ArticleImmuno-oncology technology2025
Subtype-specific genetic drivers of immune evasion in breast cancer.
Article in Immuno-oncology technology, 2025. 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Immune evasion is a hallmark of cancer and a driver of therapeutic resistance. Although immunotherapy is effective in highly immunogenic cancers, its efficacy in breast cancer (BC) remains limited. We aimed to determine the prognostic relevance of immune-related gene signatures across distinct BC subtypes. Materials and methods: We used transcriptomic and clinical data from three independent cohorts [Gene Expression Omnibus (GEO), The Cancer Genome Atlas, and GSE96058]. We analyzed 106 genes associated with the evasion of immune destruction (EID) and 182 genes involved in the evasion of killing by cytotoxic T lymphocytes (ECTL). Expression of signatures was stratified by BC subtypes. Cox regression and Kaplan-Meier curves were used to assess survival, with false discovery rate (FDR) correction ensuring statistical robustness. Results: High expression of the ECTL signature was significantly associated with improved overall survival (OS) in basal BC patients [hazard ratio (HR) 0.25, 95% confidence interval (CI) 0.16-0.4, Conclusions: We identified subtype-specific signatures that predict survival and immunotherapy response, providing clinically actionable biomarkers.
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.