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Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
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Expression and methylation patterns partition luminal-A breast tumors into distinct prognostic subgroups
Dvir Netanely1, Ayelet Avraham2, Adit Ben-Baruch3
1Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
Breast Cancer Research : BCR
|July 9, 2016
Summary
This study refines breast cancer subtyping by analyzing gene expression and methylation data, identifying distinct luminal-A subgroups with different prognoses for improved diagnosis and treatment.
Area of Science:
- Genomics
- Oncology
- Molecular Biology
Background:
- Breast cancer is a heterogeneous disease with distinct intrinsic subtypes (basal-like, HER2-enriched, luminal-A, luminal-B, normal-like).
- Current predictors like PAM50 have limitations in precisely identifying subtypes, particularly within the variable luminal-A class.
- The Cancer Genome Atlas (TCGA) provides extensive gene expression and methylation data for comprehensive tumor analysis.
Purpose of the Study:
- To re-evaluate breast tumor molecular classification using integrated gene expression and DNA methylation data.
- To identify novel prognostic markers and refine subtype definitions, especially within the luminal-A category.
- To improve diagnostic accuracy and guide subtype-specific treatment strategies for breast cancer patients.
Main Methods:
- Unsupervised clustering of 1148 RNA-Seq and 679 DNA methylation samples from TCGA.
- Evaluation of clusters against clinical data and PAM50 subtype assignments.
- Differential gene expression and methylation analysis, followed by enrichment testing and survival analysis (log-rank test, Cox model).
Main Results:
- Clustering showed moderate agreement with PAM50, but novel luminal partitions demonstrated superior five-year prognostic value.
- Luminal-A samples were divided into two subgroups based on gene expression, with one showing higher recurrence risk due to immune gene differences.
- Methylation analysis identified a poorer survival cluster within luminal-A, characterized by developmental gene hyper-methylation.
- Cox multivariate analysis confirmed the prognostic significance of these partitions, independent of age and pathological stage.
Conclusions:
- Genomic data reveal significant heterogeneity within luminal breast tumors, particularly in the luminal-A subtype.
- Two prognostic gene sets were identified, effectively dissecting tumor variability within luminal-A.
- This research advances subtype-specific diagnosis and treatment by providing refined prognostic tools for breast cancer.
