Identification of key genes to predict response to chemoradiotherapy and prognosis in esophageal squamous cell carcinoma.

Front Mol Biosci

State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, China.

Published: November 2024

AI Article Synopsis

  • * Using the Gene Expression Omnibus database, researchers identified three key genes that can predict how well ESCC patients respond to neoadjuvant chemoradiotherapy and are associated with immune cell activity.
  • * A prognostic nomogram was created that combines these key genes with clinical data, showing reliable predictions for ESCC outcomes while revealing the genes' roles in important tumor signaling pathways, such as epithelial-mesenchymal transition and P53.

Article Abstract

Background: Chemoradiotherapy is a crucial treatment modality for esophageal squamous cell carcinoma (ESCC). This study aimed to identify chemoradiotherapy sensitivity-related genes and analyze their prognostic value and potential associations with the tumor microenvironment in ESCC.

Methods: Utilizing the Gene Expression Omnibus database, we identified differentially expressed genes between ESCC patients who achieved complete and incomplete pathological responses following chemoradiotherapy. Prognostic genes were then screened, and key genes associated with chemoradiotherapy sensitivity were determined using random survival forest analysis. We examined the relationships between key genes, infiltrating immune cells, and immunoregulatory genes. Additionally, drug sensitivity and enrichment analyses were conducted to assess the impact of key genes on chemotherapy responses and signaling pathways. A prognostic nomogram for ESCC was developed incorporating key genes, and its effectiveness was evaluated. Genome-wide association study data were employed to investigate chromosomal pathogenic regions associated with key genes.

Results: Three key genes including , , and were identified. These genes can predict the sensitivity of ESCC patients to neoadjuvant chemoradiotherapy and hold significant clinical relevance in prognostication. These genes were also found to be significantly correlated with certain immune cells and immunoregulatory genes within the tumor microenvironment and were involved in critical tumor-related signaling pathways, including the epithelial-mesenchymal transition and P53 pathways. A nomogram was established to predict the prognosis of ESCC by integrating key genes with clinical stages, demonstrating favorable predictability and reliability.

Conclusion: This study identified three key genes that predict chemoradiotherapy sensitivity and prognosis and are involved in multiple tumor-related biological processes in ESCC. These findings provide predictive biomarkers for chemoradiotherapy response and support the development of individualized treatment strategies for ESCC patients.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11614722PMC
http://dx.doi.org/10.3389/fmolb.2024.1512715DOI Listing

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