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ePoster Display

1836P - Development of an autophagy-related gene expression signature for long term prognosis prediction in neuroblastoma patients

Date

16 Sep 2021

Session

ePoster Display

Topics

Clinical Research

Tumour Site

Presenters

Wenjuan Kang

Citation

Annals of Oncology (2021) 32 (suppl_5): S1237-S1256. 10.1016/annonc/annonc701

Authors

W. Kang1, J. Hu2, F. Song3, Q. Zhao4

Author affiliations

  • 1 Department Of Epidemiology And Biostatistics, Tianjin Medical University Cancer Institute and Hospital, 300000 - Tianjin/CN
  • 2 Pediatrcs Oncology, Tianjin Medical University Cancer Institute & Hospital, 300011 - Tianjin/CN
  • 3 Department Of Epidemiology And Biostatistics, Tianjin Medical University Cancer Institute & Hospital, 300000 - Tianjin/CN
  • 4 Pediatrcs Oncology, Tianjin Medical University Cancer Institute & Hospital, 300000 - Tianjin/CN

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Abstract 1836P

Background

Neuroblastoma is one of the most malignant tumors in children. Autophagy-related genes (ARGs) play an essential role in neuroblastoma, but the expression signature has rarely been investigated in prognosis. We aimed to identify and assess prognostic ARGs signature to predict overall survival (OS) in the patients.

Methods

234 ARGs were obtained from The Human Autophagy Database. Differentially expressed ARGs were identified based on Therapeutically Applicable Research To Generate Effective Treatments database. Bioinformatics analysis using the Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes platforms was performed. The Lasso cox regression analysis was performed to screen hub prognostic ARGs for overall survival, hub genes were used to calculate the risk score of each patient. The prognostic nomogram based on risk score and clinical factors was constructed. its performance was evaluated by receiver operating characteristic (ROC), and calibration curves. Finally, we prepared a Shiny R application to automatically calculate the predicted OS rate.

Results

The OS-related prognostic model was constructed based on 4 ARGs (VTN, EXOC4, BIRC5, CFTR) and significantly stratified patients into high- and low-risk groups in terms of OS (P < 0.001). The area under the curve of the model were 0.7 in 3- year survival, 0.672 in 5- year survival, 0.819 in 10- year survival. Risk score based on the expression of 4 hub genes and 3 clinical factors (DNA ploidy, INSS stage and MKI index) were identified as significant prognostic factors (P < 0.001). A nomogram was constructed by the above 4 poor factors, the calibration curves showed optimal agreement between the probability as predicted by the nomogram and the actual probability. A interactive online shiny website was constructed finally.

Conclusions

Our ARGs based prediction model is a reliable prognostic and predictive tool for long term overall survival in neuroblastoma.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Tianjin Medical University Cancer Institute and Hospital.

Funding

National Key R&D Program of China.

Disclosure

All authors have declared no conflicts of interest.

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