ArticleZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences2026
[Construction of a ubiquitination-related gene prognostic model for breast cancer based on taxane treatment response].
Article in Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences, 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
Abstract
objectivesTaxanes are first-line cchemotherapeutic agents for breast cancer; however, the development of resistance often leads to treatment failure. Ubiquitination plays a critical regulatory role in tumor progression and drug resistance. This study aims to construct a prognostic model based on ubiquitination-related genes (URGs) according to taxane treatment response, to predict patient prognosis and drug sensitivity, identify potential therapeutic targets, and provide a basis for individualized treatment of breast cancer.
methodsBreast cancer samples treated with taxanes were obtained from The Cancer Genome Atlas (TCGA) and classified into taxane-sensitive and taxane-resistant groups as the training cohort. The GSE25055 dataset from the Gene Expression Omnibus (GEO) was used as the validation cohort. A comprehensive list of URGs was retrieved from the Integrated Annotations for Ubiquitin and Ubiquitin-like Conjugation Database (iUUCD), and differentially expressed URGs between sensitive and resistant groups were identified. Univariate Cox regression analysis was performed to screen prognostic genes, followed by least absolute shrinkage and selection operator (LASSO) Cox regression with 10-fold cross-validation to identify core genes and construct a risk score model. Patients were stratified into high- and low-risk groups based on the risk score. Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were used to evaluate predictive performance. A nomogram integrating risk score and clinical factors was developed and validated. Drug sensitivity differences between risk groups were analyzed using the Genomics of Drug Sensitivity in Cancer (GDSC) and the pRRophetic R package, with estimation of half-maximal inhibitory concentration (IC
resultsA total of 59 differentially expressed URGs were identified between taxane-sensitive and resistant groups. Through univariate Cox and LASSO-Cox analyses, 4 core genes (
conclusionsThe prognostic model based on
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.