ArticleMolecular oncology2018
Using microarray-based subtyping methods for breast cancer in the era of high-throughput RNA sequencing.
Article in Molecular oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 16 citations in OpenAlex.
- IRDRM: Exploring Biological Traits and Clinical Significance in Breast Cancer Through Gene Pairs and Somatic Mutation Profiles.Interdisciplinary sciences, computational life sciences · 2026Article
- The clinical relevance of apocrine morphology in breast cancer depends on the estrogen receptor status.NPJ breast cancer · 2026Article
- Evaluating Cross-Platform Batch Correction Methods for Integrated Microarray and RNA-seq Data Analysis.bioRxiv : the preprint server for biology · 2026Article
- tRNA modification genes are associated with genomic instability, proliferative programs, and poor prognosis in breast cancer.Breast cancer (Tokyo, Japan) · 2026Article
- Molecular convergence of luminal androgen receptor and molecular apocrine defines a distinct entity in ER-negative breast tumors.Breast cancer research : BCR · 2025Article
- Enhancing HER2-low breast cancer detection with quantitative transcriptomics.NPJ breast cancer · 2025Article
- Molecular subtyping improves breast cancer diagnosis in the Copenhagen Breast Cancer Genomics Study.JCI insight · 2024Article
- Building flexible and robust analysis frameworks for molecular subtyping of cancers.Molecular oncology · 2024Article
- Multigene profiles to guide the use of neoadjuvant chemotherapy for breast cancer: a Copenhagen Breast Cancer Genomics Study.NPJ breast cancer · 2023Article
- An mRNA characterization model predicting survival in patients with invasive breast cancer based on The Cancer Genome Atlas database.Cancer biomarkers : section A of Disease markers · 2021Article
- Identification of Platform-Independent Diagnostic Biomarker Panel for Hepatocellular Carcinoma Using Large-Scale Transcriptomics Data.Frontiers in genetics · 2019Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Breast cancer is a highly heterogeneous disease that can be classified into multiple subtypes based on the tumor transcriptome. Most of the subtyping schemes used in clinics today are derived from analyses of microarray data from thousands of different tumors together with clinical data for the patients from which the tumors were isolated. However, RNA sequencing (RNA-Seq) is gradually replacing microarrays as the preferred transcriptomics platform, and although transcript abundances measured by the two different technologies are largely compatible, subtyping methods developed for probe-based microarray data are incompatible with RNA-Seq as input data. Here, we present an RNA-Seq data processing pipeline, which relies on the mapping of sequencing reads to the probe set target sequences instead of the human reference genome, thereby enabling probe-based subtyping of breast cancer tumor tissue using sequencing-based transcriptomics. By analyzing 66 breast cancer tumors for which gene expression was measured using both microarrays and RNA-Seq, we show that RNA-Seq data can be directly compared to microarray data using our pipeline. Additionally, we demonstrate that the established subtyping method CITBCMST (Guedj et al., ), which relies on a 375 probe set-signature to classify samples into the six subtypes basL, lumA, lumB, lumC, mApo, and normL, can be applied without further modifications. This pipeline enables a seamless transition to sequencing-based transcriptomics for future clinical purposes.
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