Evidence map›Paper›PMID 38001949›Full record

ArticleBiomedicines2023

Development of a Comprehensive Gene Signature Linking Hypoxia, Glycolysis, Lactylation, and Metabolomic Insights in Gastric Cancer through the Integration of Bulk and Single-Cell RNA-Seq Data.

Xiangqian Zhang, Yun Li, Yongheng Chen

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.8field-weighted citation impact, top 6% of its field
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

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.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 16 citations in OpenAlex.

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  6. The impact of hypoxia and glycolysis on liver fibrosis.Journal of translational medicine · 2026
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  7. Role of histone modifications in gastric cancer (Review).International journal of oncology · 2026
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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

3 authors at 1 institution in 1 country.

Xiangqian ZhangNHC Key Laboratory of Cancer Proteomics & State Local Joint Engineering Laboratroy for Anticancer Drugs, Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China.
Yun LiNHC Key Laboratory of Cancer Proteomics & State Local Joint Engineering Laboratroy for Anticancer Drugs, Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China.
Yongheng ChenNHC Key Laboratory of Cancer Proteomics & State Local Joint Engineering Laboratroy for Anticancer Drugs, Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China.ORCID 0000-0001-8139-6892
Central South University · CN

Funding

National Natural Science Foundation of China 81974074National Natural Science Foundation of China 82172654the Hunan Provincial Science and Technology Department 2021RC4012
6 · The paper itself

Abstract

backgroundHypoxia and anaerobic glycolysis are cancer hallmarks and sources of the metabolite lactate. Intriguingly, lactate-induced protein lactylation is considered a novel epigenetic mechanism that predisposes cells toward a malignant state. However, the significance of comprehensive hypoxia-glycolysis-lactylation-related genes (HGLRGs) in cancer is unclear. We aimed to construct a model centered around HGLRGs for predicting survival, metabolic features, drug responsiveness, and immune response in gastric cancer.

methodsThe integration of bulk and single-cell RNA-Seq data was achieved using data obtained from the TCGA and GEO databases to analyze HGLRG expression patterns. A HGLRG risk-score model was developed based on univariate Cox regression and a LASSO-Cox regression model and subsequently validated. Additionally, the relationships between the identified HGLRG signature and multiple metabolites, drug sensitivity and various cell clusters were explored.

resultsThirteen genes were identified as constituting the HGLRG signature. Using this signature, we established predictive models, including HGLRG risk scores and nomogram and Cox regression models. The stratification of patients into high- and low-risk groups based on HGLRG risk scores showed a better prognosis in the latter. The high-risk group displayed increased sensitivity to cytotoxic drugs and targeted inhibitors. The expression of the HGLRG

conclusionThe innovative HGLRG signature demonstrates efficacy in predicting survival and providing a practical clinical model for gastric cancer. The HGLRG signature reflects the internal metabolism, drug responsiveness, and immune microenvironment components of gastric cancer and is expected to boost patients' response to targeted therapy and immunotherapy.

Indexed as

drug responsivenessgastric cancerglycolysis-related geneshypoxia-related genesimmunotherapylactylation-related genesprognostic modelstomach adenocarcinomatumor immune microenvironment

Identifiers

PMID38001949
PMCPMC10669360
OpenAlexW4388141536

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.