Evidence map›Paper›PMID 36723760›Full record

ArticleJournal, genetic engineering & biotechnology2023

Systematic approach to identify therapeutic targets and functional pathways for the cervical cancer.

Md Tanvir Hasan, Md Rakibul Islam, Md Rezwan Islam, Baraa Riyadh Altahan, Kawsar Ahmed, Francis M Bui, Sami Azam, Mohammad Ali Moni

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

8 authors at 5 institutions in 5 countries.

Md Tanvir HasanDepartment of Business Engineering, Ghent University, 9000 Gent, Belgium.
Md Rakibul IslamDepartment of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh.
Md Rezwan IslamDepartment of Software Engineering, Daffodil International University (DIU), Ashulia, Savar, Dhaka, 1342, Bangladesh.
Baraa Riyadh AltahanDepartment of Medical Instrumentation Engineering Techniques, Al-Mustaqbal University College, Hilla, Babil, 51001, Iraq.
Kawsar AhmedDepartment of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada. kawsar.ict@mbstu.ac.bd.ORCID http://orcid.org/0000-0002-4034-9819
Francis M BuiDepartment of Electrical and Computer Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, SK, S7N 5A9, Canada.
Sami AzamCollege of Engineering, IT and Environment, Charles Darwin University, Casuarina, NT, 0909, Australia.
Mohammad Ali MoniFaculty of Health and Behavioural Sciences, School of Health and Rehabilitation Sciences, The University of Queensland, St. Lucia, QLD, 4072, Australia. m.moni@uq.edu.au.ORCID https://orcid.org/0000-0003-0756-1006
Daffodil International University · BDUniversity of Saskatchewan · CACharles Darwin University · AUGhent University · BEThe University of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn today's society, cancer has become a big concern. The most common cancers in women are breast cancer (BC), endometrial cancer (EC), ovarian cancer (OC), and cervical cancer (CC). CC is a type of cervix cancer that is the fourth most common cancer in women and the fourth major cause of death.

resultsThis research uses a network approach to discover genetic connections, functional enrichment, pathways analysis, microRNAs transcription factors (miRNA-TF) co-regulatory network, gene-disease associations, and therapeutic targets for CC. Three datasets from the NCBI's GEO collection were considered for this investigation. Then, using a comparison approach between the datasets, 315 common DEGs were discovered. The PPI network was built using a variety of combinatorial statistical approaches and bioinformatics tools, and the PPI network was then utilized to identify hub genes and critical modules.

conclusionFurthermore, we discovered that CC has specific similar links with the progression of different tumors using Gene Ontology terminology and pathway analysis. Transcription factors-gene linkages, gene-disease correlations, and the miRNA-TF co-regulatory network were revealed to have functional enrichments. We believe the candidate drugs identified in this study could be effective for advanced CC treatment.

Identifiers

PMID36723760
PMCPMC9892376
OpenAlexW4318754166

What OpenQuestion holds

Textmetadata
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.