Aug 2026· Omics· pp.
15578100261479258
· 0 citations· 21 references
Medicine
TL;DR
The results nominate testable macrophage regulatory and signaling hypotheses for HFpEF but do not establish drug-specific reversal or cross-model conservation.
Abstract
Heart failure with preserved ejection fraction (HFpEF) involves interacting immune, vascular, and stromal abnormalities. We asked whether macrophage genes showing opposite diet-associated and dapagliflozin-associated effects could identify regulatory and signaling programs relevant to HFpEF. Genes were ranked in a 2 × 2 × 2 dataset of sorted murine cardiac macrophages, and the locked signatures were evaluated in cardiac single-cell and single-nucleus datasets. Regulon analysis and network-constrained sensitivity testing identified BHLHE40 as the more robust program-level candidate. NFKB1, in turn, was linked to the broadest curated communication network, including TNF-, IL1B-, and PDGFB-related endothelial and fibroblast branches. External evidence varied across datasets and cell compartments. In myocardium from 19 HFpEF and 24 control donors, the CCR2- and cross-subset signatures were higher in macrophages, and the CCR2- signature was also higher in fibroblasts. PDGFB-related fibroblast branches received broader external evidence than the discovery-ranked TNF-TNFRSF1A endothelial branch, whose direction was not retained in human myocardium. These results nominate testable macrophage regulatory and signaling hypotheses for HFpEF but do not establish drug-specific reversal or cross-model conservation.
Background Postinfarction cardiac repair is orchestrated by macrophages that undergo sequential polarization from proinflammatory M1 to reparative M2 states. These macrophage subsets regulate inflammation resolution, angiogenesis, and fibrotic remodeling in the infarcted myocardium. Tumor‐associated macrophages (TAMs) in breast cancer share transcriptional features with cardiac M2 macrophages, providing an opportunity for cross‐disease comparison of shared immune programs. Understanding the molecular programs common to reparative macrophages across pathological contexts may identify candidate regulatory nodes for future therapeutic investigation. Methods Single‐cell RNA sequencing data were obtained from GEO: GSE136088 (murine post‐AMI cardiac macrophages), GSE176078 and GSE167036 (human primary breast cancer). Analyses included quality control, UMAP/t‐SNE dimensionality reduction, graph‐based clustering, diffusion pseudotime trajectory reconstruction, ligand‐receptor communication analysis, principal component analysis, and cross‐dataset correlation analysis. All analyses were performed in Python using scanpy with cross‐species ortholog mapping in R (biomaRt, 14,892 one‐to‐one mouse‐human orthologs) with downstream analyses in Python (scanpy). Results Post‐QC datasets (GSE136088: ~14,900 cells; GSE176078: 100,064 cells; and GSE167036: 49,141 cells) were analyzed. UMAP and t‐SNE resolved multiple macrophage and immune subpopulations across all three datasets. Diffusion pseudotime analysis reconstructed a sequential activation trajectory with an M1/M2 fate bifurcation. A 7‐gene coexpression module (Spp1, Mif, Tgfb1, Arg1, Il10, Tnf, and Mrc1) was identified in cardiac macrophages and showed partially conserved expression patterns in breast cancer macrophage populations (GSE176078: Pearson r = 0.72; GSE167036: 6 of 7 genes detected, ARG1 not detected). Ligand‐receptor communication analysis identified MIF‐ACKR3, SPP1‐CD44, and TGFB1‐TGFBR2 as shared ligand‐receptor pairs mediating macrophage‐stromal communication in both cardiac and tumor microenvironments. Cross‐dataset Pearson correlation of the 7‐gene module between cardiac macrophages and breast cancer macrophage populations reached r = 0.72 (GSE176078) and r = −0.07 (GSE167036, n.s.). Conclusion This single‐cell transcriptomic analysis characterizes macrophage polarization programs in postinfarction cardiac repair and evaluates their partial conservation in breast cancer. The identified 7‐gene module showed moderate cross‐dataset correlation with GSE176078 (r = 0.72) but was not replicated in GSE167036, where M2‐polarized macrophages were not detected. The MIF‐ACKR3 signaling axis represents a computationally derived hypothesis for future experimental validation. These findings highlight both shared features and context‐dependent differences in macrophage polarization across disease states, underscoring the need for functional studies in paired cardiac and tumor models.
Baobao Liu, Fu Liang· International Journal of Gen...· 0 citations
BACKGROUND
Chronic transplant arteriosclerosis is the primary cause of long-term graft failure. Selectively targeting specific inflammatory macrophage subpopulations is essential for inhibiting the primary triggers of inflammatory and immune responses. Therefore, elucidating the origins and regulatory mechanisms of these macrophages in allograft arteriosclerosis is key for the development of targeted therapies.
METHODS
We performed single-cell RNA sequencing and spatial transcriptomics or integrated transcriptomic data from human chronic allograft vasculopathy specimens and mouse vascular allograft models. Flow cytometry and immunofluorescence staining were used to characterize macrophage subpopulations within remodeled allograft arteries. To determine cellular origins, CD34+ lineage tracing and depletion strategies were used. The interactions among COL1A1 (collagen type 1 α1), CD44, and SLC7A11 (solute carrier family 7 member 11) were analyzed using proximity ligation assays and coimmunoprecipitation. Furthermore, metabolic profiles were investigated with ultraperformance liquid chromatography coupled with high-resolution mass spectrometry. To validate the role of cystine transport in macrophage differentiation, we used pharmacologic inhibitors and a genetic approach using myeloid-specific Slc7a11 knockout mice (Lysm-Slc7a11-KO). The mechanisms identified in vivo were further corroborated through in vitro experiments.
RESULTS
We identified a novel proinflammatory foam-like macrophage phenotype in allograft arterial adventitia. These macrophages primarily originated from bone marrow-derived CD34+ lineage cells and exhibit heightened de novo lipogenesis and proinflammatory activity. Their lipogenesis is driven by increased cystine uptake, facilitated by enhanced membrane expression of the CD44-SLC7A11 complex, which activates mTORC1 (mechanistic target of rapamycin complex 1)-HIF-1α (hypoxia-inducible factor 1α) signaling. We also revealed that fibroblast-secreted COL1A1 is essential for anchoring the complex to the cell membrane through its direct interaction with CD44. Blocking COL1A1, CD44, or SLC7A11 effectively attenuated mTORC1-HIF-1α signaling, inflammation, and lipogenesis in macrophages as well as accumulation of foam-like cells and intimal hyperplasia in allograft arteries.
CONCLUSIONS
This study has revealed previously uncharacterized foam-like macrophages in transplant arteriosclerosis, with COL1A1-enhanced amino acid metabolism modulating lipogenesis and foamy macrophage formation. This study offers potential therapeutic targets to modulate immune response and enhance transplant outcomes.
A systems-level framework is provided that transforms broad observations of inflammation into ranked therapeutic targets and support combined strategies aimed at blocking the IL-6/STAT3–myostatin/SMAD–FOXO1/3–MuRF1/Atrogin-1 axis to mitigate NSCLC-associated sarcopenia.
Gautam Kumar, Shailza Singh· Frontiers in Immunology· 0 citations
Objectives: Heart failure (HF) arises from multiple interrelated pathological processes. Among these, lysosomal impairment and loss of autophagic homeostasis are increasingly recognized as important contributors to myocardial damage and ventricular remodeling. This study sought to identify lysophagy-associated signature genes in HF and to define their biological roles, cellular origins, and potential diagnostic relevance. Methods: Bulk myocardial transcriptome datasets, including GSE16499, GSE57338, and GSE76701, were integrated with the human cardiac single-cell dataset GSE145154. Differential expression analysis was first performed to identify lysophagy-related differentially expressed genes (DEGs). Candidate hub genes were then screened using support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression. Functional enrichment analysis, Gene Set Enrichment Analysis (GSEA), immune infiltration assessment, single-cell transcriptomic mapping, and regulatory network analysis were subsequently conducted. The expression profiles of the selected genes were validated in a murine HF model, and VAMP8 overexpression assays were performed in H9c2 cells. Results: Five hub genes, namely VAMP8, STX2, MCOLN1, DERL1, and PTP4A2, were consistently and markedly decreased in failing myocardial tissue. These genes were mainly linked to SNARE-dependent vesicle trafficking and lysophagy regulation. A diagnostic model incorporating these hub genes demonstrated good discriminatory performance in both the training dataset and a small independent validation cohort, supporting further evaluation of their potential diagnostic value. Single-cell analysis further indicated that these genes were primarily enriched in cardiac FOLR2+ tissue-resident macrophages (TRMs). Pseudotime and cell–cell communication analyses associated this module with FOLR2+ TRM cell states and predicted interactions with cardiac stromal cells. In the HF mouse model, the mRNA levels of all five hub genes were decreased, with concurrent reductions in VAMP8, MCOLN1 and DERL1 protein expression. In Ang II/LLOMe-induced H9c2 cells, VAMP8 overexpression was associated with reduced cardiomyocyte injury, attenuation of changes in the abundance of lysosome- and autophagy-related proteins, and fewer ultrastructural abnormalities, suggesting a potential cardioprotective effect. Conclusions: VAMP8, STX2, MCOLN1, DERL1, and PTP4A2 were identified as candidate molecular markers of HF that reflect alterations in a lysophagy- and vesicular-transport-related program associated with FOLR2+ tissue-resident macrophages. These findings provide new insights into immune-microenvironment remodeling in HF and suggest potential directions for mechanistic and therapeutic investigations.
Qi Cheng, Yan-Li Wang, De-Qiang Wang et al.· Genes· 0 citations
Background: FIBP has been linked to adverse acute myeloid leukemia (AML) features, but whether its expression identifies a ferroptosis-related biological state is unknown. We evaluated the association of FIBP with iron handling, lipid-peroxidation defense, immune signatures, and survival while explicitly separating association from causal mechanism.
Methods: The KEGG ferroptosis pathway was compared with the STRING first-shell FIBP network. Legacy TCGA-LAML RNA-sequencing data were analyzed in 173 samples after log2(RSEM+1) transformation. Eleven prespecified genes covering iron homeostasis, antioxidant defense, lipid remodeling, and mitochondrial function were compared across median-defined FIBP groups and correlated with continuous FIBP expression. Marker-derived regulatory T-cell (Treg) and M2-like macrophage scores were examined exploratorily. A ferroptosis sensitivity score was defined as mean Z(TFRC, SLC11A2, ACSL4, LPCAT3) minus mean Z(FTH1, GPX4, AIFM2, DHODH). Overall survival was analyzed in 149 matched patients using Kaplan-Meier estimates, log-rank tests, 3-year restricted mean survival time (RMST), continuous-variable Cox models with proportional-hazards diagnostics, bootstrap-corrected C-index, and time-dependent area under the curve (AUC).
Results: The strict STRING and KEGG sets had no direct gene overlap. Four target genes were higher in FIBP-high AML after transcriptome-wide false-discovery correction: FTH1, GPX4, AIFM2/FSP1, and LPCAT3. FIBP correlated positively with GPX4 (rho=0.619), FTH1 (rho=0.512), LPCAT3 (rho=0.502), and AIFM2 (rho=0.285), and negatively with SLC11A2 (rho=-0.220) and ACSL4 (rho=-0.196). The global FIBP-M2 association was nominal (rho=0.157; P=0.039) but did not remain significant after correction across the two immune scores (q=0.077); the Treg association was not reproduced. Survival differed among low-FIBP, high-FIBP/high-score, and high-FIBP/low-score groups (log-rank P<0.001). Three-year RMST was 729, 492, and 448 days, respectively; the two high-FIBP groups did not differ (RMST difference -44 days; bootstrap 95% CI, -236 to 137). Continuous FIBP remained associated with mortality after adjustment for the score and age (hazard ratio per SD, 1.420; 95% CI, 1.119-1.803; P=0.004), whereas the score was not independently associated (P=0.657). Adding the score did not improve the FIBP-only C-index (0.637 vs 0.636; delta 0.0008, bootstrap 95% CI, -0.0470 to 0.0014).
Conclusions: High FIBP expression is associated with an iron-buffering and antioxidant transcriptional phenotype and adverse survival in AML, but the current data do not demonstrate direct FIBP control of ferroptosis or independent prognostic value of the proposed sensitivity score. GPX4-, FSP1-, and ferritin-centered defenses are testable biological hypotheses rather than established therapeutic indications.
Meng Tang, Jianxin Guo· World Journal of Advanced Re...· 0 citations
Background Diabetes markedly increases the risk of heart failure, yet the molecular signals connecting metabolic stress, myocardial fibrosis, and impaired cardiac repair remain incompletely understood. Methods We integrated bulk transcriptomic data from postischemic hearts (GSE26887), fibrosis‐related genes from the CTD database, protein–protein interaction (PPI) analysis, and pathway enrichment (GO, KEGG, GSEA, and GSVA) to identify candidate mediators in diabetic versus nondiabetic heart failure. Single‐cell RNA‐sequencing datasets were analyzed with Seurat to map the cellular distribution of key genes. Pan‐cancer analyses using TCGA cohorts were performed to evaluate prognostic, immune, and tumor mutation burden (TMB) correlations. Mechanistic validation was conducted in human cardiac progenitor cells (CPCs) exposed to normoglycemia or high glucose with S100A9 knockdown or overexpression, recombinant S100A8/A9, and a neutralizing S100A9 antibody. Cell viability (CCK‐8); qPCR panels for fibrosis, inflammation, and metabolic genes; ROS production (DCF‐DA and MitoSOX); and mitochondrial respiration were quantified. Results Differential expression and PPI network analyses identified S100A8 as a fibrosis‐related hub specifically enriched in diabetic heart failure. Single‐cell mapping revealed predominant S100A8 expression in CPCs rather than mature cardiomyocytes. Pathway analyses linked S100A8 to collagen fibril organization, ECM–receptor interaction, oxidative phosphorylation, and fatty acid β‐oxidation. Functionally, high glucose upregulated S100A8/S100A9 and profibrotic and proinflammatory genes in CPCs, increased total and mitochondrial ROS, and reduced basal, ATP‐linked, and maximal respiration and spare capacity. S100A9 knockdown partially restored CPC proliferation, redox balance, and mitochondrial function, whereas S100A9 overexpression or recombinant S100A8/A9 further exacerbated oxidative stress and bioenergetic failure; S100A9 neutralization attenuated these effects. Pan‐cancer analyses showed that high S100A8 expression was associated with adverse prognosis, altered immune infiltration, and increased TMB in several TCGA cohorts. Conclusions S100A8/S100A9 emerges as a central mediator linking hyperglycemia‐induced oxidative stress, metabolic inflexibility, and fibrotic reprogramming of CPCs, thereby promoting diabetic heart failure. S100A8/S100A9 may serve as a biomarker and therapeutic target at the interface of immunometabolism, cardiac regeneration, and cardio‐oncology.