RNA Sequencing for Breast Cancer Diagnostics
Insights into the molecular markup of tumors have transformed cancer research in recent years. Many people worldwide work on translating these insights into the clinic to improve diagnostic areas such as patient risk stratification and treatment selection. Most of these efforts focus on DNA-based short-read high-throughput sequencing (DNA-seq).
RNA sequencing (RNA-seq) is a sister technology to DNA-seq that probes the current state of the cell’s transcriptional machinery (the transcriptome) and is commonly used for research, but is underused as a diagnostic tool. RNA-seq is inexpensive and can provide a wealth of information that is not accessible from DNA (gene/isoform expression), in addition to being able, to some degree, to detect features commonly determined from DNA (e.g., point mutations, short insertions and deletions, copy number, structural variants). As such it is possible to develop a variety of diagnostics that can be derived from a single sequencing dataset, making RNA-seq a potentially powerful diagnostic tool.
My ongoing PhD work is about exploring the diagnostic power of RNA-seq by developing and evaluating computational resources for the Sweden Cancerome Analysis Network–Breast (SCAN-B) breast cancer project, and by developing diagnostic tools from the generated data. Within SCAN-B the vast majority of breast cancer patients from the participating hospital regions are being enrolled since 2010, and RNA-seq data is being generated from their tumors within one week from surgery.
See below for a list of results generated from this work.
- Defining the Mutational Landscape of the Primary Breast Cancer Transcriptome through large-scale RNA-seq in the Sweden Cancerome Analysis Network–Breast (SCAN-B) Project
- Detection of circulating tumor cells and circulating tumor DNA before and after mammographic breast compression in a cohort of breast cancer patients scheduled for neoadjuvant treatment
- Towards Better Breast Cancer Diagnostics: Large-scale Profiling of Tumor Transcriptomes
- RNA-seq-Based Classifiers for Prediction of the Five Conventional Breast Cancer Biomarkers in the Population-Based Multicenter SCAN-B Study
- 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