ArticleBMC medicine2026
Targeted lipidomics unveils complex lipids in cervicovaginal environment as diagnostic and prognostic biomarkers for endometrial cancer.
Article in BMC medicine, 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
3 authors.
Funding
Abstract
backgroundGlobal incidence of endometrial cancer (EC) is on the rise. EC-associated risk factors like obesity, metabolic syndrome, and genetic predisposition increase a person's risk for developing EC in their lifetime and negatively affect prognostic outcomes. Present methods for EC diagnosis rely on invasive endometrial biopsies or dilation and curettage. Our previous global untargeted metabolomics analysis of minimally invasive cervicovaginal lavage (CVL) samples revealed an enrichment in simple lipid signatures associated with EC presence and pathophysiology. This study investigated complex lipids beyond those reported previously, with intent to identify novel lipid biomarkers for accurate, minimally invasive EC detection and prognosis.
methodsWe analysed 223 CVL samples collected by a physician from women diagnosed with EC (n = 66), benign pathological conditions (n = 108) and asymptomatic, healthy women (n = 49). The concentrations (nmol/mL) of 914 individual lipid species, 14 lipid classes and 28 fatty acid (FA) side chains were detected across CVL samples using the Complex Lipid Targeted Panel (Metabolon Inc.). Tumour size, grade, myometrial invasion, and mismatch repair (MMR) status in women with EC were determined from histopathologic reports. MetaboAnalyst and Prism were used for statistical and biomarker analysis which included Receiver Operating Characteristic (ROC) curves, measuring the Area Under the Curve (AUC) and Youden Index (J).
resultsWomen with EC exhibited significant enrichment of neutral lipid species, especially those containing long chained polyunsaturated fatty acid side chains. Cholesteryl ester (CE) species, specifically CE(22:4), were consistently identified as top predictive features when applied individually and when incorporated into multivariable diagnostic models. A 10-feature model developed in the exploratory dataset, discriminated EC from a combined group of benign and healthy controls with ≥75% sensitivity and specificity when validated using previously internal held-out samples. Top predictive CE species for EC also held prognostic value as they related to MMR status and histologic type.
conclusionsThese findings revealed EC-associated alterations in lipid metabolism within the cervicovaginal environment, highlighting the potential use of complex lipid species detected in CVLs as minimally invasive diagnostic biomarkers for EC and markers associated with EC prognostic features.
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.