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Published on: October 4, 2019
Integrative single-cell and bulk transcriptomics identify an ALK-associated three-gene signature predicting
Aiguo Zhu1,2, Yuren Xia1,2, Xin Li1,2
1Tianjin Cancer Hospital Airport Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Background:
Activating anaplastic lymphoma kinase (ALK) mutations define a clinically relevant subset of neuroblastoma (NB), yet ALK-linked transcriptional programs with robust prognostic value remain insufficiently characterized. This study aimed to identify ALK-associated transcriptional features across single-cell and bulk datasets and to develop a reproducible prognostic signature for NB.
Methods:
We integrated a public single-cell atlas of high-risk NB from CELL×GENE with bulk RNA sequencing (RNA-seq) cohorts and NB cell-line datasets. Differential expression between ALK-mutant and ALK-wild-type samples was analyzed in (I) pseudobulk malignant cells from the single-cell dataset, (II) the Kids First (Maris) cohort, and (III) GSE89413 NB cell lines, followed by direction-consistent intersection. A prognostic model was developed in GSE62564 using Cox regression and evaluated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curves. External validation was performed in GSE181559 and TARGET-NBL. Biological significance was further explored using preranked gene set enrichment analysis (GSEA).
Results:
Three concordant ALK-associated genes, DLK1, RTL1, and ISLR2, were identified across all three analytical contexts and were consistently upregulated in ALK-mutant samples. A three-gene risk score significantly stratified overall survival and event-free survival in GSE62564 and remained predictive in GSE181559 and TARGET-NBL without model re-fitting. High-risk tumors were enriched for translational and ribosome biogenesis pathways, whereas low-risk tumors were enriched for adaptive immune activation programs.
Conclusions:
Cross-context transcriptomic integration identified a minimal ALK-associated three-gene signature that reproducibly predicts NB outcomes and reflects distinct underlying biological states, supporting its potential value for risk stratification and hypothesis-driven therapeutic development.
