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Br J Cancer. 2019 Jun;120(12):1129-1136. doi: 10.1038/s41416-019-0486-6. Epub 2019 May 22.

A key genomic subtype associated with lymphovascular invasion in invasive breast cancer.

Author information

1
Nottingham Breast Cancer Research Centre, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
2
Department of General Surgical Science, Gunma University Graduate School of Medicine, Gunma, Japan.
3
Faculty of Medicine, Menoufyia University, Shebin al Kawm, Egypt.
4
Cancer Research UK Cambridge Institute and Department of Oncology, University of Cambridge, Cambridge, UK.
5
Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.
6
Department of Histopathology, St. David's South Austin Medical Center, Austin, TX, USA.
7
Laboratory for Translational Breast Cancer Research, Department of Oncology, KU Leuven, Leuven, Belgium.
8
Biology and Translational Research, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.
9
Department of Pharmacology, Weill Cornell Medicine, New York, NY, USA.
10
Nottingham Breast Cancer Research Centre, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK. Emad.Rakha@nottingham.ac.uk.
11
Faculty of Medicine, Menoufyia University, Shebin al Kawm, Egypt. Emad.Rakha@nottingham.ac.uk.

Abstract

BACKGROUND:

Lymphovascular invasion (LVI) is associated with the development of metastasis in invasive breast cancer (BC). However, the complex molecular mechanisms of LVI, which overlap with other oncogenic pathways, remain unclear. This study, using available large transcriptomic datasets, aims to identify genes associated with LVI in early-stage BC patients.

METHODS:

Gene expression data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort (nā€‰=ā€‰1565) was used as a discovery dataset, and The Cancer Genome Atlas (TCGA; nā€‰=ā€‰854) cohort was used as a validation dataset. Key genes were identified on the basis of differential mRNA expression with respect to LVI status as characterised by histological review. The relationships among LVI-associated genomic subtype, clinicopathological features and patient outcomes were explored.

RESULTS:

A 99-gene set was identified that demonstrated significantly different expression between LVI-positive and LVI-negative cases. Clustering analysis with this gene set further divided cases into two molecular subtypes (subtypes 1 and 2), which were significantly associated with pathology-determined LVI status in both cohorts. The 10-year overall survival of subtype 2 was significantly worse than that of subtype 1.

CONCLUSION:

This study demonstrates that LVI in BC is associated with a specific transcriptomic profile with potential prognostic value.

PMID:
31114020
DOI:
10.1038/s41416-019-0486-6

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