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Updated: Sep 10, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
The changes of immune function after neuroblastoma chemotherapy and the prediction of potential immune targets
Yunfei Ma1, Yan Su2, Jing Huang3
1Department of Traditional Chinese Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, 56 Nanlishi Lu Xicheng District, Beijing, 100045, China.
Background:
High-dose chemotherapy for neuroblastoma is often intolerable for children, and its effectiveness is difficult to determine. Immunotherapy has become a popular research focus as a potential treatment. Therefore, identifying effective immune targets and drug synergistic chemotherapy against neuroblastoma is crucial.
Methods:
We conducted proteomics exploratory analysis of urine from 12 neuroblastoma before and after chemotherapy. The immune-related differential proteins before and after chemotherapy were obtained through differential expression analysis and dynamic expression model analysis. The ESTIMATE and ssGSEA analyses used indirectly infer the characteristics of the immune microenvironment. Gene ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted to reveal the biological functions of the candidate genes.
Results:
Immune analysis indicated that the immunosuppressive state in neuroblastoma patients caused by chemotherapy was closely related to CD8 T cells. Chemotherapy-associated differentially expressed proteins were significantly enriched in the mTOR signaling pathway. Neuroblastoma chemotherapy can significantly inhibit the expression of SEMA7A protein, and it is closely related to CD8T cell infiltration. Tetrachlorodibenzodioxin acting on SEMA7A was predicted using CTD databases.
Conclusions:
This study combines proteomics and bioinformatics to predict and explore potential immune targets for synergistic chemotherapy against neuroblastoma, providing a new direction for clinical treatment that warrant further validation.
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