[HTML][HTML] Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis
Annals of oncology, 2018•Elsevier
Background Recent efforts of genome-wide gene expression profiling analyses have
improved our understanding of the biological complexity and diversity of triple-negative
breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely
Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M),
mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is
known regarding the potential driving molecular events within each subtype, their difference …
improved our understanding of the biological complexity and diversity of triple-negative
breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely
Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M),
mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is
known regarding the potential driving molecular events within each subtype, their difference …
Background
Recent efforts of genome-wide gene expression profiling analyses have improved our understanding of the biological complexity and diversity of triple-negative breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is known regarding the potential driving molecular events within each subtype, their difference in survival and response to therapy. Further insight into the underlying genomic alterations is therefore needed.
Patients and methods
This study was carried out using copy-number aberrations, somatic mutations and gene expression data derived from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas. TNBC samples (n = 550) were classified according to Lehmann’s molecular subtypes using the TNBCtype online subtyping tool (http://cbc.mc.vanderbilt.edu/tnbc/).
Results
Each subtype showed significant clinic-pathological characteristic differences. Using a multivariate model, IM subtype showed to be associated with a better prognosis (HR = 0.68; CI = 0.46–0.99; P = 0.043) whereas LAR subtype was associated with a worst prognosis (HR = 1.47; CI = 1.0–2.14; P = 0.046). BL1 subtype was found to be most genomically instable subtype with high TP53 mutation (92%) and copy-number deletion in genes involved in DNA repair mechanism (BRCA2, MDM2, PTEN, RB1 and TP53). LAR tumours were associated with higher mutational burden with significantly enriched mutations in PI3KCA (55%), AKT1 (13%) and CDH1 (13%) genes. M and MSL subtypes were associated with higher signature score for angiogenesis. Finally, IM showed high expression levels of immune signatures and check-point inhibitor genes such as PD1, PDL1 and CTLA4.
Conclusion
Our findings highlight for the first time the substantial genomic heterogeneity that characterize TNBC molecular subtypes, allowing for a better understanding of the disease biology as well as the identification of several candidate targets paving novel approaches for the development of anticancer therapeutics for TNBC.
Elsevier