Evidence map›Paper›PMID 39692826›Full record

ArticleDiscover oncology2024

Palmitoylation-related gene expression and its prognostic value in ovarian cancer: insights into immune infiltration and therapeutic potential.

Shaoying Zeng, Lijian Zeng, Xiaoying Xie, Liang Peng

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Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

9 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Shaoying Zeng *Department of Gynecology and Obstetrics, The First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Lijian Zeng *Department of Gynecology and Obstetrics, The First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Xiaoying XieDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Liang PengDepartment of Gynecology, The Second People's Hospital of Jingdezhen, Jingdezhen, 333000, Jiangxi, China. drpengliang@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPalmitoylation, a key post-translational modification, plays a significant role in ovarian cancer (OV) progression. However, the impact of palmitoylation-related genes on genomic instability, immune infiltration, and therapeutic response in OV remains poorly understood. This study aimed to investigate these factors to facilitate risk stratification and therapeutic intervention, providing insights into personalized treatment strategies.

methodsData from TCGA and GEO were utilized to develop a prognostic model based on palmitoylation-related genes. Differential expression, functional enrichment, and immune infiltration analyses were performed. Immune cell composition and pathway activities in different risk groups were assessed using CIBERSORT and ssGSEA algorithms. Immunotherapy response was predicted using TIDE and SubMap, while drug sensitivity differences were evaluated using the GDSC database.

resultsUnivariate, LASSO, and multivariate Cox regression analyses identified palmitoylation-related genes with significant prognostic value. The prognostic model effectively stratified patients into high- and low-risk groups, demonstrating significant survival differences. Immune infiltration analysis revealed distinct immune cell compositions and functions between risk groups. Low-risk patients exhibited higher immune scores and increased expression of immune checkpoints (PD-1, CD274, CTLA4), suggesting greater response to immunotherapy. Drug sensitivity analysis identified compounds with differential efficacy between risk groups, highlighting potential targeted treatment options.

conclusionPalmitoylation-related genomic features significantly influence OV progression and the immune landscape, offering potential for improved risk stratification and informing immunotherapy strategies to enhance patient outcomes.

Indexed as

Genomic instabilityImmune InfiltrationImmunotherapyOVPalmitoylationPrognostic model

Identifiers

PMID39692826
PMCPMC11655903

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