A pan-pediatric gene-regulatory network analysis reveals druggable dependencies across pediatric solid tumors

Background: Pediatric tumors often co-opt normal developmental gene-regulatory programs, with errors in lineage-restricted progenitors that halt or reverse differentiation. Because these cancers arise within restricted developmental windows, display fetal-like programs, and carry relatively few driver mutations compared to adult tumors, we hypothesized that a pan-pediatric, transcriptome-inferred gene-regulatory network (GRN) analysis will discover lineage-specific regulons that anchor each tumor to a developmentally arrested state, which would identify actionable biomarkers and therapeutic targets. Methods: We analyzed 2541 bulk RNA-seq from 35 pediatric cranial and extracranial solid-tumor samples, after batch correction. We inferred a pan-pediatric GRN from gene expression data, integrating networks inferred by ARACNe-AP and GENIE3 into a consensus GRN across all tumor types. We used a one-vs-rest strategy to identify tumor-specific differentially expressed genes (DEGs) within the regulons. Using hypergeometric tests, we quantified transcription factor (TF) activity and their regulons across tumors by assessing the enrichment of tumor-specific DEGs within each regulon. To map genes to drugs, we queried drug libraries, including Mechanistic Interrogation PlatE, Profiling Relative Inhibition Simultaneously in Mixtures, ChEMBL, DrugBank, and DrugCentral. We filtered druggable genes among TFs, their regulon members, and their interactors using log fold change and adjusted p-values, and ranked candidates in 19 tumors with DepMap data by using effect size. Results: We identified 281 enriched TFs across tumors. The functional enrichment analyses showed that TF programs are usually restricted to specific tumor classes, mirroring their developmental cell-of-origin and highlighting candidate tumor-specific biomarkers. Examples include neurodevelopmental and neural-crest-related TFs (e.g., PHOX2B, ASCL1, and SOX10) in neuroblastoma (NB) and muscle-lineage TFs (e.g., MYOG, MYOD1, and PAX3/7) in fusion-positive rhabdomyosarcomas (FP-RMS). Our analysis suggests that TFs behave as robust, tumor-type-specific expression signatures and can distinguish tumors that may be histologically similar but arise from different developmental lineages. Furthermore, we used our TF-centric approach to identify known and new drug targets, such as SIX1, RRM2, AURKA, and BIRC5 in FP-RMS, and ACVR2B & BMPR1B in NB. Conclusions and Future Directions: A unified GRN framework analysis of pan pediatric solid tumors resolves lineage-specific regulons associated with tumorigenesis and yields a ranked set of druggable genetic dependencies. In vitro and in vivo validation studies are currently underway.