ArticleDiscover oncology2025
Prognostic and therapeutic response prediction in glioblastoma multiforme using a lactylation-associated gene signature.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundGlioblastoma (GBM) is a highly aggressive brain tumor characterized by immunosuppressive tumor microenvironment and metabolic reprogramming. Dysregulated lactate metabolism has been observed in the glioma microenvironment, yet the functional roles of lactate accumulation and lactylation modification in driving GBM progression remain poorly understood.
methodsWe identified core genes associated with lactylation by analyzing gene expression data from GBM tumor tissues and normal tissues, combined with the screening of lactylation-related genes. Utilizing LASSO regression analysis, we developed an optimized five-gene lactylation-related signature, validated within the CGGA cohort. Patients were categorized into high- and low- LRGS groups based on risk scores. Subsequently, we compared clinical outcomes, immune profiles, and therapeutic sensitivities between these two groups. To further elucidate the impact of lactylation on immune cells, we analyzed single-cell sequencing data from the tumor microenvironment of GBM patients.
resultsWe identified five lactylation-related hub genes strongly associated with GBM and constructed a lactylation-related gene prognostic model. The risk scores of this lactylation-related model showed strong correlations with immune cell infiltration levels. Single-cell sequencing analysis revealed that significant differences in lactylation levels across various immune cell subtypes, with tumor-associated fibroblasts exhibiting markedly higher lactylation activity. Additionally, patients in the low- LRGS group demonstrated enhanced sensitivity to chemotherapy and targeted therapies.
conclusionThe lactylation-related gene signature established in this study demonstrates robust predictive efficacy in glioblastoma, serving not only as a prognostic biomarker but also offering new directions for personalized treatment strategies.
Indexed as
Identifiers
What Socratic 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 Socratic graph.