Analysis of transcriptomic patterns in a dilated cardiomyopathy (DCM) dataset and pan-cancer data only for descriptive context did not establish ferroptosis as a causal mechanism, biomarker, or treatment target in primary HHD.
Abstract
Background and Aims Ferroptosis-related pathways have been implicated in cardiovascular remodeling and cancer, but their relevance to hypertensive heart disease (HHD) remains uncertain. This study examined transcriptomic patterns in a dilated cardiomyopathy (DCM) dataset and used pan-cancer data only for descriptive context; it did not analyze primary HHD tissue. Methods GSE183852 data were restricted to the explicitly identified non-diseased sample H_ZC-11-292 (8,749 cells) and DCM sample HDCM1 (7,202 cells). H_ZC-LVAD-1 was excluded because GEO metadata classify it as DCM. Full-rank cell-level Wilcoxon results were retained, with all single-cell tests treated as descriptive. GSE5406 groups were assigned from GEO sample titles (194 failing and 16 non-failing myocardium samples), and TCGA data were used for descriptive pan-cancer context. GPX4, SLC7A11, ACSL4, and TFRC mRNA were assessed by RT-qPCR in Ang II-stimulated H9c2 cells. Results Fourteen cluster-derived cell categories were retained. Cardiomyocytes, macrophages, and endothelial cells were not detected in the selected DCM donor, so no condition-specific inference was made for those categories. Among 109 detected ferroptosis-related genes, 60 met the cell-level up threshold, 24 met the down threshold, and 25 were nonsignificant; these counts are not donor-level evidence. In GSE5406, 5 of 99 tested ferroptosis-related genes met |log2FC| > 0.5 and BH-adjusted p < 0.05. Fold changes for 96 detected genes were uncorrelated across platforms (r = 0.034, p = 0.740). RT-qPCR showed lower GPX4 and SLC7A11 and higher ACSL4 and TFRC mRNA, with gene- and context-specific directionality (Supplementary Table S1). Conclusion The analyses identify exploratory, donor- and context-dependent transcriptional patterns. They do not establish ferroptosis as a causal mechanism, biomarker, or treatment target in primary HHD. Multi-donor disease-specific cohorts and protein-level and functional experiments are required.
This study identifies Acot1 and Txnip as ferroptosis-related molecular signatures in DCM and provides multistep prioritization and validation spanning bulk transcriptomics, single-cell and spatial transcriptomics, and in vivo experimental verification, offering potential targets for ferroptosis-targeted therapeutic int...
Feng Zhou, Jia-Bin Zhou, Ling Zhang et al.· Current Issues in Molecular...· 0 citations
FDR-supported candidate-level evidence linking macrophage- and ferroptosis-related transcriptional alterations to immune signatures in MI is provided and warrant further validation in larger cohorts and mechanistic studies.
Guo-Qin Wang, Zhulin Zhang, Guan-Rui Yang et al.· PLoS ONE· 0 citations
Background Ferroptosis contributes to myocardial ischemia/reperfusion injury (MIRI), but time-stable ferroptosis-related transcriptional features across reperfusion stages and their links to peripheral immune profiles remain unclear. This study aimed to identify time-stable ferroptosis-related candidates in MIRI using...
Rong Huang, Jun Wang, Jun-Chen He et al.· Journal of Inflammation Rese...· 0 citations
Network pharmacology nominates targets but cannot show that they are altered in the relevant cell, distinguishable from a hypothesis-free analysis of the same data, or linked to disease. Taking the candidates nominated for Yangxin Decoction in dilated cardiomyopathy (DCM) and viral myocarditis, we asked how many surviv...
Objectives: This study aimed to identify ferro-aging-related hub genes in chronic kidney disease (CKD) and elucidate their potential roles in proximal tubular (PT) cells. Methods: Differential expression analysis was performed using GSE104954, and the differentially expressed genes were intersected with a set of ferro-...
Bin Xia, Ru-Jie Zhou, Jiang-Long Chen et al.· Biomedicines· 0 citations
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.