Identification of TIG1 Associated Molecular Targets for Breast Cancer Using Bioinformatic Approach

e-posta/e-mail: [email protected]/[email protected] Kabul Tarihi/Accepted: Tazarotene-induced gene 1 (TIG1) is involved in modulating the α-tubulin modification and effectively inhibiting tumor growth. In this bioinformatics study, we aim to propose novel therapeutic targets in breast cancer by utilizing differentially expressed genes (DEGs) of TIG1 in inflammatory breast cancer (IBC) and examining their correlation with the molecular and immune subtypes. Using the GEO2R tool, we analyzed DEGs in the GSE30543 dataset, specifically comparing suppressed TIG1 groups with control samples from SUM149 cells. Functional annotation analysis of DEGs were explored using SRplot with data from STRING (|log2(FC)| >2 and p

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Publication Details

Journal
Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi
Published
2024-12-25
DOI
https://doi.org/10.37989/gumussagbil.1459020
Primary Topic
Galectins and Cancer Biology
Type
article
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article

Identification of TIG1 Associated Molecular Targets for Breast Cancer Using Bioinformatic Approach

Merve Gülşen Bal Albayrak, Murat Kasap, Gürler Akpınar, Tuğcan Korak
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Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi
Galectins and Cancer Biology
article

Identification of TIG1 Associated Molecular Targets for Breast Cancer Using Bioinformatic Approach

Merve Gülşen Bal Albayrak, Murat Kasap, Gürler Akpınar, Tuğcan Korak
article en

Abstract

e-posta/e-mail: [email protected]/[email protected] Kabul Tarihi/Accepted: Tazarotene-induced gene 1 (TIG1) is involved in modulating the α-tubulin modification and effectively inhibiting tumor growth. In this bioinformatics study, we aim to propose novel therapeutic targets in breast cancer by utilizing differentially expressed genes (DEGs) of TIG1 in inflammatory breast cancer (IBC) and examining their correlation with the molecular and immune subtypes. Using the GEO2R tool, we analyzed DEGs in the GSE30543 dataset, specifically comparing suppressed TIG1 groups with control samples from SUM149 cells. Functional annotation analysis of DEGs were explored using SRplot with data from STRING (|log2(FC)| >2 and p

Gümüşhane Üniversitesi Sağlık Bilimleri DergisiVol. 13(4)
Kocaeli Üniversitesi (TR)
Good health and well-being
Openalex Percentile: Top 69%
Galectins and Cancer Biology
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