Allele-specific copy number analysis of tumor samples with aneuploidy and tumor heterogeneity

We describe a bioinformatic tool, Tumor Aberration Prediction Suite (TAPS), for the identification of allele-specific copy numbers in tumor samples using data from Affymetrix SNP arrays. It includes detailed visualization of genomic segment characteristics and iterative pattern recognition for copy number identification, and does not require patient-matched normal samples. TAPS can be used to identify chromosomal aberrations with high sensitivity even when the proportion of tumor cells is as low as 30%. Analysis of cancer samples indicates that TAPS is well suited to investigate samples with aneuploidy and tumor heterogeneity, which is commonly found in many types of solid tumors.     

Identification of tumor suppressors and oncogenes from genomic and epigenetic features in ovarian cancer

The identification of genetic and epigenetic alterations from primary tumor cells has become a common method to identify genes critical to the development and progression of cancer. We seek to identify those genetic and epigenetic aberrations that have the most impact on gene function within the tumor. First, we perform a bioinformatic analysis of copy number variation (CNV) and DNA methylation covering the genetic landscape of ovarian cancer tumor cells. We separately examined CNV and DNA methylation for 42 primary serous ovarian cancer samples using MOMA-ROMA assays and 379 tumor samples analyzed by The Cancer Genome Atlas. We have identified 346 genes with significant deletions or amplifications among the tumor samples. Utilizing associated gene expression data we predict 156 genes with altered copy number and correlated changes in expression. Among these genes CCNE1, POP4, UQCRB, PHF20L1 and C19orf2 were identified within both data sets. We were specifically interested in copy number variation as our base genomic property in the prediction of tumor suppressors and oncogenes in the altered ovarian tumor. We therefore identify changes in DNA methylation and expression for all amplified and deleted genes. We statistically define tumor suppressor and oncogenic features for these modalities and perform a correlation analysis with expression. We predicted 611 potential oncogenes and tumor suppressors candidates by integrating these data types. Genes with a strong correlation for methylation dependent expression changes exhibited at varying copy number aberrations include CDCA8, ATAD2, CDKN2A, RAB25, AURKA, BOP1 and EIF2C3. We provide copy number variation and DNA methylation analysis for over 11,500 individual genes covering the genetic landscape of ovarian cancer tumors. We show the extent of genomic and epigenetic alterations for known tumor suppressors and oncogenes and also use these defined features to identify potential ovarian cancer gene candidates.     

Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis

We present a computational method, TuMult, for reconstructing the sequence of copy number changes driving carcinogenesis, based on the analysis of several tumor samples from the same patient. We demonstrate the reliability of the method with simulated data, and describe applications to three different cancers, showing that TuMult is a valuable tool for the establishment of clonal relationships between tumor samples and the identification of chromosome aberrations occurring at crucial steps in cancer progression.     

Estimation of parent specific DNA copy number in tumors using high-density genotyping arrays

Chromosomal gains and losses comprise an important type of genetic change in tumors, and can now be assayed using microarray hybridization-based experiments. Most current statistical models for DNA copy number estimate total copy number, which do not distinguish between the underlying quantities of the two inherited chromosomes. This latter information, sometimes called parent specific copy number, is important for identifying allele-specific amplifications and deletions, for quantifying normal cell contamination, and for giving a more complete molecular portrait of the tumor. We propose a stochastic segmentation model for parent-specific DNA copy number in tumor samples, and give an estimation procedure that is computationally efficient and can be applied to data from the current high density genotyping platforms. The proposed method does not require matched normal samples, and can estimate the unknown genotypes simultaneously with the parent specific copy number. The new method is used to analyze 223 glioblastoma samples from the Cancer Genome Atlas (TCGA) project, giving a more comprehensive summary of the copy number events in these samples. Detailed case studies on these samples reveal the additional insights that can be gained from an allele-specific copy number analysis, such as the quantification of fractional gains and losses, the identification of copy neutral loss of heterozygosity, and the characterization of regions of simultaneous changes of both inherited chromosomes.     

Patchwork: allele-specific copy number analysis of whole-genome sequenced tumor tissue

Whole-genome sequencing of tumor tissue has the potential to provide comprehensive characterization of genomic alterations in tumor samples. We present Patchwork, a new bioinformatic tool for allele-specific copy number analysis using whole-genome sequencing data. Patchwork can be used to determine the copy number of homologous sequences throughout the genome, even in aneuploid samples with moderate sequence coverage and tumor cell content. No prior knowledge of average ploidy or tumor cell content is required. Patchwork is freely available as an R package, installable via R-Forge (http://patchwork.r-forge.r-project.org/).     

GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays

There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies.     

Estimation of Copy Number Alterations from Exome Sequencing Data

Exome sequencing constitutes an important technology for the study of human hereditary diseases and cancer. However, the ability of this approach to identify copy number alterations in primary tumor samples has not been fully addressed. Here we show that somatic copy number alterations can be reliably estimated using exome sequencing data through a strategy that we have termed exome2cnv. Using data from 86 paired normal and primary tumor samples, we identified losses and gains of complete chromosomes or large genomic regions, as well as smaller regions affecting a minimum of one gene. Comparison with high-resolution comparative genomic hybridization (CGH) arrays revealed a high sensitivity and a low number of false positives in the copy number estimation between both approaches. We explore the main factors affecting sensitivity and false positives with real data, and provide a side by side comparison with CGH arrays. Together, these results underscore the utility of exome sequencing to study cancer samples by allowing not only the identification of substitutions and indels, but also the accurate estimation of copy number alterations.     

TAFFYS: An Integrated Tool for Comprehensive Analysis of Genomic Aberrations in Tumor Samples

Background

Tumor single nucleotide polymorphism (SNP) array is a common platform for investigating the cancer genomic aberration and the functionally important altered genes. Original SNP array signals are usually corrupted by noise, and need to be de-convoluted into absolute copy number profile by analytical methods. Unfortunately, in contrast with the popularity of tumor Affymetrix SNP array, the methods that are specifically designed for this platform are still limited. The complicated characteristics of noise in signals is one of the difficulties for dissecting tumor Affymetrix SNP array data, as they inevitably blur the distinction between aberrations and create an obstacle for the copy number aberration (CNA) identification.

Results

We propose a tool named TAFFYS for comprehensive analysis of tumor Affymetrix SNP array data. TAFFYS introduce a wavelet-based de-noising approach and copy number-specific signal variance model for suppressing and modelling the noise in signals. Then a hidden Markov model is employed for copy number inference. Finally, by using the absolute copy number profile, statistical significance of each aberration region is calculated in term of different aberration types, including amplification, deletion and loss of heterozygosity (LOH). The result shows that copy number specific-variance model and wavelet de-noising algorithm fits well with the Affymetrix SNP array signals, leading to more accurate estimation for diluted tumor sample (even with only 30% of cancer cells) than other existed methods. Results of examinations also demonstrate a good compatibility and extensibility for different Affymetrix SNP array platforms. Application on the 35 breast tumor samples shows that TAFFYS can automatically dissect the tumor samples and reveal statistically significant aberration regions where cancer-related genes locate.

Conclusions

TAFFYS provide an efficient and convenient tool for identifying the copy number alteration and allelic imbalance and assessing the recurrent aberrations for the tumor Affymetrix SNP array data.     

Copy number increase of aurora kinase A in colorectal cancers: a correlation with tumor progression

The centrosome-associated kinase aurora A (AURKA) is involved in genetic instability and is over-expressed in several human carcinomas including colorectal cancer (CRC). The choromosome locus of AURKA, 20q13, is frequently amplified in CRC, and the functional impact of such regions needs to be extensively investigated in large amount of clinical samples. Case-matched tissues of colorectal adenocarcinomas and adjacent normal epithelium (n= 134) were included in this study. Quantitative PCR was carried out to examine the copy number and mRNA level of AURKA in CRC. Our results showed that copy number gains of AUKRA were detected in a relative high percentage of CRC samples (32.4%, 43 of 134). There was a positive correlation between copy number increase of AURKA and tumor progression. And copy number gains of AURKA also showed a positive correlation with mRNA over-expression in CRC. However, the expression level of AURKA mRNA was also enhanced in the group of CRC samples with unaltered copy numbers. These findings indicated that sporadic colorectal cancers exhibit different mechanisms of aurora A regulation and this may impact the efficacy of aurora-targeted therapies.     

Pan cancer patterns of allelic imbalance from chromosomal alterations in 33 tumor types

Somatic copy number alterations (SCNAs) serve as hallmarks of tumorigenesis and often result in deviations from one-to-one allelic ratios at heterozygous loci, leading to allelic imbalance (AI). The Cancer Genome Atlas (TCGA) reports SCNAs identified using a circular binary segmentation algorithm, providing segment mean copy number estimates from single-nucleotide polymorphism DNA microarray total intensities (log R ratio), but not allele-specific intensities (“B allele” frequencies) that inform of AI. Our approach provides more sensitive identification of SCNAs by modeling the “B allele” frequencies jointly, thereby bolstering the catalog of chromosomal alterations in this widely utilized resource. Here we present AI summaries for all 33 tumor sites in TCGA, including those induced by SCNAs and copy-neutral loss-of-heterozygosity (cnLOH). We identified AI in 94% of the tumors, higher than in previous reports. Recurrent events included deletions of 17p, 9q, 3p, amplifications of 8q, 1q, 7p, as well as mixed event types on 8p and 13q. We also observed both site-specific and pan-cancer (spanning 17p) cnLOH, patterns which have not been comprehensively characterized. The identification of such cnLOH events elucidates tumor suppressors and multi-hit pathways to carcinogenesis. We also contrast the landscapes inferred from AI- and total intensity-derived SCNAs and propose an automated procedure to improve and adjust SCNAs in TCGA for cases where high levels of aneuploidy obscured baseline intensity identification. Our findings support the exploration of additional methods for robust automated inference procedures and to aid empirical discoveries across TCGA.     

General assessment of copy number variation in normal and tumor tissues of the domestic dog (Canis lupus familiaris)

In recent years, characterization of a copy number variation (CNV) of the genomic DNA has provided evidence for the relationship of this type of genetic variation with the occurrence of a broad spectrum of diseases, including cancer lesions. Copy number variants (CNVs) also occur in the genomes of healthy individuals as a result of abnormal recombination processes in germ cells and have a hereditary character contributing to the natural genetic diversity. Recent image analysis methods and advanced computational techniques allow for identification of CNVs using SNPs genotyping microarrays based on the analysis of signal intensity observed for markers located in the specific genomic regions. In this study we used CanineHD BeadChip assay (Illumina) to identify both natural and cancer-induced CNVs in the genomes of different dog breeds and in different cancer types occurring in this species. The obtained results showed that structural aberrations are a common phenomenon arising during a tumor progression and are more complex and widespread in tumors of mesenchymal tissue origin than in epithelial tissue originating tumors. The tumor derived CNVs, in comparison to healthy samples, were characterized by larger sizes of regions, higher number of amplifications, and in some cases encompassed genes with potential effect on tumor progression.     

Estimation of tumor heterogeneity using CGH array data

Background  

Array-based comparative genomic hybridization (CGH) is a commonly-used approach to detect DNA copy number variation in whole genome-wide screens. Several statistical methods have been proposed to define genomic segments with different copy numbers in cancer tumors. However, most tumors are heterogeneous and show variation in DNA copy numbers across tumor cells. The challenge is to reveal the copy number profiles of the subpopulations in a tumor and to estimate the percentage of each subpopulation.     

Analysis of mitochondrial DNA copy number variation in blood and tissue samples of metastatic breast cancer patients (A pilot study)

Changes in mitochondrial DNA (mt-DNA) copy number in blood/tissue have been linked to increased risk of several cancers; however, studies on their association in breast cancer is still lacking. In this pilot study, we investigated mt-DNA copy number variation in peripheral blood and tissue samples from metastatic breast cancer patients and compared their differences. For the study, peripheral blood samples from non-cancer individuals (control) and breast cancer patients, along with resected tissues from adjacent and tumor sites from same breast cancer patients were collected. Total genomic DNA was isolated and changes in mt-DNA copy number were measured by relative quantification using SYBR green based quantitative real time PCR method. Our results indicated a significant reduction in mt-DNA copy number in blood samples of breast cancer patients compared to control. However, a significantly higher mt-DNA copy number was observed in tumor tissue when compared with paired non tumor tissue. There was no significant difference in mt-DNA copy number between blood and adjacent tumor tissue samples of the breast cancer patients. Overall, our study reports for the first time a comparison of mt-DNA copy number in blood and paired tissue together and suggested that mt-DNA copy number is differentially regulated in blood and tumor tissues in breast cancer.     

Bayesian estimation of genomic copy number with single nucleotide polymorphism genotyping arrays

Background

The identification of copy number aberration in the human genome is an important area in cancer research. We develop a model for determining genomic copy numbers using high-density single nucleotide polymorphism genotyping microarrays. The method is based on a Bayesian spatial normal mixture model with an unknown number of components corresponding to true copy numbers. A reversible jump Markov chain Monte Carlo algorithm is used to implement the model and perform posterior inference.

Results

The performance of the algorithm is examined on both simulated and real cancer data, and it is compared with the popular CNAG algorithm for copy number detection.

Conclusions

We demonstrate that our Bayesian mixture model performs at least as well as the hidden Markov model based CNAG algorithm and in certain cases does better. One of the added advantages of our method is the flexibility of modeling normal cell contamination in tumor samples.     

Accurate and simple evaluation of vascular anastomoses in monochorionic placenta using colored dye

The presence of placental vascular anastomoses is a conditio sine qua non for the development of twin-to-twin transfusion syndrome (TTTS) and twin anemia polycythemia sequence (TAPS)(1,2). Injection studies of twin placentas have shown that such anastomoses are almost invariably present in monochorionic twins and extremely rare in dichorionic twins(1). Three types of anastomoses have been documented: from artery to artery, from vein to vein and from artery to vein. Arterio-venous (AV) anastomoses are unidirectional and are referred to as "deep" anastomoses since they proceed through a shared placental cotyledon, whereas arterio-arterial (AA) and veno-venous (VV) anastomoses are bi-directional and are referred to as "superficial" since they lie on the chorionic plate. Both TTTS and TAPS are caused by net imbalance of blood flow between the twins due to AV anastomoses. Blood from one twin (the donor) is pumped through an artery into the shared placental cotyledon and then drained through a vein into the circulation of the other twin (the recipient). Unless blood is pumped back from the recipient to the donor through oppositely directed deep AV anastomoses or through superficial anastomoses, an imbalance of blood volumes occurs, gradually leading to the development of TTTS or TAPS. The presence of an AA anastomosis has been shown to protect against the development of TTTS and TAPS by compensating for the circulatory imbalance caused by the uni-directional AV anastomoses(1,2). Injection of monochorionic placentas soon after birth is a useful mean to understand the etiology of various (hematological) complications in monochorionic twins and is a required test to reach the diagnosis of TAPS(2). In addition, injection of TTTS placentas treated with fetoscopic laser surgery allows identification of possible residual anastomoses(3-5). This additional information is of paramount importance for all perinatologists involved in the management and care of monochorionic twins with TTTS or TAPS. Several placental injection techniques are currently being used. We provide a simple protocol to accurately evaluate the presence of (residual) vascular anastomoses using colored dye injection.     

Cell-free DNA ultra-low-pass whole genome sequencing to distinguish malignant peripheral nerve sheath tumor (MPNST) from its benign precursor lesion: A cross-sectional study

BackgroundThe leading cause of mortality for patients with the neurofibromatosis type 1 (NF1) cancer predisposition syndrome is the development of malignant peripheral nerve sheath tumor (MPNST), an aggressive soft tissue sarcoma. In the setting of NF1, this cancer type frequently arises from within its common and benign precursor, plexiform neurofibroma (PN). Transformation from PN to MPNST is challenging to diagnose due to difficulties in distinguishing cross-sectional imaging results and intralesional heterogeneity resulting in biopsy sampling errors.Methods and findingsThis multi-institutional study from the National Cancer Institute and Washington University in St. Louis used fragment size analysis and ultra-low-pass whole genome sequencing (ULP-WGS) of plasma cell-free DNA (cfDNA) to distinguish between MPNST and PN in patients with NF1. Following in silico enrichment for short cfDNA fragments and copy number analysis to estimate the fraction of plasma cfDNA originating from tumor (tumor fraction), we developed a noninvasive classifier that differentiates MPNST from PN with 86% pretreatment accuracy (91% specificity, 75% sensitivity) and 89% accuracy on serial analysis (91% specificity, 83% sensitivity). Healthy controls without NF1 (participants = 16, plasma samples = 16), PN (participants = 23, plasma samples = 23), and MPNST (participants = 14, plasma samples = 46) cohorts showed significant differences in tumor fraction in plasma (P = 0.001) as well as cfDNA fragment length (P < 0.001) with MPNST samples harboring shorter fragments and being enriched for tumor-derived cfDNA relative to PN and healthy controls. No other covariates were significant on multivariate logistic regression. Mutational analysis demonstrated focal NF1 copy number loss in PN and MPNST patient plasma but not in healthy controls. Greater genomic instability including alterations associated with malignant transformation (focal copy number gains in chromosome arms 1q, 7p, 8q, 9q, and 17q; focal copy number losses in SUZ12, SMARCA2, CDKN2A/B, and chromosome arms 6p and 9p) was more prominently observed in MPNST plasma. Furthermore, the sum of longest tumor diameters (SLD) visualized by cross-sectional imaging correlated significantly with paired tumor fractions in plasma from MPNST patients (r = 0.39, P = 0.024). On serial analysis, tumor fraction levels in plasma dynamically correlated with treatment response to therapy and minimal residual disease (MRD) detection before relapse. Study limitations include a modest MPNST sample size despite accrual from 2 major referral centers for this rare malignancy, and lack of uniform treatment and imaging protocols representing a real-world cohort.ConclusionsTumor fraction levels derived from cfDNA fragment size and copy number alteration analysis of plasma cfDNA using ULP-WGS significantly correlated with MPNST tumor burden, accurately distinguished MPNST from its benign PN precursor, and dynamically correlated with treatment response. In the future, our findings could form the basis for improved early cancer detection and monitoring in high-risk cancer-predisposed populations.

Jeffrey J. Szymanski and colleagues investigate the use of cell-free DNA ultra-low-pass whole genome sequencing to distinguish the malignant peripheral nerve sheath tumor (MPNST) from its benign precursor lesion in patients with Neurofibromatosis type 1 in United States.     

Potentiation of UVB-induced apoptosis by novel phytosphingosine derivative, tetraacetyl phytosphingosine in HaCaT cell and mouse skin

Inappropriate apoptosis results in the epidermal hyperplasia as in psoriasis and UVB irradiation has been successfully used to treat this kind of skin disorders. Previously, we reported that the novel phytosphingosine derivative, tetraacetyl phytosphingosine (TAPS) induced apoptosis in HaCaT cells. This study examined the effect of UVB irradiation and/or TAPS on the induction of apoptosis in HaCaT. 10 mJ/cm2 of UVB irradiation or 10 microM of TAPS alone exhibited weak cytotoxicity but co-treatment of UVB and TAPS synergistically enhanced the cytotoxicity and apoptosis in HaCaT. The cells treated with UVB and TAPS showed much higher levels of cleaved caspase-3, -8, -9 and Bax than with UVB or TAPS alone, whereas Bcl-2 level was decreased by co-administration of UVB and TAPS. In hairless mice, co-treatment of UVB and TAPS synergistically increased apoptosis, as shown in the HaCaT co-treated with UVB and TAPS. Furthermore, UVB irradiation caused an increase of apoptotic cells in the epidermis and the TAPS-treated mice showed an increase of apoptotic cells in the dermis as well as in the epidermis. These results suggest that the TAPS co-treatment synergistically increases the level of UVB-induced apoptosis via caspase activation by regulating the level of pro-apoptotic Bax and anti-apoptotic Bcl-2.     

Quantifying stability in gene list ranking across microarray derived clinical biomarkers

Background

Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) as a mechanism underlying tumorigenesis. Using microarrays and other technologies, tumor CNA are detected by comparing tumor sample CN to normal reference sample CN. While advances in microarray technology have improved detection of copy number alterations, the increase in the number of measured signals, noise from array probes, variations in signal-to-noise ratio across batches and disparity across laboratories leads to significant limitations for the accurate identification of CNA regions when comparing tumor and normal samples.

Methods

To address these limitations, we designed a novel "Virtual Normal" algorithm (VN), which allowed for construction of an unbiased reference signal directly from test samples within an experiment using any publicly available normal reference set as a baseline thus eliminating the need for an in-lab normal reference set.

Results

The algorithm was tested using an optimal, paired tumor/normal data set as well as previously uncharacterized pediatric malignant gliomas for which a normal reference set was not available. Using Affymetrix 250K Sty microarrays, we demonstrated improved signal-to-noise ratio and detected significant copy number alterations using the VN algorithm that were validated by independent PCR analysis of the target CNA regions.

Conclusions

We developed and validated an algorithm to provide a virtual normal reference signal directly from tumor samples and minimize noise in the derivation of the raw CN signal. The algorithm reduces the variability of assays performed across different reagent and array batches, methods of sample preservation, multiple personnel, and among different laboratories. This approach may be valuable when matched normal samples are unavailable or the paired normal specimens have been subjected to variations in methods of preservation.     

Genomic comparison between cerebrospinal fluid and primary tumor revealed the genetic events associated with brain metastasis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is most common pathological type of lung cancer. LUAD with brain metastases (BMs) usually have poor prognosis. To identify the potential genetic factors associated with BM, a genomic comparison for BM cerebrospinal fluid (CSF) and primary lung tumor samples obtained from 1082 early- and late-stage LUAD patients was performed. We found that single nucleotide variation (SNV) of EGFR was highly enriched in CSF (87% of samples). Compared with the other primary lung tissues, copy number gain of EGFR (27%), CDK4 (11%), PMS2 (11%), MET (10%), IL7R (8%), RICTOR (7%), FLT4 (5%), and FGFR4 (4%), and copy number loss of CDKN2A (28%) and CDKN2B (18%) were remarkably more frequent in CSF samples. CSF had significantly lower tumor mutation burden (TMB) level but more abundant copy number variant. It was also found that the relationships among co-occurrent and mutually exclusive genes were dynamically changing with LUAD development. Additionally, CSF (97% of samples) harbored more abundant targeted drugs related driver and fusion genes. The signature 15 associated with defective DNA mismatch repair (dMMR) was only identified in the CSF group. Cancer associated pathway analysis further revealed that ErbB (95%) and cell cycle (84%) were unique pathways in CSF samples. The tumor evolution analysis showed that CSF carried significantly fewer clusters, but subclonal proportion of EGFR was remarkably increased with tumor progression. Collectively, CSF sequencing showed unique genomic characteristics and the intense copy number instability associated with cell cycle disorder and dMMR might be the crucial genetic factors in BM of LUAD.Subject terms: Cancer genomics, Non-small-cell lung cancer, Oncogenes     

DNA fragmentation simulation method (FSM) and fragment size matching improve aCGH performance of FFPE tissues

Whole-genome copy number analysis platforms, such as array comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) arrays, are transformative research discovery tools. In cancer, the identification of genomic aberrations with these approaches has generated important diagnostic and prognostic markers, and critical therapeutic targets. While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations. Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues. Using self-hybridizations of a single DNA sample we observed that aCGH performance is significantly improved by accurate DNA size determination and the matching of test and reference DNA samples so that both possess similar fragment sizes. Based on this observation, we developed a novel DNA fragmentation simulation method (FSM) that allows customized tailoring of the fragment sizes of test and reference samples, thereby lowering array failure rates. To validate our methods, we combined FSM with Universal Linkage System (ULS) labeling to study a cohort of 200 tumor samples using Agilent 1 M feature arrays. Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA). This study demonstrates that rigorous control of DNA fragment size improves aCGH performance. This methodological advance will permit the routine analysis of FFPE tumor samples for clinical trials and in daily clinical practice.