Expression Profiling of EMT Transcription Factors in Epithelial Cancer vs. Colon Cancer from a Clini-cal Dataset (Snail, Slug, Zeb-1, Twist)

Colorectal cancer (CRC) is the second most common cancer and a leading cause of cancer-related deaths worldwide. Epithelial-mesenchymal transition (EMT) is a biological process that enables a polarized epithelial cell to go through a variety of biochemical changes and adopt the phenotype of a mesenchymal cell, which includes increased migratory ability and invasiveness. Here, we aim to explore the role of a comprehensive analysis of the dynamic regulation of EMT transcription factors Slug, Snail, Twist, and Zeb1 in CRC. By examining expression patterns across different tumor stages, age groups, and genders, the research elucidates the stage-dependent and demographic-specific modulation of EMT drivers. Findings reveal that key EMT regulators such as Slug and Snail are predominantly active during early CRC stages, contributing to tumor initiation and local invasion. At the same time, Twist and Zeb1 become more prominent during advanced stages, facilitating metastasis and tumor progression. Notably, gender differences influence the expression of these factors, with females exhibiting higher levels of Slug and Twist. The study underscores the potential of these transcription factors as stage- and patient-specific biomarkers and therapeutic targets, emphasizing the importance of personalized strategies in CRC management. Future investigations aimed at functional validation and clinical trials could pave the way for stage-specific EMT-targeted interventions, ultimately improving prognosis and treatment efficacy in CRC.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-07-14
DOI
https://doi.org/10.22214/ijraset.2025.73040
Primary Topic
Gene expression and cancer classification
Type
article
Field-Weighted Citation Impact
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article

Expression Profiling of EMT Transcription Factors in Epithelial Cancer vs. Colon Cancer from a Clini-cal Dataset (Snail, Slug, Zeb-1, Twist)

Supriya Soni
International Journal for Research in Applied Science and Engineering Technology
Gene expression and cancer classification
article

Expression Profiling of EMT Transcription Factors in Epithelial Cancer vs. Colon Cancer from a Clini-cal Dataset (Snail, Slug, Zeb-1, Twist)

Supriya Soni
article en

Abstract

Colorectal cancer (CRC) is the second most common cancer and a leading cause of cancer-related deaths worldwide. Epithelial-mesenchymal transition (EMT) is a biological process that enables a polarized epithelial cell to go through a variety of biochemical changes and adopt the phenotype of a mesenchymal cell, which includes increased migratory ability and invasiveness. Here, we aim to explore the role of a comprehensive analysis of the dynamic regulation of EMT transcription factors Slug, Snail, Twist, and Zeb1 in CRC. By examining expression patterns across different tumor stages, age groups, and genders, the research elucidates the stage-dependent and demographic-specific modulation of EMT drivers. Findings reveal that key EMT regulators such as Slug and Snail are predominantly active during early CRC stages, contributing to tumor initiation and local invasion. At the same time, Twist and Zeb1 become more prominent during advanced stages, facilitating metastasis and tumor progression. Notably, gender differences influence the expression of these factors, with females exhibiting higher levels of Slug and Twist. The study underscores the potential of these transcription factors as stage- and patient-specific biomarkers and therapeutic targets, emphasizing the importance of personalized strategies in CRC management. Future investigations aimed at functional validation and clinical trials could pave the way for stage-specific EMT-targeted interventions, ultimately improving prognosis and treatment efficacy in CRC.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(7)
Openalex Percentile: Top 85%
Gene expression and cancer classification
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