ArticleScientific reports2019
Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series.
Article in Scientific reports, 2019. 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 28 papers, 1 of them a synthesis that pooled it.
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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
28 citing papers in PubMed, 1 synthesis or guideline pooled it.
- An original study assessing biomarker success rate in breast cancer recurrence biomarker research.BMC medicine · 2024Pooled it
- Molecular profiling of the Basal-like intrinsic molecular subtype in primary ER-positive HER2-negative breast cancer.Genome medicine · 2025Article
- Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer.International journal of molecular sciences · 2025Article
- Genomic characterization of the HER2-enriched intrinsic molecular subtype in primary ER-positive HER2-negative breast cancer.Nature communications · 2025Article
- NEDD9 is transcriptionally regulated by HDAC4 and promotes breast cancer metastasis and macrophage M2 polarization via the FAK/NF-κB signaling pathway.Neoplasia (New York, N.Y.) · 2024Article
- A triple hormone receptor ER, AR, and VDR signature is a robust prognosis predictor in breast cancer.Breast cancer research : BCR · 2024Article
- Validation of an AI-based solution for breast cancer risk stratification using routine digital histopathology images.Breast cancer research : BCR · 2024Article
- Molecular subtyping improves breast cancer diagnosis in the Copenhagen Breast Cancer Genomics Study.JCI insight · 2024Article
- Digital PCR quantification of ultrahigh ERBB2 copy number identifies poor breast cancer survival after trastuzumab.NPJ breast cancer · 2024Article
- Development and prognostic validation of a three-level NHG-like deep learning-based model for histological grading of breast cancer.Breast cancer research : BCR · 2024Observational
- Perturbation and stability of PAM50 subtyping in population-based primary invasive breast cancer.NPJ breast cancer · 2023Article
- Prognostic significance of pretreatmentBreast cancer research and treatment · 2023Article
- Harnessing the value of TCTP in breast cancer treatment resistance: an opportunity for personalized therapy.Cancer drug resistance (Alhambra, Calif.) · 2023Review
- Article
- Molecular Research and Treatment of Breast Cancer.International journal of molecular sciences · 2022Article
- Subtype and cell type specific expression of lncRNAs provide insight into breast cancer.Communications biology · 2022Article
- RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer.NPJ breast cancer · 2022Article
- Regulatory networks and 5' partner usage of miRNA host gene fusions in breast cancer.International journal of cancer · 2022Article
- Article
- Sample Preparation Approach Influences PAM50 Risk of Recurrence Score in Early Breast Cancer.Cancers · 2021Article
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Multigene expression signatures provide a molecular subdivision of early breast cancer associated with patient outcome. A gap remains in the validation of such signatures in clinical treatment groups of patients within population-based cohorts of unselected primary breast cancer representing contemporary disease stages and current treatments. A cohort of 3520 resectable breast cancers with RNA sequencing data included in the population-based SCAN-B initiative (ClinicalTrials.gov ID NCT02306096) were selected from a healthcare background population of 8587 patients diagnosed within the years 2010-2015. RNA profiles were classified according to 19 reported gene signatures including both gene expression subtypes (e.g. PAM50, IC10, CIT) and risk predictors (e.g. Oncotype DX, 70-gene, ROR). Classifications were analyzed in nine adjuvant clinical assessment groups: TNBC-ACT (adjuvant chemotherapy, n = 239), TNBC-untreated (n = 82), HER2+/ER- with anti-HER2+ ACT treatment (n = 110), HER2+/ER+ with anti-HER2 + ACT + endocrine treatment (n = 239), ER+/HER2-/LN- with endocrine treatment (n = 1113), ER+/HER2-/LN- with endocrine + ACT treatment (n = 243), ER+/HER2-/LN+ with endocrine treatment (n = 423), ER+/HER2-/LN+ with endocrine + ACT treatment (n = 433), and ER+/HER2-/LN- untreated (n = 200). Gene signature classification (e.g., proportion low-, high-risk) was generally well aligned with stratification based on current immunohistochemistry-based clinical practice. Most signatures did not provide any further risk stratification in TNBC and HER2+/ER- disease. Risk classifier agreement (low-, medium/intermediate-, high-risk groups) in ER+ assessment groups was on average 50-60% with occasional pair-wise comparisons having <30% agreement. Disregarding the intermediate-risk groups, the exact agreement between low- and high-risk groups was on average ~80-95%, for risk prediction signatures across all assessment groups. Outcome analyses were restricted to assessment groups of TNBC-ACT and endocrine treated ER+/HER2-/LN- and ER+/HER2-/LN+ cases. For ER+/HER2- disease, gene signatures appear to contribute additional prognostic value even at a relatively short follow-up time. Less apparent prognostic value was observed in the other groups for the tested signatures. The current study supports the usage of gene expression signatures in specific clinical treatment groups within population-based breast cancer. It also stresses the need of further development to reach higher consensus in individual patient classifications, especially for intermediate-risk patients, and the targeting of patients where current gene signatures and prognostic variables provide little support in clinical decision-making.
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