ArticleCancer cell international2025
Metabolomics reveals the therapeutic efficacy of liposomal resvida in endometrial cancer through regulating autophagy-related gene expression.
Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Autophagy modulation in gynaecologic oncology: insights into immune regulation and therapeutic potential.Frontiers in immunology · 2026Review
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
Endometrial cancer (EC) is the fourth most abundant gynecological cancer. There is an increase in the incidence of mortality from uterine cancers in the past few decades. A comprehensive systematic study to provide an overview on the relationship between autophagy, metabolomics and the risk of oestradiol valerate (OV) induced endometrial cancer was conducted correlated with the use of liposomal loaded-resvida as an innovate drug delivery system. This article explores how metabolomic technology can offer valuable insights on autophagy molecular aspects in EC by identifying new possible metabolite biomarkers that has the potential to improve the accuracy of diagnosis, prognosis and disease monitoring. Metabolomics approach, included orthogonal partial least squares discriminant analysis (OPLS-DA), thus revolutionizes the management of endometrial cancer. Autophagy described in endometrial cancer, includes the role of HSP-70/C-fos/PTEN/mTOR/ERDj-4/p53 signaling pathways that trigger/inhibit the process and consequently represent a potential molecular targets in therapeutic approaches. Endometrial cancer exhibits a molecular complexity and heterogeneity coherent with histopathologic and metabolomic variability. Multivariate statistical analyses pointed out a noteworthy deviation in serum chemical profiles among control, oestradiol valerate, and Resvida and liposomal-Resvida treated groups. Loading plot guided the selection of differential metabolites, elucidating significant variation in metabolite concentration. Improved characterization of molecular alterations of each histological type provides relevant information about the prognosis and potential response to new liposomal therapies. CA125 as EC biomarker was ameliorated post Resvida (108.7 IU/mL) and liposomal Resvida (82.2 IU/Ml) treatment at P ≤ 0.05 in addition to up regulating autophagy biomarkers including mTOR/Cfos/ERDj-4/ PTEN by 20, 25, 14, and 17 fold change respectively and down regulating p53 protein expression by 0.4 ng/ml at P ≤ 0.05 post OV intoxication with liposomal regimen reflecting the most significant impact in modulating these altered genes. The current metabolomics study is the integration of histopathologic and autophagy molecular factors to improve the diagnosis, prognosis, and treatment of endometrial cancer in coherent with liposomal drug delivery system as a targeted therapy.
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.