ArticleiLIVER2024
Evaluating the role of IER3+ macrophages in the prognosis of liver fibrosis by bulk and single-cell transcriptional analyses.
Article in iLIVER, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- IER3 as an RFX5 transcriptional co-activator promotes hepatocellular carcinoma progression via AKR1B10-mediated p53 transcriptional regulation.Discover oncology · 2026Article
- IER3 drives the transition from sepsis-associated AKI to CKD by suppressing the mitochondrial translocation of PRDX5.Cellular and molecular life sciences : CMLS · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and aims: Liver fibrosis (LF) is the common pathological process of almost all liver diseases, but the pathogenesis is extremely complicated and has not been fully clarified. Therefore, we want to explore LF's complex pathogenesis and identify key genetic markers that can predict LF prognosis. Methods: From Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/), we contained datasets GSE84044 and GSE130970. And involved GSE15654 whose survival data were for the validation of our model's prognostic value. Then, Bulk RNA sequencing was used to establish a LF-related prognostic model and to determine key genes.The key genes were later analyzed using single-cell RNA sequencing (scRNA-seq) and the role of macrophages in LF was investigated. Results: We established a comprehensive LF-related prognostic model (FMSig, i.e., fibrosis macrophage-related prognostic signature) containing four genes (IER3, AKR1B10, ADCY1, and PGM1). FMSig can distinguish between survival outcomes in dataset GSE15654. IER3 showed a higher hazard ratio than the other three FMSig genes. Moreover, further scRNA-seq analysis showed that IER3 is highly expressed in myeloid cells while the other three genes were rarely expressed in six immune cell types and other cell clusters. After reclustering the myeloid cells into seven clusters, we found that IER3 was highly expressed in myeloid cell cluster 3, shown to be related to anti-inflammation and lipid metabolism functions. Based on pseudotime analysis, we suggest that myeloid cell type 3 is transformed from myeloid cell type 0 in the liver cirrhosis microenvironment. On immunohistochemical staining, LF showed significantly higher IER3 expression than healthy controls. Conclusion: This study established a predictive model, FMSig, to evaluate LF prognosis, and showed that IER3 and macrophages are related to LF.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.