Identification of Treg-related prognostic molecular subtypes and individualized characteristics in clear cell renal cell carcinoma through single-cell transcriptomes and bulk RNA sequencing

Abstract

Background: In clear cell renal cell carcinoma (ccRCC), the role of Regulatory T cells (Treg cells) as prognostic and immunotherapy response predictors is not fully explored.

Methods: Analyzing renal clear cell carcinoma datasets from TISCH, TCGA, and GEO, we focused on 8 prognostic Treg genes to study patient subtypes in ccRCC. We assessed Treg subtypes in relation to patient prognosis, tumor microenvironment, metabolism. Using Cox regression and principal component analysis, we devised Treg scores for individual patient characterization and explored the molecular role of C1QL1, a critical gene in the Treg model, through in vivo and in vitro studies.

Results: Eight Treg-associated prognostic genes were identified, classifying ccRCC patients into cluster A and B. Cluster A patients showed poorer prognosis with distinct clinical and molecular profiles, potentially benefiting more from immunotherapy. Low Treg scores correlated with worse outcomes and clinical progression. Low scores also suggested that patients might respond better to immunotherapy and targeted therapies. In ccRCC, C1QL1 knockdown reduced tumor proliferation and invasion via NF-kb-EMT pathways and decreased Treg cell infiltration, enhancing immune efficacy.

Conclusions: The molecular subtype and Treg score in ccRCC, based on Treg cell marker genes, are crucial in personalizing ccRCC treatment and underscore C1QL1's potential as a tumor biomarker and target for immunotherapy.

Keywords: Bulk RNA sequencing; Clear cell renal cell carcinoma; Molecular subtypes; Single-cell RNA sequencing; Treg cells.