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Published on: June 13, 2018
Machine learning screening for disulfidptosis genes-associated immunosuppression status in osteosarcoma and
1Department of Pediatric Surgery, Children's Medical Center, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
Background:
The recent identification of disulfidptosis, a novel form of cell death, offers significant potential for advancing cancer therapeutics. Osteosarcoma (OS) and rhabdomyosarcoma (RMS) are prevalent malignant sarcomas in children and young adults, yet their molecular underpinnings remain poorly understood, hampering treatment options. This study aimed to delineate the role of disulfidptosis in these malignancies and to identify key molecular determinants of prognosis.
Methods:
We analyzed extensive RNA transcriptome data from the Gene Expression Omnibus (GEO) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) databases. Non-negative matrix factorization (NMF) clustering was employed to identify disulfidptosis-associated molecular subtypes. Furthermore, we integrated 100 machine-learning algorithms to pinpoint core prognostic genes.
Results:
Based on disulfidptosis-related genes, we identified a distinct immunosuppressive subtype in both OS and RMS, characterized by significantly poorer immune cell infiltration. A robust prognostic signature comprising five genes (ACTN4, MYH9, FLNA, MYH10, and IQGAP1) was established, which effectively characterized the immunosuppressive subtypes and stratified patient risk. Notably, IQGAP1 emerged as an independent prognostic factor in RMS, highlighting its potential as both a therapeutic target and biomarker. Additionally, our analysis revealed a strong correlation between macrophage infiltration and disulfidptosis, suggesting a potential role in shaping the tumor immune microenvironment and influencing patient prognosis.
Conclusions:
Our findings illuminate the landscape of disulfidptosis in OS and RMS, revealing a novel immunosuppressive subtype and a defined five-gene signature for risk stratification. The identification of IQGAP1 and the link to macrophages provides new insights for developing targeted therapies and immunotherapeutic strategies for these malignancies.
Insights
Discovered a new immunosuppressive subtype in osteosarcoma and rhabdomyosarcoma linked to disulfidptosis. A five-gene signature, including IQGAP1, aids in risk stratification and identifies potential therapeutic targets.
Area of Science:
- Oncology
- Cell Death Research
- Molecular Biology
Background:
- Disulfidptosis, a novel cell death pathway, presents new therapeutic avenues.
- Osteosarcoma (OS) and Rhabdomyosarcoma (RMS) are pediatric sarcomas with poorly understood molecular drivers.
- Understanding disulfidptosis in OS and RMS is crucial for improving treatment options.
Purpose of the Study:
- To investigate the role of disulfidptosis in osteosarcoma and rhabdomyosarcoma.
- To identify molecular subtypes associated with disulfidptosis.
- To discover prognostic gene signatures for these sarcomas.
Main Methods:
- Analyzed RNA transcriptome data from GEO and TARGET databases.
- Utilized Non-negative Matrix Factorization (NMF) for molecular subtyping.
- Integrated 100 machine-learning algorithms to identify prognostic genes.
Main Results:
- Identified a distinct immunosuppressive subtype in OS and RMS with reduced immune cell infiltration.
- Developed a five-gene prognostic signature (ACTN4, MYH9, FLNA, MYH10, IQGAP1) for risk stratification.
- IQGAP1 identified as an independent prognostic factor in RMS; macrophage infiltration correlated with disulfidptosis.
Conclusions:
- Discovered a novel immunosuppressive subtype in OS and RMS driven by disulfidptosis.
- Established a five-gene signature for risk stratification and identified IQGAP1 as a potential therapeutic target.
- Findings offer new insights for targeted and immunotherapeutic strategies against pediatric sarcomas.
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