Evidence map›Paper›PMID 40896419›Full record

ArticleRSC medicinal chemistry2025

Novel lithocholic acid-diindolylmethane hybrids as potent sialyltransferase inhibitors targeting triple-negative breast cancer: a molecular hybridization approach.

Christian Angelo P Concio, Ser John Lynon P Perez, Tzu-Ting Chang, Chia-Ling Chen, Yi-Ting He, Susan D Arco, Wen-Shan Li

Abstract read
In one paragraph

Article in RSC medicinal chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Christian Angelo P ConcioBiomedical Translational Research Center, Academia Sinica No. 99, Lane 130, Section 1, Yanyuan Road, Nangang District Taipei City 115 Taiwan wenshan@as.edu.tw.ORCID https://orcid.org/0000-0003-0281-5601
Ser John Lynon P PerezBiomedical Translational Research Center, Academia Sinica No. 99, Lane 130, Section 1, Yanyuan Road, Nangang District Taipei City 115 Taiwan wenshan@as.edu.tw.ORCID https://orcid.org/0000-0003-3724-1142
Tzu-Ting ChangBiomedical Translational Research Center, Academia Sinica No. 99, Lane 130, Section 1, Yanyuan Road, Nangang District Taipei City 115 Taiwan wenshan@as.edu.tw.
Chia-Ling ChenInstitute of Chemistry, Academia Sinica No. 128, Section 2, Yuanyuan Road, Nangang District Taipei City 115 Taiwan.
Yi-Ting HeInstitute of Chemistry, Academia Sinica No. 128, Section 2, Yuanyuan Road, Nangang District Taipei City 115 Taiwan.
Susan D ArcoInstitute of Chemistry, College of Science, University of the Philippines Diliman Quezon City Metro Manila Philippines.
Wen-Shan LiBiomedical Translational Research Center, Academia Sinica No. 99, Lane 130, Section 1, Yanyuan Road, Nangang District Taipei City 115 Taiwan wenshan@as.edu.tw.ORCID https://orcid.org/0000-0002-8359-4582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular hybridization, an emerging strategy for the discovery of new anticancer therapeutics, shows promise as a powerful tool for the development of new sialyltransferase (ST) inhibitors for cancer treatment. This concept inspired the design of novel ST inhibitors through the hybridization of lithocholic acid and diindolylmethane, leading to the discovery of LCA-DIM hybrids as potential chemical entities targeting STs. Preliminary screening revealed the significance of the DIM moiety and incorporation of Asp linker on enhancing the inhibitory activity and selectivity of the hybrids towards ST6GAL1, inhibiting up to 100% of ST6GAL1 activity at 25 μM with no ST3GAL1 inhibition even at 500 μM. Incorporation of various 5,5'-substituents enhanced the inherent antimigration properties of the hybrids, with

Identifiers

PMID40896419
PMCPMC12394899

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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.