Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions

Triple negative breast cancer (TNBC) is the most aggressive subtype and disproportionately affects African American women. The development of breast cancer is highly associated with interactions between tumor cells and the extracellular matrix (ECM), and recent research suggests that cellular compon...

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Main Authors: Kylie L. King, Hamed Abdollahi, Zoe Dinkel, Alannah Akins, Homayoun Valafar, Heather Dunn
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Computational and Structural Biotechnology Journal
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Online Access:http://www.sciencedirect.com/science/article/pii/S2001037025000273
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author Kylie L. King
Hamed Abdollahi
Zoe Dinkel
Alannah Akins
Homayoun Valafar
Heather Dunn
author_facet Kylie L. King
Hamed Abdollahi
Zoe Dinkel
Alannah Akins
Homayoun Valafar
Heather Dunn
author_sort Kylie L. King
collection DOAJ
description Triple negative breast cancer (TNBC) is the most aggressive subtype and disproportionately affects African American women. The development of breast cancer is highly associated with interactions between tumor cells and the extracellular matrix (ECM), and recent research suggests that cellular components of the ECM vary between racial groups. This pilot study aimed to evaluate gene expression in TNBC samples from patients who identified as African American and Caucasian using traditional statistical methods and emerging Machine Learning (ML) approaches. ML enables the analysis of complex datasets and the extraction of useful information from small datasets. We selected four regions of interest from tumor biopsy samples and used laser microdissection to extract tissue for gene expression characterization via RT-qPCR. Both parametric and non-parametric statistical analyses identified genes differentially expressed between the two ethnic groups. Out of 40 genes analyzed, 4 were differentially expressed in the edge of tumor (ET) region and 8 in the ECM adjacent to the tumor (ECMT) region. In addition to statistical approach, ML was used to generate decision trees (DT) for a broader analysis of gene expression and ethnicity. Our DT models achieved 83.33 % accuracy and identified the most significant genes, including CD29 and EGF from the ET region and SNAI1 and CHD2 from the ECMT region. All significant genes were analyzed for pathway enrichment using MSigDB and Gene Ontology databases, most notably the epithelial to mesenchymal transition and cell motility pathways. This pilot study highlights key genes of interest that are differentially expressed in African American and Caucasian TNBC samples.
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spelling doaj-art-9eff2d267d9c4cd8bb702e6451a113e72025-02-02T05:27:04ZengElsevierComputational and Structural Biotechnology Journal2001-03702025-01-0127548555Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regionsKylie L. King0Hamed Abdollahi1Zoe Dinkel2Alannah Akins3Homayoun Valafar4Heather Dunn5Department of Bioengineering, Clemson University, Clemson, SC, USADepartment of Computer Science and Engineering, University of South Carolina, Columbia, SC, USADepartment of Bioengineering, Clemson University, Clemson, SC, USADepartment of Bioengineering, Clemson University, Clemson, SC, USADepartment of Computer Science and Engineering, University of South Carolina, Columbia, SC, USADepartment of Bioengineering, Clemson University, Clemson, SC, USA; Corresponding author.Triple negative breast cancer (TNBC) is the most aggressive subtype and disproportionately affects African American women. The development of breast cancer is highly associated with interactions between tumor cells and the extracellular matrix (ECM), and recent research suggests that cellular components of the ECM vary between racial groups. This pilot study aimed to evaluate gene expression in TNBC samples from patients who identified as African American and Caucasian using traditional statistical methods and emerging Machine Learning (ML) approaches. ML enables the analysis of complex datasets and the extraction of useful information from small datasets. We selected four regions of interest from tumor biopsy samples and used laser microdissection to extract tissue for gene expression characterization via RT-qPCR. Both parametric and non-parametric statistical analyses identified genes differentially expressed between the two ethnic groups. Out of 40 genes analyzed, 4 were differentially expressed in the edge of tumor (ET) region and 8 in the ECM adjacent to the tumor (ECMT) region. In addition to statistical approach, ML was used to generate decision trees (DT) for a broader analysis of gene expression and ethnicity. Our DT models achieved 83.33 % accuracy and identified the most significant genes, including CD29 and EGF from the ET region and SNAI1 and CHD2 from the ECMT region. All significant genes were analyzed for pathway enrichment using MSigDB and Gene Ontology databases, most notably the epithelial to mesenchymal transition and cell motility pathways. This pilot study highlights key genes of interest that are differentially expressed in African American and Caucasian TNBC samples.http://www.sciencedirect.com/science/article/pii/S2001037025000273Breast cancerDiverse patient samplesLaser microdissectionGene analysis
spellingShingle Kylie L. King
Hamed Abdollahi
Zoe Dinkel
Alannah Akins
Homayoun Valafar
Heather Dunn
Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions
Computational and Structural Biotechnology Journal
Breast cancer
Diverse patient samples
Laser microdissection
Gene analysis
title Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions
title_full Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions
title_fullStr Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions
title_full_unstemmed Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions
title_short Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions
title_sort pilot study initial investigation suggests differences in emt associated gene expression in breast tumor regions
topic Breast cancer
Diverse patient samples
Laser microdissection
Gene analysis
url http://www.sciencedirect.com/science/article/pii/S2001037025000273
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