Evidence map›Paper›PMID 39199788›Full record

ReviewBioengineering (Basel, Switzerland)2024

Advances in siRNA Drug Delivery Strategies for Targeted TNBC Therapy.

Md Abdus Subhan, Vladimir P Torchilin

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. RNA therapeutic targeting of recalcitrant and rare cancers.Exploration of targeted anti-tumor therapy · 2026
    Review
  6. Review
  7. Article
  8. AMarine drugs · 2025
    Article
  9. Review
  10. Article
  11. Review
  12. Review
  13. Review
  14. Non-Coding RNAs in Breast Cancer: Diagnostic and Therapeutic Implications.International journal of molecular sciences · 2024
    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

2 authors.

Md Abdus SubhanDivision of Nephrology, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA.ORCID 0000-0002-5623-7643
Vladimir P TorchilinCenter for Pharmaceutical Biotechnology and Nanomedicine, Department of Pharmaceutical Sciences, Northeastern University, Boston, MA 02115, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Among breast cancers, triple-negative breast cancer (TNBC) has been recognized as the most aggressive type with a poor prognosis and low survival rate. Targeted therapy for TNBC is challenging because it lacks estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). Chemotherapy, radiation therapy, and surgery are the common therapies for TNBC. Although TNBC is prone to chemotherapy, drug resistance and recurrence are commonly associated with treatment failure. Combination therapy approaches using chemotherapy, mAbs, ADC, and antibody-siRNA conjugates may be effective in TNBC. Recent advances with siRNA-based therapy approaches are promising for TNBC therapy with better prognosis and reduced mortality. This review discusses advances in nanomaterial- and nanobiomaterial-based siRNA delivery platforms for TNBC therapy exploring targeted therapy approaches for major genes, proteins, and TFs upregulated in TNBC tumors, which engage in molecular pathways associated with low TNBC prognosis. Bioengineered siRNA drugs targeting one or several genes simultaneously can downregulate desired genes, significantly reducing disease progression.

Indexed as

biomaterialsnanomaterialssiRNAtargeted therapytriple-negative breast cancer

Identifiers

PMID39199788
PMCPMC11351222

What OpenQuestion holds

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LicenceCC BY
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.