Search

Supplementary Figure legends. supplementary data

Purpose: To explore alterations in gene promoter methylation as a potential cause of acquired drug resistance to doxorubicin or combined treatment with 5-fluorouracil and mitomycin C in human breast cancers.Experimental Design: Paired tumor samples from locally advanced breast cancer patients treated with doxorubicin and 5-fluorouracil-mitomycin C were used in the genome-wide DNA methylation analysis as discovery cohort. An enlarged cohort from the same two prospective studies as those in the discovery cohort was used as a validation set in pyrosequencing analysis.Results: A total of 469 genes were differentially methylated after treatment with doxorubicin and revealed a significant association with canonical pathways enriched for immune cell response and cell-cycle regulating genes including CDKN2A, CCND2, CCNA1, which were also associated to treatment response. Treatment with FUMI resulted in 343 differentially methylated genes representing canonical pathways such as retinoate biosynthesis, gαi signaling, and LXR/RXR activation. Despite the clearly different genes and pathways involved in the metabolism and therapeutic effect of both drugs, 46 genes were differentially methylated before and after treatment with both doxorubicin and FUMI. DNA methylation profiles in genes such as BRCA1, FOXC1, and IGFBP3, and most notably repetitive elements like ALU and LINE1, were associated with TP53 mutations status.Conclusion: We identified and validated key cell-cycle regulators differentially methylated before and after neoadjuvant chemotherapy such as CDKN2A and CCNA1 and reported that methylation patterns of these genes may be potential predictive markers to anthracycline/mitomycine sensitivity. Clin Cancer Res; 20(24); 6357–66. ©2014 AACR.

Supplementary Figure 1. Canonical pathway:Communication between Innate and Adaptive Immune Cells

Supplementary Table 1-6. Supplementary Table 1: Differentially methylated genes and functions of the genes before/after treatment with doxorubicin and FUMI Supplementary Table 2: Ingenuity Pathway analysis Supplementary Table 3: List and function of the 46 differentially methylated genes Supplementary Table 4: List of the 333 differentially methylated genes Supplementary Table 5: Ingenuity Pathway analysis of the 333 differentially methylated genes Supplementary Table 6: Associations between methylation status and TP53 mutation status

Supplementary Data from A Mitochondrial Target Sequence Polymorphism in Manganese Superoxide Dismutase Predicts Inferior Survival in Breast Cancer Patients Treated with Cyclophosphamide

Supplementary Figure 2. Canonical pathway:Gαi Signalling

We have undertaken a systematic haplotype analysis of the positional type of biclusters analysing samples collected from 164 breast cancer patients and 86 women with no known history of breast cancer. We present here the haplotypes and LD patterns in more than 80 genes distributed across all chromosomes and how they differ between cases and controls. We aim by this to 1) identify genes with different haplotype distribution or LD patterns between breast cancer patients and controls and 2) to evaluate the intratumoral mRNA expression patterns in breast cancer associated particularly to the cancer susceptibility haplotypes. A significant difference in haplotype distribution between cases and controls was observed for a total of 35 genes includingABCC1, AKT2, NFKB1, TGFBR2andXRCC4. In addition we see a negative correlation between LD patterns in cases and controls for neighboring markers in 8 genes such asCDKN1A, EPHX1andXRCC1.

Context Chronic fatigue (CF) in breast cancer (BC) survivors is multifactorial and may be caused by immune activation triggered by BC or its treatment. In the Neoadjuvant Avastin in Breast Cancer study, BC patients received neoadjuvant chemotherapy (FEC100→taxane) ± bevacizumab, a monoclonal antibody with fatigue as a potential side effect. Objectives To examine fatigue levels and prevalence of CF before and during chemotherapy and at follow-up, and their associations with C-reactive protein (CRP) and clinical variables. Methods Eighty-four HER2-negative patients with cT2-4N0-3M0 BC responded to questionnaires and had CRP measured before treatment (T0), after FEC100 (T1), after taxanes before surgery (T2), and at two-year follow-up (T3). Results The prevalence of CF increased from 8% at T0 to 36% at T3, P < 0.0001. Fatigue levels peaked during chemotherapy from 12.0 at T0 to 20.0 at T2, and declined to 16.7 at T3, P < 0.001. Women with CF at T3 had higher fatigue levels at T0, T2, and T3 than those without CF (P ≤ 0.01). Psychological distress (P = 0.03) and pain (P = 0.04) at T3 were associated with CF at T3. Only psychological distress remained a significant predictor in multivariate analysis. CRP increased from T0 to T1 (P < 0.01) and declined to baseline values at T3, but changes were not associated with bevacizumab treatment. No association was found between bevacizumab or CRP, and fatigue levels or CF. Conclusion Neither bevacizumab treatment nor low-grade systemic inflammation as measured by CRP was associated with the increased fatigue levels and raised prevalence of CF, observed during and after BC therapy. Increased fatigue levels at baseline and psychological distress at T3 were associated with CF at T3. Reinertsen, Kristin V., et al. "Fatigue During and After Breast Cancer Therapy—A Prospective Study." Journal of pain and symptom management 53.3 (2017): 551-560. © 2016. This manuscript version is made available under the CC-BY-NC-ND 4.0 license.

Breast cancer is a heterogeneous disease for which alterations in DNA methylation patterns have been shown to be of biological and clinical importance. Here we report on the integrated analysis of molecular alterations including the methylation status of 27 gene promoters analyzed by highly quantitative pyrosequencing, and the association to gene expression, germline genotype and clinical parameters including survival. Breast cancer specific deregulation of DNA methylation (both hyper- and hypomethylation) was found in twenty genes including ACVR1, OGG1, IL8 and TFF1. The methylation level in the promoter regions was significantly negatively correlated to gene expression for twelve genes (such as MST1R, ST6GAL1 and TFF1) indicating that a gain of aberrant methylation (hypermethylation) inhibits gene expression. Multiple associations between molecular and clinical parameters were identified, and multivariate statistical analysis demonstrated that methylation was more strongly associated to clinical parameters than gene expression for the investigated genes. The methylation level of BCAP31 and OGG1 showed significant association to survival, and these associations were validated in a larger patient cohort (The Cancer Genome Atlas). Our study provides evidence for the promise of DNA methylation alterations for clinical applications.

Background Detection and localization of genomic alterations and breakpoints are crucial in cancer research. The purpose of this study was to investigate, in a methodological and biological perspective, different female, hormone-dependent cancers to identify common and diverse DNA aberrations, genes, and pathways. Methods In this work, we analyzed tissue samples from patients with breast (n = 112), ovarian (n = 74), endometrial (n = 84), or cervical (n = 76) cancer. To identify genomic aberrations, the Circular Binary Segmentation (CBS) and Piecewise Constant Fitting (PCF) algorithms were used and segmentation thresholds optimized. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was applied to the segmented data to identify significantly altered regions and the associated genes were analyzed by Ingenuity Pathway Analysis (IPA) to detect over-represented pathways and functions within the identified gene sets. Results and Discussion Analyses of high-resolution copy number alterations in four different female cancer types are presented. For appropriately adjusted segmentation parameters the two segmentation algorithms CBS and PCF performed similarly. We identified one region at 8q24.3 with focal aberrations that was altered at significant frequency across all four cancer types. Considering both, broad regions and focal peaks, three additional regions with gains at significant frequency were revealed at 1p21.1, 8p22, and 13q21.33, respectively. Several of these events involve known cancer-related genes, like PPP2R2A, PSCA, PTP4A3, and PTK2. In the female reproductive system (ovarian, endometrial, and cervix [OEC]), we discovered three common events: copy number gains at 5p15.33 and 15q11.2, further a copy number loss at 8p21.2. Interestingly, as many as 75% of the aberrations (75% amplifications and 86% deletions) identified by GISTIC were specific for just one cancer type and represented distinct molecular pathways. Conclusions Our results disclose that some prominent copy number changes are shared in the four examined female, hormone-dependent cancer whereas others are definitive to specific cancer types. Note to Correction: After publication of the original article [1] the authors found that the article contained an incorrect version of Fig. 4. This does not affect the results and conclusions of the article.

Purpose The aim of the study was to identify noninvasive markers of treatment-induced side effects. Reactive oxygen species (ROS) are generated after irradiation, and genetic variation in genes related to ROS metabolism might influence the level of radiation-induced adverse effects (AEs). Methods and Materials 92 breast cancer (BC) survivors previously treated with hypofractionated radiation therapy were assessed for the AEs subcutaneous atrophy and fibrosis, costal fractures, lung fibrosis, pleural thickening, and telangiectasias (median follow-up time 17.1 years). Single-nucleotide polymorphisms (SNPs) in 203 genes were analyzed for association to AE grade. SNPs associated with subcutaneous fibrosis were validated in an independent BC survivor material (n=283). The influence of the studied genetic variation on messenger ribonucleic acid (mRNA) expression level of 18 genes previously associated with fibrosis was assessed in fibroblast cell lines from BC patients. Results Subcutaneous fibrosis and atrophy had the highest correlation ( r =0.76) of all assessed AEs. The nonsynonymous SNP rs1139793 in TXNRD2 was associated with grade of subcutaneous fibrosis, the reference T-allele being more prevalent in the group experiencing severe levels of fibrosis. This was confirmed in another sample cohort of 283 BC survivors, and rs1139793 was found significantly associated with mRNA expression level of TXNRD2 in blood. Genetic variation in 24 ROS-related genes, including EGFR , CENPE , APEX1, and GSTP1, was associated with mRNA expression of 14 genes previously linked to fibrosis ( P ≤.005). Conclusion Development of subcutaneous fibrosis can be associated with genetic variation in the mitochondrial enzyme TXNRD2, critically involved in removal of ROS, and maintenance of the intracellular redox balance.

Withdrawn by Author Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P5-17-02.

In patients with metastatic breast cancer, taxane treatment demonstrates activity but is not curative. Targeted treatment modalities are therefore necessary in order to improve outcomes in this group. A randomized placebo-controlled phase II trial was initiated to evaluate effect and toxicity of gefitinib (250 mg QD) and docetaxel 35 mg/m2(six of seven weeks) (NCT 00319618). The inclusion of 66 patients was planned. The study was closed due to treatment-related toxicity. Of the 18 included patients, seven (of which three received gefitinib) were withdrawn from the study due to toxicity. Of the nine patients receiving gefitinib and chemotherapy, one achieved a partial response and four stable disease. In the chemotherapy of nine patients, four had a partial response and four stable disease. The breast cancer patients in this study were genotyped using a panel of 14 single-nucleotide polymorphisms (SNPs), previously found associated with docetaxel clearance in a cohort of lung cancer patients. We were unable to identify genes related to toxicity in this study. Nevertheless, toxicity was aggravated by the addition of the tyrosine kinase inhibitor. In conclusion, despite adequately tolerated as monotherapy, combination regimens should be carefully considered for overlapping adverse events in order to avoid increased treatment-related toxicity.

SummaryMDM2 plays a key role in modulating p53 function. The MDM2 SNP309T > G promoter polymorphism enhances Sp1 binding and has been linked to cancer risk and young age at diagnosis although with conflicting evidence. We report a second MDM2 promoter polymorphism, SNP285G > C, residing on the SNP309G allele. SNP285C occurs in Caucasians only, where 7.7% (95% CI 7.6%–7.8%) of healthy individuals carry the SNP285C/309G haplotype. In vitro analyses reveals that SNP309G enhances but SNP285C strongly reduces Sp1 promoter binding. Comparing MDM2 promoter status among different cohorts of ovarian (n = 1993) and breast (n = 1973) cancer patients versus healthy controls (n = 3646), SNP285C reduced the risk of both ovarian (OR 0.74; CI 0.58–0.94) and breast cancer (OR 0.79; CI 0.62–1.00) among SNP309G carriers.

Breast cancer is a heterogeneous disease that can be divided in subtypes based on histology, gene expression profiles as well as differences in genomic aberrations. Distinct global DNA methylation profiles have been reported in normal breast epithelial cells as well as in breast tumors. However, the influence of the tumor methylome on the previously described subgroups of breast cancer is not fully understood. Here we report the DNA methylation profiles of 80 breast tumors using a panel of 807 cancer related genes interrogating 1505 CpG sites. We identified three major clusters based on the methylation profiles; one consisting of mainly tumors of myoepithelial origin and two other clusters with tumors of predominantly luminal epithelial origin. The clusters were different with respect to estrogen receptor status, TP53 status, ErbB2 status and grade. The most significantly differentially methylated genes including HDAC1, TFF1, OGG1, BMP3, FZD9 and HOXA11 were confirmed by pyrosequencing. Gene Ontology analysis revealed enrichment for genes involved in developmental processes including homeobox domain genes (HOXA9, HOXA11, PAX6, MYBL2, ISL1 and IPF1) and (ETS1, HDAC1, CREBBP, GAS7, SPI1 and TBX1). Extensive correlation to mRNA expression was observed. Pathway analyses identified a significant association with canonical (curated) pathways such as hepatic fibrosis including genes like EGF, NGFR and TNF, dendritic cell maturation and the NF‐κB signaling pathway. Our results show that breast tumor expression subtypes harbor major epigenetic differences and tumors with similar gene expression profiles might belong to epigenetically different subtypes. Some of the transcription factors identified, with key roles in differentiation and development might play a role in inducing and maintaining the different phenotypes.

Fatigue is a common symptom and includes both physical and mental components. It can be associated with a variety of different syndromes and diseases, but in many cases is not associated with other comorbid conditions. Most humans have experienced acute fatigue in relation to different stressors. Acute fatigue typically decreases as the effect of the triggering factor is reduced and a normal homeostatic balance is restored. Fatigue that persists for 6 months or more is termed chronic fatigue. Chronic fatigue (CF) in combination with a minimum of 4 of 8 symptoms and the absence of diseases that could explain these symptoms, constitute the case definition for chronic fatigue syndrome. In spite of its prevalence, the biology of fatigue is relatively poorly understood and biological markers have not yet been identified. This literature search was performed in PubMed to identify research on the genetics and epigenetics of fatigue. Publications were included if fatigue was a major topic and the topic was combined with genetic and/or epigenetic measurements in adult humans. A total of 40 publications were identified. Although altered functioning in the hypothalamic-pituitary-adrenal axis, the serotonergic system, and associations with infectious agents have been identified, the search for genetic or epigenetic markers of fatigue, either in the context of CF or chronic fatigue syndrome (CFS) has been relatively unproductive or, in the case of epigenetics, nonexistent. Although several studies, both hypothesis-testing and hypothesis-generating, have been performed to search for biomarkers, they have mostly been underpowered, restricted by the heterogeneity of the phenotype, or limited by an unsystematic study design. To be able to confirm the hypothesis that risk for, or levels of, fatigue are influenced by the genetic or epigenetic background of an individual, studies need to be based on larger sample sizes with a more clearly defined phenotype. Studies need to focus not only on the influence of a single aspect such as single nucleotide polymorphisms (SNPs) or differential gene expression on disease risk or state, but also on the systems biology behind the disease in combination with information on environmental influences and validation of findings in functional studies.

The dose of docetaxel is currently calculated based on body surface area and does not reflect the pharmacokinetic, metabolic potential or genetic background of the patients. The influence of genetic variation on the clearance of docetaxel was analysed in a two-stage analysis. In step one, 583 single-nucleotide polymorphisms (SNPs) in 203 genes were genotyped on samples from 24 patients with locally advanced non-small cell lung cancer. We found that many of the genes harbour several SNPs associated with clearance of docetaxel. Most notably these were four SNPs in EGF, three SNPs in PRDX4 and XPC, and two SNPs in GSTA4, TGFBR2, TNFAIP2, BCL2, DPYD and EGFR. The multiple SNPs per gene suggested the existence of common haplotypes associated with clearance. These were confirmed with detailed haplotype analysis. On the basis of analysis of variance (ANOVA), quantitative mutual information score (QMIS) and Kruskal–Wallis (KW) analysis SNPs significantly associated with clearance of docetaxel were confirmed for GSTA4, PRDX4, TGFBR2 and XPC and additional putative markers were found in CYP2C8, EPHX1, IGF2, IL1R2, MAPK7, NDUFB4, TGFBR3, TPMT (2 SNPs), (P

Purpose: Manganese superoxide dismutase protects against oxidative damage and modulates the efficacy of chemotherapeutic drugs. A functional single-nucleotide polymorphism in codon 16 of SOD2 (rs4880), which encodes manganese superoxide dismutase, results in a substitution of valine by alanine (Val16Ala). We hypothesized that this single-nucleotide polymorphism affects breast cancer survival of patients receiving chemotherapy.Experimental Design: Two patient populations from the United States (n = 248) and Norway (n = 340) were genotyped for Val16Ala. Kaplan-Meier survival and Cox proportional hazards regression analyses were used to examine the relationship between Val16Ala and disease-specific survival.Results: Val16Ala was significantly associated with breast cancer outcome in both patient populations. Carriers of the Ala allele had inferior survival rates in the multivariate analysis [hazard ratio (HR), 2.44 and 95% confidence interval (95% CI), 1.11-5.37 in U.S. cohort; HR, 1.91 and 95% CI, 1.06-3.45 in Norway cohort for Ala/Ala versus Val/Val]. In an analysis of the combined cohorts, this association was significant for patients receiving adjuvant therapy (HR, 2.47; 95% CI, 1.46-4.19), but not for patients without it (HR, 1.47; 95% CI, 0.57-3.74). After further stratification by type of chemotherapy, the effect of the Ala allele was mostly restricted to cyclophosphamide-containing chemotherapy regimens (HR, 22.0; 95% CI, 5.22-92.9; Ala/Ala versus Val/Val).Conclusion: The Val16Ala polymorphism affects survival of patients receiving cyclophosphamide-containing chemotherapy. The findings provide the first evidence pointing toward a mechanism for cyclophosphamide resistance in breast cancer patients.

The characterization of linkage disequilibrium (LD) is applied in a variety of studies including the identification of molecular determinants of the local recombination rate, the migration and population history of populations, and the role of positive selection in adaptation. LD suffers from the phase uncertainty of the haplotypes used in its calculation, which reflects limitations of the algorithms used for haplotype estimation. We introduce a LD calculation method, which deals with phase uncertainty by weighting all possible haplotype pairs according to their estimated probabilities as evaluated by PHASE. In contrast to the expectation-maximization (EM) algorithm as implemented in the HAPLOVIEWand GENETICS packages, our method considers haplotypes based on the entire genetic information available for the candidate region. We tested the method using simulated and real genotyping data. The results show that, for all practical purposes, the new method is advantageous in comparison with algorithms that calculate LD using only the most probable haplotype or bilocus haplotypes based on the EM algorithm. The new method deals especially well with low LD regions, which contribute strongly to phase uncertainty. Altogether, the method is an attractive alternative to standard LD calculation procedures, including those based on the EM algorithm. We implemented the method in the software suite R, together with an interface to the popular haplotype calculation package PHASE. Genet. Epidemiol. 32: 168–178, 2008. r 2007 Wiley-Liss, Inc.

To explore whether certain glutathione S-transferase (GST) polymorphisms are associated with an increased risk of breast cancer or the level of radiation-induced adverse effects after two fractionation patterns of adjuvant radiotherapy.The prevalence of germline polymorphic variants in GSTM1, GSTP1, and GSTT1 was determined in 272 breast cancer patients and compared with that in a control group of 270 women from the general population with no known history of breast cancer. The genetic variants were determined using multiplex polymerase chain reaction followed by restriction enzyme fragment analysis. In 253 of the patients surveyed for radiotherapy-induced side effects after a median observation time of 13.7 years (range, 7-22.8 years), the genotypes were related to the long-term effects observed after two fractionation patterns (treatment A, 4.3 Gy in 10 fractions for 156 patients; and treatment B, 2.5 Gy in 20 fractions for 97; both administered within a 5-week period).None of the GST polymorphisms conferred an increased risk of breast cancer, either alone or in combination. Compared with treatment B, treatment A was followed by an increased level of moderate to severe radiation-induced side effects for all the endpoints studied (i.e., degree of telangiectasia, subcutaneous fibrosis and atrophy, lung fibrosis, costal fractures, and pleural thickening; p0.001 for all endpoints). A significant association was found between the level of pleural thickening and the GSTP1 Ile105Val variant.The results of this study have illustrated the impact of hypofractionation on the level of adverse effects and indicated that the specific alleles of GSTP1, M1, and T1 studied here may be significant in determining the level of adverse effects after radiotherapy.

Background: DNA methylation alterations are early events in tumorigenesis and important in the regulation of gene expression in cancer cells. Lung cancer patients have in general a poor prognosis, and a deeper insight into the epigenetic landscape in lung adenocarcinoma tumors and its prognostic implications is needed. Results: We determined whole‐genome DNA methylation profiles of 164 fresh frozen lung adenocarcinoma samples and 19 samples of matched normal lung tissue using the Illumina Infinium 450K array. A large number of differentially methylated CpGs in lung adenocarcinoma tissue were identified, and specific methylation profiles were observed in tumors with mutations in the EGFR‐, KRAS‐ or TP53 genes and according to the patients' smoking status. The methylation levels were correlated with gene expression and both positive and negative correlations were seen. Methylation profiles of the tumor samples identified subtypes of tumors with distinct prognosis, including one subtype enriched for TP53 mutant tumors. A prognostic index based on the methylation levels of 33 CpGs was established, and was significantly associated with prognosis in the univariate analysis using an independent cohort of lung adenocarcinoma patients from The Cancer Genome Atlas project. CpGs in the HOX B and HOX C gene clusters were represented in the prognostic signature. Conclusions: Methylation differences mirror biologically important features in the etiology of lung adenocarcinomas and influence prognosis., Highlights Extensive DNA methylation changes linked to immune signaling.DNA methylation in EGFR‐mutated tumors associated with oncogenic pathways.DNA methylation with both positive and negative correlation with mRNA expression.DNA methylation signature with prognostic information.

TP53 gene mutation is associated with poor prognosis in breast cancer, but additional biomarkers that can further refine the impact of the p53 pathway are needed to achieve clinical utility. In this study, we evaluated a role for the HDMX-S/FL ratio as one such biomarker, based on its association with other suppressor mutations that confer worse prognosis in sarcomas, another type of cancer that is surveilled by p53. We found that HDMX-S/FL ratio interacted with p53 mutational status to significantly improve prognostic capability in patients with breast cancer. This biomarker pair offered prognostic utility that was comparable with a microarray-based prognostic assay. Unexpectedly, the utility tracked independently of DNA-damaging treatments and instead with different tumor metastasis potential. Finally, we obtained evidence that this biomarker pair might identify patients who could benefit from anti-HDM2 strategies to impede metastatic progression. Taken together, our work offers a p53 pathway marker, which both refines our understanding of the impact of p53 activity on prognosis and harbors potential utility as a clinical tool. Cancer Res; 75(4); 698–708. ©2015 AACR.

High throughput expression profiling and genotyping technologies provide the means to study the genetic determinants of population variation in gene expression variation. In this paper we present a general statistical framework for the simultaneous analysis of gene expression data and SNP genotype data measured for the same cohort. The framework consists of methods to associate transcripts with SNPs affecting their expression, algorithms to detect subsets of transcripts that share significantly many associations with a subset of SNPs, and methods to visualize the identified relations. We apply our framework to SNP-expression data collected from 50 breast cancer patients. Our results demonstrate an overabundance of transcript-SNP associations in this data, and pinpoint SNPs that are potential master regulators of transcription. We also identify several statistically significant transcript-subsets with common putative regulators that fall into well-defined functional categories.

Rapid development in the annotation of human genetic variation has increased the numbers of single nucleotide polymorphisms (SNPs) in candidate genes by several orders of magnitude. The selection of both useful target SNPs for disease-gene association studies and SNPs associated with the treatment response is therefore an increasingly challenging task. We describe a workflow for selecting SNPs based on their putative function and frequency in candidate genes extracted from PubMed resources. The annotation of each SNP and its frequency in a Caucasian population was assessed in several databases. Approximately 4000 SNPs were identified from an initial 233 candidate genes. In a case study, we performed actual genotyping of 1030 of these SNPs in 213 genes and obtained 710 successfully genotyped SNPs. Using the flow-chart outlined here, only 87 SNPs were monomorphic (approximately 12%). This study reports the frequency of SNPs in a Caucasian population, selected in silico, using a candidate gene approach and validated by actually genotyping 193 individuals. The selected genotypes represent a valuable set of verified candidate SNPs for pharmacogenetic studies in Caucasian populations.

Purpose: To explore alterations in gene promoter methylation as a potential cause of acquired drug resistance to doxorubicin or combined treatment with 5-fluorouracil and mitomycin C in human breast cancers. Experimental Design: Paired tumor samples from locally advanced breast cancer patients treated with doxorubicin and 5-fluorouracil-mitomycin C were used in the genome-wide DNA methylation analysis as discovery cohort. An enlarged cohort from the same two prospective studies as those in the discovery cohort was used as a validation set in pyrosequencing analysis. Results: A total of 469 genes were differentially methylated after treatment with doxorubicin and revealed a significant association with canonical pathways enriched for immune cell response and cell-cycle regulating genes including CDKN2A, CCND2, CCNA1, which were also associated to treatment response. Treatment with FUMI resulted in 343 differentially methylated genes representing canonical pathways such as retinoate biosynthesis, gαi signaling, and LXR/RXR activation. Despite the clearly different genes and pathways involved in the metabolism and therapeutic effect of both drugs, 46 genes were differentially methylated before and after treatment with both doxorubicin and FUMI. DNA methylation profiles in genes such as BRCA1, FOXC1, and IGFBP3, and most notably repetitive elements like ALU and LINE1, were associated with TP53 mutations status. Conclusion: We identified and validated key cell-cycle regulators differentially methylated before and after neoadjuvant chemotherapy such as CDKN2A and CCNA1 and reported that methylation patterns of these genes may be potential predictive markers to anthracycline/mitomycine sensitivity. Clin Cancer Res; 20(24); 6357–66. ©2014 AACR.

Radiotherapy (RT) is a central treatment modality for breast cancer patients. The purpose of our study was to investigate the DNA methylation changes in tumors following RT, and to identify epigenetic markers predicting treatment outcome. Paired biopsies from patients with inoperable breast cancer were collected both before irradiation (n = 20) and after receiving 10-24 Gray (Gy) (n = 19). DNA methylation analysis was performed by using Illumina Infinium 27K arrays. Fourteen genes were selected for technical validation by pyrosequencing. Eighty-two differentially methylated genes were identified in irradiated (n = 11) versus nonirradiated (n = 19) samples (false discovery rate, FDR = 1.1%). Methylation levels in pathways belonging to the immune system were most altered after RT. Based on methylation levels before irradiation, a panel of five genes (H2AFY, CTSA, LTC4S, IL5RA and RB1) were significantly associated with clinical response (p = 0.041). Furthermore, the degree of methylation changes for 2,516 probes correlated with the given radiation dose. Within the 2,516 probes, an enrichment for pathways involved in cellular immune response, proliferation and apoptosis was identified (FDR < 5%). Here, we observed clear differences in methylation levels induced by radiation, some associated with response to treatment. Our study adds knowledge on the molecular mechanisms behind radiation response.

Background Ductal carcinoma in situ (DCIS) of the breast is a precursor of invasive breast carcinoma. DNA methylation alterations are thought to be an early event in progression of cancer, and may prove valuable as a tool in clinical decision making and for understanding neoplastic development. Results We generate genome-wide DNA methylation profiles of 285 breast tissue samples representing progression of cancer, and validate methylation changes between normal and DCIS in an independent dataset of 15 normal and 40 DCIS samples. We also validate a prognostic signature on 583 breast cancer samples from The Cancer Genome Atlas. Our analysis reveals that DNA methylation profiles of DCIS are radically altered compared to normal breast tissue, involving more than 5,000 genes. Changes between DCIS and invasive breast carcinoma involve around 1,000 genes. In tumors, DNA methylation is associated with gene expression of almost 3,000 genes, including both negative and positive correlations. A prognostic signature based on methylation level of 18 CpGs is associated with survival of breast cancer patients with invasive tumors, as well as with survival of patients with DCIS and mixed lesions of DCIS and invasive breast carcinoma. Conclusions This work demonstrates that changes in the epigenome occur early in the neoplastic progression, provides evidence for the possible utilization of DNA methylation-based markers of progression in the clinic, and highlights the importance of epigenetic changes in carcinogenesis. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0435-x) contains supplementary material, which is available to authorized users.

Background Aberrant DNA methylation of regulatory genes has frequently been found in human breast cancers and correlated to clinical outcome. In the present study we investigate stage specific changes in the DNA methylation patterns in order to identify valuable markers to understand how these changes affect breast cancer progression. Methods Quantitative DNA methylation analyses of 12 candidate genes ABCB1, BRCCA1, CDKN2A, ESR1, GSTP1, IGF2, MGMT, HMLH1, PPP2R2B, PTEN, RASSF1A and FOXC1 was performed by pyrosequencing a series of 238 breast cancer tissue samples from DCIS to invasive tumors stage I to IV. Results Significant differences in methylation levels between the DCIS and invasive stage II tumors were observed for six genes RASSF1A, CDKN2A, MGMT, ABCB1, GSTP1 and FOXC1. RASSF1A, ABCB1 and GSTP1 showed significantly higher methylation levels in late stage compared to the early stage breast carcinoma. Z-score analysis revealed significantly lower methylation levels in DCIS and stage I tumors compared with stage II, III and IV tumors. Methylation levels of PTEN, PPP2R2B, FOXC1, ABCB1 and BRCA1 were lower in tumors harboring TP53 mutations then in tumors with wild type TP53. Z-score analysis showed that TP53 mutated tumors had significantly lower overall methylation levels compared to tumors with wild type TP53. Methylation levels of RASSF1A, PPP2R2B, GSTP1 and FOXC1 were higher in ER positive vs. ER negative tumors and methylation levels of PTEN and CDKN2A were higher in HER2 positive vs. HER2 negative tumors. Z-score analysis also showed that HER2 positive tumors had significantly higher z-scores of methylation compared to the HER2 negative tumors. Univariate survival analysis identifies methylation status of PPP2R2B as significant predictor of overall survival and breast cancer specific survival. Conclusions In the present study we report that the level of aberrant DNA methylation is higher in late stage compared with early stage of invasive breast cancers and DCIS for genes mentioned above.

Breast cancer is a heterogeneous disease for which alterations in DNA methylation patterns have been shown to be of biological and clinical importance. Here we report on the integrated analysis of molecular alterations including the methylation status of 27 gene promoters analyzed by highly quantitative pyrosequencing, and the association to gene expression, germline genotype and clinical parameters including survival. Breast cancer specific deregulation of DNA methylation (both hyper- and hypomethylation) was found in twenty genes including ACVR1, OGG1, IL8 and TFF1. The methylation level in the promoter regions was significantly negatively correlated to gene expression for twelve genes (such as MST1R, ST6GAL1 and TFF1) indicating that a gain of aberrant methylation (hypermethylation) inhibits gene expression. Multiple associations between molecular and clinical parameters were identified, and multivariate statistical analysis demonstrated that methylation was more strongly associated to clinical parameters than gene expression for the investigated genes. The methylation level of BCAP31 and OGG1 showed significant association to survival, and these associations were validated in a larger patient cohort (The Cancer Genome Atlas). Our study provides evidence for the promise of DNA methylation alterations for clinical applications.

Introduction We investigated the effect of genetic variation on gene expression in blood from a cohort of BC survivors. Further, we investigated the associations that were specific for BC survivors by performing identical analyses for a group of healthy women and comparing the results. Methods eQTL analysis was performed for 288 BC survivors (full data set). Further, using a subset of the data, eQTL analyses were performed on 288 BC survivors and on 81 healthy women separately and results were compared. Results A large number of associations were observed for the BC survivors, and the expression of human leukocyte antigen genes was found associated with SNPs in 100 genes. The comparison analyses with healthy women revealed associations occurring specifically in BC survivors, and the genes showed enrichment for immune system processes. Conclusions The results suggest that the immune system has a different constitution in BC survivors compared to healthy women.

Background: The ABCB1 gene encodes P-glycoprotein implicated in the development of cellular drug resistance. The aim of this study was to develop high-resolution melting (HRM) analysis for determination of ABCB1 polymorphisms and evaluate their associations with clinical data of breast carcinoma patients. Methods: HRM analysis was designed to assess five single nucleotide polymorphisms (SNPs) in ABCB1 (rs2214102, rs1128503, rs2032582, rs2032583 and rs1045642) in genomic DNA from 103 breast carcinoma patients. Results were confirmed by direct DNA sequencing. Results: HRM analysis revealed distinct patterns of melting curves for the respective genotypes of all followed SNPs. Sensitivity of HRM analysis compared with direct DNA sequencing was superior (97.1% vs. 93.9%). The overall accuracy of HRM was 97.6%. The coefficients of variation in replicate experiments encompassed the range 0.002%–0.038%. On the basis of the examined SNPs, one strong haplotype block containing rs2032582 and rs1128503 SNPs was identified. Significant associations of rs2032582 SNP with tumor size, negative HER-2/neu status, and family history of breast carcinoma were found. Patients carrying the ancestral homozygous genotype (GG) in rs2214102 had significantly worse progression-free survival in comparison with carriers of the non-ancestral allele (A) in the adjuvant set (p=0.005). Conclusions: A rapid, accurate, low-cost and time-effective method for screening ABCB1 SNPs was developed. Significant associations of ABCB1 rs2032582 and rs2214102 SNPs with prognostic factors and survival of patients were found.

Background In a cancer cell the number of copies of a locus may vary due to amplification and deletion and these variations are denoted as copy number alterations (CNAs). We focus on the disparity of CNAs in tumour samples, which were compared to those in blood in order to identify the directional loss of heterozygosity. Methods We propose a numerical algorithm and apply it to data from the Illumina 109K-SNP array on 112 samples from breast cancer patients. B-allele frequency (BAF) and log R ratio (LRR) of Illumina were used to estimate Euclidian distances. For each locus, we compared genotypes in blood and tumour for subset of samples being heterozygous in blood. We identified loci showing preferential disparity from heterozygous toward either the A/B-allele homozygous (allelic disparity). The chi-squared and Cochran-Armitage trend tests were used to examine whether there is an association between high levels of disparity in single nucleotide polymorphisms (SNPs) and molecular, clinical and tumour-related parameters. To identify pathways and network functions over-represented within the resulting gene sets, we used Ingenuity Pathway Analysis (IPA). Results To identify loci with a high level of disparity, we selected SNPs 1) with a substantial degree of disparity and 2) with substantial frequency (at least 50% of the samples heterozygous for the respective locus). We report the overall difference in disparity in high-grade tumours compared to low-grade tumours (p-value < 0.001) and significant associations between disparity in multiple single loci and clinical parameters. The most significantly associated network functions within the genes represented in the loci of disparity were identified, including lipid metabolism, small-molecule biochemistry, and nervous system development and function. No evidence for over-representation of directional disparity in a list of stem cell genes was obtained, however genes appeared to be more often altered by deletion than by amplification. Conclusions Our data suggest that directional loss and amplification exist in breast cancer. These are highly associated with grade, which may indicate that they are enforced with increasing number of cell divisions. Whether there is selective pressure for some loci to be preferentially amplified or deleted remains to be confirmed.

Chronic fatigue (CF) in breast cancer survivors (BCSs) has been associated with increased serum C-reactive protein-levels (CRP), pro-inflammatory cytokines and cytokine gene single nucleotide polymorphisms (SNPs). Still, there are few studies on these topics, and due to small study-cohorts the possibility to adjust for other conditions related to inflammatory processes, e.g. depression, has been limited. In 302 BCSs, examined approximately four years after treatment for breast cancer stage II/III, data on high sensitivity (hs)CRP, leukocytes and mRNA interleukin (IL)1β and IL6R expression, depression and chronic fatigue were available. Three years thereafter, 236 BCSs were re-examined. The associations between fatigue and SNPs in inflammation-related genes; IL1β (rs16944), IL6 (rs1800795), IL6receptor (rs4129267, rs4845617, rs2228145), CRP (rs2794521, rs3091244) were investigated, together with the relations between SNPs in IL6R,IL1β and CRP genes and mRNA blood expression levels of IL6R and IL1β and serum hsCRP-levels, respectively. All analyses were repeated after exclusion of depressed individuals and separating BCSs with persistent fatigue from never-fatigued individuals. Even after exclusion of depressed individuals neither the SNPs nor the mRNA IL1β and IL6R expression levels were associated with chronic or persistent fatigue. In the subset of persistent fatigued and never-fatigued individuals the CRP SNP (rs3091244) was associated with hsCRP level (p=0.02). IL1β and IL6R mRNA expression levels were not related to the IL1β and IL6R genotypes. In a large cohort of BCSs the investigated SNPs in inflammation-related genes were not associated with fatigue, though subset analyses indicated an association between the CRP SNP (rs3091244) and serum hsCRP.

Purpose To extend knowledge on the mechanisms and pathways involved in maintenance of radiation-induced fibrosis (RIF) by performing gene expression profiling of whole blood from breast cancer (BC) survivors with and without fibrosis 3–7 years after end of radiotherapy treatment. Methods and Materials Gene expression profiles from blood were obtained for 254 BC survivors derived from a cohort of survivors, treated with adjuvant radiotherapy for breast cancer 3–7 years earlier. Analyses of transcriptional differences in blood gene expression between BC survivors with fibrosis ( n = 31) and BC survivors without fibrosis ( n = 223) were performed using R version 2.8.0 and tools from the Bioconductor project. Gene sets extracted through a literature search on fibrosis and breast cancer were subsequently used in gene set enrichment analysis. Results Substantial differences in blood gene expression between BC survivors with and without fibrosis were observed, and 87 differentially expressed genes were identified through linear analysis. Transforming growth factor-β1 signaling was identified as the most significant gene set, showing a down-regulation of most of the core genes, together with up-regulation of a transcriptional activator of the inhibitor of fibrinolysis, Plasminogen activator inhibitor 1 in the BC survivors with fibrosis. Conclusion Transforming growth factor-β1 signaling was found down-regulated during the maintenance phase of fibrosis as opposed to the up-regulation reported during the early, initiating phase of fibrosis. Hence, once the fibrotic tissue has developed, the maintenance phase might rather involve a deregulation of fibrinolysis and altered degradation of extracellular matrix components.

Background A recent genome-wide association study (GWAS) has identified a single nucleotide polymorphism (SNP) rs11249433 in the 1p11.2 region as a novel genetic risk factor for breast cancer, and this association was stronger in patients with estrogen receptor (ER)+ versus ER- cancer. Results We found association between SNP rs11249433 and expression of the NOTCH2 gene located in the 1p11.2 region. Examined in 180 breast tumors, the expression of NOTCH2 was found to be lowest in tumors with TP53 mutations and highest in TP53 wild-type/ER+ tumors (p = 0.0059). In the latter group, the NOTCH2 expression was particularly increased in carriers of the risk genotypes (AG/GG) of rs11249433 when compared to the non-risk AA genotype (p = 0.0062). Similar association between NOTCH2 expression and rs11249433 was observed in 60 samples of purified monocytes from healthy controls (p = 0.015), but not in total blood samples from 302 breast cancer patients and 76 normal breast tissue samples. We also identified the first possible dominant-negative form of NOTCH2, a truncated version of NOTCH2 consisting of only the extracellular domain. Conclusion This is the first study to show that the expression of NOTCH2 differs in subgroups of breast tumors and by genotypes of the breast cancer-associated SNP rs11249433. The NOTCH pathway has key functions in stem cell differentiation of ER+ luminal cells in the breast. Therefore, increased expression of NOTCH2 in carriers of rs11249433 may promote development of ER+ luminal tumors. Further studies are needed to investigate possible mechanisms of regulation of NOTCH2 expression by rs11249433 and the role of NOTCH2 splicing forms in breast cancer development.

Background The course of fatigue in long-term breast cancer survivors (BCSs) is unknown. The current study examined chronic fatigue (CF) cross-sectionally and longitudinally in relapse-free women up to 10 years after multimodal treatment for BC stage II/III. The prevalence of persistent fatigue (PF: having CF at two assessments separated by >2 years) and its predictors were also investigated. Methods Data from questionnaires (including the Fatigue Questionnaire and questions regarding socio-demographics and physical symptoms) were collected twice from 249 BCSs: 2.5–7 years post-BC diagnosis (T1) and 2.5–3 years thereafter (T2). A physical examination including blood sampling was performed at T1. Results CF was diagnosed in 33% of the women at T1 and in 39% at T2, including 57 (23%) subjects with PF. Current psychological distress, treatment-area related discomfort and high body mass index (BMI) were associated with CF at T1 and predicted PF. Increased leukocyte count also predicted PF. Treatment for mental problems prior to the BC, increased hsCRP-level and respiratory symptoms were associated with CF at T1 but did not predict PF. Conclusions Women may experience fatigue up to 10 years after multimodal BC treatment, with about one third having CF and about one fourth having PF. Implications for cancer survivors During follow-up, BCSs and their doctors should maximize their efforts to reduce psychological distress, overweight and pain within the BC-treated area, all linked to the development of persistent fatigue.

To determine the distribution of clinically important CYP2C genotypes and allele frequencies in healthy Nordic populations with special focus on linkage disequilibrium. A total of 896 healthy subjects from three Nordic populations (Danish, Faroese, and Norwegian) were genotyped for five frequent and clinically important CYP2C allelic variants: the defective CYP2C8*3, CYP2C9*2, CYP2C9*3, and CYP2C19*2 alleles, and the CYP2C19*17 allele that causes rapid drug metabolism. Linkage disequilibrium was evaluated and CYP2C haplotypes were inferred in the entire population. Ten CYP2C haplotypes were inferred, the most frequent of which (49%) was the CYP2C wildtype haplotype carrying CYP2C8*1, CYP2C9*1, and CYP2C19*1. The second most frequent haplotype (19%) is composed of CYP2C19*17, CYP2C8*1, and CYP2C9*1. This predicted haplotype accounts for 99.7% of the CYP2C19*17 alleles found in the 896 subjects. CYP2C19*17 is a frequent genetic variant in Nordic populations that exists in strong linkage disequilibrium with wildtype CYP2C8*1 and CYP2C9*1 alleles, which effectively makes it a determinant for a haplotype exhibiting an efficient CYP2C substrate metabolism.

Background The ATM protein is activated as a result of ionizing radiation, and genetic variants of the ATM gene may therefore affect the level of radiation-induced damage. Individuals heterozygous for ATM mutations have been reported to have an increased risk of malignancy, especially breast cancer. Materials and methods Norwegian breast cancer patients (272) treated with radiation (252 of which were evaluated for radiation-induced adverse side effects), 95 Norwegian women with no known history of cancer and 95 American breast cancer patients treated with radiation (44 of which developed ipsilateral breast tumour recurrence, IBTR) were screened for sequence variations in all exons of the ATM gene as well as known intronic variants by denaturating high performance liquid chromatography (dHPLC) followed by sequencing to determine the nature of the variant. Results and Conclusion A total of 56 variants were identified in the three materials combined. A borderline significant association with breast cancer risk was found for the 1229 T>C (Val>Ala) substitution in exon 11 (P-value 0.055) between the Norwegian controls and breast cancer patients as well as a borderline significant difference in haplotype distribution (P-value 0.06). Adverse side effects, such as: development of costal fractures and telangiectasias, subcutaneous and lung fibrosis, pleural thickening and atrophy were evaluated in the Norwegian patients. Significant associations were found for several of the identified variants such as rs1800058 (Leu > Phe) where a decrease in minor allele frequency was found with increasing level of adverse side effects for the clinical end-points pleural thickening and lung fibrosis, thus giving a protective effect. Overall our results indicate a role for variation in the ATM gene both for risk of developing breast cancer, and in radiation induced adverse side effects. No association could be found between risk of developing ipsilateral breast tumour recurrence and any of the sequence variants found in the American patient material.

Background Individuals heterozygous for germline ATM mutations have been reported to have an increased risk for breast cancer but the role for ATM genetic variants for breast cancer risk has remained unclear. Recently, a common ATM variant, ATMivs38 -8T>C in cis with the ATMex39 5557G>A (D1853N) variant, was suggested to associate with bilateral breast cancer among familial breast cancer patients from Northern Finland. We have here evaluated the 5557G>A and ivs38-8T>C variants in an extensive case-control association analysis. We also aimed to investigate whether there are other ATM mutations or variants contributing to breast cancer risk in our population. Methods Two common ATM variants, 5557G>A and ivs38-8T>C, previously suggested to associate with bilateral breast cancer, were genotyped in an extensive set of 786 familial and 884 unselected breast cancer cases as well as 708 healthy controls. We also screened the entire coding region and exon-intron boundaries of the ATM gene in 47 familial breast cancer patients and constructed haplotypes of the patients. The identified variants were also evaluated for increased breast cancer risk among additional breast cancer cases and controls. Results Neither of the two common variants, 5557G>A and ivs38-8T>C, nor any haplotype containing them, was significantly associated with breast cancer risk, bilateral breast cancer or multiple primary cancers in any of the patient groups or subgoups. Three rare missense alterations and one intronic change were each found in only one patient of over 250 familial patients studied and not among controls. The fourth missense alteration studied further was found with closely similar frequencies in over 600 familial cases and controls. Conclusion Altogether, our results suggest very minor effect, if any, of ATM genetic variants on familial breast cancer in Southern Finland. Our results do not support association of the 5557G>A or ivs38-8T>C variant with increased breast cancer risk or with bilateral breast cancer.

Candidate single-nucleotide polymorphisms (SNPs) were analyzed for associations to an unselected whole genome pool of tumor mRNA transcripts in 50 unrelated patients with breast cancer. SNPs were selected from 203 candidate genes of the reactive oxygen species pathway. We describe a general statistical framework for the simultaneous analysis of gene expression data and SNP genotype data measured for the same cohort, which revealed significant associations between subsets of SNPs and transcripts, shedding light on the underlying biology. We identified SNPs in EGF , IL1A , MAPK8 , XPC , SOD2 , and ALOX12 that are associated with the expression patterns of a significant number of transcripts, indicating the presence of regulatory SNPs in these genes. SNPs were found to act in trans in a total of 115 genes. SNPs in 43 of these 115 genes were found to act both in cis and in trans. Finally, subsets of SNPs that share significantly many common associations with a set of transcripts (biclusters) were identified. The subsets of transcripts that are significantly associated with the same set of SNPs or to a single SNP were shown to be functionally coherent in Gene Ontology and pathway analyses and coexpressed in other independent data sets, suggesting that many of the observed associations are within the same functional pathways. To our knowledge, this article is the first study to correlate SNP genotype data in the germ line with somatic gene expression data in breast tumors. It provides the statistical framework for further genotype expression correlation studies in cancer data sets.

Tumor heterogeneity is an area of intense research, revealing tumors with high complexity consisting of different subclones and infiltrating cells. Identification of subclones that are resistant to therapy may be critical to improve treatment outcome. The NeoAva study is a randomized phase II, clinical trial of Her2 negative breast cancer patients treated in a neoadjuvant setting with chemotherapy (FEC and taxane) +/- bevacizumab. Core needle biopsies were obtained at screening and after 12 weeks, and the tumor was surgically removed after 25 weeks. DNA copy number changes in the tumors were analyzed using Affymetrix SNP Array 6.0. Allele specific copy number changes were assessed using the Allele-Specific Copy number Analysis of Tumors (ASCAT) algorithm (Van Loo, Norgard et al., PNAS 2010) and allele-specific Piecewise Constant Fitting (asPCF) algorithms (Nilsen, Liestol et al., BMC Genomics 2012). Measures of genomic instability were obtained through the complex arm-wise aberration index (CAAI) that captures local rearrangements (‘firestorms’) (Russnes, Vollan et al., Sci Transl Med 2010). Changes in copy number aberrations between the three different time points were observed in almost all tumors. Some tumors showed a decrease in tumor percentage and aberrations after just 12 weeks of treatment, where others showed loss of aberrations only at the time of surgery (25 weeks). Most of the tumors that did retain aberrations at all time points during treatment, did not demonstrate any decrease in tumor size. Other profiles indicated subclonal reduction, where some aberrations are kept throughout treatment and others disappear. Many of the tumors shrinking in size showed fewer whole arm aberrations than before treatment, but retained their focal amplicons. Some of the tumor aberrations seem to disappear after 12 weeks, but to reappear after 25 weeks, but with the addition of novel aberration. Complex rearrangements were identified in 67% of tumors before treatment. The most frequent ‘firestorms’ were found on 20p, 11q and 8p. Some events were persistent through therapy, but the majority changed. An association between complex tumor genomes and patients having progressive disease/non-responders were observed. These results show the complex structure of a tumor and suggest that heterogeneity will influence the response to treatment. The subclonal patterns of tumors may be of great importance for clinical decision-making, as well as for monitoring treatment efficacy. Citation Format: Elen K. Møller, Silje Nord, Hans Kristian Moen Vollan, Hedda von der Lippe Gythfeldt, Hege Edvardsen, Laxmi Silwal- Pandit, Marit Krohn, Thomas Fleischer, Ellen Schlitchting, Elin Borgen, Øystein Garred, Anne Fangberget, Marit M. Holmen, Helle Skjerven, Steinar Lundgren, Erik Wist, Bjørn Naume, Anne-Lise Børresen-Dale, Ole Christian Lingjærde, Olav Engebråten, Vessela N. Kristensen. A time course study of genomic instability in breast cancer patients receiving neoadjuvant therapy with or without bevacizumab. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1533. doi:10.1158/1538-7445.AM2014-1533

Background: In this paper we report the prevalence of copy number aberration events at various stages (subclasses) of breast cancer as assessed by two different statistical methods, GISTIC, a well-known