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1.  Repeatability of the Maximum Standard Uptake Value (SUVmax) in FDG PET 
Objective: SUVmax is often calculated at FDG PET examinations in systematic studies as well as at clinical examinations. Since SUVmax represents a very small portion of a lesion it may be questioned how statistically reliable the figure is. This was studied by assessing the repeatability of SUVmax between two FDG acquisitions acquired immediately upon each other in patients with chest lesions.
Methods: In 100 clinical patients with a known chest lesion, two identical 3 min PET registrations (PET1 and PET2, respectively) were initiated within 224±31 sec of each other. The difference in SUVmax between the lesion for the two PET scans (ΔSUVmax) was calculated and the uncertainty expressed as the coefficient of variation, CV (%). The correlation between ΔSUVmax and the lowest SUVmax from PET1 or PET2, the approximate metabolic lesion volume, the time from FDG injection to PET1 and the time between PET1 and PET2, respectively, was also assessed.
Results: In 56 patients SUVmax increased at the second acquisition and in 44 patients it decreased. Mean of SUVmax was 7.8±6.1 and 7.8±6.2 for PET1 and PET2, respectively. The mean percentage difference was 0.9±7.8. The difference was not significant (p=0.20). CV gave an uncertainty of 4.3% between the two measurements which is a strong indicator of equivalence. There was no correlation between ΔSUVmax and any of the assessed four parameters. The difference between the acquisitions, 0.9%, was much lower compared to the 3 previous published similar, but more restricted studies where the difference was 2.5-8.2%.
Conclusion: From camera and computational perspectives, SUVmax is a stable parameter
Conflict of interest:None declared.
doi:10.4274/Mirt.76376
PMCID: PMC3957966  PMID: 24653930
Examinations and diagnoses; Positron-emission tomography; Fluorodeoxyglucose F18; reproducibility of results
2.  Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to EGFR and KRAS Mutation Status 
PLoS ONE  2013;8(10):e78614.
Introduction
In lung adenocarcinoma, the mutational spectrum is dominated by EGFR and KRAS mutations. Improved knowledge about genomic and transcriptional alterations in and between mutation-defined subgroups may identify genes involved in disease development or progression.
Methods
Genomic profiles from 457 adenocarcinomas, including 113 EGFR-mutated, 134 KRAS-mutated and 210 EGFR and KRAS-wild type tumors (EGFRwt/KRASwt), and gene expression profiles from 914 adenocarcinomas, including 309 EGFR-mutated, 192 KRAS-mutated, and 413 EGFRwt/KRASwt tumors, were assembled from different repositories. Genomic and transcriptional differences between the three mutational groups were analyzed by both supervised and unsupervised methods.
Results
EGFR-mutated adenocarcinomas displayed a larger number of copy number alterations and recurrent amplifications, a higher fraction of total loss-of-heterozygosity, higher genomic complexity, and a more distinct expression pattern than EGFR-wild type adenocarcinomas. Several of these differences were also consistent when the three mutational groups were stratified by stage, gender and smoking status. Specific copy number alterations were associated with mutation status, predominantly including regions of gain with the highest frequency in EGFR-mutated tumors. Differential regions included both large and small regions of gain on 1p, 5q34-q35.3, 7p, 7q11.21, 12p12.1, 16p, and 21q, and losses on 6q16.3-q21, 8p, and 9p, with 20-40% frequency differences between the mutational groups. Supervised gene expression analyses identified 96 consistently differentially expressed genes between the mutational groups, and together with unsupervised analyses these analyses highlighted the difficulty in broadly resolving the three mutational groups into distinct transcriptional entities.
Conclusions
We provide a comprehensive overview of the genomic and transcriptional landscape in lung adenocarcinoma stratified by EGFR and KRAS mutations. Our analyses suggest that the overall genomic and transcriptional landscape of lung adenocarcinoma is affected, but only to a minor extent, by EGFR and KRAS mutation status.
doi:10.1371/journal.pone.0078614
PMCID: PMC3812039  PMID: 24205279
3.  Identification of novel candidate genes associated with cleft lip and palate using array comparative genomic hybridization 
Journal of medical genetics  2007;45(2):81-86.
Introduction and methods
We analyzed DNA samples isolated from individuals born with cleft lip and cleft palate to identify deletions and duplications of candidate gene loci using array comparative genomic hybridization (array-CGH).
Results
Of 83 syndromic cases analyzed we identified one subject with a previously unknown 2.7 Mb deletion at 22q11.21 coinciding with the DiGeorge syndrome region. Eighteen of the syndromic cases had clinical features of Van der Woude syndrome and deletions were identified in 5 of these, all of which encompassed the interferon regulatory factor 6 (IRF6) gene. In a series of 104 nonsyndromic cases we found one subject with a 3.2 Mb deletion at chromosome 6q25.1-25.2 and another with a 2.2 Mb deletion at 10q26.11-26.13. Analyses of parental DNA demonstrated that the two deletion cases at 22q11.21 and 6q25.1-25.2 were de novo, while the deletion of 10q26.11-26.13 was inherited from the mother, who also has cleft lip. These deletions appear likely to be causally associated with the phenotypes of the subjects. Estrogen receptor 1 (ESR1) and fibroblast growth factor receptor 2 (FGFR2) genes from the 6q25.1-25.2 and 10q26.11-26.13, respectively, were identified as likely causative genes using a gene prioritization software.
Discussion
We have shown that array-CGH analysis of DNA samples derived from cleft lip and palate subjects is an efficient and productive method for identifying candidate chromosomal loci and genes, complementing traditional genetic mapping strategies.
doi:10.1136/jmg.2007.052191
PMCID: PMC3732463  PMID: 17873121
cleft lip; cleft palate; array-CGH; candidate gene
4.  Molecular Profiling Reveals Low- and High-Grade Forms of Primary Melanoma 
Purpose
For primary melanomas, tumor thickness, mitotic rate, and ulceration are well-laid cornerstones of prognostication. However, a molecular exposition of melanoma aggressiveness is critically missing. We recently uncovered a four-class structure in metastatic melanoma, which predicts outcome and informs biology. This raises the possibility that a molecular structure exists even in the early stages of melanoma and that molecular determinants could underlie histophenotype and eventual patient outcome.
Experimental Design
We subjected 223 archival primary melanomas to a horizontally integrated analysis of RNA expression, oncogenic mutations at 238 lesions, histomorphometry, and survival data.
Results
Our previously described four-class structure that was elucidated in metastatic lesions was evident within the expression space of primary melanomas. Because these subclasses converged into two larger prognostic and phenotypic groups, we used the metastatic lesions to develop a binary subtype-based signature capable of distinguishing between "high" and "low" grade forms of the disease. The two-grade signature was subsequently applied to the primary melanomas. Compared with low-grade tumors, high-grade primary melanomas were significantly associated with increased tumor thickness, mitotic rate, ulceration (all P < 0.01), and poorer relapse-free (HR = 4.94; 95% CI, 2.84–8.59), and overall (HR = 3.66; 95% CI, 2.40–5.58) survival. High-grade melanomas exhibited elevated levels of proliferation and BRCA1/DNA damage signaling genes, whereas low-grade lesions harbored higher expression of immune genes. Importantly, the molecular-grade signature was validated in two external gene expression data sets.
Conclusions
We provide evidence for a molecular organization within melanomas, which is preserved across all stages of disease.
doi:10.1158/1078-0432.CCR-12-0343
PMCID: PMC3467105  PMID: 22675174
5.  High expression of ZNF703 independent of amplification indicates worse prognosis in patients with luminal B breast cancer 
Cancer Medicine  2013;2(4):437-446.
Abstract
Amplification of 8p12-p11 is relatively common in breast cancer and several genes within the region have been suggested to affect breast tumor progression. The aim of the study was to map the amplified 8p12-p11 region in a large set of breast tumors in an effort to identify the genetic driver and to explore its impact on tumor progression and prognosis. Copy number alterations (CNAs) were mapped in 359 tumors, and gene expression data from 577 tumors (359 tumors included) were correlated with CNA, clinical–pathological factors, and protein expression (39 tumors). 8p12-p11 was amplified in 11.4% of tumors. The smallest region of amplification harbored one full-length gene, ZNF703. ZNF703 mRNA expression was significantly higher in estrogen receptor (ER)-positive than ER-negative tumors (P = 2 × 10−16), a reflection of high expression in luminal tumors. Forty-eight percent of tumors with ZNF703 amplification were luminal B tumors in which the best correlation between DNA copy number and mRNA was seen (P = 1.2 × 10−7) as well as correlation between mRNA and protein expression (P = 0.02). High ZNF703 mRNA correlated with poor survival in patients with ER-positive luminal B tumors (log rank P = 0.04). Furthermore, high ZNF703 mRNA expression correlated with poor outcome in patients with ZNF703 copy number neutral, ER-positive, luminal B tumors (log rank P = 0.004). The results support ZNF703 as the driver gene of the 8p12 amplification and suggest that independent of amplification, high expression of the gene affects prognosis in luminal B tumors.
Our mapping of 8p12-p11 and analyses of ZNF703 mRNA and protein expression in breast tumors support ZNF703 as an oncogene in luminal B tumors. High ZNF703 expression, independent of the amplification, correlated with worse prognosis for the breast cancer patients with ER-positive luminal tumors, particularly of the luminal B subtype.
doi:10.1002/cam4.88
PMCID: PMC3799278  PMID: 24156016
8p12-p11 amplification; ER positive; luminal tumors; prognosis; tumor progression; ZNF703
6.  Detailed Analysis of Focal Chromosome Arm 1q and 6p Amplifications in Urothelial Carcinoma Reveals Complex Genomic Events on 1q, and SOX4 as a Possible Auxiliary Target on 6p 
PLoS ONE  2013;8(6):e67222.
Background
Urothelial carcinoma shows frequent amplifications at 6p22 and 1q21–24. The main target gene at 6p22 is believed to be E2F3, frequently co-amplified with CDKAL1 and SOX4. There are however reports on 6p22 amplifications that do not include E2F3. Previous analyses have identified frequent aberrations occurring at 1q21–24. However, due to complex rearrangements it has been difficult to identify specific 1q21–24 target regions and genes.
Methods
We selected 29 cases with 6p and 37 cases with 1q focal genomic amplifications from 261 cases of urothelial carcinoma analyzed by array-CGH for high resolution zoom-in oligonucleotide array analyses. Genomic analyses were combined with gene expression data and genomic sequence analyses to characterize and fine map 6p22 and 1q21–24 amplifications.
Results
We show that the most frequently amplified gene at 6p22 is SOX4 and that SOX4 can be amplified and overexpressed without the E2F3 or CDKAL1 genes being included in the amplicon. Hence, our data point to SOX4 as an auxiliary amplification target at 6p22. We further show that at least three amplified regions are observed at 1q21–24. Copy number data, combined with gene expression data, highlighted BCL9 and CHD1L as possible targets in the most proximal region and MCL1, SETDB1, and HIF1B as putative targets in the middle region, whereas no obvious targets could be determined in the most distal amplicon. We highlight enrichment of G4 quadruplex sequence motifs and a high number of intraregional sequence duplications, both known to contribute to genomic instability, as prominent features of the 1q21–24 region.
Conclusions
Our detailed analyses of the 6p22 amplicon suggest SOX4 as an auxiliary target gene for amplification. We further demonstrate three separate target regions for amplification at 1q21–24 and identified BCL9, CHD1L, and MCL1, SETDB1, and HIF1B as putative target genes within these regions.
doi:10.1371/journal.pone.0067222
PMCID: PMC3688975  PMID: 23825644
7.  The gene expression landscape of breast cancer is shaped by tumor protein p53 status and epithelial-mesenchymal transition 
Breast Cancer Research : BCR  2012;14(4):R113.
Introduction
Gene expression data derived from clinical cancer specimens provide an opportunity to characterize cancer-specific transcriptional programs. Here, we present an analysis delineating a correlation-based gene expression landscape of breast cancer that identifies modules with strong associations to breast cancer-specific and general tumor biology.
Methods
Modules of highly connected genes were extracted from a gene co-expression network that was constructed based on Pearson correlation, and module activities were then calculated using a pathway activity score. Functional annotations of modules were experimentally validated with an siRNA cell spot microarray system using the KPL-4 breast cancer cell line, and by using gene expression data from functional studies. Modules were derived using gene expression data representing 1,608 breast cancer samples and validated in data sets representing 971 independent breast cancer samples as well as 1,231 samples from other cancer forms.
Results
The initial co-expression network analysis resulted in the characterization of eight tightly regulated gene modules. Cell cycle genes were divided into two transcriptional programs, and experimental validation using an siRNA screen showed different functional roles for these programs during proliferation. The division of the two programs was found to act as a marker for tumor protein p53 (TP53) gene status in luminal breast cancer, with the two programs being separated only in luminal tumors with functional p53 (encoded by TP53). Moreover, a module containing fibroblast and stroma-related genes was highly expressed in fibroblasts, but was also up-regulated by overexpression of epithelial-mesenchymal transition factors such as transforming growth factor beta 1 (TGF-beta1) and Snail in immortalized human mammary epithelial cells. Strikingly, the stroma transcriptional program related to less malignant tumors for luminal disease and aggressive lymph node positive disease among basal-like tumors.
Conclusions
We have derived a robust gene expression landscape of breast cancer that reflects known subtypes as well as heterogeneity within these subtypes. By applying the modules to TP53-mutated samples we shed light on the biological consequences of non-functional p53 in otherwise low-proliferating luminal breast cancer. Furthermore, as in the case of the stroma module, we show that the biological and clinical interpretation of a set of co-regulated genes is subtype-dependent.
doi:10.1186/bcr3236
PMCID: PMC3680939  PMID: 22839103
8.  Integrated Genomic and Gene Expression Profiling Identifies Two Major Genomic Circuits in Urothelial Carcinoma 
PLoS ONE  2012;7(6):e38863.
Similar to other malignancies, urothelial carcinoma (UC) is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21), and BCL2L1 (20q11). We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.
doi:10.1371/journal.pone.0038863
PMCID: PMC3369837  PMID: 22685613
9.  Relation between smoking history and gene expression profiles in lung adenocarcinomas 
BMC Medical Genomics  2012;5:22.
Background
Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, but all lung cancers are not attributable to smoking. Specifically, lung cancer in never-smokers has been suggested to represent a distinct disease entity compared to lung cancer arising in smokers due to differences in etiology, natural history and response to specific treatment regimes. However, the genetic aberrations that differ between smokers and never-smokers’ lung carcinomas remain to a large extent unclear.
Methods
Unsupervised gene expression analysis of 39 primary lung adenocarcinomas was performed using Illumina HT-12 microarrays. Results from unsupervised analysis were validated in six external adenocarcinoma data sets (n=687), and six data sets comprising normal airway epithelial or normal lung tissue specimens (n=467). Supervised gene expression analysis between smokers and never-smokers were performed in seven adenocarcinoma data sets, and results validated in the six normal data sets.
Results
Initial unsupervised analysis of 39 adenocarcinomas identified two subgroups of which one harbored all never-smokers. A generated gene expression signature could subsequently identify never-smokers with 79-100% sensitivity in external adenocarcinoma data sets and with 76-88% sensitivity in the normal materials. A notable fraction of current/former smokers were grouped with never-smokers. Intriguingly, supervised analysis of never-smokers versus smokers in seven adenocarcinoma data sets generated similar results. Overlap in classification between the two approaches was high, indicating that both approaches identify a common set of samples from current/former smokers as potential never-smokers. The gene signature from unsupervised analysis included several genes implicated in lung tumorigenesis, immune-response associated pathways, genes previously associated with smoking, as well as marker genes for alveolar type II pneumocytes, while the best classifier from supervised analysis comprised genes strongly associated with proliferation, but also genes previously associated with smoking.
Conclusions
Based on gene expression profiling, we demonstrate that never-smokers can be identified with high sensitivity in both tumor material and normal airway epithelial specimens. Our results indicate that tumors arising in never-smokers, together with a subset of tumors from smokers, represent a distinct entity of lung adenocarcinomas. Taken together, these analyses provide further insight into the transcriptional patterns occurring in lung adenocarcinoma stratified by smoking history.
doi:10.1186/1755-8794-5-22
PMCID: PMC3447685  PMID: 22676229
Lung cancer; Smoking; Gene expression analysis; Adenocarcinoma; EGFR; Never-smokers; Immune response
10.  Landscape of somatic allelic imbalances and copy number alterations in HER2-amplified breast cancer 
Breast Cancer Research : BCR  2011;13(6):R129.
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.
doi:10.1186/bcr3075
PMCID: PMC3326571  PMID: 22169037
11.  GOBO: Gene Expression-Based Outcome for Breast Cancer Online 
PLoS ONE  2011;6(3):e17911.
Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo), allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1) rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2) identification of co-expressed genes for creation of potential metagenes, 3) association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.
doi:10.1371/journal.pone.0017911
PMCID: PMC3061871  PMID: 21445301
12.  Recurrent gross mutations of the PTEN tumor suppressor gene in breast cancers with deficient DSB repair 
Nature genetics  2007;40(1):102-107.
Basal-like breast cancer (BBC) is a subtype of breast cancer with poor prognosis1–3. Inherited mutations of BRCA1, a cancer susceptibility gene involved in double-strand DNA break (DSB) repair, lead to breast cancers that are nearly always of the BBC subtype3–5; however, the precise molecular lesions and oncogenic consequences of BRCA1 dysfunction are poorly understood. Here we show that heterozygous inactivation of the tumor suppressor gene Pten leads to the formation of basal-like mammary tumors in mice, and that loss of PTEN expression is significantly associated with the BBC subtype in human sporadic and BRCA1-associated hereditary breast cancers. In addition, we identify frequent gross PTEN mutations, involving intragenic chromosome breaks, inversions, deletions and micro copy number aberrations, specifically in BRCA1-deficient tumors. These data provide an example of a specific and recurrent oncogenic consequence of BRCA1-dependent dysfunction in DNA repair and provide insight into the pathogenesis of BBC with therapeutic implications. These findings also argue that obtaining an accurate census of genes mutated in cancer will require a systematic examination for gross gene rearrangements, particularly in tumors with deficient DSB repair.
doi:10.1038/ng.2007.39
PMCID: PMC3018354  PMID: 18066063
13.  Genomic subtypes of breast cancer identified by array-comparative genomic hybridization display distinct molecular and clinical characteristics 
Introduction
Breast cancer is a profoundly heterogeneous disease with respect to biologic and clinical behavior. Gene-expression profiling has been used to dissect this complexity and to stratify tumors into intrinsic gene-expression subtypes, associated with distinct biology, patient outcome, and genomic alterations. Additionally, breast tumors occurring in individuals with germline BRCA1 or BRCA2 mutations typically fall into distinct subtypes.
Methods
We applied global DNA copy number and gene-expression profiling in 359 breast tumors. All tumors were classified according to intrinsic gene-expression subtypes and included cases from genetically predisposed women. The Genomic Identification of Significant Targets in Cancer (GISTIC) algorithm was used to identify significant DNA copy-number aberrations and genomic subgroups of breast cancer.
Results
We identified 31 genomic regions that were highly amplified in > 1% of the 359 breast tumors. Several amplicons were found to co-occur, the 8p12 and 11q13.3 regions being the most frequent combination besides amplicons on the same chromosomal arm. Unsupervised hierarchical clustering with 133 significant GISTIC regions revealed six genomic subtypes, termed 17q12, basal-complex, luminal-simple, luminal-complex, amplifier, and mixed subtypes. Four of them had striking similarity to intrinsic gene-expression subtypes and showed associations to conventional tumor biomarkers and clinical outcome. However, luminal A-classified tumors were distributed in two main genomic subtypes, luminal-simple and luminal-complex, the former group having a better prognosis, whereas the latter group included also luminal B and the majority of BRCA2-mutated tumors. The basal-complex subtype displayed extensive genomic homogeneity and harbored the majority of BRCA1-mutated tumors. The 17q12 subtype comprised mostly HER2-amplified and HER2-enriched subtype tumors and had the worst prognosis. The amplifier and mixed subtypes contained tumors from all gene-expression subtypes, the former being enriched for 8p12-amplified cases, whereas the mixed subtype included many tumors with predominantly DNA copy-number losses and poor prognosis.
Conclusions
Global DNA copy-number analysis integrated with gene-expression data can be used to dissect the complexity of breast cancer. This revealed six genomic subtypes with different clinical behavior and a striking concordance to the intrinsic subtypes. These genomic subtypes may prove useful for understanding the mechanisms of tumor development and for prognostic and treatment prediction purposes.
doi:10.1186/bcr2596
PMCID: PMC2917037  PMID: 20576095
14.  Molecular subtypes of breast cancer are associated with characteristic DNA methylation patterns 
Introduction
Five different molecular subtypes of breast cancer have been identified through gene expression profiling. Each subtype has a characteristic expression pattern suggested to partly depend on cellular origin. We aimed to investigate whether the molecular subtypes also display distinct methylation profiles.
Methods
We analysed methylation status of 807 cancer-related genes in 189 fresh frozen primary breast tumours and four normal breast tissue samples using an array-based methylation assay.
Results
Unsupervised analysis revealed three groups of breast cancer with characteristic methylation patterns. The three groups were associated with the luminal A, luminal B and basal-like molecular subtypes of breast cancer, respectively, whereas cancers of the HER2-enriched and normal-like subtypes were distributed among the three groups. The methylation frequencies were significantly different between subtypes, with luminal B and basal-like tumours being most and least frequently methylated, respectively. Moreover, targets of the polycomb repressor complex in breast cancer and embryonic stem cells were more methylated in luminal B tumours than in other tumours. BRCA2-mutated tumours had a particularly high degree of methylation. Finally, by utilizing gene expression data, we observed that a large fraction of genes reported as having subtype-specific expression patterns might be regulated through methylation.
Conclusions
We have found that breast cancers of the basal-like, luminal A and luminal B molecular subtypes harbour specific methylation profiles. Our results suggest that methylation may play an important role in the development of breast cancers.
doi:10.1186/bcr2590
PMCID: PMC2917031  PMID: 20565864
15.  High-resolution genomic and expression analyses of copy number alterations in HER2-amplified breast cancer 
Introduction
HER2 gene amplification and protein overexpression (HER2+) define a clinically challenging subgroup of breast cancer with variable prognosis and response to therapy. Although gene expression profiling has identified an ERBB2 molecular subtype of breast cancer, it is clear that HER2+ tumors reside in all molecular subtypes and represent a genomically and biologically heterogeneous group, needed to be further characterized in large sample sets.
Methods
Genome-wide DNA copy number profiling, using bacterial artificial chromosome (BAC) array comparative genomic hybridization (aCGH), and global gene expression profiling were performed on 200 and 87 HER2+ tumors, respectively. Genomic Identification of Significant Targets in Cancer (GISTIC) was used to identify significant copy number alterations (CNAs) in HER2+ tumors, which were related to a set of 554 non-HER2 amplified (HER2-) breast tumors. High-resolution oligonucleotide aCGH was used to delineate the 17q12-q21 region in high detail.
Results
The HER2-amplicon was narrowed to an 85.92 kbp region including the TCAP, PNMT, PERLD1, HER2, C17orf37 and GRB7 genes, and higher HER2 copy numbers indicated worse prognosis. In 31% of HER2+ tumors the amplicon extended to TOP2A, defining a subgroup of HER2+ breast cancer associated with estrogen receptor-positive status and with a trend of better survival than HER2+ breast cancers with deleted (18%) or neutral TOP2A (51%). HER2+ tumors were clearly distinguished from HER2- tumors by the presence of recurrent high-level amplifications and firestorm patterns on chromosome 17q. While there was no significant difference between HER2+ and HER2- tumors regarding the incidence of other recurrent high-level amplifications, differences in the co-amplification pattern were observed, as shown by the almost mutually exclusive occurrence of 8p12, 11q13 and 20q13 amplification in HER2+ tumors. GISTIC analysis identified 117 significant CNAs across all autosomes. Supervised analyses revealed: (1) significant CNAs separating HER2+ tumors stratified by clinical variables, and (2) CNAs separating HER2+ from HER2- tumors.
Conclusions
We have performed a comprehensive survey of CNAs in HER2+ breast tumors, pinpointing significant genomic alterations including both known and potentially novel therapeutic targets. Our analysis sheds further light on the genomically complex and heterogeneous nature of HER2+ tumors in relation to other subgroups of breast cancer.
doi:10.1186/bcr2568
PMCID: PMC2917012  PMID: 20459607
16.  Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios 
BMC Bioinformatics  2008;9:409.
Background
Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples.
Results
We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina's proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300 k version 1 and 2, 370 k and 550 k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations.
Conclusion
The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.
doi:10.1186/1471-2105-9-409
PMCID: PMC2572624  PMID: 18831757
17.  Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays 
Genome Biology  2008;9(9):R136.
A strategy is presented for detection of loss-of-heterozygosity and allelic imbalance in cancer cells from whole genome SNP genotyping data.
We present a strategy for detection of loss-of-heterozygosity and allelic imbalance in cancer cells from whole genome single nucleotide polymorphism genotyping data. Using a dilution series of a tumor cell line mixed with its paired normal cell line and data generated on Affymetrix and Illumina platforms, including paired tumor-normal samples and tumors characterized by fluorescent in situ hybridization, we demonstrate a high sensitivity and specificity of the strategy for detecting both minute and gross allelic imbalances in heterogeneous tumor samples.
doi:10.1186/gb-2008-9-9-r136
PMCID: PMC2592714  PMID: 18796136
18.  Tumor Genome Wide DNA Alterations Assessed by Array CGH in Patients with Poor and Excellent Survival Following Operation for Colorectal Cancer 
Cancer Informatics  2007;3:341-355.
Genome wide DNA alterations were evaluated by array CGH in addition to RNA expression profiling in colorectal cancer from patients with excellent and poor survival following primary operations.
DNA was used for CGH in BAC and cDNA arrays. Global RNA expression was determined by 44K arrays. DNA and RNA from tumor and normal colon were used from cancer patients grouped according to death, survival or Dukes A, B, C and D tumor stage. Confirmed DNA alterations in all Dukes A – D were judged relevant for carcinogenesis, while changes in Dukes C and D only were regarded relevant for tumor progression.
Copy number gain was more common than loss in tumor tissue (p < 0.01). Major tumor DNA alterations occurred in chromosome 8, 13, 18 and 20, where short survival included gain in 8q and loss in 8p. Copy number gains related to tumor progression were most common on chromosome 7, 8, 19, 20, while corresponding major losses appeared in chromosome 8. Losses at chromosome 18 occurred in all Dukes stages. Normal colon tissue from cancer patients displayed gains in chromosome 19 and 20. Mathematical Vector analysis implied a number of BAC-clones in tumor DNA with genes of potential importance for death or survival.
The genomic variation in colorectal cancer cells is tremendous and emphasizes that BAC array CGH is presently more powerful than available statistical models to discriminate DNA sequence information related to outcome. Present results suggest that a majority of DNA alterations observed in colorectal cancer are secondary to tumor progression. Therefore, it would require an immense work to distinguish primary from secondary DNA alterations behind colorectal cancer.
PMCID: PMC2675850  PMID: 19455253
Colorectal cancer array CGH; Tumor DNA
19.  Normalization of array-CGH data: influence of copy number imbalances 
BMC Genomics  2007;8:382.
Background
High-resolution microarray-based comparative genomic hybridization (CGH) techniques have successfully been applied to study copy number imbalances in a number of settings such as the analysis of cancer genomes. For normalization of array-CGH data, methods initially developed for gene expression microarray analysis have, in general, been directly adopted and used. However, these methods are designed to work under assumptions that may not be valid for array-CGH data when copy number imbalances are present. We therefore sought to investigate the effect on normalization imposed by copy number imbalances.
Results
Here we demonstrate that copy number imbalances correlate with intensity in array-CGH data thereby causing problems for conventional normalization methods. We propose a strategy to circumvent these problems by taking copy number imbalances into account during normalization, and we test the proposed strategy using several data sets from the analysis of cancer genomes. In addition, we show how the strategy can be applied to conveniently define adaptive sample-specific boundaries between balanced copy number, losses, and gains to facilitate management of variation in tissue heterogeneity when calling copy number changes.
Conclusion
We highlight the importance of considering copy number imbalances during normalization of array-CGH data, and show how failure to do so can deleteriously affect data and hamper interpretation.
doi:10.1186/1471-2164-8-382
PMCID: PMC2190775  PMID: 17953745
20.  Non-coding antisense transcription detected by conventional and single-stranded cDNA microarray 
BMC Genomics  2007;8:295.
Background
Recent studies revealed that many mammalian protein-coding genes also transcribe their complementary strands. This phenomenon raises questions regarding the validity of data obtained from double-stranded cDNA microarrays since hybridization to both strands may occur. Here, we wanted to analyze experimentally the incidence of antisense transcription in human cells and to estimate their influence on protein coding expression patterns obtained by double-stranded microarrays. Therefore, we profiled transcription of sense and antisense independently by using strand-specific cDNA microarrays.
Results
Up to 88% of expressed protein coding loci displayed concurrent expression from the complementary strand. Antisense transcription is cell specific and showed a strong tendency to be positively correlated to the expression of the sense counterparts. Even if their expression is wide-spread, detected antisense signals seem to have a limited distorting effect on sense profiles obtained with double-stranded probes.
Conclusion
Antisense transcription in humans can be far more common than previously estimated. However, it has limited influence on expression profiles obtained with conventional cDNA probes. This can be explained by a biological phenomena and a bias of the technique: a) a co-ordinate sense and antisense expression variation and b) a bias for sense-hybridization to occur with more efficiency, presumably due to variable exonic overlap between antisense transcripts.
doi:10.1186/1471-2164-8-295
PMCID: PMC2020490  PMID: 17727707

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