Project description:Chromosomal breakage followed by faulty DNA repair leads to gene amplifications and deletions in cancers. However, the mere assessment of the extent of genomic changes, amplifications and deletions may reduce the complexity of genomic data observed by array comparative genomic hybridization (array CGH). We present here a novel approach to array CGH data analysis, which focuses on putative breakpoints responsible for rearrangements within the genome.We performed array comparative genomic hybridization in 29 primary tumors from high risk patients with breast cancer. The specimens were flow sorted according to ploidy to increase tumor cell purity prior to array CGH. We describe the number of chromosomal breaks as well as the patterns of breaks on individual chromosomes in each tumor. There were differences in chromosomal breakage patterns between the 3 clinical subtypes of breast cancers, although the highest density of breaks occurred at chromosome 17 in all subtypes, suggesting a particular proclivity of this chromosome for breaks. We also observed chromothripsis affecting various chromosomes in 41% of high risk breast cancers.Our results provide a new insight into the genomic complexity of breast cancer. Genomic instability dependent on chromosomal breakage events is not stochastic, targeting some chromosomes clearly more than others. We report a much higher percentage of chromothripsis than described previously in other cancers and this suggests that massive genomic rearrangements occurring in a single catastrophic event may shape many breast cancer genomes.
Project description:Distinct molecular subtypes of breast carcinomas have been identified, but translation into clinical use has been limited. We have developed two platform-independent algorithms to explore genomic architectural distortion using array comparative genomic hybridization data to measure (i) whole-arm gains and losses [whole-arm aberration index (WAAI)] and (ii) complex rearrangements [complex arm aberration index (CAAI)]. By applying CAAI and WAAI to data from 595 breast cancer patients, we were able to separate the cases into eight subgroups with different distributions of genomic distortion. Within each subgroup data from expression analyses, sequencing and ploidy indicated that progression occurs along separate paths into more complex genotypes. Histological grade had prognostic impact only in the luminal-related groups, whereas the complexity identified by CAAI had an overall independent prognostic power. This study emphasizes the relation among structural genomic alterations, molecular subtype, and clinical behavior and shows that objective score of genomic complexity (CAAI) is an independent prognostic marker in breast cancer.
Project description:We used a combination of spectral karyotyping, array comparative genomic hybridization, and cDNA microarrays to gain insights into the structural and functional changes of the genome in the MCF10 human breast cancer progression model cell lines. Spectral karyotyping data showed several chromosomal aberrations and array comparative genomic hybridization analysis identified numerous genomic gains and losses that might be involved in the progression toward cancer. Analysis of the expression levels of genes located within these genomic regions revealed a lack of correlation between chromosomal gains and losses and corresponding up-regulation or down-regulation for the majority of the approximately 1,000 genes analyzed in this study. We conclude that other mechanisms of gene regulation that are not directly related to chromosomal gains and losses play a major role in breast cancer progression.
Project description:Age is one of the most important risk factors for human malignancies, including breast cancer; in addition, age at diagnosis has been shown to be an independent indicator of breast cancer prognosis. Except for inherited forms of breast cancer, however, there is little genetic or epigenetic understanding of the biological basis linking aging with sporadic breast cancer incidence and its clinical behavior.DNA and RNA samples from matched estrogen receptor (ER)-positive sporadic breast cancers diagnosed in either younger (age <or= 45 years) or older (age >or= 70 years) Caucasian women were analyzed by array comparative genomic hybridization and by expression microarrays. Array comparative genomic hybridization data were analyzed using hierarchical clustering and supervised age cohort comparisons. Expression microarray data were analyzed using hierarchical clustering and gene set enrichment analysis; differential gene expression was also determined by conditional permutation, and an age signature was derived using prediction analysis of microarrays.Hierarchical clustering of genome-wide copy-number changes in 71 ER-positive DNA samples (27 younger women, 44 older women) demonstrated two age-independent genotypes; one with few genomic changes other than 1q gain/16q loss, and another with amplifications and low-level gains/losses. Age cohort comparisons showed no significant differences in total or site-specific genomic breaks and amplicon frequencies. Hierarchical clustering of 5.1 K genes variably expressed in 101 ER-positive RNA samples (53 younger women, 48 older women) identified six transcriptome subtypes with an apparent age bias (P < 0.05). Samples with higher expression of a poor outcome-associated proliferation signature were predominantly (65%) younger cases. Supervised analysis identified cancer-associated genes differentially expressed between the cohorts; with younger cases expressing more cell cycle genes and more than threefold higher levels of the growth factor amphiregulin (AREG), and with older cases expressing higher levels of four different homeobox (HOX) genes in addition to ER (ESR1). An age signature validated against two other independent breast cancer datasets proved to have >80% accuracy in discerning younger from older ER-positive breast cancer cases with characteristic differences in AREG and ESR1 expression.These findings suggest that epigenetic transcriptome changes, more than genotypic variation, account for age-associated differences in sporadic breast cancer incidence and prognosis.
Project description:Genomic copy number alterations (CNA) are common in breast cancer. Identifying characteristic CNAs associated with specific breast cancer subtypes is a critical step in defining potential mechanisms of disease initiation and progression. We used genome-wide array comparative genomic hybridization to identify distinctive CNAs in breast cancer subtypes from 259 young (diagnosed with breast cancer at <55 years) African American (AA) and Caucasian American (CA) women originally enrolled in a larger population-based study. We compared the average frequency of CNAs across the whole genome for each breast tumor subtype and found that estrogen receptor (ER)-negative tumors had a higher average frequency of genome-wide gain (P < 0.0001) and loss (P = 0.02) compared to ER-positive tumors. Triple-negative (TN) tumors had a higher average frequency of genome-wide gain (P < 0.0001) and loss (P = 0.003) than non-TN tumors. No significant difference in CNA frequency was observed between HER2-positive and -negative tumors. We also identified previously unreported recurrent CNAs (frequency >40%) for TN breast tumors at 10q, 11p, 11q, 16q, 20p, and 20q. In addition, we report CNAs that differ in frequency between TN breast tumors of AA and CA women. This is of particular relevance because TN breast cancer is associated with higher mortality and young AA women have higher rates of TN breast tumors compared to CA women. These data support the possibility that higher overall frequency of genomic alteration events as well as specific focal CNAs in TN breast tumors might contribute in part to the poor breast cancer prognosis for young AA women.
Project description:In situ detection of genomic alterations in cancer provides information at the single cell level, making it possible to investigate genomic changes in cells in a tissue context. Such topological information is important when studying intratumor heterogeneity as well as alterations related to different steps in tumor progression. We developed a quantitative multigene fluorescence in situ hybridization (QM FISH) method to detect multiple genomic regions in single cells in complex tissues. As a "proof of principle" we applied the method to breast cancer samples to identify partners in whole arm (WA) translocations. WA gain of chromosome arm 1q and loss of chromosome arm 16q are among the most frequent genomic events in breast cancer. By designing five specific FISH probes based on breakpoint information from comparative genomic hybridization array (aCGH) profiles, we visualized chromosomal translocations in clinical samples at the single cell level. By analyzing aCGH data from 295 patients with breast carcinoma with known molecular subtype, we found concurrent WA gain of 1q and loss of 16q to be more frequent in luminal A tumors compared to other molecular subtypes. QM FISH applied to a subset of samples (n = 26) identified a derivative chromosome der(1;16)(q10;p10), a result of a centromere-close translocation between chromosome arms 1q and 16p. In addition, we observed that the distribution of cells with the translocation varied from sample to sample, some had a homogenous cell population while others displayed intratumor heterogeneity with cell-to-cell variation. Finally, for one tumor with both preinvasive and invasive components, the fraction of cells with translocation was lower and more heterogeneous in the preinvasive tumor cells compared to the cells in the invasive component.
Project description:Lymph-node metastasis (LNM) predict high recurrence rates in breast cancer patients. Systemic treatment aims to eliminate (micro)metastatic cells. However decisions regarding systemic treatment depend largely on clinical and molecular characteristics of primary tumours. It remains, however, unclear to what extent metastases resemble the cognate primary breast tumours, especially on a genomic level, and as such will be eradicated by the systemic therapy chosen. In this study we used high-resolution aCGH to investigate DNA copy number differences between primary breast cancers and their paired LNMs. To date, no recurrent LNM-specific genomic aberrations have been identified using array comparative genomic hybridization (aCGH) analysis. In our study we employ a high-resolution platform and we stratify on different breast cancer subtypes, both aspects that might have underpowered previously performed studies.To test the possibility that genomic instability in triple-negative breast cancers (TNBCs) might cause increased random and potentially also recurrent copy number aberrations (CNAs) in their LNMs, we studied 10 primary TNBC-LNM pairs and 10 ER-positive (ER+) pairs and verified our findings adding additionally 5 TNBC-LNM and 22 ER+-LNM pairs. We found that all LNMs clustered nearest to their matched tumour except for two cases, of which one was due to the presence of two distinct histological components in one tumour. We found no significantly altered CNAs between tumour and their LNMs in the entire group or in the subgroups. Within the TNBC subgroup, no absolute increase in CNAs was found in the LNMs compared to their primary tumours, suggesting that increased genomic instability does not lead to more CNAs in LNMs. Our findings suggest a high clonal relationship between primary breast tumours and its LNMs, at least prior to treatment, and support the use of primary tumour characteristics to guide adjuvant systemic chemotherapy in breast cancer patients.
Project description:Genomic DNA copy number aberrations are frequent in solid tumors, although the underlying causes of chromosomal instability in tumors remain obscure. Genes likely to have genomic instability phenotypes when mutated (e.g. those involved in mitosis, replication, repair, and telomeres) are rarely mutated in chromosomally unstable sporadic tumors, even though such mutations are associated with some heritable cancer prone syndromes.We applied array comparative genomic hybridization (CGH) to the analysis of breast tumors. The variation in the levels of genomic instability amongst tumors prompted us to investigate whether alterations in processes/genes involved in maintenance and/or manipulation of the genome were associated with particular types of genomic instability.We discriminated three breast tumor subtypes based on genomic DNA copy number alterations. The subtypes varied with respect to level of genomic instability. We find that shorter telomeres and altered telomere related gene expression are associated with amplification, implicating telomere attrition as a promoter of this type of aberration in breast cancer. On the other hand, the numbers of chromosomal alterations, particularly low level changes, are associated with altered expression of genes in other functional classes (mitosis, cell cycle, DNA replication and repair). Further, although loss of function instability phenotypes have been demonstrated for many of the genes in model systems, we observed enhanced expression of most genes in tumors, indicating that over expression, rather than deficiency underlies instability.Many of the genes associated with higher frequency of copy number aberrations are direct targets of E2F, supporting the hypothesis that deregulation of the Rb pathway is a major contributor to chromosomal instability in breast tumors. These observations are consistent with failure to find mutations in sporadic tumors in genes that have roles in maintenance or manipulation of the genome.
Project description:BACKGROUND: The characterization of copy number alteration patterns in breast cancer requires high-resolution genome-wide profiling of a large panel of tumor specimens. To date, most genome-wide array comparative genomic hybridization studies have used tumor panels of relatively large tumor size and high Nottingham Prognostic Index (NPI) that are not as representative of breast cancer demographics. RESULTS: We performed an oligo-array-based high-resolution analysis of copy number alterations in 171 primary breast tumors of relatively small size and low NPI, which was therefore more representative of breast cancer demographics. Hierarchical clustering over the common regions of alteration identified a novel subtype of high-grade estrogen receptor (ER)-negative breast cancer, characterized by a low genomic instability index. We were able to validate the existence of this genomic subtype in one external breast cancer cohort. Using matched array expression data we also identified the genomic regions showing the strongest coordinate expression changes ('hotspots'). We show that several of these hotspots are located in the phosphatome, kinome and chromatinome, and harbor members of the 122-breast cancer CAN-list. Furthermore, we identify frequently amplified hotspots on 8q22.3 (EDD1, WDSOF1), 8q24.11-13 (THRAP6, DCC1, SQLE, SPG8) and 11q14.1 (NDUFC2, ALG8, USP35) associated with significantly worse prognosis. Amplification of any of these regions identified 37 samples with significantly worse overall survival (hazard ratio (HR) = 2.3 (1.3-1.4) p = 0.003) and time to distant metastasis (HR = 2.6 (1.4-5.1) p = 0.004) independently of NPI. CONCLUSION: We present strong evidence for the existence of a novel subtype of high-grade ER-negative tumors that is characterized by a low genomic instability index. We also provide a genome-wide list of common copy number alteration regions in breast cancer that show strong coordinate aberrant expression, and further identify novel frequently amplified regions that correlate with poor prognosis. Many of the genes associated with these regions represent likely novel oncogenes or tumor suppressors.
Project description:INTRODUCTION: Human epidermal growth factor receptor 2 (HER2)-amplified breast cancer represents a clinically well-defined subgroup due to availability of targeted treatment. However, HER2-amplified tumors have been shown to be heterogeneous at the genomic level by genome-wide microarray analyses, pointing towards a need of further investigations for identification of recurrent copy number alterations and delineation of patterns of allelic imbalance. METHODS: High-density whole genome array-based comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) array data from 260 HER2-amplified breast tumors or cell lines, and 346 HER2-negative breast cancers with molecular subtype information were assembled from different repositories. Copy number alteration (CNA), loss-of-heterozygosity (LOH), copy number neutral allelic imbalance (CNN-AI), subclonal CNA and patterns of tumor DNA ploidy were analyzed using bioinformatical methods such as genomic identification of significant targets in cancer (GISTIC) and genome alteration print (GAP). The patterns of tumor ploidy were confirmed in 338 unrelated breast cancers analyzed by DNA flow cytometry with concurrent BAC aCGH and gene expression data. RESULTS: A core set of 36 genomic regions commonly affected by copy number gain or loss was identified by integrating results with a previous study, together comprising > 400 HER2-amplified tumors. While CNN-AI frequency appeared evenly distributed over chromosomes in HER2-amplified tumors, not targeting specific regions and often < 20% in frequency, the occurrence of LOH was strongly associated with regions of copy number loss. HER2-amplified and HER2-negative tumors stratified by molecular subtypes displayed different patterns of LOH and CNN-AI, with basal-like tumors showing highest frequencies followed by HER2-amplified and luminal B cases. Tumor aneuploidy was strongly associated with increasing levels of LOH, CNN-AI, CNAs and occurrence of subclonal copy number events, irrespective of subtype. Finally, SNP data from individual tumors indicated that genomic amplification in general appears as monoallelic, that is, it preferentially targets one parental chromosome in HER2-amplified tumors. CONCLUSIONS: We have delineated the genomic landscape of CNAs, amplifications, LOH, and CNN-AI in HER2-amplified breast cancer, but also demonstrated a strong association between different types of genomic aberrations and tumor aneuploidy irrespective of molecular subtype.