Related Experiment Video
Updated: Sep 12, 2026
Genetic Profiling and Genome-Scale Dropout Screening to Identify Therapeutic Targets in Mouse Models of Malignant Peripheral Nerve Sheath Tumor
Published on: August 25, 2023
Integrative network toxicology and virtual knockout analysis suggest TSNA-associated molecular features in large cell
Zhe Xiong1, Liuzhe Yin1, Jiahui Yu1
1Hubei Key Laboratory of Economic Forest Germplasm Improvement and Resources Comprehensive Utilization, Hubei Collaborative Innovation Center for the Characteristic Resources Exploitation of Dabie Mountains, Huanggang Normal University, Huangzhou, 438000, China.
Objective:
Electronic nicotine delivery systems (ENDS) may contain or generate low levels of tobacco-specific nitrosamines (TSNAs), including N-nitrosoanatabine (NAT) and N-nitrosoanabasine (NAB), under certain thermal conditions. Given the uncertain long-term carcinogenic effects of ENDS, this study explored potential molecular associations between TSNA-related exposure signatures and LCNEC using an integrative computational framework.
Methods:
We integrated network toxicology, clinical transcriptomics (GSE1037), and single-cell RNA sequencing (GSE269942) to identify key targets. Protein-protein interaction (PPI) networks and hub genes were established. Interactions between TSNAs and hub targets were validated using molecular docking and 100-ns molecular dynamics (MD) simulations. Potential network-level perturbation effects were explored via scTenifoldKnk-based virtual knockouts (vKO), diagnostic ROC analysis, and CIBERSORT-based immune infiltration analysis.
Results:
Network analysis identified EGFR, CASP3, CCND1, STAT3, and SRC as central toxicological sensors, with MD simulations suggesting stable predicted interactions with NAT and NAB.The PI3K-Akt pathway emerged as a recurrently enriched pathway linking predicted TSNA targets with LCNEC-associated transcriptomic alterations. Single-cell profiling localized the transcriptomic reprogramming-characterized by IGFBP2 upregulation and EDNRB silencing-specifically to malignant LCNEC clusters. EDNRB (AUC=0.954) and IGFBP2 (AUC=0.855) demonstrated high diagnostic accuracy. vKO simulations suggested that IGFBP2 and EDNRB may be associated with network-level perturbations involving growth-related and immune-related genes.Drug screening anchored this signature to nicotine and prioritized EGFR-related inhibitors and natural compounds as hypothesis-generating candidates for further validation.
Conclusion:
This study proposes a hypothesis-generating computational model in which TSNA-associated target networks converge on PI3K-Akt-related signaling and the IGFBP2/EDNRB expression axis in LCNEC.These findings provide exploratory molecular evidence that may inform future experimental studies on TSNA-related lung cancer biology and potential biomarker discovery.