Abstract 4942: Unraveling a prognostic and predictive 8-gene signature related to cuproplasia in pan-cancer

Abstract This study aims at identifying a cuproplasia-related gene signature to predict outcome for cancer patients based on gene regulatory networks. Copper is a vital micronutrient involved in many biological processes. Copper influences tumor growth through a process called cuproplasia, defined as abnormal copper-dependent cell-growth and proliferation. Copper-chelation therapy targeting this process has demonstrated efficacy in several clinical trials against cancer. While the molecular pathways associated with cuproplasia are partially known, genetic heterogeneity across different cancer types has limited the understanding of how cuproplasia impacts patient survival. We proposed a novel framework based on gene regulatory networks to identify critical cuproplasia-related genes (CCGs) across different cancer types. Utilizing RNA-sequencing data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) datasets, we generated gene regulatory networks for 23 different cancer types. We applied a network control method to discover critical genes in these networks and combined with copper metabolism related genes to identify CCGs across 23 cancer types. We then performed a comprehensive analysis on the identified CCGs to better understand their potential roles and associations with cancer patient survival. We discovered 30 CCGs which were enriched in pathways related to a wide range of biological processes supporting cancer progression and immune evasion processes. The specific processes related to the identified CCGs include autophagy, cell cycle regulation, cell proliferation, kinase signaling pathways, immune infiltration, and immune checkpoint regulation. From this, we identified a novel 8-CCG signature significantly associated with survival pan-cancer, including CDK1, AP1S1, CASP3, MAP1LC3A, SNCA, TMPRSS6, MAPT, and GSK3B. Although some of these genes are known for their important roles in various malignancies and are associated with poor survival, this is the first study defining their connection with high copper levels in cancer cells. Furthermore, in keeping with previous studies that have used metal regulatory genes to predict outcomes in a specific cancer type, we specifically used low grade glioma (LGG), a cancer type highly impacted by intracellular copper level, as an example to explore the role of CCGs in a specific cancer type. Through our proposed gene regulatory network methodology, we identified a 3-gene signature that overlapped with a 6-gene prognostic risk score model for LGG patients. These 6 genes included ALB, CASP3, CDK1, CP, CYP1A1, and MT-CO1. To our knowledge, this is the first pan-cancer analysis for genes related to cuproplasia. The findings from our study highlight the use of gene regulatory networks to identify CCGs which could be used to develop novel targeted therapeutic strategies. Citation Format: Vu Viet Hoang Pham, Toni Jue, Jessica Bell, Fabio Luciani, Filip Michniewicz, Giuseppe Cirillo, Linda Vahdat, Chelsea Mayoh, Orazio Vittorio. Unraveling a prognostic and predictive 8-gene signature related to cuproplasia in pan-cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4942.