ArticleDiscover oncology2026
Comprehensive analysis of metabolic reprogramming-related gene signatures for predicting ovarian cancer prognosis, the immune landscape, and potential treatment options.
Article in Discover oncology, 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
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ovarian cancer (OV) is the most lethal gynaecologic malignancy. Metabolic reprogramming is a distinct feature of cancer and is associated with tumourigenesis and progression. It could be a potential therapeutic target for cancer treatment and a biomarker for assessing cancer prognosis. In this study, we identified metabolic reprogramming-related differentially expressed genes (MRRDEGs) in OV through differential gene expression analysis and conducted a comprehensive characterization of these MRRDEGs. On the basis of the MRRDEGs, we constructed a prognostic risk model that included five model genes for OV. The risk score was an independent prognostic factor that could predict the survival of OV patients. It could classify OV patients into distinct risk groups with significant differences in survival. We observed significant differences between risk groups in terms of biological pathway activity, immune cell infiltration patterns, and immunotherapy responses. Specifically, compared with the high-risk group, the low-risk group had a potentially superior immunotherapy response. These findings significantly advance our understanding of the relationships between metabolic reprogramming and OV pathogenesis, progression, prognosis, and immunotherapy response, laying a foundation for the development of novel biomarkers and therapeutic targets in the future and providing an important reference for the formulation of precision medicine strategies.
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.