Evidence map›Paper›PMID 40591077›Full record

ArticleDiscover oncology2025

A lactate related signature for predicting prognosis and tumor microenvironment in lung adenocarcinoma.

Ying Wang, Huiting Li, Chao Chen, Hui Yu, Lichao Xu

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
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

5 authors.

Ying Wang *Department of Interventional Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Huiting Li *Department of Radiation Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Chao ChenDepartment of Interventional Radiology, Fudan University Shanghai Cancer Center, Shanghai, China.
Hui YuDepartment of Oncology, Shanghai Medical College, Fudan University, No. 270 Dong'an Road, Xuhui District, Shanghai, 200032, China. yuhui5650@163.com.
Lichao XuDepartment of Interventional Radiology, Fudan University Shanghai Cancer Center, Shanghai, China. lichaoxu@shca.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLactate plays a critical role in tumor development, metastasis, drug resistance, and regulation of tumor microenvironment. This study aimed to develop a prognostic signature for lung adenocarcinoma (LUAD) based on lactate-related genes (LRGs).

methodsWe initially performed univariate Cox regression analysis on 269 cases of LRGs in TCGA- LUAD cohort to determine LRGs related to overall survival (OS). Fourteen LRGs were used to construct a prognostic risk model and verified in three external cohorts (GSE31210, GSE68465, and GSE30219). The relationship between risk model and immune cell infiltration, as well as drug sensitivity was explored. The expression of 14 key genes in lung cancer cell lines (A549, NCI-H2009, and NCI-H1975) and normal bronchial epithelial cell line (BEAS-2B) was detected by qRT-PCR.

resultsA 14-LRG prognosis signature was constructed. Patients in the high-risk group had significant worse OS compared to those in the low-risk group (HR = 2.33; 95%CI, 1.72-3.14; P < 0.0001). Three independent external verification cohorts were used to verify our results, and consistent results were observed in them. There are significant differences in the infiltration of seven kinds of immune cells between high-risk and low-risk patients with LUAD. Low-risk patients responded well to carboplatin and paclitaxel, whereas high-risk patients were more sensitive to docetaxel (P < 0.05). Additionally, qRT-PCR confirmed that the expression of prognostic genes was basically consistent with the results of bioinformatics analysis.

conclusionWe successfully developed and validated a 14-LRG prognostic signature for LUAD, which was associated with immune status and drug resistance.

Indexed as

Immune microenvironmentLactateLung adenocarcinomaPrognosis

Identifiers

PMID40591077
PMCPMC12214210

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