The scPagwas analysis of single-cell sequencing combined with Bayesian deconvolution with SMR Reveals Tumor Heterogeneity and Predicts Immunotherapy Response in Neuroblastoma
Year: 2026
Type: article
Abstract: Objective: High-risk neuroblastoma, the predominant driver of pediatric cancer deaths, is marked by marked intratumoral heterogeneity that fuels therapy resistance. To predict response to and targets for immunotherapy, we use single-cell and bulk RNA sequencing data to reveal tumor heterogeneity in neuroblastoma, and to identify prognostic genes for neuroblastoma. Methodology: Single-cell data were analyzed for trait-associated subpopulations and genes using single-cell Pathway-based genome-wide association study (scPagwas), and TARGET data were analyzed for differentially expressed genes. Bayesian deconvolution of trait-related subpopulations was performed to analyze the association between differences in convoluted cellular fractions, survival, and clinical traits. Further analysis of the association of convoluted cellular fractions with various immune-related gene sets with immunotherapy. Core gene validation survival, function, and correlation analysis of a convolutional cell-based screen for neuroblastoma. Summary-data-based Mendelian Randomization (SMR) was used to further validate the core genes. Results: T cell subpopulation is strongly associated with multiple features in neuroblastoma. The convoluted cellular fractions obtained from this cell subpopulation also correlate with several features of neuroblastoma and can predict response to immunotherapy. Core genes from convoluted cell-based screens have been associated with a variety of traits including survival and cell function in neuroblastoma. Conclusions: , could play a central role in neuroblastoma development.
Source: Journal of Cancer
DOI: 10.7150/jca.138740
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,337
Funder: Midwestern University
OpenAlex ID: W7214650880