Evidence map›Paper›PMID 39502516›Full record

ArticleInternational journal of microbiology2024

Potential Target Metabolites From Gut Microbiota Against Hepatocellular Carcinoma: A Network Pharmacology and Molecular Docking Study.

Sehar Aslam, Muhammad Qasim, Fatima Noor, Muhammad Shahid, Usman Ali Ashfaq, Samman Munir, Helal F Al-Harthi, Mutaib M Mashraqi, Umair Waqas, Mohsin Khurshid

Abstract read
In one paragraph

Article in International journal of microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

10 authors.

Sehar AslamDepartment of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.ORCID https://orcid.org/0009-0002-8894-9087
Muhammad QasimDepartment of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.ORCID https://orcid.org/0000-0001-8139-538X
Fatima NoorDepartment of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.
Muhammad ShahidDepartment of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.
Usman Ali AshfaqDepartment of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.ORCID https://orcid.org/0000-0002-5495-805X
Samman MunirDepartment of Bioinformatics and Biotechnology, Government College University Faisalabad, Faisalabad, Pakistan.ORCID https://orcid.org/0000-0002-6659-5735
Helal F Al-HarthiBiology Department, Turabah University College, Taif University, Taif 21995, Saudi Arabia.ORCID https://orcid.org/0000-0002-0248-573X
Mutaib M MashraqiDepartment of Clinical Laboratory Sciences, College of Applied Medical Science, Najran University, Najran 61441, Saudi Arabia.ORCID https://orcid.org/0000-0002-2931-296X
Umair WaqasCollege of Science and Engineering, Flinders University, Bedford Park, Adelaide, South Australia, Australia.ORCID https://orcid.org/0000-0002-5340-4987
Mohsin KhurshidInstitute of Microbiology, Government College University Faisalabad, Faisalabad, Pakistan.ORCID https://orcid.org/0000-0002-3196-2857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide, posing significant challenges and economic burdens on healthcare systems. Gut microbiota metabolites have shown promise in cancer treatment, but the specific active metabolites and their key targets remain unclear. This study employed a network pharmacology-based approach to identify potent metabolites of gut microbiota and their key targets. Active metabolites produced by gut microbiota were retrieved using the database gutMGene, and targets associated with these metabolites were identified using the Swiss Target Prediction tool. HCC-related targets were obtained from the GeneCards database, and overlapping targets were selected through a Venn diagram tool. An integrated metabolites-target-pathway network was analyzed to identify active inhibitors against HCC, including

Indexed as

AKT1anti-HCC drugsEGFRgut microbiotahepatocellular carcinomasignaling pathwaystherapeutic targets

Identifiers

PMID39502516
PMCPMC11537736

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.