Integrated Multi-Omics Analysis Identified PTPRG and CHL1 as Key Regulators of Immunophenotypes in Clear Cell Renal...

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Immune checkpoint blockade (ICB) is crucial for cancer therapy, but its efficacy in clear cell renal cell carcinoma (ccRCC) depends on poorly understood molecular mechanisms.
• Identifying specific immune cell roles and molecular drivers is essential for optimizing ccRCC treatment strategies.

Purpose of the Study:

• To elucidate the molecular mechanisms underlying ccRCC response to ICB.
• To identify immune cell signatures and molecular targets that predict patient prognosis.

Main Methods:

• Analysis of ccRCC samples from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets.
• Screening of immune cells correlated with PD-L1 and interferon-gamma (IFN-γ) expression.
• Unsupervised clustering, lasso regression, and differential gene expression analysis (mRNA, somatic mutations, copy number variations, DNA methylation, miRNA, lncRNA).
• Construction of a gene regulatory network and development of a prognostic model using Lasso-Cox regression and Kaplan-Meier analysis.

Main Results:

• Six immune cells were identified as strongly correlated with PD-L1 and IFN-γ expression.
• ccRCC samples were grouped into four clusters, with distinct sub-clusters A1 and B1 selected for detailed comparison.
• PTPRG and CHL1 were identified as key regulatory nodes in ccRCC immunophenotypes.
• WNT2, C17orf66, and PAEP were identified as independent risk factors, while IRF4 served as a protective factor in the prognostic model.

Conclusions:

• This study provides critical insights into the molecular landscape of ccRCC and its immunophenotypes.
• The identified molecular players and prognostic factors offer potential therapeutic targets and predictive biomarkers for ccRCC patients receiving ICB therapy.