ArticleTranslational cancer research2025
The role of liquid-liquid phase separation in hepatocellular carcinoma: single-cell analysis and identification of prognostic biomarkers.
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The function of liquid-liquid phase separation (LLPS) in the progression of hepatocellular carcinoma (HCC) has not been extensively clarified. This study aimed to assess the predictive value and immunotherapeutic response associated with an LLPS-related signature (LLPSRS) in HCC. Methods: LLPS was characterized via single-cell RNA sequencing. By using single-cell and transcriptome analysis, we applied The Cancer Genome Atlas (TCGA) data and the least absolute shrinkage and selection operator (LASSO) Cox regression to construct the LLPSRS. In order to enhance the practicality of LLPSRS, we established and externally validated a LLPSRS nomogram, providing a quantitative prognostic tool for patients with HCC. Furthermore, we investigated the mechanisms related to the LLPSRS at the transcriptome, genomic, and single-cell levels, revealing important connections between the LLPSRS, HCC prognosis, and the immune landscape. Finally, we examined the different responses of the risk subgroups to immune checkpoint inhibitors and their sensitivity to major LLPSRS-targeted drugs. Results: We developed a risk prediction scoring model based on the 9-gene LLPSRS. The high-risk group exhibited notably lower overall survival (OS) compared to the low-risk group. High area under the curve (AUC) values from time-dependent receiver operating characteristic (ROC) curves demonstrated the model's robust performance. A nomogram that integrated the risk score and clinical features showed excellent prognostic ability. The LLPSRS's associations with clinicopathological characteristics, tumor microenvironment, immunotherapy response, and chemotherapy sensitivity indicated their significant clinical relevance. Conclusions: We developed a model that can accurately predict the outcomes of patients with HCC, clarified the mechanisms underlying the LLPSRS's relationship to HCC, and generated findings that contribute to the personalized treatment and development of immunotherapy for patients with 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.