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 [cohort 405]
PURPOSE In 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. METHODS In total, 3,678 p...
Provenance — who produced it, who reused it
Linked to 20 papers in the literature. Roles are inferred factual signals (who deposited the data vs who reused it), with counts — never a judgement about any author.
- bc-GenExMiner 4.5: new mining module computes breast cancer diff... 2021 · 222 cites
- Predicting Molecular Phenotypes from Histopathology Images: A Tr... 2021 · 91 cites
- Removing unwanted variation from large-scale RNA sequencing data... 2022 · 82 cites
- FADS1/2 control lipid metabolism and ferroptosis susceptibility... 2024 · 77 cites
15 further papers cite this accession but reuse could not be confirmed.
Deep data QC
metadata only · no data-level QC for this typeStandardized, field-standard QC computed by touching the data — every metric states how it was obtained
measured = computed from the data · extrapolated/reported = derived or from the repository · dq-1.0 · provisional — verify independently