ArticleTranslational cancer research2026
Exploring the lactate-metabolism related characteristics during the development of medulloblastoma through single-cell and bulk RNA-seq.
Article in Translational cancer research, 2026. 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Medulloblastoma (MB) is a common central nervous system malignancy in children, and its relationship with lactate metabolism has become an important area of cancer research in recent years, especially in metabolic reprogramming. This study aimed to determine the effects of lactate metabolism-related genes in the biological mechanisms involved in MB. Methods: A single-cell analysis was performed on the GEO dataset (GSE155446) in order to analyse the lactate metabolism-related characteristics of differing MB cell populations. Following this, MB cells were divided according to their lactate metabolism-related characteristics, and further developmental trajectories between MB subsets were analyzed. Further studies encompassed cell communication and pathway analysis to elucidate their function and association with immune cells. Additionally, a MB-related bulk dataset (GSE85217) was procured for machine learning-based identification of core lactate-metabolism related genes, with the objective of gaining novel insights into clinical diagnosis and therapeutic targets. Results: In light of the findings from the scRNA-seq analysis, three primary cell types were identified. It was found that cells in MB clusters exhibited distinct biological functions. Metabolic analysis of MB clusters revealed heterogeneity in glycolysis, gluconeogenesis, and lactate metabolism reprogramming. The lactate-metabolism related genes score (LMRGs score) was found to be significantly elevated in MB clusters. Furthermore, differential expression analysis among MB cell clusters revealed distinct metabolic profiles. The Random Forest learning method confirmed that COX4I1, CYC1, MECP2, MYC, NDUFAF3, NDUFS3, COX20, CALR, POMT1 and C1QBP are highly expressed in MB. Conclusions: The results of the present study demonstrate a close association between lactate-metabolism-related genes and their functions, and the development of MB.
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.