ArticleBreast cancer research and treatment2019
Re-interpretation of PAM50 gene expression as quantitative tumor dimensions shows utility for clinical trials: application to prognosis and response to paclitaxel in breast cancer.
Article in Breast cancer research and treatment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT00129922 (Phase III Study to Compare 6 Courses of FEC), which is not on this map. Cited by 9 papers.
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.
Phase III Study to Compare 6 Courses of FEC (Fluorouracil, Epirubicin and Cyclophosphamide) vs. 4 Courses of FEC Followed by 8 Weekly Paclitaxel Administrations, as Adjuvant Treatment for Node Positive Operable BC Patients
Who cites it
9 citing papers in PubMed, 20 citations in OpenAlex.
- Quantification of subtype purity in Luminal A breast cancer predicts clinical characteristics and survival.Breast cancer research and treatment · 2023Article
- A scoping review of statistical methods in studies of biomarker-related treatment heterogeneity for breast cancer.BMC medical research methodology · 2023Article
- Deep Transcriptome Profiling of Multiple Myeloma Using Quantitative Phenotypes.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Deep-learning-based survival prediction of patients with cutaneous malignant melanoma.Frontiers in medicine · 2023Article
- Fibroblast growth factor receptor signalling dysregulation and targeting in breast cancer.Open biology · 2022Review
- Deep-Learning-Based Survival Prediction of Patients in Coronary Care Units.Computational and mathematical methods in medicine · 2021Article
- Family Study Designs Informed by Tumor Heterogeneity and Multi-Cancer Pleiotropies: The Power of the Utah Population Database.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Hsa_circ_0002483 inhibited the progression and enhanced the Taxol sensitivity of non-small cell lung cancer by targeting miR-182-5p.Cell death & disease · 2019Article
- HypermethylatedOncoTargets and therapy · 2019Article
Corrections and comments
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Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundWe recently showed PAM50 gene expression data can be represented by five quantitative, orthogonal, multi-gene breast tumor traits. These novel tumor 'dimensions' were superior to categorical intrinsic subtypes for clustering in high-risk breast cancer pedigrees, indicating potential to represent underlying genetic susceptibilities and biological pathways. Here we explore the prognostic and predictive utility of these dimensions in a sub-study of GEICAM/9906, a Phase III randomized prospective clinical trial of paclitaxel in breast cancer.
methodsTumor dimensions, PC1-PC5, were calculated using pre-defined coefficients. Univariable and multivariable Cox proportional hazards (PH) models for disease-free survival (DFS) were used to identify associations between quantitative dimensions and prognosis or response to the addition of paclitaxel. Results were illustrated using Kaplan-Meier curves.
resultsDimensions PC1 and PC5 were associated with DFS (Cox PH p = 6.7 [Formula: see text] 10
conclusionsOur proof-of-concept application of quantitative dimensions illustrated novel findings and clinical utility beyond standard clinical-pathological characteristics and categorical intrinsic subtypes for prognosis and predicting chemotherapy response. Consideration of expression data as quantitative tumor dimensions offers new potential to identify clinically important patient subsets in clinical trials and advance precision medicine.
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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.