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Updated: Jun 23, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

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[Auxiliary diagnosis and prognosis evaluation of KIF4A, RAD51AP1 and CDKN3 in esophageal cancer].

S Qiu¹, C X Guo², L Li³

¹Clinical Laboratory, the Seventh Medical Center of Chinese PLA General Hospital, Beijing 100700, China.

Zhonghua Yu Fang Yi Xue Za Zhi [Chinese Journal of Preventive Medicine]

|May 8, 2024

Summary

This study identifies KIF4A, RAD51AP1, and CDKN3 as key genes in esophageal cancer (ESCA). High expression of these genes indicates poor prognosis and offers high diagnostic accuracy for ESCA.

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Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

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Development of Compendium for Esophageal Squamous Cell Carcinoma

Development of Compendium for Esophageal Squamous Cell Carcinoma

Published on: April 12, 2024

Area of Science:

Oncology
Genomics
Bioinformatics

Context:

Esophageal cancer (ESCA) poses a significant global health challenge.
Accurate diagnostic and prognostic biomarkers are crucial for effective ESCA management.
High-throughput sequencing and bioinformatics analysis offer powerful tools for biomarker discovery.

Purpose:

To identify differentially expressed genes (DEGs) in ESCA tissues.
To evaluate the diagnostic and prognostic value of identified DEGs in ESCA.
To explore the molecular pathways and biological functions associated with DEGs in ESCA.

Summary:

Utilizing TCGA data, 620 upregulated and 668 downregulated DEGs were identified between ESCA and para-cancerous tissues.
Functional enrichment analysis revealed DEGs involvement in key signaling pathways like IL-17 and TNF, crucial for ESCA development.
Survival analysis highlighted KIF4A, RAD51AP1, and CDKN3 as hub genes associated with poor prognosis in ESCA patients.

Impact:

KIF4A, RAD51AP1, and CDKN3 demonstrate high diagnostic potential for ESCA, with AUC values exceeding 0.956 individually.
A combined diagnostic model of these three genes achieved an AUC of 0.979, with 91.4% sensitivity and 100% specificity.
These genes serve as promising auxiliary diagnostic and prognostic factors, potentially improving ESCA patient outcomes.