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Updated: Jan 13, 2026
Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
Published on: June 27, 2020
Transcription factor activity-based stratification reveals prognostic subtypes and immune landscape in neuroblastoma
Mingyou Gao1, Xin Li2, Yuren Xia1
1Department of Pediatric Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University, Tianjin, China.
Background:
High-risk neuroblastoma (NB) still carries a <50% long-term survival despite risk-adapted therapy. Conventional risk metrics (age, stage, MYCN status) fail to capture transcriptional programs that drive tumor aggressiveness and immune escape. We hypothesized that systematic transcription factor (TF) activity profiling would reveal clinically actionable NB subtypes. This study aimed to profile TF activities in NB to develop and validate a TF-based prognostic score and to examine its association with the tumor immune microenvironment.
Methods:
TF activities for 498 primary NB tumors (GSE49710) were inferred with decoupleR-univariate linear model (ULM) using the OmniPath regulon. TFs that were significantly associated with overall survival (OS; Cox; P<1×10-4; n=146) were subjected to consensus clustering and Boruta-guided principal component analysis (PCA) to create a continuous TF_score. Immune infiltration and immunotherapy surrogates, Immunophenoscore (IPS) and the Tumor Immune Dysfunction and Exclusion (TIDE) framework, were compared across TF_score strata. A nomogram integrating TF_score, stage, and MYCN amplification was developed and validated with an external cohort (E-MTAB-8248; n=223) and single-cell RNA sequencing (RNA-seq) data.
Results:
Two robust NB subtypes were identified, with cluster 2 associated with worse prognosis, MYCNamplification, older age, distinct pathway activation, and higher stemness indices. The TF_score reliably quantified these clusters, showing superior predictive capability for survival compared to traditional markers (MYCN amplification and tumor stage). TF_score-high patients exhibited reduced immune infiltration and lower predicted responsiveness to immunotherapy. A validated prognostic nomogram effectively stratified risk, highlighting MYC and E2F family activation and FOXO3 and IRF1 suppression in high-risk patients. Single-cell analyses confirmed these bulk RNA-seq findings.
Conclusions:
TF activity profiling provides robust stratification for NB, integrating clinical prognostication and immune characterization. This study offers novel insights into TF-driven NB biology, with implications for targeted therapy and immunotherapeutic strategies.
