Identification of Potential Predictive Transcript Isoform-Biomarkers for the Early Diagnosis of Breast Cancer Using Bioinformatics Tools Bioinformatics tools in early diagnosis of BC

Hulya Gundesli (1), Medi Kori (2), Cihan Ergul (3)
(1) Gulhane Faculty of Medicine, University of Health Sciences, Department of Medical Biology, Ankara, Turkey, Turkey,
(2) Institute of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey; Faculty of Health Sciences, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey, Turkey,
(3) Gulhane Faculty of Medicine, University of Health Sciences, Department of Medical Biology, Ankara, Turkey, Turkey

Abstract

Background: Several studies have demonstrated that the expression status of isoforms is more informative as a biomarker than overall gene expression. This study aimed to determine highly but significantly expressed transcript isoforms and evaluate their prognostic and diagnostic impact in breast invasive carcinoma (BRCA) stage I patients.


Methods: The differentially expressed genes and their transcript isoforms in BRCA stage I were determined using the Cancer Differentially Expressed Isoform and gene (Cancer DEIso) platform based on The Cancer Genome Atlas (TCGA) data. The prognostic and diagnostic impact of significantly upregulated top 10 genes and their transcripts were revealed using the Cancer DEIso tool, the Kaplan-Meier (KM) method, and the Receiver Operating Characteristic Curve (ROC) approach, respectively. Isoform-level protein-protein interactions (PPI) were constructed using the Domain Interaction Graph Guided ExploreR (DIGGER) database. ConsensusPathDB was used to perform pathway enrichment analysis based on the constructed interactions.


Results: This study revealed that NM_024037, NM_001143782, and NM_021619 transcript isoforms have significant diagnostic ability with AUC values 93.2%, 77.1% and 75.3%, respectively to distinguish stage I BRCA patients from normal. KM-plot analysis showed that these three isoforms have no prognostic significance in stage I patients, but their upregulation was correlated with decreased survival in BRCA patients regardless of stage. Isoform-based pathway enrichment analyses indicated that these three isoforms involved in chromatin organization, senescense, DNA damage and several signalling pathways which promotes cancer when there is misregulation. .


Conclusion: NM_024037, NM_001143782, and NM_021619 transcript isoforms are potential biomarkers for detecting early-stage BRCA. Thus, it is essential to find out how these three isoforms contribute to the development of breast carcinogenesis and evolve a new approach for capturing breast tumors at an earlier stage of the clinical landscape.

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Authors

Hulya Gundesli
hulya.gundesli@sbu.edu.tr (Primary Contact)
Medi Kori
Cihan Ergul
1.
Gundesli H, Kori M, Ergul C. Identification of Potential Predictive Transcript Isoform-Biomarkers for the Early Diagnosis of Breast Cancer Using Bioinformatics Tools: Bioinformatics tools in early diagnosis of BC. Arch Breast Cancer [Internet]. 2024 Oct. 25 [cited 2024 Oct. 30];11(4). Available from: https://archbreastcancer.com/index.php/abc/article/view/950

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