Abstract
Breast cancer is a complex disease comprising molecularly distinct subtypes. The prognosis and treatment differ between subtypes; thus, it is important to distinguish one subtype from another. In this chapter, we make use of high-throughput microarray dataset to perform breast cancer subtyping of 10086 samples. Aside from the four major subtypes, that is, Basal-like, HER2-enriched, luminal A, and luminal B, we defined a normal-like subtype that has a gene expression profile similar to that found in normal and adjacent normal breast samples. Also, a group of luminal B-like samples with better prognosis was distinguished from the high-risk luminal B breast cancer. We additionally identified 33 surface-protein encoding genes whose gene expression profiles were associated with survival outcomes. We believe these genes are potential therapeutic targets and diagnostic biomarkers for breast cancer.
| Original language | English |
|---|---|
| DOIs | |
| Publication status | Published - Apr 5 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
Fingerprint
Dive into the research topics of 'Analysis of 10086 Microarray Gene Expression Data Uncovers Genes that Subclassify Breast Cancer Intrinsic Subtypes'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS