Evidence map›Paper›PMID 39695414›Full record

ArticleBMC cancer2024

Identification of pyroptosis-associated miRNAs in the immunoscape and prognosis of hepatocellular carcinoma.

Yuting Zheng, Xing Huang

Abstract read
In one paragraph

Article in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yuting ZhengDepartments of Anaesthesiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China.ORCID https://orcid.org/0000-0001-6112-8487
Xing HuangDepartments of Anaesthesiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China. huangxinghhh@163.com.ORCID https://orcid.org/0000-0001-7321-8244

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatocellular carcinoma is one of the most prevalent types of liver malignancy and poses a severe threat to global health. Despite recent improvements in therapeutic approaches, treatment options for patients with advanced or recurrent HCC are still limited. MATERIALS AND

methodsOur study analyzed miRNA differential expression using data from hepatocellular carcinoma patients in the Cancer Genome Atlas. Pyroptosis-related genes were identified from gene cards. Differential expression of miRNAs was analyzed using DESeq2 and visualized using ggplot2 and pheatmap. A prognostic risk model for pyroptosis-associated miRNAs was constructed using LASSO regression and validated by principal component analysis, Kaplan-Meier survival and ROC curve analysis. We also performed gene and pathway enrichment analysis. Immune cell infiltration and function in HCC were assessed using single-sample genomic enrichment analysis, and correlations with immune cells and function were explored. Also, CCK-8 assay as well as migration and invasion assays were performed after knockdown of miR-6844.

resultsWe have established and validated a prognostic risk model based on ten DEmiRNAs, which is important for the survival of HCC patients. Significant changes in immune cell infiltration and immune function were also found in high-risk patients. It also demonstrated that knockdown of miR-6844 inhibited HCC cell proliferation, migration and invasion, highlighting its role in HCC progression.

conclusionOur study reveals the implications of pyroptosis-associated differential miRNAs on the prognosis of patients with hepatocellular carcinoma and provides a foundation for novel HCC therapies, especially immunotherapy.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsMicroRNAsPyroptosisBiomarkers, TumorCell Line, TumorCell MovementCell ProliferationComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMalePrognosisBiomarkers, TumorMicroRNAsHepatocellular carcinomaImmune infiltrationmiR-6844Pyroptosis

Identifiers

PMID39695414
PMCPMC11657507

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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.