Evidence map›Paper›PMID 38931924›Full record

ReviewPharmaceutics2024

Recent Progress of Multifunctional Molecular Probes for Triple-Negative Breast Cancer Theranostics.

Deyi Zhao, Zhe Li, Ding-Kun Ji, Qian Xia

Abstract readReview
In one paragraph

Review in Pharmaceutics, 2024. 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. Article
  3. Review
  4. 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

4 authors.

Deyi ZhaoSchool of Life Sciences, Shanghai University, Shanghai 200444, China.
Zhe LiSchool of Life Sciences, Shanghai University, Shanghai 200444, China.
Ding-Kun JiInstitute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.
Qian XiaInstitute of Molecular Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200127, China.

Funding

Fundamental Research Funds for the Central Universities 2020JCPT02National Key Research and Development Program of China 2020YFA0909000National Natural Science Foundation of China 22205139Natural Science Foundation of Shanghai 22ZR1437800Shanghai Sailing Program 20YF1424500
6 · The paper itself

Abstract

Breast cancer (BC) poses a significant threat to women's health, with triple-negative breast cancer (TNBC) representing one of the most challenging and aggressive subtypes due to the lack of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression. Traditional TNBC treatments often encounter issues such as low drug efficiency, limited tumor enrichment, and substantial side effects. Therefore, it is crucial to explore novel diagnostic and treatment systems for TNBC. Multifunctional molecular probes (MMPs), which integrate target recognition as well as diagnostic and therapeutic functions, introduce advanced molecular tools for TNBC theranostics. Using an MMP system, molecular drugs can be precisely delivered to the tumor site through a targeted ligand. Real-time dynamic monitoring of drug release achieved using imaging technology allows for the evaluation of drug enrichment at the tumor site. This approach enables accurate drug release, thereby improving the therapeutic effect. Therefore, this review summarizes the recent advancements in MMPs for TNBC theranostics, encompassing the design and synthesis of MMPs as well as their applications in the field of TNBC theranostics.

Indexed as

drug deliverymolecular imagingmolecular probestreatment strategiestriple-negative breast cancer

Identifiers

PMID38931924
PMCPMC11207493

What OpenQuestion holds

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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.