Integrated Multi-Omics Analyses Identify Core Determinants Governing Newcastle Disease Virus Oncolytic Therapy Efficacy Under Tumor Heterogeneity

Newcastle disease virus (NDV) is a promising oncolytic virus, but tumor heterogeneity constrains its clinical translation. The key determinants driving variable NDV oncolytic potency amid tumor heterogeneity remain incompletely elucidated. The main scope of this study included analyzing 22 human cancer cell lines representing 11 tumor types and identifying five gene co-expression modules associated with NDV susceptibility through weighted gene co-expression network analysis. Integrative multi-omics analyses of NDV-infected HCT116 cells, the least-susceptible cell line in our panel, predicted metabolic processes, innate immune defenses, and multiple forms of cell death as candidate pathways modulating NDV oncolytic efficacy. These key bioinformatic findings were further validated by genome-wide CRISPR-Cas9 screening, which uncovered POLR2G and SREBF1 as central components of the pro-oncolytic network and TNFRSF1A, TNFAIP3, and CASP9 as core mediators of the anti-oncolytic network. Their functional roles were further verified via genetic manipulation and pharmacological perturbation of JAK-STAT, TLR4, and apoptotic signaling. In conclusion, our findings support a bidirectional model wherein host metabolic programs promote NDV replication and oncolysis, whereas antiviral-innate immune signaling restricts them, providing candidate targets for host-directed combination therapy amid tumor heterogeneity.

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Journal
Microorganisms
Published
2026-09-24
DOI
https://doi.org/10.3390/microorganisms14102156
Primary Topic
Virus-based gene therapy research
Type
article
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article

Integrated Multi-Omics Analyses Identify Core Determinants Governing Newcastle Disease Virus Oncolytic Therapy Efficacy Under Tumor Heterogeneity

Shufeng Feng, Changbo Ou, Hongchun Yang, Xuefeng Li et al.
Microorganisms
Virus-based gene therapy research
article

Integrated Multi-Omics Analyses Identify Core Determinants Governing Newcastle Disease Virus Oncolytic Therapy Efficacy Under Tumor Heterogeneity

Shufeng Feng, Changbo Ou, Hongchun Yang, Xuefeng Li, Hai Li, Lu Cui, Yongxin Zhu, Huimin Duan
article en

Abstract

Newcastle disease virus (NDV) is a promising oncolytic virus, but tumor heterogeneity constrains its clinical translation. The key determinants driving variable NDV oncolytic potency amid tumor heterogeneity remain incompletely elucidated. The main scope of this study included analyzing 22 human cancer cell lines representing 11 tumor types and identifying five gene co-expression modules associated with NDV susceptibility through weighted gene co-expression network analysis. Integrative multi-omics analyses of NDV-infected HCT116 cells, the least-susceptible cell line in our panel, predicted metabolic processes, innate immune defenses, and multiple forms of cell death as candidate pathways modulating NDV oncolytic efficacy. These key bioinformatic findings were further validated by genome-wide CRISPR-Cas9 screening, which uncovered POLR2G and SREBF1 as central components of the pro-oncolytic network and TNFRSF1A, TNFAIP3, and CASP9 as core mediators of the anti-oncolytic network. Their functional roles were further verified via genetic manipulation and pharmacological perturbation of JAK-STAT, TLR4, and apoptotic signaling. In conclusion, our findings support a bidirectional model wherein host metabolic programs promote NDV replication and oncolysis, whereas antiviral-innate immune signaling restricts them, providing candidate targets for host-directed combination therapy amid tumor heterogeneity.

MicroorganismsVol. 14(10)
Guangxi University (CN), Second Affiliated Hospital of Xi'an Jiaotong University (CN), Xi'an Jiaotong University (CN)
Good health and well-being
Openalex Percentile: Top 12%
Virus-based gene therapy research
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Integrated Multi-Omics Analyses Identify Core Determinants Governing Newcastle Disease Virus Oncolytic Therapy Efficacy Under Tumor Heterogeneity — Shufeng Feng, Changbo Ou, et al. · Microorganisms (2026) | TGRS Research Map | TGRS