ArticleBreast cancer research and treatment2012
PAM50 assay and the three-gene model for identifying the major and clinically relevant molecular subtypes of breast cancer.
Article in Breast cancer research and treatment, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01973660 (PAMELA), which is not on this map. Cited by 100 papers, 2 of them syntheses 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.
PAMELA: PAM50 HER2-enriched Phenotype as a Predictor of Early Response to Neoadjuvant Lapatinib Plus Trastuzumab in Stage I to IIIA HER2-positive Breast Cancer
Who cites it
100 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Role of Intrinsic Subtype Analysis with PAM50 in Hormone Receptors Positive HER2 Negative Metastatic Breast Cancer: A Systematic Review.International journal of molecular sciences · 2022Pooled it
- Elevated long noncoding RNA MALAT-1 expression is predictive of poor prognosis in patients with breast cancer: a meta-analysis.Bioscience reports · 2020Pooled it
- Correlative Biomarker Analysis of Intrinsic Subtypes and Efficacy Across the MONALEESA Phase III Studies.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2021Trial
- High-throughput proteomics of breast cancer interstitial fluid: identification of tumor subtype-specific serologically relevant biomarkers.Molecular oncology · 2021Trial
- A PAM50-Based Chemoendocrine Score for Hormone Receptor-Positive Breast Cancer with an Intermediate Risk of Relapse.Clinical cancer research : an official journal of the American Association for Cancer Research · 2017Trial
- Robust Heterogeneity Adjustment for Gaussian Graphical Model With Latent Variables.Statistics in medicine · 2026Article
- Gene-Morphology Alignment via Graph-Constrained Latent Modeling for Molecular Subtype Prediction from Histopathology in Pancreatic Cancer.medRxiv : the preprint server for health sciences · 2026Article
- IdentifiHR predicts homologous recombination deficiency in high-grade serous ovarian carcinoma using gene expression.Communications medicine · 2026Article
- Article
- Benchmarking single-sample gene set scoring methods for application in precision medicine.Briefings in bioinformatics · 2025Article
- EGFR amplification and PI3K pathway mutations identify a subset of breast cancers that synergistically respond to EGFR and PI3K inhibition.bioRxiv : the preprint server for biology · 2025Article
- A Comprehensive Review of Deep Learning Applications with Multi-Omics Data in Cancer Research.Genes · 2025Review
- A machine learning-based investigation of integrin expression patterns in cancer and metastasis.Scientific reports · 2025Article
- Clinical Implications of Breast Cancer Intrinsic Subtypes.Advances in experimental medicine and biology · 2025Review
- OmicsFootPrint: a framework to integrate and interpret multi-omics data using circular images and deep neural networks.Nucleic acids research · 2024Article
- EMBER creates a unified space for independent breast cancer transcriptomic datasets enabling precision oncology.NPJ breast cancer · 2024Article
- The DNA Damage Response (DDR) landscape of endometrial cancer defines discrete disease subtypes and reveals therapeutic opportunities.NAR cancer · 2024Article
- Article
- Breast Cancer Molecular Subtyping in Practice: A Real-World Study of the APIS Breast Cancer Subtyping Assay in a Consecutive Series of Breast Core Biopsies.International journal of molecular sciences · 2024Article
- Intrinsic Subtype and Overall Survival of Patients with Advanced HR+/HER2- Breast Cancer Treated with Ribociclib and ET: Correlative Analysis of MONALEESA-2, -3, -7.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Article
40 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
4 authors.
Funding
Abstract
It has recently been proposed that a three-gene model (SCMGENE) that measures ESR1, ERBB2, and AURKA identifies the major breast cancer intrinsic subtypes and provides robust discrimination for clinical use in a manner very similar to a 50-gene subtype predictor (PAM50). However, the clinical relevance of both predictors was not fully explored, which is needed given that a ~30 % discordance rate between these two predictors was observed. Using the same datasets and subtype calls provided by Haibe-Kains and colleagues, we compared the SCMGENE assignments and the research-based PAM50 assignments in terms of their ability to (1) predict patient outcome, (2) predict pathological complete response (pCR) after anthracycline/taxane-based chemotherapy, and (3) capture the main biological diversity displayed by all genes from a microarray. In terms of survival predictions, both assays provided independent prognostic information from each other and beyond the data provided by standard clinical-pathological variables; however, the amount of prognostic information was found to be significantly greater with the PAM50 assay than the SCMGENE assay. In terms of chemotherapy response, the PAM50 assay was the only assay to provide independent predictive information of pCR in multivariate models. Finally, compared to the SCMGENE predictor, the PAM50 assay explained a significantly greater amount of gene expression diversity as captured by the two main principal components of the breast cancer microarray data. Our results show that classification of the major and clinically relevant molecular subtypes of breast cancer are best captured using larger gene panels.
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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.