana, India.
P Dharani PrasadDepartment of Pharmacology, MB School of Pharmaceutical Sciences (Erstwhile Sree Vidyanikethan College of Pharmacy), Mohan Babu University, Tirupati, Andhra Pradesh, 517102, India.
Akugizibwe CatherineDepartment of Pharmaceutics and Pharmaceutical Technology, Kampala International University, Western Campus, P.O. Box 71, Ishaka, Bushenyi, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is a prevalent and aggressive subtype of breast cancer, accounting for approximately 10-15% of all cases. Its lack of hormone receptors and poor clinical prognosis make targeted therapy particularly challenging, leaving chemotherapy as the mainstay treatment. However, conventional chemotherapy is associated with significant limitations, including cardiotoxicity and inadequate tumor cell specificity. Nanoparticle-based drug delivery systems have emerged as a promising strategy for enhancing the therapeutic efficacy of doxorubicin (DOX) in TNBC. Among these, cell membrane-coated nanoparticles, exosome-sheathed porous silica nanoparticles, and FZD7-targeted nanoparticles have demonstrated substantial potential. These platforms improve drug delivery efficiency while minimizing systemic toxicity and adverse effects. Cell membrane-coated nanoparticles evade immune surveillance, allowing for selective targeting of TNBC cells. Exosome-sheathed nanoparticles facilitate the co-delivery of DOX with other therapeutic agents aimed at inhibiting cancer stem cell-driven epithelial-to-mesenchymal transition. FZD7-targeted nanoparticles enhance DOX accumulation within tumor cells by binding specifically to FZD7 receptors, leading to increased apoptosis and reduced cancer cell metabolic activity. This review aims to examine recent advancements in nanoparticle-based delivery systems for DOX in the treatment of TNBC. It further explores various formulations-including liposomes and polymeric nanoparticles-used for DOX delivery, assesses active and passive targeting strategies, and evaluates the advantages of controlled drug release. The review also identifies current gaps in the literature and proposes future research directions to advance the clinical applicability of these systems. Emerging concepts such as the active transport and retention mechanism and macrophage-mediated delivery systems offer new opportunities to improve tumor localization and retention of DOX-loaded nanoparticles. Collectively, these developments underscore the transformative potential of nanoparticle-based DOX delivery in revolutionizing TNBC therapy.

Indexed as

Doxorubicin (DOX)Nanoparticle-based drug deliveryPrecision medicineTargeted & controlled drug deliveryTriple-negative breast cancer (TNBC)

Identifiers

PMID40658288
PMCPMC12259515

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.