Candidate luminal B breast cancer genes identified by genome, gene expression and DNA methylation profiling.

Breast cancers (BCs) of the luminal B subtype are estrogen receptor-positive (ER+), highly proliferative, resistant to standard therapies and have a poor prognosis. To better understand this subtype we compared DNA copy number aberrations (CNAs), DNA promoter methylation, gene expression profiles, and somatic mutations in nine selected genes, in 32 luminal B tumors with those observed in 156 BCs of the other molecular subtypes. Frequent CNAs included 8p11-p12 and 11q13.1-q13.2 amplifications, 7q11.22-q34, 8q21.12-q24.23, 12p12.3-p13.1, 12q13.11-q24.11, 14q21.1-q23.1, 17q11.1-q25.1, 20q11.23-q13.33 gains and 6q14.1-q24.2, 9p21.3-p24,3, 9q21.2, 18p11.31-p11.32 losses. A total of 237 and 101 luminal B-specific candidate oncogenes and tumor suppressor genes (TSGs) presented a deregulated expression in relation with their CNAs, including 11 genes previously reported associated with endocrine resistance. Interestingly, 88% of the potential TSGs are located within chromosome arm 6q, and seven candidate oncogenes are potential therapeutic targets. A total of 100 candidate oncogenes were validated in a public series of 5,765 BCs and the overexpression of 67 of these was associated with poor survival in luminal tumors. Twenty-four genes presented a deregulated expression in relation with a high DNA methylation level. FOXO3, PIK3CA and TP53 were the most frequent mutated genes among the nine tested. In a meta-analysis of next-generation sequencing data in 875 BCs, KCNB2 mutations were associated with luminal B cases while candidate TSGs MDN1 (6q15) and UTRN (6q24), were mutated in this subtype. In conclusion, we have reported luminal B candidate genes that may play a role in the development and/or hormone resistance of this aggressive subtype.

Kinome expression profiling and prognosis of basal breast cancers.

BACKGROUND: Basal breast cancers (BCs) represent ~15% of BCs. Although overall poor, prognosis is heterogeneous. Identification of good- versus poor-prognosis patients is difficult or impossible using the standard histoclinical features and the recently defined prognostic gene expression signatures (GES). Kinases are often activated or overexpressed in cancers, and constitute targets for successful therapies. We sought to define a prognostic model of basal BCs based on kinome expression profiling. METHODS: DNA microarray-based gene expression and histoclinical data of 2515 early BCs from thirteen datasets were collected. We searched for a kinome-based GES associated with disease-free survival (DFS) in basal BCs of the learning set using a metagene-based approach. The signature was then tested in basal tumors of the independent validation set. RESULTS: A total of 591 samples were basal. We identified a 28-kinase metagene associated with DFS in the learning set (N = 73). This metagene was associated with immune response and particularly cytotoxic T-cell response. On multivariate analysis, a metagene-based predictor outperformed the classical prognostic factors, both in the learning and the validation (N = 518) sets, independently of the lymphocyte infiltrate. In the validation set, patients whose tumors overexpressed the metagene had a 78% 5-year DFS versus 54% for other patients (p = 1.62E-4, log-rank test). CONCLUSIONS: Based on kinome expression, we identified a predictor that separated basal BCs into two subgroups of different prognosis. Tumors associated with higher activation of cytotoxic tumor-infiltrative lymphocytes harbored a better prognosis. Such classification should help tailor the treatment and develop new therapies based on immune response manipulation.

Genome profiling of ERBB2-amplified breast cancers.

BACKGROUND: Around 20% of breast cancers (BC) show ERBB2 gene amplification and overexpression of the ERBB2 tyrosine kinase receptor. They are associated with a poor prognosis but can benefit from targeted therapy. A better knowledge of these BCs, genomically and biologically heterogeneous, may help understand their behavior and design new therapeutic strategies. METHODS: We defined the high resolution genome and gene expression profiles of 54 ERBB2-amplified BCs using 244K oligonucleotide array-comparative genomic hybridization and whole-genome DNA microarrays. Expression of ERBB2, phosphorylated ERBB2, EGFR, IGF1R and FOXA1 proteins was assessed by immunohistochemistry to evaluate the functional ERBB2 status and identify co-expressions. RESULTS: First, we identified the ERBB2-C17orf37-GRB7 genomic segment as the minimal common 17q12-q21 amplicon, and CRKRS and IKZF3 as the most frequent centromeric and telomeric amplicon borders, respectively. Second, GISTIC analysis identified 17 other genome regions affected by copy number aberration (CNA) (amplifications, gains, losses). The expression of 37 genes of these regions was deregulated. Third, two types of heterogeneity were observed in ERBB2-amplified BCs. The genomic profiles of estrogen receptor-positive (ER+) and negative (ER-) ERBB2-amplified BCs were different. The WNT/ß-catenin signaling pathway was involved in ER- ERBB2-amplified BCs, and PVT1 and TRPS1 were candidate oncogenes associated with ER+ ERBB2-amplified BCs. The size of the ERBB2 amplicon was different in inflammatory (IBC) and non-inflammatory BCs. ERBB2-amplified IBCs were characterized by the downregulated and upregulated mRNA expression of ten and two genes in proportion to CNA, respectively. IHC results showed (i) a linear relationship between ERBB2 gene amplification and its gene and protein expressions with a good correlation between ERBB2 expression and phosphorylation status; (ii) a potential signaling cross-talk between EGFR or IGF1R and ERBB2, which could influence response of ERBB2-positive BCs to inhibitors. FOXA1 was frequently coexpressed with ERBB2 but its expression did not impact on the outcome of patients with ERBB2-amplified tumors. CONCLUSION: We have shown that ER+ and ER- ERBB2-amplified BCs are different, distinguished ERBB2 amplicons in IBC and non-IBC, and identified genomic features that may be useful in the design of alternative therapeutical strategies.

Combined mutations of ASXL1, CBL, FLT3, IDH1, IDH2, JAK2, KRAS, NPM1, NRAS, RUNX1, TET2 and WT1 genes in myelodysplastic syndromes and acute myeloid leukemias.

BACKGROUND: Gene mutation is an important mechanism of myeloid leukemogenesis. However, the number and combination of gene mutated in myeloid malignancies is still a matter of investigation. METHODS: We searched for mutations in the ASXL1, CBL, FLT3, IDH1, IDH2, JAK2, KRAS, NPM1, NRAS, RUNX1, TET2 and WT1 genes in 65 myelodysplastic syndromes (MDSs) and 64 acute myeloid leukemias (AMLs) without balanced translocation or complex karyotype. RESULTS: Mutations in ASXL1 and CBL were frequent in refractory anemia with excess of blasts. Mutations in TET2 occurred with similar frequency in MDSs and AMLs and associated equally with either ASXL1 or NPM1 mutations. Mutations of RUNX1 were mutually exclusive with TET2 and combined with ASXL1 but not with NPM1. Mutations in FLT3 (mutation and internal tandem duplication), IDH1, IDH2, NPM1 and WT1 occurred primarily in AMLs. CONCLUSION: Only 14% MDSs but half AMLs had at least two mutations in the genes studied. Based on the observed combinations and exclusions we classified the 12 genes into four classes and propose a highly speculative model that at least a mutation in one of each class is necessary for developing AML with simple or normal karyotype.

Absence of R140Q mutation of isocitrate dehydrogenase 2 in gliomas and breast cancers.

Somatic mutations of isocitrate dehydrogenase (IDH)-1 and IDH2 proteins have been described in gliomas. The mutations target the R132 amino acid residue and the R172 residue in IDH1 and IDH2, respectively. The same mutations were observed in acute myeloid leukemias with normal karyotype, but a new mutation in IDH2 (R140Q substitution) was detected in malignant myeloid diseases and appears to be the most frequent IDH mutation in these pathologies. To the best of our knowledge, no study thus far has reported the presence of this R140Q mutation in IDH2 in tumors of the nervous system and breast cancers. We evaluated IDH1 and IDH2 exon 4 in 48 low-grade gliomas, 58 primary glioblastomas and 94 breast cancers to evaluate the frequency of mutation and investigated the R140Q substitution in IDH2. The results were compared to our recently obtained results in hematopoietic diseases. The frequency of IDH1 and IDH2 mutations in our panel of gliomas was similar to previously reported mutations. No IDH2 R140 mutation was observed. Compared to hematopoietic diseases, the IDH2 R172 mutation was also more rare and IDH1 mutations more prominent in tumors of the nervous system. No IDH1 or IDH2 mutation was detected in the 94 breast cancer samples. Thus, the IDH2 R140 mutation appears to be restricted to hematopoietic diseases.