(S-040) Time-to-event analysis of iron homeostasis to inform survival in cancer patients

Xiaoqing Fan – School of Pharmacy – The Chinese University of Hong Kong; Kangna Cao – School of Pharmacy – The Chinese University of Hong Kong; Xu Steven Xu – Clinical Pharmacology and Quantitative Science – Genmab Inc.; Xiaoyu Yan – School of Pharmacy – The Chinese University of Hong Kong

Objectives: Emerging evidence has demonstrated that cancer cells enhanced iron uptake and/or decreased iron efflux to increase the intracellular iron amount to support their increased demands of rapid division, and metastasis[1,2]. However, the quantitative relationship between iron homeostasis and cancer progression remains underexplored. Here, we aim to develop parametric time-to-event (TTE) models using the expression profile of the major proteins that control iron uptake and efflux to quantify the contribution of the expression level of these proteins on the outcome of cancer patients.

Methods: We first reviewed the major mediators for iron uptake or export in cancer[3-7]. We collected data from UALCAN, a comprehensive database that integrates publicly available cancer OMICS data[8]. The RNA expressions of the iron transport-related proteins in cancer patients were compared with the corresponding normal subjects from TCGA. To evaluate the impact of patient iron transport-related proteins expression level on the overall survival, TTE models were developed[9,10]. Visual predictive checks (VPCs) were compared. To exploit the potential of iron homeostasis profiles to predict long-term survival outcomes across cancers, we developed a cancer-specific iron risk score (CIRS) based on the TTE modeling results. We divided the patients into tertile groups based on stratified CIRS.

Results: We found that, at least 1 iron uptake protein, either transferrin receptor 1 (TFR1) or CD44, overexpressed, or the iron efflux protein ferroportin (FPN) was decreased, or both, in the analysis of cancer patients. TTE modeling results suggested that, an increase in TFR1 and CD44 raised the hazards of death, whereas higher FPN was beneficial for survival. These results are consistent with the findings that iron homeostasis alterations and cancer progression are interrelated. These results indicate that the expression of TFR1, CD44, and FPN has the clinical significance of prognostic biomarkers in response to cancer progression and predicted clinical outcomes. The VPCs stratified by cancer type showed good agreement between the observed data and model prediction, demonstrating acceptable predictive performance. The KM curves showed distinctive paths between the three risk groups stratified by CIRS across 15 cancers, individuals in the high-risk group had notably elevated risk of mortality.

Conclusions: This study provided useful insights to identify cancer patient subgroups at higher risk based on predefined CIRS using RNA-seq data, and guide optimal clinical interventions regarding the significant predictors, which would constitute a novel strategy for cancer diagnosis, staging, and lead to potential therapeutic strategies to target these tumor-specific events.

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[8] Chandrashekar DS, Karthikeyan SK, Korla PK, et al. UALCAN: An update to the integrated cancer data analysis platform. Neoplasia. Mar 2022;25:18-27.
[9] Holford N. A time to event tutorial for pharmacometricians. CPT Pharmacometrics Syst Pharmacol. May 15 2013;2(5):e43.
[10] Yao Y, Wang Z, Yong L, et al. Longitudinal and time-to-event modeling for prognostic implications of radical surgery in retroperitoneal sarcoma. CPT Pharmacometrics Syst Pharmacol. Sep 2022;11(9):1170-1182.

Keywords: Iron, time-to-event, cancer