ArticleJournal of translational medicine2019
Identification of a novel glycolysis-related gene signature for predicting metastasis and survival in patients with lung adenocarcinoma.
Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 124 papers.
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.
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.
Who cites it
124 citing papers in PubMed.
- Identification of a Lactylation-Related Gene Signature and Candidate Biomarkers for Dilated Cardiomyopathy.Journal of cellular and molecular medicine · 2026Article
- SLC16A3 links tumor metabolism to therapeutic opportunities in hepatocellular carcinoma.Translational cancer research · 2026Review
- Glucose oxidase-powered nanocatalytic medicine: Rewiring tumor metabolism for multimodal cancer therapy.Materials today. Bio · 2026Review
- Proteoglycans in Breast Cancer: Friends and Foes.Biomolecules · 2025Review
- Revealing Causal Protein Biomarkers and Potential Therapeutic Targets for Histologic-Specific Lung Cancer.Journal of cellular and molecular medicine · 2025Article
- Metabolic Adaptations in Cancer Progression: Optimization Strategies and Therapeutic Targets.Cancers · 2025Review
- The Emerging Roles of Metabolic Reprogramming in Non-Small Cell Lung Cancer Progression.Frontiers in bioscience (Landmark edition) · 2025Review
- Comprehensive pan-cancer analysis identified SLC16A3 as a potential prognostic and diagnostic biomarker.Cancer cell international · 2025Article
- EXT1 and Its Methylation Involved in the Progression of Uterine Corpus Endometrial Carcinoma Pathogenesis.Applied biochemistry and biotechnology · 2025Article
- Machine learning developed an immune evasion signature for predicting prognosis and immunotherapy benefits in lung adenocarcinoma.Frontiers in cell and developmental biology · 2025Article
- Circular RNA hsa_circ_103089 modulates metabolic glycolysis and influences migration, invasion, and cisplatin sensitivity in non-small cell lung cancer cells via the miR-876-5p/EGFR axis.American journal of cancer research · 2025Article
- SLC16A3 is a Prognostic Marker and Affects Immune Regulation in Bladder Cancer.Combinatorial chemistry & high throughput screening · 2025Article
- A Glycolysis and gluconeogenesis-related model for breast cancer prognosis.Cancer biomarkers : section A of Disease markers · 2024Article
- Enhanced prognostic signature for lung adenocarcinoma through integration of adjacent normal and tumor gene expressions.Heliyon · 2024Article
- Spatiotemporal evolutionary process of osteosarcoma immune microenvironment remodeling and C1QBP-driven drug resistance deciphered through single-cell multi-dimensional analysis.Bioengineering & translational medicine · 2024Article
- Article
- Crosstalk among Alternative Polyadenylation, Genetic Variants and Ubiquitin Modification Contribute to Lung Adenocarcinoma Risk.International journal of molecular sciences · 2024Article
- Programmed Cell Death-Related Gene Signature Associated with Prognosis and Immune Infiltration and the Roles of HMOX1 in the Proliferation and Apoptosis were Investigated in Uveal Melanoma.Genes & genomics · 2024Article
- Article
- MiR-181c-5p Regulates Lung Adenocarcinoma Progression via Targeting PRKN.Biochemical genetics · 2024Article
64 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLung cancer (LC) is one of the most lethal and most prevalent malignant tumors, and its incidence and mortality are increasing annually. Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer. Several biomarkers have been confirmed by data excavation to be related to metastasis, prognosis and survival. However, the moderate predictive effect of a single gene biomarker is not sufficient. Thus, we aimed to identify new gene signatures to better predict the possibility of LUAD.
methodsUsing an mRNA-mining approach, we performed mRNA expression profiling in large LUAD cohorts (n = 522) from The Cancer Genome Atlas (TCGA) database. Gene Set Enrichment Analysis (GSEA) was performed, and connections between genes and glycolysis were found in the Cox proportional regression model.
resultsWe confirmed a set of nine genes (HMMR, B4GALT1, SLC16A3, ANGPTL4, EXT1, GPC1, RBCK1, SOD1, and AGRN) that were significantly associated with metastasis and overall survival (OS) in the test series. Based on this nine-gene signature, the patients in the test series could be divided into high-risk and low-risk groups. Additionally, multivariate Cox regression analysis revealed that the prognostic power of the nine-gene signature is independent of clinical factors.
conclusionOur study reveals a connection between the nine-gene signature and glycolysis. This research also provides novel insights into the mechanisms underlying glycolysis and offers a novel biomarker of a poor prognosis and metastasis for LUAD patients.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.