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mRNA表达干性指数特征的综合基因组分析预测肺腺癌的预后和免疫格局。

Integrated genomic analysis of the stemness index signature of mRNA expression predicts lung adenocarcinoma prognosis and immune landscape.

作者信息

Lu Xingzhao, Du Wei, Zhou Jianping, Li Weiyang, Fu Zhimin, Ye Zhibin, Chen Guobiao, Huang Xian, Guo Yuliang, Liao Jingsheng

机构信息

Thoracic Surgery Department, The Tenth Affiliated Hospital of Southern Medical University, Dongguan Institute of Clinical Cancer Research, Affiliated Dongguan People's Hospital, Southern Medical University, Dongguan, China.

Department of Medical Oncology, The Tenth Affiliated Hospital of Southern Medical University, Dongguan Institute of Clinical Cancer Research, Affiliated Dongguan People's Hospital, Southern Medical University, Dongguan, China.

出版信息

PeerJ. 2025 Feb 13;13:e18945. doi: 10.7717/peerj.18945. eCollection 2025.


DOI:10.7717/peerj.18945
PMID:39959839
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11830367/
Abstract

mRNA expression-based stemness index (mRNAsi) has been used for prognostic assessment in various cancers, but its application in lung adenocarcinoma (LUAD) is limited, which is the focus of this study. Low mRNAsi in LUAD predicted a better prognosis. Eight genes () associated with mRNAsi were screened to establish a risk model. The differentially expressed genes between the high and low risk groups were mainly enriched in the metabolism, cell cycle functions pathway. The low risk score group had higher immune cell scores. Patients with lower TIDE scores in the low risk group had better immunotherapy outcomes. In addition, risk score was effective in assessing drug sensitivity of LUAD. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) data showed that eight genes were differentially expressed in LUAD cell lines, and knockdown of reduced the invasion and migration ability of LUAD cells. This study designed a risk model based on the eight mRNAsi-related genes for predicting LUAD prognosis. The model accurately predicted the prognosis and survival of LUAD patients, facilitating the assessment of the sensitivity of patients to immunotherapy and chemotherapy.

摘要

基于mRNA表达的干性指数(mRNAsi)已用于多种癌症的预后评估,但其在肺腺癌(LUAD)中的应用有限,这是本研究的重点。LUAD中低mRNAsi预示着更好的预后。筛选出与mRNAsi相关的8个基因()以建立风险模型。高风险组和低风险组之间的差异表达基因主要富集在代谢、细胞周期功能途径中。低风险评分组具有更高的免疫细胞评分。低风险组中TIDE评分较低的患者免疫治疗效果更好。此外,风险评分在评估LUAD的药物敏感性方面有效。逆转录定量聚合酶链反应(RT-qPCR)数据显示,8个基因在LUAD细胞系中差异表达,敲低可降低LUAD细胞的侵袭和迁移能力。本研究基于8个与mRNAsi相关的基因设计了一个风险模型,用于预测LUAD的预后。该模型准确预测了LUAD患者的预后和生存情况,有助于评估患者对免疫治疗和化疗的敏感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/c288d9348c53/peerj-13-18945-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/945ebacdc233/peerj-13-18945-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/16c903135519/peerj-13-18945-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/03ce404871fb/peerj-13-18945-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/09988eeb081e/peerj-13-18945-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/3ed50a46bb49/peerj-13-18945-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/43161a89d7bf/peerj-13-18945-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/ae0bfcd0c3c4/peerj-13-18945-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/c288d9348c53/peerj-13-18945-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/945ebacdc233/peerj-13-18945-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/16c903135519/peerj-13-18945-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/03ce404871fb/peerj-13-18945-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/09988eeb081e/peerj-13-18945-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/3ed50a46bb49/peerj-13-18945-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/43161a89d7bf/peerj-13-18945-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/ae0bfcd0c3c4/peerj-13-18945-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6240/11830367/c288d9348c53/peerj-13-18945-g008.jpg

相似文献

[1]
Integrated genomic analysis of the stemness index signature of mRNA expression predicts lung adenocarcinoma prognosis and immune landscape.

PeerJ. 2025-2-13

[2]
Immune- and Stemness-Related Genes Revealed by Comprehensive Analysis and Validation for Cancer Immunity and Prognosis and Its Nomogram in Lung Adenocarcinoma.

Front Immunol. 2022

[3]
A nicotinamide metabolism-related gene signature for predicting immunotherapy response and prognosis in lung adenocarcinoma patients.

PeerJ. 2025-2-27

[4]
Cancer Stemness-Based Prognostic Immune-Related Gene Signatures in Lung Adenocarcinoma and Lung Squamous Cell Carcinoma.

Front Endocrinol (Lausanne). 2021

[5]
Fatty acid metabolism prognostic signature predicts tumor immune microenvironment and immunotherapy, and identifies tumorigenic role of MOGAT2 in lung adenocarcinoma.

Front Immunol. 2024

[6]
Fatty acid metabolism-derived prognostic model for lung adenocarcinoma: unraveling the link to survival and immune response.

Front Immunol. 2025-3-13

[7]
Disulfidptosis-related lncRNAs signature predicting prognosis and immunotherapy effect in lung adenocarcinoma.

Aging (Albany NY). 2024-6-10

[8]
Development of a reliable risk prognostic model for lung adenocarcinoma based on the genes related to endotheliocyte senescence.

Sci Rep. 2025-4-12

[9]
Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature.

J Cell Mol Med. 2024-7

[10]
B-cell signatures characterize the immune landscape and predict LUAD prognosis via the integration of scRNA-seq and bulk RNA-seq.

Sci Rep. 2025-2-14

本文引用的文献

[1]
Knockdown of ANLN inhibits the progression of lung adenocarcinoma via pyroptosis activation.

Mol Med Rep. 2023-9

[2]
GNPNAT1 promotes the stemness of breast cancer and serves as a potential prognostic biomarker.

Oncol Rep. 2023-8

[3]
Eukaryotic Initiation Factor 5A2 localizes to actively translating ribosomes to promote cancer cell protrusions and invasive capacity.

Cell Commun Signal. 2023-3-13

[4]
GAPDH Is a Novel Ferroptosis-Related Marker and Correlates with Immune Microenvironment in Lung Adenocarcinoma.

Metabolites. 2023-1-17

[5]
Bioinformatics analyses of combined databases identify shared differentially expressed genes in cancer and autoimmune disease.

J Transl Med. 2023-2-10

[6]
Targeting USP10 induces degradation of oncogenic ANLN in esophageal squamous cell carcinoma.

Cell Death Differ. 2023-2

[7]
The pleiotropic roles of eIF5A in cellular life and its therapeutic potential in cancer.

Biochem Soc Trans. 2022-12-16

[8]
A novel online calculator to predict early recurrence and long-term survival of patients with resectable pancreatic ductal adenocarcinoma after pancreaticoduodenectomy: A multicenter study.

Int J Surg. 2022-10

[9]
mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning.

Front Immunol. 2022

[10]
Promotes Gastric Cancer Metastasis by Modulating Focal Adhesion Pathway and Tumor Microenvironment.

Int J Biol Sci. 2022

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