The precise cellular identity and molecular features of non-myocytes (non-CMs) in a mammalian heart at a single-cell level remain elusive. Depiction of epigenetic landscape with transcriptomic signatures using the latest single-cell multi-omics has the potential to unravel the molecular programs underlying the cellular diversity of cardiac non-myocytes. Here, we characterized the molecular and cellular features of cardiac non-CM populations in the adult murine heart at the single-cell level. Through single-cell dual omics analysis, we mapped the epigenetic landscapes, characterized the transcriptomic profiles and delineated the molecular signatures of cardiac non-CMs in the adult murine heart. Distinct cis-regulatory elements and trans-acting factors for the individual major non-CM cell types (endothelial cells, fibroblast, pericytes, and immune cells) were identified. In particular, unbiased sub-clustering and functional annotation of cardiac fibroblasts (FBs) revealed extensive FB heterogeneity and identified FB sub-types with functional states related to the cellular response to stimuli, cytoskeleton organization, and immune regulation, respectively. We further explored the function of marker genes Hsd11b1 and Gfpt2 that label major FB subpopulations and determined the distribution of Hsd11b1+ and Gfp2+ FBs in murine healthy and diseased hearts. In summary, we characterized the non-CM cellular identity at the transcriptome and epigenome levels using single-cell omics approaches and discovered previously unrecognized cardiac fibroblast subpopulations with unique functional states.

Direct reprogramming of fibroblasts to alternative cell fates by forced expression of transcription factors offers a platform to explore fundamental molecular events governing cell fate identity. The discovery and study of induced cardiomyocytes (iCMs) not only provides alternative therapeutic strategies for heart disease but also sheds lights on basic biology underlying CM fate determination. The iCM field has primarily focused on early transcriptome and epigenome repatterning, whereas little is known about how reprogramming iCMs remodel, erase, and exit the initial fibroblast lineage to acquire final cell identity. Here, we show that autophagy-related 5 (Atg5)–dependent autophagy, an evolutionarily conserved self-digestion process, was induced and required for iCM reprogramming. Unexpectedly, the autophagic factor Beclin1 (Becn1) was found to suppress iCM induction in an autophagy-independent manner. Depletion of Becn1 resulted in improved iCM induction from both murine and human fibroblasts. In a mouse genetic model, Becn1 haploinsufficiency further enhanced reprogramming factor–mediated heart function recovery and scar size reduction after myocardial infarction. Mechanistically, loss of Becn1 up-regulated Lef1 and down-regulated Wnt inhibitors, leading to activation of the canonical Wnt/β-catenin signaling pathway. In addition, Becn1 physically interacts with other classical class III phosphatidylinositol 3-kinase (PI3K III) complex components, the knockdown of which phenocopied Becn1 depletion in cardiac reprogramming. Collectively, our study revealed an inductive role of Atg5-dependent autophagy as well as a previously unrecognized autophagy-independent inhibitory function of Becn1 in iCM reprogramming.

Objectives: To predict CTLA4 expression levels and prognosis of clear cell renal cell carcinoma (ccRCC) by constructing a computed tomography‐based radiomics model and establishing a nomogram using clinicopathologic factors.Methods: The clinicopathologic parameters and genomic data were extracted from 493 ccRCC cases of the Cancer Genome Atlas (TCGA)‐KIRC database. Univariate and multivariate Cox regression and Kaplan–Meier analysis were performed for prognosis analysis. Cibersortx was applied to evaluate the immune cell composition. Radiomic features were extracted from the TCGA/the Cancer Imaging Archive (TCIA) (n = 102) datasets. The support vector machine (SVM) was employed to establish the radiomics signature for predicting CTLA4 expression. Receiver operating characteristic curve (ROC), decision curve analysis (DCA), and precision‐recall curve were utilized to assess the predictive performance of the radiomics signature. Correlations between radiomics score (RS) and selected features were also evaluated. An RS‐based nomogram was constructed to predict prognosis.Results: CTLA4 was significantly overexpressed in ccRCC tissues and was related to lower overall survival. A higher CTLA4 expression was independently linked to the poor prognosis (HR = 1.458, 95% CI 1.13–1.881, p = 0.004). The radiomics model for the prediction of CTLA4 expression levels (AUC = 0.769 in the training set, AUC = 0.724 in the validation set) was established using seven radiomic features. A significant elevation in infiltrating M2 macrophages was observed in the RS high group (p < 0.001). The predictive efficiencies of the RS‐based nomogram measured by AUC were 0.826 at 12 months, 0.805 at 36 months, and 0.76 at 60 months.Conclusions: CTLA4 mRNA expression status in ccRCC could be predicted noninvasively using a radiomics model based on nephrographic phase contrast‐enhanced CT images. The nomogram established by combining RS and clinicopathologic factors could predict overall survival for ccRCC patients. Our findings may help stratify prognosis of ccRCC patients and identify those who may respond best to ICI‐based treatments.

Transplantation of stem cell–derived retinal pigment epithelial (RPE) cells is considered a viable therapeutic option for age-related macular degeneration (AMD). Several landmark Phase I/II clinical trials have demonstrated safety and tolerability of RPE transplants in AMD patients, albeit with limited efficacy. Currently, there is limited understanding of how the recipient retina regulates the survival, maturation, and fate specification of transplanted RPE cells. To address this, we transplanted stem cell–derived RPE into the subretinal space of immunocompetent rabbits for 1 mo and conducted single-cell RNA sequencing analyses on the explanted RPE monolayers, compared to their age-matched in vitro counterparts. We observed an unequivocal retention of RPE identity, and a trajectory-inferred survival of all in vitro RPE populations after transplantation. Furthermore, there was a unidirectional maturation toward the native adult human RPE state in all transplanted RPE, regardless of stem cell resource. Gene regulatory network analysis suggests that tripartite transcription factors ( FOS , JUND , and MAFF ) may be specifically activated in posttransplanted RPE cells, to regulate canonical RPE signature gene expression crucial for supporting host photoreceptor function, and to regulate prosurvival genes required for transplanted RPE’s adaptation to the host subretinal microenvironment. These findings shed insights into the transcriptional landscape of RPE cells after subretinal transplantation, with important implications for cell-based therapy for AMD.

(1) Background: Intravitreal anti-vascular endothelial growth factor (anti-VEGF) is an established treatment for center-involving diabetic macular edema (ci-DME). However, the clinical response is heterogeneous. This study investigated miRNAs as a biomarker to predict treatment response to anti-VEGF in DME. (2) Methods: Tear fluid, aqueous, and blood were collected from patients with treatment-naïve DME for miRNA expression profiling with quantitative polymerase chain reaction. Differentially expressed miRNAs between good and poor responders were identified from tear fluid. Bioinformatics analysis with the miEAA tool, miRTarBase Annotations, Gene Ontology categories, KEGG, and miRWalk pathways identified interactions between enriched miRNAs and biological pathways. (3) Results: Of 24 participants, 28 eyes received bevacizumab (15 eyes) or aflibercept (13 eyes). Tear fluid had the most detectable miRNA species (N = 315), followed by serum (N = 309), then aqueous humor (N = 134). MiRNAs that correlated with change in macular thickness were miR-214-3p, miR-320d, and hsa-miR-874-3p in good responders; and miR-98-5p, miR-196b-5p, and miR-454-3p in poor responders. VEGF-related pathways and the angiogenin-PRI complex were enriched in good responders, while transforming growth factor-β and insulin-like growth factor pathways were enriched in poor responders. (4) Conclusions: We reported a panel of novel miRNAs that provide insight into biological pathways in DME. Validation in larger independent cohorts is needed to determine the predictive performance of these miRNA candidate biomarkers.