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Published on: May 3, 2021
A Transient Receptor Potential-related Gene Model for the Prognostic Assessment and Drug Sensitivity Prediction in
Xiangming Li1, Minghang Zhang2, Ziyi Xu2
1Department of Orthopedics, The First Affiliated Hospital, College of Clinical Medicine, Henan University of Science and Technology, Luoyang, 471000, China.
Current Medicinal Chemistry
|July 13, 2026
Summary
This study developed a five-gene prognostic model for Osteosarcoma (OS) using Transient Receptor Potential (TRP)-related genes. This model accurately predicts patient prognosis and drug sensitivity, offering potential for improved OS therapies.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Osteosarcoma (OS) prognosis and treatment remain challenging.
- Understanding the role of Transient Receptor Potential (TRP)-related Genes (TRGs) in OS is crucial for therapeutic advancements.
Purpose of the Study:
- To investigate the correlation between TRGs, prognosis, and drug sensitivity in Osteosarcoma.
- To develop a prognostic model for OS based on TRGs.
Main Methods:
- Utilized Single-Sample Gene Set Enrichment Analysis (ssGSEA) and Weighted Gene Co-expression Network Analysis (WGCNA) on OS datasets.
- Constructed a prognostic RiskScore model using selected prognostic genes.
- Performed in vitro validation using siRNA-mediated gene knockdown and overexpression.
Main Results:
- A five-gene prognostic model (APBB1IP, CYFIP1, LASP1, MYC, PCDHB6) demonstrated robust predictive performance for OS.
- Patients with a low TRP score showed a tendency towards metastasis.
- The model revealed distinct pathway enrichments and drug sensitivities between high- and low-risk groups.
Conclusions:
- The developed five-gene TRG-related model effectively predicts prognosis and drug sensitivity in Osteosarcoma.
- This model holds potential for guiding therapeutic strategies and improving patient outcomes in OS.
