ArticleBritish journal of cancer2013
Identification of key clinical phenotypes of breast cancer using a reduced panel of protein biomarkers.
Article in British journal of cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic value of RANK signalling in breast cancer: a systematic review and meta-analysis.BMJ open · 2025Pooled it
- Cholesterol and Its Derivatives: Multifaceted Players in Breast Cancer Progression.Frontiers in oncology · 2022Pooled it
- The Impact of IGFBP6 Knockdown on Cholesterol Metabolism in Breast Cancer Cells.Current medicinal chemistry · 2026Article
- Female breast cancer classification using immunohistochemistry biomarkers staining in Botswana.BMC cancer · 2025Article
- The amino acid transporter SLC7A11 expression in breast cancer.Cancer biology & therapy · 2024Article
- RANK is a poor prognosis marker and a therapeutic target in ER-negative postmenopausal breast cancer.EMBO molecular medicine · 2023Article
- Phenotyping in acute respiratory distress syndrome: state of the art and clinical implications.Current opinion in critical care · 2022Review
- Establishment and characterization of a new spontaneously immortalized ERScientific reports · 2021Article
- Genomics applied to the treatment of breast cancer.Oncotarget · 2019Review
- Nottingham Prognostic Index is an Applicable Prognostic Tool in Non-Metastatic Triple-Negative Breast CancerAsian Pacific journal of cancer prevention : APJCP · 2019Article
- Human Antibody Fusion Proteins/Antibody Drug Conjugates in Breast and Ovarian Cancer.Transfusion medicine and hemotherapy : offizielles Organ der Deutschen Gesellschaft fur Transfusionsmedizin und Immunhamatologie · 2017Review
- Ki67 expression in invasive breast cancer: the use of tissue microarrays compared with whole tissue sections.Breast cancer research and treatment · 2017Article
- Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer.Breast cancer research and treatment · 2016Article
- Nottingham Prognostic Index Plus: Validation of a clinical decision making tool in breast cancer in an independent series.The journal of pathology. Clinical research · 2016Article
- Evaluation of Protein Profiles From Treated Xenograft Tumor Models Identifies an Antibody Panel for Formalin-fixed and Paraffin-embedded (FFPE) Tissue Analysis by Reverse Phase Protein Arrays (RPPA).Molecular & cellular proteomics : MCP · 2015Article
- Classification of patients with breast cancer according to Nottingham prognostic index highlights significant differences in immunohistochemical marker expression.World journal of surgical oncology · 2014Article
- High level of HSF1 associates with aggressive endometrial carcinoma and suggests potential for HSP90 inhibitors.British journal of cancer · 2014Article
- Molecular classification of breast cancer.Virchows Archiv : an international journal of pathology · 2014Article
- Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.British journal of cancer · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
backgroundBreast cancer is a heterogeneous disease characterised by complex molecular alterations underlying the varied behaviour and response to therapy. However, translation of cancer genetic profiling for use in routine clinical practice remains elusive or prohibitively expensive. As an alternative, immunohistochemical analysis applied to routinely processed tissue samples could be used to identify distinct biological classes of breast cancer.
methodsIn this study, 1073 archival breast tumours previously assessed for 25 key breast cancer biomarkers using immunohistochemistry and classified using clustering algorithms were further refined using naïve Bayes classification performance. Criteria for class membership were defined using the expression of a reduced panel of 10 proteins able to identify key molecular classes. We examined the association between these breast cancer classes with clinicopathological factors and patient outcome.
resultsWe confirm patient classification similar to established genotypic biological classes of breast cancer in addition to novel sub-divisions of luminal and basal tumours. Correlations between classes and clinicopathological parameters were in line with expectations and showed highly significant association with patient outcome. Furthermore, our novel biological class stratification provides additional prognostic information to the Nottingham Prognostic Index.
conclusionThis study confirms that distinct molecular phenotypes of breast cancer can be identified using robust and routinely available techniques and both the luminal and basal breast cancer phenotypes are heterogeneous and contain distinct subgroups.
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.