ArticleGenes2026
Integrated Single-Cell and Bulk RNA-Sequencing Analysis Identifies an Aging-Related Gene Signature for Prognosis in Breast Cancer.
Article in Genes, 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCellular senescence exerts a complex influence on BRCA progression and TME remodeling. However, the specific roles of ASIGs in regulating the TME and determining patient outcomes remain unclear.
methodsUsing TCGA (training), METABRIC (validation), and single-cell RNA-seq datasets, we systematically characterized ASIGs in BRCA. Prognostic ASIGs were identified to define molecular subtypes and construct a 17-gene LASSO-Cox risk model, which was integrated with clinical factors to develop a prognostic nomogram. Microenvironmental features and cell-cell communication networks were deconstructed using computational deconvolution and single-cell algorithms (SCISSOR and CellChat).
resultsWe established a robust 17-gene ASIG-based prognostic signature that effectively stratified BRCA patients into high- and low-risk groups and served as an independent prognostic predictor (HR = 3.94,
conclusionsThe ASIG-based prognostic risk model is independent of traditional clinicopathological factors, providing a robust tool for patient risk stratification and offering biological insights into senescence-driven microenvironmental remodeling.
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.