Vessela N. Kristensen

Allele-specific copy number analysis of tumors

We present an allele-specific copy number analysis of the in vivo breast cancer genome. We describe a unique bioinformatics approach, ASCAT (allele-specific copy number analysis of tumors), to accurately dissect the allele-specific copy number of solid tumors, simultaneously estimating and adjusting for both tumor ploidy and nonaberrant cell admixture. This allows calculation of “ASCAT profiles” (genome-wide allele-specific copy-number profiles) from which gains, losses, copy number-neutral events, and loss of heterozygosity (LOH) can accurately be determined. In an early-stage breast carcinoma series, we observe aneuploidy (>2.7n) in 45% of the cases and an average nonaberrant cell admixture of 49%. By aggregation of ASCAT profiles across our series, we obtain genomic frequency distributions of gains and losses, as well as genome-wide views of LOH and copy number-neutral events in breast cancer. In addition, the ASCAT profiles reveal differences in aberrant tumor cell fraction, ploidy, gains, losses, LOH, and copy number-neutral events between the five previously identified molecular breast cancer subtypes. Basal-like breast carcinomas have a significantly higher frequency of LOH compared with other subtypes, and their ASCAT profiles show large-scale loss of genomic material during tumor development, followed by a whole-genome duplication, resulting in near-triploid genomes. Finally, from the ASCAT profiles, we construct a genome-wide map of allelic skewness in breast cancer, indicating loci where one allele is preferentially lost, whereas the other allele is preferentially gained. We hypothesize that these alternative alleles have a different influence on breast carcinoma development.

miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors

Introduction Few studies have performed expression profiling of both miRNA and mRNA from the same primary breast carcinomas. In this study we present and analyze data derived from expression profiling of 799 miRNAs in 101 primary human breast tumors, along with genome-wide mRNA profiles and extensive clinical information. Methods We investigate the relationship between these molecular components, in terms of their correlation with each other and with clinical characteristics. We use a systems biology approach to examine the correlative relationship between miRNA and mRNAs using statistical enrichment methods. Results We identify statistical significant differential expression of miRNAs between molecular intrinsic subtypes, and between samples with different levels of proliferation. Specifically, we point to miRNAs significantly associated with TP53 and ER status. We also show that several cellular processes, such as proliferation, cell adhesion and immune response, are strongly associated with certain miRNAs. We validate the role of miRNAs in regulating proliferation using high-throughput lysate-microarrays on cell lines and point to potential drivers of this process. Conclusion This study provides a comprehensive dataset as well as methods and system-level results that jointly form a basis for further work on understanding the role of miRNA in primary breast cancer.

Protein lysate microarray analysis to identify microRNAs regulating estrogen receptor signaling in breast cancer cell lines.

Predicting the impact of microRNAs (miRNAs) on target proteins is challenging because of their different regulatory effects at the transcriptional and translational levels. In this study, we applied a novel protein lysate microarray (LMA) technology to systematically monitor for target protein levels after high-throughput transfections of 319 pre-miRs into breast cancer cells. We identified 21 miRNAs that downregulated the estrogen receptor-α (ERα), as validated by western blotting and quantitative real time–PCR, and by demonstrating the inhibition of estrogen-stimulated cell growth. Five potent ERα-regulating miRNAs, miR-18a, miR-18b, miR-193b, miR-206 and miR-302c, were confirmed to directly target ERα in 3′-untranslated region reporter assays. The gene expression signature that they repressed highly overlapped with that of a small interfering RNA against ERα, and across all the signatures tested, was most closely associated with the repression of known estrogen-induced genes. Furthermore, miR-18a and miR-18b showed higher levels of expression in ERα-negative as compared with ERα-positive clinical tumors. In summary, we present systematic and direct functional evidence of miRNAs inhibiting ERα signaling in breast cancer, and demonstrate the high-throughput LMA technology as a novel, powerful technique in determining the relative impact of various miRNAs on key target proteins and associated cellular processes and pathways.

Principles and methods of integrative genomic analyses in cancer

Combined analyses of molecular data, such as DNA copy-number alteration, mRNA and protein expression, point to biological functions and molecular pathways being deregulated in multiple cancers. Genomic, metabolomic and clinical data from various solid cancers and model systems are emerging and can be used to identify novel patient subgroups for tailored therapy and monitoring. The integrative genomics methodologies that are used to interpret these data require expertise in different disciplines, such as biology, medicine, mathematics, statistics and bioinformatics, and they can seem daunting. The objectives, methods and computational tools of integrative genomics that are available to date are reviewed here, as is their implementation in cancer research.

Genetic variants of CYP19 (aromatase) and breast cancer risk

The effect of a SNP in exon 10 of CYP19 on tumor mRNA levels and splice variants were studied and correlated with clinical parameters and risk of breast cancer. In the vast majority of breast cancers, the estrogen levels modulate the tumor growth and depend on the activity of CYP19. Patients (n=481) and controls (n=236) were genotyped by T-tracks in a single sequencing reaction (SSR). The frequency of TT genotypes was significantly higher in patients versus controls (P=0.007) particularly among those with stage III and IV disease (P=0.004) and with tumors larger than 5 cm (P=0.001). A significant association between presence of the T allele and the level of aromatase mRNA in the tumors was observed (P=0.018), as well as with a switch from adipose promoter to ovary promoter (P=0.004). Previously, we reported a rare polymorphic allele of CYP19 (repeat (TTTA)12) to be significantly more frequent in breast cancer patients than in controls. Here we describe another polymorphism, a C–T substitution in exon 10 of the CYP19 gene which is in strong linkage disequilibrium with the (TTTA)n polymorphism but with higher frequency of the variant allele. Our data suggest that the T-allele of the CYP19 gene is associated with a ‘high activity’ phenotype.

The epigenetics of breast cancer

Epigenetic changes can be defined as stable molecular alterations of a cellular phenotype such as the gene expression profile of a cell that are heritable during somatic cell divisions (and sometimes germ line transmissions) but do not involve changes of the DNA sequence itself. Epigenetic phenomena are mediated by several molecular mechanisms comprising histone modifications, polycomb/trithorax protein complexes, small non‐coding or antisense RNAs and DNA methylation. These different modifications are closely interconnected. Epigenetic regulation is critical in normal growth and development and closely conditions the transcriptional potential of genes. Epigenetic mechanisms convey genomic adaption to an environment thereby ultimately contributing towards given phenotype. In this review we will describe the various aspects of epigenetics and in particular DNA methylation in breast carcinogenesis and their potential application for diagnosis, prognosis and treatment decision.

A rare CYP19 (aromatase) variant may increase the risk of breast cancer

The aromatase P450 (coded by the CYP19 gene) is responsible for the rate limiting step in the metabolism of C19 steroids to estrogens and is expressed in most breast carcinomas. A polymorphic tetranucleotide repeat (TTTA)n in intron 5, about 80 nucleotides downstream of exon 4 has previously been described. The allele frequencies of the polymorphic repeat were studied in series of 182 sporadic and 185 familial breast cancer patients as well as in 252 healthy control individuals. Five different alleles containing 7, 8, 9, 11 and 12-TTTA-repeats were detected. A relatively rare allele (A1) containing the longest repeat (TTTA)12 was found significantly more frequently in breast cancer patients than in control individuals. This indicates that individuals carrying the A1 allele of CYP19 may have an increased risk of developing breast cancer, OR 2.42 (95% confidence interval [CI] 1.03-5.80). The higher frequency was observed in both sporadic and familial patients, although when each of the groups was compared to the control group only a borderline significance was seen. A higher frequency of A1 allele carriers was also found in the group of patients with positive estrogen receptor and progesterone receptor positive tumors. These data suggest that the CYP19 gene may be involved as a low penetrance gene in breast cancer susceptibility.

Tumour hypoxia causes DNA hypermethylation by reducing TET activity

Hypermethylation of the promoters of tumour suppressor genes represses transcription of these genes, conferring growth advantages to cancer cells. How these changes arise is poorly understood. Here we show that the activity of oxygen-dependent ten-eleven translocation (TET) enzymes is reduced by tumour hypoxia in human and mouse cells. TET enzymes catalyse DNA demethylation through 5-methylcytosine oxidation. This reduction in activity occurs independently of hypoxia-associated alterations in TET expression, proliferation, metabolism, hypoxia-inducible factor activity or reactive oxygen species, and depends directly on oxygen shortage. Hypoxia-induced loss of TET activity increases hypermethylation at gene promoters in vitro. In patients, tumour suppressor gene promoters are markedly more methylated in hypoxic tumour tissue, independent of proliferation, stromal cell infiltration and tumour characteristics. Our data suggest that up to half of hypermethylation events are due to hypoxia, with these events conferring a selective advantage. Accordingly, increased hypoxia in mouse breast tumours increases hypermethylation, while restoration of tumour oxygenation abrogates this effect. Tumour hypoxia therefore acts as a novel regulator of DNA methylation.

Frequent aberrant DNA methylation of ABCB1, FOXC1, PPP2R2B and PTEN in ductal carcinoma in situ and early invasive breast cancer

IntroductionDuctal carcinoma in situ (DCIS) is a non-invasive lesion of the breast that is frequently detected by mammography and subsequently removed by surgery. However, it is estimated that about half of the detected lesions would never have progressed into invasive cancer. Identifying DCIS and invasive cancer specific epigenetic lesions and understanding how these epigenetic changes are involved in triggering tumour progression is important for a better understanding of which lesions are at risk of becoming invasive.MethodsQuantitative DNA methylation analysis of ABCB1, CDKN2A/p16INK4a, ESR1, FOXC1, GSTP1, IGF2, MGMT, MLH1, PPP2R2B, PTEN and RASSF1A was performed by pyrosequencing in a series of 27 pure DCIS, 28 small invasive ductal carcinomas (IDCs), 34 IDCs with a DCIS component and 5 normal breast tissue samples. FOXC1, ABCB1, PPP2R2B and PTEN were analyzed in 23 additional normal breast tissue samples. Real-Time PCR expression analysis was performed for FOXC1.ResultsAberrant DNA methylation was observed in all three diagnosis groups for the following genes: ABCB1, FOXC1, GSTP1, MGMT, MLH1, PPP2R2B, PTEN and RASSF1A. For most of these genes, methylation was already present at the DCIS level with the same frequency as within IDCs. For FOXC1 significant differences in methylation levels were observed between normal breast tissue and invasive tumours (P < 0.001). The average DNA methylation levels were significantly higher in the pure IDCs and IDCs with DCIS compared to pure DCIS (P = 0.007 and P = 0.001, respectively). Real-time PCR analysis of FOXC1 expression from 25 DCIS, 23 IDCs and 28 normal tissue samples showed lower gene expression levels of FOXC1 in both methylated and unmethylated tumours compared to normal tissue (P < 0.001). DNA methylation levels of FOXC1, GSTP1, ABCB1 and RASSF1A were higher in oestrogen receptor (ER) positive vs. ER negative tumours; whereas methylation levels of FOXC1, ABCB1, PPP2R2B and PTEN were lower in tumours with a TP53 mutation.ConclusionsQuantitative methylation analysis identified ABCB1, FOXC1, PPP2R2B and PTEN as novel genes to be methylated in DCIS. In particular, FOXC1 showed a significant increase in the methylation frequency in invasive tumours. Low FOXC1 gene expression in both methylated and unmethylated DCIS and IDCs indicates that the loss of its expression is an early event during breast cancer progression.

Integrated molecular profiles of invasive breast tumors and ductal carcinoma in situ (DCIS) reveal differential vascular and interleukin signaling

We use an integrated approach to understand breast cancer heterogeneity by modeling mRNA, copy number alterations, microRNAs, and methylation in a pathway context utilizing the pathway recognition algorithm using data integration on genomic models (PARADIGM). We demonstrate that combining mRNA expression and DNA copy number classified the patients in groups that provide the best predictive value with respect to prognosis and identified key molecular and stromal signatures. A chronic inflammatory signature, which promotes the development and/or progression of various epithelial tumors, is uniformly present in all breast cancers. We further demonstrate that within the adaptive immune lineage, the strongest predictor of good outcome is the acquisition of a gene signature that favors a high T-helper 1 (Th1)/cytotoxic T-lymphocyte response at the expense of Th2-driven humoral immunity. Patients who have breast cancer with a basal HER2-negative molecular profile (PDGM2) are characterized by high expression of protumorigenic Th2/humoral-related genes (24–38%) and a low Th1/Th2 ratio. The luminal molecular subtypes are again differentiated by low or high FOXM1 and ERBB4 signaling. We show that the interleukin signaling profiles observed in invasive cancers are absent or weakly expressed in healthy tissue but already prominent in ductal carcinoma in situ, together with ECM and cell-cell adhesion regulating pathways. The most prominent difference between low and high mammographic density in healthy breast tissue by PARADIGM was that of STAT4 signaling. In conclusion, by means of a pathway-based modeling methodology (PARADIGM) integrating different layers of molecular data from whole-tumor samples, we demonstrate that we can stratify immune signatures that predict patient survival.