Evidence map›Paper›PMID 38717954›Full record

ArticleCancer reports (Hoboken, N.J.)2024

Transcriptomic analysis revealed potential regulatory biomarkers and repurposable drugs for breast cancer treatment.

Most Shornale Akter, Md Helal Uddin, Sheikh Atikur Rahman, Md Arju Hossain, Md Ashiqur Rahman Ashik, Nurun Nesa Zaman, Omar Faruk, Md Sanwar Hossain, Anzana Parvin, Md Habibur Rahman

Abstract 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 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
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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

10 authors.

Most Shornale AkterDepartment of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh.
Md Helal UddinDepartment of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh.
Sheikh Atikur RahmanDepartment of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh.
Md Arju HossainDepartment of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Md Ashiqur Rahman AshikDepartment of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh.
Nurun Nesa ZamanDepartment of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh.
Omar FarukDepartment of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Tangail, Bangladesh.
Md Sanwar HossainDepartment of Statistics, Jagannath University, Dhaka, Bangladesh.
Anzana ParvinDepartment of Biotechnology and Genetic Engineering, Islamic University, Kushtia, Bangladesh.
Md Habibur RahmanDepartment of Computer Science and Engineering, Islamic University, Kushtia, Bangladesh.ORCID 0000-0002-5068-2690

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer (BC) is the most widespread cancer worldwide. Over 2 million new cases of BC were identified in 2020 alone. Despite previous studies, the lack of specific biomarkers and signaling pathways implicated in BC impedes the development of potential therapeutic strategies. We employed several RNAseq datasets to extract differentially expressed genes (DEGs) based on the intersection of all datasets, followed by protein-protein interaction network construction. Using the shared DEGs, we also identified significant gene ontology (GO) and KEGG pathways to understand the signaling pathways involved in BC development. A molecular docking simulation was performed to explore potential interactions between proteins and drugs. The intersection of the four datasets resulted in 146 DEGs common, including AURKB, PLK1, TTK, UBE2C, CDCA8, KIF15, and CDC45 that are significant hub-proteins associated with breastcancer development. These genes are crucial in complement activation, mitotic cytokinesis, aging, and cancer development. We identified key microRNAs (i.e., hsa-miR-16-5p, hsa-miR-1-3p, hsa-miR-147a, hsa-miR-195-5p, and hsa-miR-155-5p) that are associated with aggressive tumor behavior and poor clinical outcomes in BC. Notable transcription factors (TFs) were FOXC1, GATA2, FOXL1, ZNF24 and NR2F6. These biomarkers are involved in regulating cancer cell proliferation, invasion, and migration. Finally, molecular docking suggested Hesperidin, 2-amino-isoxazolopyridines, and NMS-P715 as potential lead compounds against BC progression. We believe that these findings will provide important insight into the BC progression as well as potential biomarkers and drug candidates for therapeutic development.

Indexed as

Biomarkers, TumorBreast NeoplasmsGene Expression ProfilingGene Expression Regulation, NeoplasticAntineoplastic AgentsFemaleGene Regulatory NetworksHumansMicroRNAsMolecular Docking SimulationProtein Interaction MapsSignal TransductionTranscriptomeAntineoplastic AgentsBiomarkers, TumorMicroRNAsbiomarkerbreast cancerhub‐proteinin silico analysismolecular dockingtranscriptomics

Identifiers

PMID38717954
PMCPMC11078332

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LicenceCC BY
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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.