ArticleAnnals of translational medicine2022
Differentially expressed liver exosome-related genes as candidate prognostic biomarkers for hepatocellular carcinoma.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Computational integration of in vivo single cell and in vitro bulk transcriptomics across 236 human and mouse datasets differentiates physiological versus non-physiological hepatic cell lines for hepatotoxicity screening.Toxicological sciences : an official journal of the Society of Toxicology · 2026Article
- Roles of skeletal muscle-derived exosomes in osteoporosis.Journal of translational medicine · 2025Review
- Exosome-Mediated Communication in Thyroid Cancer: Implications for Prognosis and Therapeutic Targets.Biochemical genetics · 2025Article
- Interferon Gamma Inducible Protein 30: from biological functions to potential therapeutic target in cancers.Cellular oncology (Dordrecht, Netherlands) · 2024Review
- Role of exosomes in hepatocellular carcinoma and the regulation of traditional Chinese medicine.Frontiers in pharmacology · 2023Review
- Role of exosomes in the development of the immune microenvironment in hepatocellular carcinoma.Frontiers in immunology · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Exosomes are involved in cell-to-cell communication, neovascularization, cancer metastasis, and drug resistance, which all play an important role in the occurrence and progression of hepatocellular carcinoma (HCC). Because there are few mechanistic studies about the function of exosomes in HCC, the goals of this study were to identify exosome-related genes in HCC, to establish a reliable prognostic model for HCC, and to explore underlying mechanisms. Methods: The exoRBase and The Cancer Genome Atlas (TCGA) databases were used to analyze differentially expressed genes (DEGs). Cox regression and least absolute shrinkage and selection operator analyses were used to identify DEGs closely related to the overall survival of patients with HCC. An exosome-related prognostic model was then constructed in TCGA and validated in the International Cancer Genome Consortium database. A nomogram was developed to predict survival. CIBERSORT was used to estimate the abundance of different types of immune cells. Immunotherapy-related DEGs were used to predict the effect of immunotherapy. Results: Forty-eight exosome-related DEGs were obtained; of them, five [exportin 1 ( Conclusions: This study has identified a novel signature based on exosome-related genes that has potential as a prognostic biomarker for HCC. Our research provides an immunological perspective for the development of precision treatment for HCC.
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.