Evidence mapPaperPMID 39698277Full record

ReviewACS pharmacology & translational science2024

Harnessing Drug Repurposing to Combat Breast Cancer by Targeting Altered Metabolism and Epithelial-to-Mesenchymal Transition Pathways.

Thirukumaran Kandasamy, Shilpi Sarkar, Siddhartha Sankar Ghosh

Abstract readReview
In one paragraph

Review in ACS pharmacology & translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Targeting CAF-specific metabolic pathways in breast cancer.Naunyn-Schmiedeberg's archives of pharmacology · 2025
    Review
  3. Article
  4. Review
  5. 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

3 authors.

Thirukumaran KandasamyDepartment of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati-39, Assam India.
Shilpi SarkarDepartment of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati-39, Assam India.
Siddhartha Sankar GhoshDepartment of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati-39, Assam India.ORCID https://orcid.org/0000-0002-7121-5610

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer remains one of the most prevalent and challenging cancers to treat due to its complexity and heterogenicity. Cellular processes such as metabolic reprogramming and epithelial-to-mesenchymal transition (EMT) contribute to the complexity of breast cancer by driving uncontrolled cell division, metastasis, and resistance to therapies. Strategically targeting these intricate pathways can effectively impede breast cancer progression, thereby revealing significant potential for therapeutic interventions. Among various emerging therapeutic approaches, drug repurposing offers a promising avenue for enhancing clinical outcomes. In recent years, high-throughput screening, QSAR, and network pharmacology have been widely employed to identify promising repurposed drugs. As an outcome, several drugs, such as Metformin, Itraconazole, Pimozide, and Disulfiram, were repurposed to regulate metabolic and EMT pathways. Moreover, strategies such as combination therapy, targeted delivery, and personalized medicine were utilized to enhance the efficacy and specificity of the repurposed drugs. This review focuses on the potential of targeting altered metabolism and EMT in breast cancer through drug repurposing. It also highlights recent advancements in drug screening techniques, associated limitations, and strategies to overcome these challenges.

Identifiers

PMID39698277
PMCPMC11650739

What Socratic holds

Textmetadata
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 Socratic graph.