Abstract
Accumulating studies have highlighted the biologic significances of ferroptosis modification in tumor progression, but little is known whether ferroptosis modification patterns have potential roles in tumor microenvironment (TME) immune cell infiltration of hepatocellular carcinoma (HCC). In this study, we evaluated 51 ferroptosis regulators and performed consensus clustering algorithm to determine ferroptosis modification patterns and the ferroptosis related gene signature in HCC. Gene set variation analysis (GSVA) was employed to explore biological molecular variations in distinct ferroptosis modification patterns. Single sample gene set enrichment analysis (ssGSEA) algorithm was performed to quantify the relative infiltration levels of various immune cell subsets. Principal component analysis (PCA) algorithm was used to construct the ferroptosisSig score to quantify ferroptosis modification patterns of individual tumors with immune responses. Three distinct ferroptosis modification patterns were identified. GSVA enrichment analysis indicated that three ferroptosis modification subgroups were enriched in different metabolic pathways. ssGSEA analysis determined that 19 of 24 immune infiltrating cells had significant differences in three distinct ferroptosis patterns. A 91-ferroptosis gene signature was constructed to stratify patients into two ferroptosisSig score groups. Patients in the higher ferroptosisSig score were characterized by significantly prolonged survival time compared with patients in the lower ferroptosisSig score group (p < .0001). An immunotherapy cohort confirmed patients with higher ferroptosisSig score determined significant therapeutic advantages and clinical benefits. Receiver operating characteristic (ROC) curve analysis confirmed the predictive capacity of anti-PD/L1 immunotherapy by ferroptosisSig score. Our study indicated the ferroptosis modification played a significant role in TME heterogeneity and complexity. Evaluating the ferroptosis modification pattern of individual tumor could strengthen our cognition of TME infiltration characteristics and guide more effective clinic immunotherapy strategies.
Highlights
Ferroptosis is a novel discovered type of non-apoptotic-regulated programmed cell death induced by the iron-dependent accumulation of lipid reactive oxygen species (ROS) of metabolic dysfunctions (Dixon et al, 2012)
We identified the roles of 51 ferroptosis regulatory genes in Hepatocellular carcinoma (HCC)
Further analysis showed that most of ferroptosis regulators such as ACSL4, EMC2, HSPB1, G6PD, RPLB, and TFRC were significantly decreased in HCC samples compared to normal specimens, while only five ferroptosis regulators including PBEB1, STEAP3, NFE2L2, GOT1, and AOC1 were markedly increased in HCC patients indicating that the expression of ferroptosis regulators with copy number variation (CNV) alterations were the principal factors leading to disordered expressions of ferroptosis regulators (Figures 1C,F)
Summary
Ferroptosis is a novel discovered type of non-apoptotic-regulated programmed cell death induced by the iron-dependent accumulation of lipid reactive oxygen species (ROS) of metabolic dysfunctions (Dixon et al, 2012). Growing evidence indicated that dysregulated expression and genetic variations of FRGs were associated with the disorders of various biological process including tumor carcinogenesis, cell death and proliferation dysregulation, tumor progression and immunomodulatory abnormality (Yagoda et al, 2007; Yang et al, 2014; Sun et al, 2016; Hassannia et al, 2019). Plenty of phase I and II clinical trials suggest that immune-based therapies, such as antiPD-1/PD-L1/CTLA-4 monoclonal antibody strategies, could benefit the patients with HCC (Hilmi et al, 2019). HCC cells could induce various biological behavior changes through direct and indirect complex interactions with tumor microenvironment (TME) including inhibiting apoptosis, inducing proliferation as well as immune evasion. Comprehensive analyses of TME landscape heterogeneity and complexity might be helpful to identify different tumor immune-phenotypes and improve the ability to guide and predict immunotherapy responsiveness
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