Gene expression in 16q is associated with survival and differs between Sørlie breast cancer subtypes

Genome and transcriptome delineation of two major oncogenic pathways governing invasive ductal breast cancer development

Invasive ductal carcinoma (IDC) is a major histo-morphologic type of breast cancer. Histological grading (HG) of IDC is widely adopted by oncologists as a prognostic factor. However, HG evaluation is highly subjective with only 50%-85% inter-observer agreements. Specifically, the subjectivity in the assignment of the intermediate grade (histologic grade 2, HG2) breast cancers (comprising ~50% of IDC cases) results in uncertain disease outcome prediction and sub-optimal systemic therapy. Despite several attempts to identify the mechanisms underlying the HG classification, their molecular bases are poorly understood.We performed integrative bioinformatics analysis of TCGA and several other cohorts (total 1246 patients). We identified a 22-gene tumor aggressiveness grading classifier (22g-TAG) that reflects global bifurcation in the IDC transcriptomes and reclassified patients with HG2 tumors into two genetically and clinically distinct subclasses: histological grade 1-like (HG1-like) and histological grade 3-like (HG3-like). The expression profiles and clinical outcomes of these subclasses were similar to the HG1 and HG3 tumors, respectively. We further reclassified IDC into low genetic grade (LGG = HG1+HG1-like) and high genetic grade (HGG = HG3-like+HG3) subclasses. For the HG1-like and HG3-like IDCs we found subclass-specific DNA alterations, somatic mutations, oncogenic pathways, cell cycle/mitosis and stem cell-like expression signatures that discriminate between these tumors. We found similar molecular patterns in the LGG and HGG tumor classes respectively.Our results suggest the existence of two genetically-predefined IDC classes, LGG and HGG, driven by distinct oncogenic pathways. They provide novel prognostic and therapeutic biomarkers and could open unique opportunities for personalized systemic therapies of IDC patients.

Lessons learned from the intrinsic subtypes of breast cancer in the quest for precision therapy

BACKGROUND

Wide variability in breast cancer, between patients and within each individual neoplasm, adds confounding complexity to the treatment of the disease. In clinical practice, hormone receptor status has been used to classify breast tumours and to guide treatment. Modern classification systems should take the wide tumour heterogeneity into account to improve patient outcome.

METHODS

This article reviews the identification of the intrinsic molecular subtypes of breast cancer, their prognostic and therapeutic implications, and the impact of tumour heterogeneity on cancer progression and treatment. The possibility of functionally addressing tumour-specific characteristics in in vivo models to inform decisions for precision therapies is also discussed.

RESULTS

Despite the robust breast tumour classification system provided by gene expression profiling, heterogeneity is also evident within these molecular portraits. A complicating factor in breast cancer classification is the process of selective clonality within developing neoplasms. Phenotypically and functionally distinct clones representing the intratumour heterogeneity might confuse molecular classification. Molecular portraits of the heterogeneous primary tumour might not necessarily reflect the subclone of cancer cells that causes the disease to relapse. Studies of reciprocal relationships between cancer cell subpopulations within developing tumours are therefore needed, and are possible only in genetically engineered mouse models or patient-derived xenograft models, in which the treatment-induced selection pressure on individual cell clones can be mimicked.

CONCLUSION

In the future, more refined classifications, based on integration of information at several molecular levels, are required to improve treatment guidelines. Large-scale translational research efforts paved the way for identification of the intrinsic subtypes, and are still fundamental for ensuring future progress in cancer care.

Analysis of copy number changes on chromosome 16q in male breast cancer by multiplex ligation-dependent probe amplification

Gene copy number changes have an important role in carcinogenesis and could serve as potential biomarkers for prognosis and targets for therapy. Copy number changes mapping to chromosome 16 have been reported to be the most frequent alteration observed in female breast cancer and a loss on 16q has been shown to be associated with low grade and better prognosis. In the present study, we aimed to characterize copy number changes on 16q in a group of 135 male breast cancers using a novel multiplex ligation-dependent probe amplification kit. One hundred and twelve out of 135 (83%) male breast cancer showed copy number changes of at least one gene on chromosome 16, with frequent loss of 16q (71/135; 53%), either partial (66/135; 49%) or whole arm loss (5/135; 4%). Losses on 16q were thereby less often seen in male breast cancer than previously described in female breast cancer. Loss on 16q was significantly correlated with favorable clinicopathological features such as negative lymph node status, small tumor size, and low grade. Copy number gain of almost all genes on the short arm was also significantly correlated with lymph node negative status. A combination of 16q loss and 16p gain correlated even stronger with negative lymph node status (n=112; P=0.012), which was also underlined by unsupervised clustering. In conclusion, copy number loss on 16q is less frequent in male breast cancer than in female breast cancer, providing further evidence that male breast cancer and female breast cancer are genetically different. Gain on 16p and loss of 16q identify a group of male breast cancer with low propensity to develop lymph node metastases.

Influence of whole arm loss of chromosome 16q on gene expression patterns in oestrogen receptor-positive, invasive breast cancer

A whole chromosome arm loss of 16q belongs to the most frequent and earliest chromosomal alterations in invasive and in situ breast cancers of all common subtypes. Besides E-cadherin, several putative tumour suppressor genes residing on 16q in breast cancer have been investigated. However, the significance of these findings has remained unclear. Thus, other mechanisms leading to gene loss of function (eg haploinsufficiency, or distortion of multiple regulative subnetworks) remain to be tested as a hypothesis. To define the effect on gene expression of whole-arm loss of chromosome 16q in invasive breast cancer, we performed global gene expression analysis on a series of 18 genetically extensively characterized invasive ductal breast carcinomas and verified the results by quantitative real-time PCR (qRT-PCR). The distribution of the differential genes across the genome and their expression status was studied. A second approach by qRT-PCR in an independent series of 30 breast carcinomas helped to narrow down the observed effect. Whole-arm chromosome 16q losses, irrespective of other chromosomal changes, are associated with decreased expression of a number of candidate genes located on 16q (eg CDA08, CGI-128, SNTB2, NQO1, SF3B3, KIAA0174, ATBF1, GABARAPL2, KARS, GCSH, MBTPS1 and ZDHHC7) in breast carcinomas with a low degree of genetic instability. qRT-PCR provided evidence to suggest that the expression of these genes was reduced in a gene dosage-dependent manner. The differential expression of the candidate genes according to the chromosomal 16q-status vanished in genetically advanced breast cancer cases and changed ER status. These results corroborate previous reports about the importance of whole-arm loss of chromosome 16q in breast carcinogenesis and give evidence for the first time that haploinsufficiency, in the sense of a gene dosage effect, might be an important contributing factor in the early steps of breast carcinogenesis.

Genomic differences between estrogen receptor (ER)-positive and ER-negative human breast carcinoma identified by single nucleotide polymorphism array comparative genome hybridization analysis

BACKGROUND

Estrogen receptor (ER) remains one of the most important biomarkers for breast cancer subtyping and prognosis, and comparative genome hybridization has greatly contributed to the understanding of global genetic imbalance. The authors used single-nucleotide polymorphism (SNP) arrays to compare overall copy number aberrations (CNAs) as well as loss of heterozygosity (LOH) of the entire human genome in ER-positive and ER-negative breast carcinomas.

METHODS

DNA was extracted from frozen tumor sections of 21 breast carcinoma specimens and analyzed with a proprietary 50K XbaI SNP array. Copy number and LOH probability values were derived for each sample. Data were analyzed using bioinformatics and computational software, and permutation tests were used to estimate the significance of these values.

RESULTS

There was a global increase in CNAs and LOH in ER-negative relative to ER-positive cancers. Gain of the long arm of chromosome 1 (1q) and 8q were the most obvious changes common in both subtypes: An increase in the chromosome 1 short arm (1p)/1q ratio was observed in ER-negative samples, and an increased 16p/16q ratio was observed in ER-positive samples. Significant CNAs (adjusted P<.05) in ER-negative relative to ER-positive tumors included 5q deletion, loss of 15q, and gain of 2p and 21q. Copy-neutral LOH (cnLOH) common to both ER-positive and ER-negative samples included 9p21, the p16 tumor suppressor locus, and 4q13, the RCHY1 (ring finger and CHY zinc finger domain-containing 1) oncogene locus. Of particular interest was an enrichment of 17q LOH among the ER-negative tumors, potentially suggesting breast cancer 1 gene (BRCA1) mutations.

CONCLUSIONS

SNP array detected both genetic imbalances and cnLOH and was capable of discriminating ER-negative breast cancer from ER-positive breast cancer.

Triple negative breast carcinomas: similarities and differences with basal like carcinomas

The cDNA microarrays allows the classification of breast cancers into 6 groups: luminal A, luminal B, luminal C, normal breast-like, human epidermal growth factor receptor 2-positive, and basal-like. This latter is characterized by the expression of basal cytokeratins (CKs), and frequent negativity for hormone receptors and human epidermal growth factor receptor 2. There is a marked parallelism between triple negative breast carcinomas and basal-like carcinoma, but these are not equivalent terms. Estimated concordance is around 80%. CK5 seems to be the best marker for the identification of these tumors. Other good markers to identify these tumors are CK14, CK17, and epidermal growth factor receptor. A subset of triple negative breast carcinomas has myoepithelial differentiation, with positivities for smooth muscle actin, p63, S-100, and CD10 among others. Recent studies suggest that basal like carcinomas are originated from mammary stem cells.

Prognostic and predictive value of 16p12.1 and 16q22.1 copy number changes in human breast cancer

The present study investigated DNA copy number changes mapping to the p and q arms of chromosome 16 in breast cancer with the goal to determine their potential in identifying breast cancer patients with poor prognosis. We identified the minimal overlapping regions on chromosome 16 that are commonly deleted and amplified in breast tumors. Fluorescence in situ hybridization was used to screen a custom-made breast carcinoma tissue microarray representing all tumor grades, in order to detect DNA copy number changes mapping to 16p12.1 and 16q22.1. We generated 16q/16p ratios for each patient and examined the correlation between DNA copy number alterations and the patients' clinical and pathological parameters. We observed lower q/p ratios in grade I invasive carcinomas, compared with grade III carcinomas, which consistently showed high q/p ratios (P < 0.0091 and 0.0075). In addition, age adjusted for grade analysis revealed that tumors from younger patients (<45 yr) had significantly higher q/p ratios, suggesting that in younger individuals those tumors might be more aggressive (P < 0.0001). The finding that higher q/p ratios occur in younger patients offers a tool to identify high-risk individuals most likely to proceed to high grade.

Gene expression meta-analysis identifies chromosomal regions involved in ovarian cancer survival

Ovarian cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth, whereas others are causal for metastasis and recurrence. By using publicly available data sets, we have investigated the relation of gene expression and chromosomal position to identify chromosomal regions of importance for early recurrence of ovarian cancer. By use of *Gene Set Enrichment Analysis*, we have ranked chromosomal regions according to their association to survival. Over-representation analysis including 1-4 consecutive cytogenetic bands identified regions with increased expression for chromosome 5q12-14, and a very large region of chromosome 7 with the strongest signal at 7p15-13 among tumors from short-living patients. Reduced gene expression was identified at 4q26-32, 6p12-q15, 9p21-q32, and 11p14-11. We summarized mutation load in these regions by a combined mutation score that is statistical significantly associated to survival by analysis in the data sets used for identification of the regions. Furthermore, the prognostic value of the combined mutation score was validated in an independent large data set using death (P = 0.015) and recurrence (P = 0.002) as outcome. The combined mutation score is strongly associated to upregulation of several growth factor pathways.

Genome-wide analysis identifies 16q deletion associated with survival, molecular subtypes, mRNA expression, and germline haplotypes in breast cancer patients

Breast carcinomas are characterized by DNA copy number alterations (CNAs) with biological and clinical significance. This explorative study integrated CNA, expression, and germline genotype data of 112 early-stage breast cancer patients. Recurrent CNAs differed substantially between tumor subtypes classified according to expression pattern. Deletion of 16q was overrepresented in Luminal A, and a predictor of good prognosis, both overall and for the nonluminal A subgroups. The deleted region most significantly associated with survival mapped to 16q22.2, harboring the genes TXNL4B and DXH38, whose expression was strongly correlated with the deletion. The area most frequently deleted resided on 16q23.1, 3.5 MB downstream of the area most significantly associated with survival, and included the tumor suppressor gene ADAMTS18 and the cell recognition gene CNTNAP4. Whole-genome association analysis identified germline single nucleotide polymorphisms (SNPs) and their corresponding haplotypes, residing on several different chromosomes, to be associated with deletion of 16q. The genes where these SNPs reside encode proteins involved in the extracellular matrix (CHST3 and SPOCK2), in regulation of the cell cycle (JMY, PTPRN2, and Cwf19L2) and chromosome stability (KPNB1).

Gene expression meta-analysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis

Breast cancer cells exhibit complex karyotypic alterations causing deregulation of numerous genes. Some of these genes are probably causal for cancer formation and local growth whereas others are causal for the various steps of metastasis. In a fraction of tumors deregulation of the same genes might be caused by epigenetic modulations, point mutations or the influence of other genes. We have investigated the relation of gene expression and chromosomal position, using eight datasets including more than 1200 breast tumors, to identify chromosomal regions and candidate genes possibly causal for breast cancer metastasis. By use of "Gene Set Enrichment Analysis" we have ranked chromosomal regions according to their relation to metastasis. Overrepresentation analysis identified regions with increased expression for chromosome 1q41-42, 8q24, 12q14, 16q22, 16q24, 17q12-21.2, 17q21-23, 17q25, 20q11, and 20q13 among metastasizing tumors and reduced gene expression at 1p31-21, 8p22-21, and 14q24. By analysis of genes with extremely imbalanced expression in these regions we identified DIRAS3 at 1p31, PSD3, LPL, EPHX2 at 8p21-22, and FOS at 14q24 as candidate metastasis suppressor genes. Potential metastasis promoting genes includes RECQL4 at 8q24, PRMT7 at 16q22, GINS2 at 16q24, and AURKA at 20q13.

An integrated analysis of genes and pathways exhibiting metabolic differences between estrogen receptor positive breast cancer cells

Background

The sex hormone estrogen (E2) is pivotal to normal mammary gland growth and differentiation and in breast carcinogenesis. In this in silico study, we examined metabolic differences between ER(+)ve breast cancer cells during E2 deprivation.

Methods

Public repositories of SAGE and MA gene expression data generated from E2 deprived ER(+)ve breast cancer cell lines, MCF-7 and ZR75-1 were compared with normal breast tissue. We analyzed gene ontology (GO), enrichment, clustering, chromosome localization, and pathway profiles and performed multiple comparisons with cell lines and tumors with different ER status.

Results

In all GO terms, biological process (BP), molecular function (MF), and cellular component (CC), MCF-7 had higher gene utilization than ZR75-1. Various analyses showed a down-regulated immune function, an up-regulated protein (ZR75-1) and glucose metabolism (MCF-7). A greater percentage of 77 common genes localized to the q arm of all chromosomes, but in ZR75-1 chromosomes 11, 16, and 19 harbored more overexpressed genes. Despite differences in gene utilization (electron transport, proteasome, glycolysis/gluconeogenesis) and expression (ribosome) in both cells, there was an overall similarity of ZR75-1 with ER(-)ve cell lines and ER(+)ve/ER(-)ve breast tumors.

Conclusion

This study demonstrates integral metabolic differences may exist within the same cell subtype (luminal A) in representative ER(+)ve cell line models. Selectivity of gene and pathway usage for strategies such as energy requirement minimization, sugar utilization by ZR75-1 contrasted with MCF-7 cells, expressing genes whose protein products require ATP utilization. Such characteristics may impart aggressiveness to ZR75-1 and may be prognostic determinants of ER(+)ve breast tumors.

Origins of breast cancer subtypes and therapeutic implications

This Review summarizes and evaluates the current evidence for the cellular origins of breast cancer subtypes identified by different approaches such as histology, molecular pathology, genetic and gene-expression analysis. Emerging knowledge of the normal breast cell types has led to the hypothesis that the subtypes of breast cancer might arise from mutations or genetic rearrangements occurring in different populations of stem cells and progenitor cells. We describe the common distinguishing features of these breast cancer subtypes and explain how these features relate both to prognosis and to selection of the most appropriate therapy. Recent data indicate that breast tumors may originate from cancer stem cells. Consequently, inhibition of stem-cell self-renewal pathways should be explored because of the likelihood that residual stem cells might be resistant to current therapies.