ArticleJCO precision oncology2018
Clinical Value of RNA Sequencing-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers: A Report From the Population-Based Multicenter Sweden Cancerome Analysis Network-Breast Initiative.
Article in JCO precision oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02306096 (SCAN-B), which is not on this map. Cited by 143 papers, 1 of them a synthesis that pooled it.
What it found
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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.
SCAN-B: The Sweden Cancerome Analysis Network - Breast Initiative
Who cites it
143 citing papers in PubMed, 1 synthesis or guideline pooled it, 204 citations in OpenAlex.
- A systematic review of datasets that can help elucidate relationships among gene expression, race, and immunohistochemistry-defined subtypes in breast cancer.Cancer biology & therapy · 2021Pooled it
- The spatially informed mFISHseq assay resolves biomarker discordance and predicts treatment response in breast cancer.Nature communications · 2025Trial
- ESR1 mutations are associated with enhanced MTORC1 signaling in a context-dependent manner.Communications biology · 2026Article
- Transcriptome-Based Synthetic Lethality Predictions to Improve Targeted Therapy/Immunotherapy Treatment Prioritization in Nonmetastatic Breast Cancer: BC-SELECT.Cancer research communications · 2026Article
- Acidosis-associated gene signature defines novel subtypes and dual-target therapeutic candidates in breast cancer.Journal of translational medicine · 2026Article
- Tumor-infiltrating lymphocytes display prognostic signatures associated with chemotherapy response in TNBC patients.iScience · 2026Article
- A Multiresolution Breast Cancer CIBERSORTx Resource Validated for Accuracy, Interpretive Limits, and Biological and Clinical Coherence in Tumor Microenvironment Deconvolution.Methods and protocols · 2026Article
- Machine learning-based programmed cell death gene signature for prognosis and drug sensitivity in breast cancer.Oncology letters · 2026Article
- CNet-Cox for interpretable network biomarker discovery and survival risk scoring in precise breast cancer prognosis.NPJ digital medicine · 2026Article
- CorePAM: a 24-gene PAM50-derived expression score with cross-platform external validation for breast cancer prognosis.Breast cancer research : BCR · 2026Article
- Endothelial-derived PANoptosis factor IL33 is a potential immunotherapy in breast cancer.iScience · 2026Article
- Discovery of a Small-Molecule Inhibitor Targeting the ELF3-HSP27 Interaction to Suppress Breast Cancer Progression.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Statistical knockoffs improve biomarker discovery from transcriptomic data.Briefings in bioinformatics · 2026Article
- Everolimus destabilizes thymidylate synthase via suppressing its O-GlcNAcylation and sensitizes HER2-negative breast cancer to fluorouracil.Cell death & disease · 2026Article
- New causal discovery algorithm over censored variables identifies subtype-specific drivers of breast cancer progression.GigaScience · 2026Article
- CA9+ cancer-associated fibroblasts cooperate with SPP1+ tumor-associated macrophages driving immune resistance in triple-negative breast cancer.Cellular and molecular life sciences : CMLS · 2026Article
- Tumor-derived neutrophil extracellular trap-associated DNA impairs treatment efficacy in breast cancer via CCDC25-dependent epithelial-mesenchymal transition.The Journal of clinical investigation · 2026Article
- CancerSubtypeXplore: A Modular Platform for Multiomics Cancer Subtype Prediction and Biomarker Consensus Discovery.Computational and structural biotechnology journal · 2026Article
- Visual analytics framework for survival analysis and biomarker discovery from gene expression data.PloS one · 2026Article
- Identification and validation of a seven-gene metastasis-associated prognostic model in breast cancer.Frontiers in genetics · 2026Article
83 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeIn early breast cancer (BC), five conventional biomarkers-estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), Ki67, and Nottingham histologic grade (NHG)-are used to determine prognosis and treatment. We aimed to develop classifiers for these biomarkers that were based on tumor mRNA sequencing (RNA-seq), compare classification performance, and test whether such predictors could add value for risk stratification.
methodsIn total, 3,678 patients with BC were studied. For 405 tumors, a comprehensive multi-rater histopathologic evaluation was performed. Using RNA-seq data, single-gene classifiers and multigene classifiers (MGCs) were trained on consensus histopathology labels. Trained classifiers were tested on a prospective population-based series of 3,273 BCs that included a median follow-up of 52 months (Sweden Cancerome Analysis Network-Breast [SCAN-B], ClinicalTrials.gov identifier: NCT02306096), and results were evaluated by agreement statistics and Kaplan-Meier and Cox survival analyses.
resultsPathologist concordance was high for ER, PgR, and HER2 (average κ, 0.920, 0.891, and 0.899, respectively) but moderate for Ki67 and NHG (average κ, 0.734 and 0.581). Concordance between RNA-seq classifiers and histopathology for the independent cohort of 3,273 was similar to interpathologist concordance. Patients with discordant classifications, predicted as hormone responsive by histopathology but non-hormone responsive by MGC, had significantly inferior overall survival compared with patients who had concordant results. This extended to patients who received no adjuvant therapy (hazard ratio [HR], 3.19; 95% CI, 1.19 to 8.57), or endocrine therapy alone (HR, 2.64; 95% CI, 1.55 to 4.51). For cases identified as hormone responsive by histopathology and who received endocrine therapy alone, the MGC hormone-responsive classifier remained significant after multivariable adjustment (HR, 2.45; 95% CI, 1.39 to 4.34).
conclusionClassification error rates for RNA-seq-based classifiers for the five key BC biomarkers generally were equivalent to conventional histopathology. However, RNA-seq classifiers provided added clinical value in particular for tumors determined by histopathology to be hormone responsive but by RNA-seq to be hormone insensitive.
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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.