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Jialu Wang

Publications and source records attributed to Jialu Wang.

3 recordsLinked to original sources
PubMed2026

scRNA-seq and bulk RNA-seq reveal the characteristics of macrophage copper metabolism and establish a risk signature in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent malignancy with an urgent need for improved prognostic stratification and treatment-response prediction. This study aimed to explore a macrophage copper metabolism-associated prognostic model and to investigate the relationship between this risk model and the tumor immune microenvironment. METHODS: The FindClusters function was used to analyze cell clusters, and CellChat and CellPhoneDB/LIANA were employed for cell-cell communication analysis. Copper metabolism-related genes were sourced from the MSigDB database. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis, and a nomogram was constructed by integrating the prognostic model with clinicopathological factors. Additional analyses were performed to map the seven model genes in single-cell data, assess model uncertainty and robustness, evaluate macrophage/copper/cuproptosis-related transcriptional programs, and examine the correlations between risk score, immune infiltration and predicted drug sensitivity. RESULTS: Using single-cell RNA sequencing (scRNA-seq) data, we identified four macrophage subpopulations. Macrophages with high SPP1 expression showed close interaction with T cell populations and were associated with copper ion metabolism. By incorporating 141 copper metabolism-related genes and using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort, we constructed a seven-gene risk prediction model. Additional single-cell mapping showed that the model genes were detectable in the HCC single-cell dataset and showed a macrophage-associated expression pattern. The model showed moderate prognostic discrimination in TCGA-LIHC, whereas its external performance was heterogeneous and remained evaluable across external cohorts, with performance varying among datasets. Immune and mechanism-related analyses suggested that the risk signature was associated with macrophage-related infiltration, copper metabolism and cuproptosis-related transcriptional programs. Drug sensitivity analysis nominated Daporinad as a computationally predicted candidate compound, supporting Daporinad as a pharmacogenomic candidate for follow-up investigation. CONCLUSIONS: By integrating scRNA-seq and bulk RNA sequencing (RNA-seq) data, we constructed a macrophage copper metabolism-associated prognostic signature for HCC. The risk score was associated with survival, immune microenvironment features and predicted drug response, providing a transcriptomic framework for risk stratification and therapeutic hypothesis generation.

Hepatocellular carcinoma (HCC)↗
PubMed2024

In vivo editing of lung stem cells for durable gene correction in mice.

In vivo genome correction holds promise for generating durable disease cures; yet, effective stem cell editing remains challenging. In this work, we demonstrate that optimized lung-targeting lipid nanoparticles (LNPs) enable high levels of genome editing in stem cells, yielding durable responses. Intravenously administered gene-editing LNPs in activatable tdTomato mice achieved >70% lung stem cell editing, sustaining tdTomato expression in >80% of lung epithelial cells for 660 days. Addressing cystic fibrosis (CF), NG-ABE8e messenger RNA (mRNA)-sgR553X LNPs mediated >95% cystic fibrosis transmembrane conductance regulator (CFTR) DNA correction, restored CFTR function in primary patient-derived bronchial epithelial cells equivalent to Trikafta for F508del, corrected intestinal organoids and corrected R553X nonsense mutations in 50% of lung stem cells in CF mice. These findings introduce LNP-enabled tissue stem cell editing for disease-modifying genome correction.

Animals↗
PubMed2023

Lung SORT LNPs enable precise homology-directed repair mediated CRISPR/Cas genome correction in cystic fibrosis models.

Approximately 10% of Cystic Fibrosis (CF) patients, particularly those with CF transmembrane conductance regulator (CFTR) gene nonsense mutations, lack effective treatments. The potential of gene correction therapy through delivery of the CRISPR/Cas system to CF-relevant organs/cells is hindered by the lack of efficient genome editor delivery carriers. Herein, we report improved Lung Selective Organ Targeting Lipid Nanoparticles (SORT LNPs) for efficient delivery of Cas9 mRNA, sgRNA, and donor ssDNA templates, enabling precise homology-directed repair-mediated gene correction in CF models. Optimized Lung SORT LNPs deliver mRNA to lung basal cells in Ai9 reporter mice. SORT LNP treatment successfully corrected the CFTR mutations in homozygous G542X mice and in patient-derived human bronchial epithelial cells with homozygous F508del mutations, leading to the restoration of CFTR protein expression and chloride transport function. This proof-of-concept study will contribute to accelerating the clinical development of mRNA LNPs for CF treatment through CRISPR/Cas gene correction.

Humans↗