Identification and characterization of lncRNA-stemness-immune regulatory patterns.

Area of Science:

• Oncology
• Molecular Biology
• Immunology

Background:

• Long noncoding RNAs (lncRNAs) are crucial regulators of stemness signature genes (SSGs) and tumor immunity.
• Cancer stem cell traits are linked to immune evasion and therapeutic resistance, necessitating a comprehensive understanding of their interactions.

Purpose of the Study:

• To characterize the pan-cancer interplay among SSGs, lncRNAs, and tumor immunity.
• To identify core regulatory triplets (STEM-LncCRTs) involving lncRNAs, SSGs, and immune genes.

Main Methods:

• Developed an integrative analytical framework combining network-based modeling and Bayesian network inference.
• Identified STEM-LncCRTs comprising an lncRNA, an SSG, and an immune gene.
• Validated predictive potential using machine learning algorithms across independent immunotherapy cohorts.

Main Results:

• Specific stemness-related lncRNAs can differentiate cancer subtypes and correlate with immune cell infiltration.
• The ATAD5/PRR11-AS1/SKP2 triplet demonstrates prognostic value across multiple cancers.
• STEM-LncCRTs accurately predict immune checkpoint inhibitor response, with improved accuracy when combined with tumor mutation burden.

Conclusions:

• This study provides a systems-level perspective on lncRNA regulation in tumor immunity.
• Identified STEM-LncCRTs serve as practical biomarkers for predicting immunotherapy efficacy and patient prognosis.