Evidence map›Paper›PMID 38600056›Full record

ArticleCancer reports (Hoboken, N.J.)2024

Network-based identification of key proteins and repositioning of drugs for non-small cell lung cancer.

Oluwatosin Maryam Adeyemo, Zainab Ashimiyu-Abdusalam, Mary Adewunmi, Temitope Ayanfunke Ayano, Muhammad Sohaib, Reem Abdel-Salam

Open access · goldAbstract read
In one paragraph

Article in Cancer reports (Hoboken, N.J.), 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
1.2field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

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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

6 authors at 4 institutions in 3 countries.

Oluwatosin Maryam AdeyemoDepartment of Biochemistry, Federal University of Technology, Akure, Nigeria.ORCID 0000-0002-1234-5239
Zainab Ashimiyu-AbdusalamCancer Research with AI (CaresAI), Hobart, Australia.ORCID 0000-0003-2511-3151
Mary AdewunmiCancer Research with AI (CaresAI), Hobart, Australia.ORCID 0000-0002-3727-5417
Temitope Ayanfunke AyanoCancer Research with AI (CaresAI), Hobart, Australia.ORCID 0000-0002-7187-7112
Muhammad SohaibCancer Research with AI (CaresAI), Hobart, Australia.ORCID 0000-0002-6216-9261
Reem Abdel-SalamCancer Research with AI (CaresAI), Hobart, Australia.ORCID 0000-0002-4594-211X
Cancer Australia · AUCairo University · EGFederal University of Technology · NGUniversity of Tasmania · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNSCLC is a lethal cancer that is highly prevalent and accounts for 85% of cases of lung cancer. Conventional cancer treatments, such as chemotherapy and radiation, frequently exhibit limited efficacy and notable adverse reactions. Therefore, a drug repurposing method is proposed for effective NSCLC treatment.

aimsThis study aims to evaluate candidate drugs that are effective for NSCLC at the clinical level using a systems biology and network analysis approach.

methodsDifferentially expressed genes in transcriptomics data were identified using the systems biology and network analysis approaches. A network of gene co-expression was developed with the aim of detecting two modules of gene co-expression. Following that, the Drug-Gene Interaction Database was used to find possible drugs that target important genes within two gene co-expression modules linked to non-small cell lung cancer (NSCLC). The use of Cytoscape facilitated the creation of a drug-gene interaction network. Finally, gene set enrichment analysis was done to validate candidate drugs.

resultsUnlike previous research on repositioning drugs for NSCLC, which uses a gene co-expression network, this project is the first to research both gene co-expression and co-occurrence networks. And the co-occurrence network also accounts for differentially expressed genes in cancer cells and their adjacent normal cells. For effective management of non-small cell lung cancer (NSCLC), drugs that show higher gene regulation and gene affinity within the drug-gene interaction network are thought to be important. According to the discourse, NSCLC genes have a lot of control over medicines like vincristine, fluorouracil, methotrexate, clotrimazole, etoposide, tamoxifen, sorafenib, doxorubicin, and pazopanib.

conclusionHence, there is a possibility of repurposing these drugs for the treatment of non-small-cell lung cancer.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsDrug RepositioningGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansdrug–gene interactiondrug repurposingnetwork analysisnon‐small cell lung cancer (NSCLC)therapeutics

Identifiers

PMID38600056
PMCPMC11006715
OpenAlexW4394723881

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Registered trials

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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.