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Poster Display session

49P - An 8-spliceosome related genes (SRGs) risk signature to predict survival outcomes in adrenocortical carcinoma (ACC)

Date

21 Mar 2025

Session

Poster Display session

Presenters

Mohammed Hashki

Citation

Annals of Oncology (2025) 10 (suppl_3): 1-7. 10.1016/esmoop/esmoop104347

Authors

M.K. Hashki1, I. Alfarrajin2, M. Barbarawi3, M. Bani Baker4, O. Al-Qaqa4, A. Mistarihi4, M. Rababa4, M. Alasadi1, A. Abdulkareem1, S. Alhushki5

Author affiliations

  • 1 Faculty Of Medicine, JUST - Jordan University of Science and Technology, 22110 - Irbid/JO
  • 2 Department Of Medicine, Saint Agnes Hospital, 21229 - Baltimore/US
  • 3 Gme Internal Medicine, DHR Health, 78539 - Edinburg/US
  • 4 Faculty Of Medicine, Mutah University, 61710 - Al-Karak/JO
  • 5 Division Of Hematology And Oncology, University of Alabama at Birmingham, 35233 - Birmingham/US

Resources

This content is available to ESMO members and event participants.

Abstract 49P

Background

The spliceosome plays an important role in mRNA splicing and is aberrantly expressed in many malignancies. Herein, we study the association between SRGs, survival outcomes, and clinical features of patients with ACC.

Methods

Genetic and clinical data of 79 ACC patients were obtained from TCGA, with gene expression data of 274 normal adrenal gland samples retrieved from the Genotype Tissue Expression database. GEO studies (GSE3337, GSE10927) with 47 ACC patients served as validation cohorts. Differential expression analysis was performed between ACC and normal tissues, and the resulting differentially expressed genes (DEGs) were intersected with 127 SRGs obtained from the molecular signature database. Intersecting the DEGs with SRGs identified the differentially expressed SRGs, which were analyzed via uni- and multivariate Cox models to identify survival predictors. The risk score was calculated by multiplying the expression level of each significant gene by its hazard regression coefficient and summing the values across all significant genes. Kaplan-Meier analysis and log-rank tests correlated the risk score with overall survival (OS), progression-free survival (PFS), and disease-specific survival (DSS). Time-dependent ROC curves evaluated prognostic performance at 1, 3, and 5-year intervals. Pearson’s Chi-squared and Wilcoxon rank sum tests correlated risk groups with clinical features.

Results

Eight SRGs (SNRPG, SNRPD1, HNRNPA1, LSM4, HSPA2, ALYREF, SF3A2, and SLU7) were identified as independent predictors of survival. The median of the risk score stratified patients into High (n=40) and Low (n=39) risk groups. The low risk group had superior OS, PFS, and DSS (p= 0.0005, p= 0.0002, p=0.0006) respectively. Time dependent-ROC curves showed the risk score had higher AUCs for 1- and 3-year OS prediction (AUC:0.80, 0.88). The high risk group had higher TMB values (p<0.05) but no significant differences in other clinical variables. Validation cohorts provided consistent results with low-risk group (n=22) showing better OS (p = 0.00088).

Conclusions

Our findings highlight the association between SRGs and survival outcomes in ACC, supporting the utility of a SRGs risk signature to predict survival in this disease.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

The authors.

Funding

Has not received any funding.

Disclosure

All authors have declared no conflicts of interest.

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