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.     

Genomic DNA extraction methods using formalin-fixed paraffin-embedded tissue

As new technologies come within reach for the average cytogenetic laboratory, the study of chromosome structure has become increasingly more sophisticated. Resolution has improved from karyotyping (in which whole chromosomes are discernible) to fluorescence in situ hybridization and comparative genomic hybridization (CGH, with which specific megabase regions are visualized), array-based CGH (aCGH, examining hundreds of base pairs), and next-generation sequencing (providing single base pair resolution). Whole genome next-generation sequencing remains a cost-prohibitive method for many investigators. Meanwhile, the cost of aCGH has been reduced during recent years, even as resolution has increased and protocols have simplified. However, aCGH presents its own set of unique challenges. DNA of sufficient quantity and quality to hybridize to arrays and provide meaningful results is required. This is especially difficult for DNA from formalin-fixed paraffin-embedded (FFPE) tissues. Here, we compare three different methods for acquiring DNA of sufficient length, purity, and “amplifiability” for aCGH and other downstream applications. Phenol–chloroform extraction and column-based commercial kits were compared with adaptive focused acoustics (AFA). Of the three extraction methods, AFA samples showed increased amplicon length and decreased polymerase chain reaction (PCR) failure rate. These findings support AFA as an improvement over previous DNA extraction methods for FFPE tissues.     

Identification of high-confidence somatic mutations in whole genome sequence of formalin-fixed breast cancer specimens

The utilization of archived, formalin-fixed paraffin-embedded (FFPE) tumor samples for massive parallel sequencing has been challenging due to DNA damage and contamination with normal stroma. Here, we perform whole genome sequencing of DNA isolated from two triple-negative breast cancer tumors archived for >11 years as 5 μm FFPE sections and matched germline DNA. The tumor samples show differing amounts of FFPE damaged DNA sequencing reads revealed as relatively high alignment mismatch rates enriched for C · G > T · A substitutions compared to germline samples. This increase in mismatch rate is observable with as few as one million reads, allowing for an upfront evaluation of the sample integrity before whole genome sequencing. By applying innovative quality filters incorporating global nucleotide mismatch rates and local mismatch rates, we present a method to identify high-confidence somatic mutations even in the presence of FFPE induced DNA damage. This results in a breast cancer mutational profile consistent with previous studies and revealing potentially important functional mutations. Our study demonstrates the feasibility of performing genome-wide deep sequencing analysis of FFPE archived tumors of limited sample size such as residual cancer after treatment or metastatic biopsies.     

Deep Clonal Profiling of Formalin Fixed Paraffin Embedded Clinical Samples

Formalin fixed paraffin embedded (FFPE) tissues are a vast resource of annotated clinical samples. As such, they represent highly desirable and informative materials for the application of high definition genomics for improved patient management and to advance the development of personalized therapeutics. However, a limitation of FFPE tissues is the variable quality of DNA extracted for analyses. Furthermore, admixtures of non-tumor and polyclonal neoplastic cell populations limit the number of biopsies that can be studied and make it difficult to define cancer genomes in patient samples. To exploit these valuable tissues we applied flow cytometry-based methods to isolate pure populations of tumor cell nuclei from FFPE tissues and developed a methodology compatible with oligonucleotide array CGH and whole exome sequencing analyses. These were used to profile a variety of tumors (breast, brain, bladder, ovarian and pancreas) including the genomes and exomes of matching fresh frozen and FFPE pancreatic adenocarcinoma samples.     

Amplifying small amounts of tumor DNA allows detection of DNA copy number abberations with array-CGH

Array comparative genomic hybridization (aCGH) is a powerful tool to detect relative DNA copy number at a resolution limited only by the coverage of bacterial artificial chromosomes (BACs) used to print the genomic array. The amount of DNA needed to perform a reliable aCGH analysis has been a limiting factor, especially on minute tissue samples where limited DNA is available. Here we report a simple, highly sensitive and reliable aCGH method to analyze samples of no more than 1 ng genomic DNA. The speed and simplicity of the technique are ideal for studies on small clinical samples such as needle biopsies.     

Array CGH using whole genome amplification of fresh-frozen and formalin-fixed, paraffin-embedded tumor DNA

The ability to utilize formalin-fixed, paraffin-embedded (FFPE) archival specimens reliably for high-resolution molecular genetic analysis would be of immense practical application in the study of human disease. We have evaluated the ability of the GenomePlex whole genome amplification (WGA) kit to amplify frozen and FFPE tissue for use in array CGH (aCGH). GenomePlex gave highly representative data compared with unamplified controls both from frozen material (Pearson's R(2) = 0.898) and from FFPE (R(2) = 0.883). Artifactual amplification observed using DOP-PCR at chromosomes 1p, 3, 13q, and 16p was not seen with GenomePlex. Highly reproducible aCGH profiles were obtained using as little as 5 ng starting material from FFPE (R(2) = 0.918). This WGA method should readily lend itself to the determination of DNA copy number alterations from small fresh-frozen and FFPE clinical tumor specimens, although some care must be taken to optimize the DNA extraction procedure.     

Using next-generation sequencing for high resolution multiplex analysis of copy number variation from nanogram quantities of DNA from formalin-fixed paraffin-embedded specimens

The use of next-generation sequencing technologies to produce genomic copy number data has recently been described. Most approaches, however, reply on optimal starting DNA, and are therefore unsuitable for the analysis of formalin-fixed paraffin-embedded (FFPE) samples, which largely precludes the analysis of many tumour series. We have sought to challenge the limits of this technique with regards to quality and quantity of starting material and the depth of sequencing required. We confirm that the technique can be used to interrogate DNA from cell lines, fresh frozen material and FFPE samples to assess copy number variation. We show that as little as 5 ng of DNA is needed to generate a copy number karyogram, and follow this up with data from a series of FFPE biopsies and surgical samples. We have used various levels of sample multiplexing to demonstrate the adjustable resolution of the methodology, depending on the number of samples and available resources. We also demonstrate reproducibility by use of replicate samples and comparison with microarray-based comparative genomic hybridization (aCGH) and digital PCR. This technique can be valuable in both the analysis of routine diagnostic samples and in examining large repositories of fixed archival material.     

Identification of cancer genes using a statistical framework for multiexperiment analysis of nondiscretized array CGH data

Tumor formation is in part driven by DNA copy number alterations (CNAs), which can be measured using microarray-based Comparative Genomic Hybridization (aCGH). Multiexperiment analysis of aCGH data from tumors allows discovery of recurrent CNAs that are potentially causal to cancer development. Until now, multiexperiment aCGH data analysis has been dependent on discretization of measurement data to a gain, loss or no-change state. Valuable biological information is lost when a heterogeneous system such as a solid tumor is reduced to these states. We have developed a new approach which inputs nondiscretized aCGH data to identify regions that are significantly aberrant across an entire tumor set. Our method is based on kernel regression and accounts for the strength of a probe's signal, its local genomic environment and the signal distribution across multiple tumors. In an analysis of 89 human breast tumors, our method showed enrichment for known cancer genes in the detected regions and identified aberrations that are strongly associated with breast cancer subtypes and clinical parameters. Furthermore, we identified 18 recurrent aberrant regions in a new dataset of 19 p53-deficient mouse mammary tumors. These regions, combined with gene expression microarray data, point to known cancer genes and novel candidate cancer genes.     

Validation and Application of a Custom-Designed Targeted Next-Generation Sequencing Panel for the Diagnostic Mutational Profiling of Solid Tumors

The inevitable switch from standard molecular methods to next-generation sequencing for the molecular profiling of tumors is challenging for most diagnostic laboratories. However, fixed validation criteria for diagnostic accreditation are not in place because of the great variability in methods and aims. Here, we describe the validation of a custom panel of hotspots in 24 genes for the detection of somatic mutations in non-small cell lung carcinoma, colorectal carcinoma and malignant melanoma starting from FFPE sections, using 14, 36 and 5 cases, respectively. The targeted hotspots were selected for their present or future clinical relevance in solid tumor types. The target regions were enriched with the TruSeq approach starting from limited amounts of DNA. Cost effective sequencing of 12 pooled libraries was done using a micro flow cell on the MiSeq and subsequent data analysis with MiSeqReporter and VariantStudio. The entire workflow was diagnostically validated showing a robust performance with maximal sensitivity and specificity using as thresholds a variant allele frequency >5% and a minimal amplicon coverage of 300. We implemented this method through the analysis of 150 routine diagnostic samples and identified clinically relevant mutations in 16 genes including KRAS (32%), TP53 (32%), BRAF (12%), APC (11%), EGFR (8%) and NRAS (5%). Importantly, the highest success rate was obtained when using also the low quality DNA samples. In conclusion, we provide a workflow for the validation of targeted NGS by a custom-designed pan-solid tumor panel in a molecular diagnostic lab and demonstrate its robustness in a clinical setting.     

Determining Frequent Patterns of Copy Number Alterations in Cancer

Cancer progression is often driven by an accumulation of genetic changes but also accompanied by increasing genomic instability. These processes lead to a complicated landscape of copy number alterations (CNAs) within individual tumors and great diversity across tumor samples. High resolution array-based comparative genomic hybridization (aCGH) is being used to profile CNAs of ever larger tumor collections, and better computational methods for processing these data sets and identifying potential driver CNAs are needed. Typical studies of aCGH data sets take a pipeline approach, starting with segmentation of profiles, calls of gains and losses, and finally determination of frequent CNAs across samples. A drawback of pipelines is that choices at each step may produce different results, and biases are propagated forward. We present a mathematically robust new method that exploits probe-level correlations in aCGH data to discover subsets of samples that display common CNAs. Our algorithm is related to recent work on maximum-margin clustering. It does not require pre-segmentation of the data and also provides grouping of recurrent CNAs into clusters. We tested our approach on a large cohort of glioblastoma aCGH samples from The Cancer Genome Atlas and recovered almost all CNAs reported in the initial study. We also found additional significant CNAs missed by the original analysis but supported by earlier studies, and we identified significant correlations between CNAs.     

Micro-Scale Genomic DNA Copy Number Aberrations as Another Means of Mutagenesis in Breast Cancer

Introduction

In breast cancer, the basal-like subtype has high levels of genomic instability relative to other breast cancer subtypes with many basal-like-specific regions of aberration. There is evidence that this genomic instability extends to smaller scale genomic aberrations, as shown by a previously described micro-deletion event in the PTEN gene in the Basal-like SUM149 breast cancer cell line.

Methods

We sought to identify if small regions of genomic DNA copy number changes exist by using a high density, gene-centric Comparative Genomic Hybridizations (CGH) array on cell lines and primary tumors. A custom tiling array for CGH (244,000 probes, 200 bp tiling resolution) was created to identify small regions of genomic change, which was focused on previously identified basal-like-specific, and general cancer genes. Tumor genomic DNA from 94 patients and 2 breast cancer cell lines was labeled and hybridized to these arrays. Aberrations were called using SWITCHdna and the smallest 25% of SWITCHdna-defined genomic segments were called micro-aberrations (<64 contiguous probes, ∼ 15 kb).

Results

Our data showed that primary tumor breast cancer genomes frequently contained many small-scale copy number gains and losses, termed micro-aberrations, most of which are undetectable using typical-density genome-wide aCGH arrays. The basal-like subtype exhibited the highest incidence of these events. These micro-aberrations sometimes altered expression of the involved gene. We confirmed the presence of the PTEN micro-amplification in SUM149 and by mRNA-seq showed that this resulted in loss of expression of all exons downstream of this event. Micro-aberrations disproportionately affected the 5′ regions of the affected genes, including the promoter region, and high frequency of micro-aberrations was associated with poor survival.

Conclusion

Using a high-probe-density, gene-centric aCGH microarray, we present evidence of small-scale genomic aberrations that can contribute to gene inactivation. These events may contribute to tumor formation through mechanisms not detected using conventional DNA copy number analyses.     

Improved RNA quality and TaqMan<Superscript>®</Superscript>Pre-amplification method (PreAmp) to enhance expression analysis from formalin fixed paraffin embedded (FFPE) materials

Background  

Archival formalin-fixed paraffin-embedded (FFPE) tissues represent an abundant source of clinical specimens; however their use is limited in applications involving analysis of gene expression due to RNA degradation and modification during fixation and processing. This study improved the quality of RNA extracted from FFPE by introducing a heating step into the selected extraction protocols. Further, it evaluated a novel pre-amplification system (PreAmp) designed to enhance expression analysis from tissue samples using assays with a range of amplicon size (62–164 bp).     

Rapid Detection of high-level oncogene amplifications in ultrasonic surgical aspirations of brain tumors

ABSTRACT: BACKGROUND: Genomic tumor information, such as identification of amplified oncogenes, can be used to plan treatment. The two sources of a brain tumor that are commonly available include formalin-fixed, paraffin-embedded (FFPE) sections from the small diagnostic biopsy and the ultrasonic surgical aspiration that contains the bulk of the tumor. In research centers, frozen tissue of a brain tumor may also be available. This study compared ultrasonic surgical aspiration and FFPE specimens from the same brain tumors for retrieval of DNA and molecular assessment of amplified oncogenes. METHODS: Surgical aspirations were centrifuged to separate erythrocytes from the tumor cells that predominantly formed large, overlying buffy coats. These were sampled to harvest nuclear pellets for DNA purification. Four glioblastomas, 2 lung carcinoma metastases, and an ependymoma were tested. An inexpensive PCR technique, multiplex ligation-dependent probe amplification (MLPA), quantified 79 oncogenes using 3 kits. Copy number (CN) results were normalized to DNA from non-neoplastic brain (NB) in calculated ratios, [tumor DNA]/[NB DNA]. Bland-Altman and Spearman rank correlative comparisons were determined. Regression analysis identified outliers. RESULTS: Purification of DNA from ultrasonic surgical aspirations was rapid (<3 days) versus FFPE (weeks) and yielded greater amounts in 6 of 7 tumors. Gene amplifications up to 15-fold corresponded closely between ultrasonic aspiration and FFPE assays in Bland-Altman analysis. Correlation coefficients ranged from 0.71 to 0.99 using 3 kit assays per tumor. Although normalized CN ratios greater than 2.0 were more numerous in FFPE specimens, some were found only in the ultrasonic surgical aspirations, consistent with tumor heterogeneity. Additionally, CN ratios revealed 9 high-level ([greater than or equal to] 6.0) gene amplifications in FFPE of which 8 were also detected in the ultrasonic aspirations at increased levels. The ultrasonic aspiration levels of these amplified genes were also greater than 6.0 CN ratio, except in one case (3.53 CN ratio). Ten of 17 mid-level ([greater than or equal to]3.0 & <6.0 CN ratio) amplifications detected in FFPE were also detected as being increased ([greater than or equal to] 2.0 CN ratio) in the aspirations. CONCLUSIONS: Buffy coats of centrifuged ultrasonic aspirations contained abundant tumor cells whose DNA permitted rapid, multiplex detection of high-level oncogene amplifications that were confirmed in FFPE. Virtual slides http://www.diagnosticpathology.diagnomx.eu/vs/1883718801686466.     

A fused lasso latent feature model for analyzing multi-sample aCGH data

Array-based comparative genomic hybridization (aCGH) enables the measurement of DNA copy number across thousands of locations in a genome. The main goals of analyzing aCGH data are to identify the regions of copy number variation (CNV) and to quantify the amount of CNV. Although there are many methods for analyzing single-sample aCGH data, the analysis of multi-sample aCGH data is a relatively new area of research. Further, many of the current approaches for analyzing multi-sample aCGH data do not appropriately utilize the additional information present in the multiple samples. We propose a procedure called the Fused Lasso Latent Feature Model (FLLat) that provides a statistical framework for modeling multi-sample aCGH data and identifying regions of CNV. The procedure involves modeling each sample of aCGH data as a weighted sum of a fixed number of features. Regions of CNV are then identified through an application of the fused lasso penalty to each feature. Some simulation analyses show that FLLat outperforms single-sample methods when the simulated samples share common information. We also propose a method for estimating the false discovery rate. An analysis of an aCGH data set obtained from human breast tumors, focusing on chromosomes 8 and 17, shows that FLLat and Significance Testing of Aberrant Copy number (an alternative, existing approach) identify similar regions of CNV that are consistent with previous findings. However, through the estimated features and their corresponding weights, FLLat is further able to discern specific relationships between the samples, for example, identifying 3 distinct groups of samples based on their patterns of CNV for chromosome 17.     

Impact of Pre-Analytical Variables on Cancer Targeted Gene Sequencing Efficiency

Tumor specimens are often preserved as formalin-fixed paraffin-embedded (FFPE) tissue blocks, the most common clinical source for DNA sequencing. Herein, we evaluated the effect of pre-sequencing parameters to guide proper sample selection for targeted gene sequencing. Data from 113 FFPE lung tumor specimens were collected, and targeted gene sequencing was performed. Libraries were constructed using custom probes and were paired-end sequenced on a next generation sequencing platform. A PCR-based quality control (QC) assay was utilized to determine DNA quality, and a ratio was generated in comparison to control DNA. We observed that FFPE storage time, PCR/QC ratio, and DNA input in the library preparation were significantly correlated to most parameters of sequencing efficiency including depth of coverage, alignment rate, insert size, and read quality. A combined score using the three parameters was generated and proved highly accurate to predict sequencing metrics. We also showed wide read count variability within the genome, with worse coverage in regions of low GC content like in KRAS. Sample quality and GC content had independent effects on sequencing depth, and the worst results were observed in regions of low GC content in samples with poor quality. Our data confirm that FFPE samples are a reliable source for targeted gene sequencing in cancer, provided adequate sample quality controls are exercised. Tissue quality should be routinely assessed for pre-analytical factors, and sequencing depth may be limited in genomic regions of low GC content if suboptimal samples are utilized.     

Reporting Tumor Molecular Heterogeneity in Histopathological Diagnosis

Background

Detection of molecular tumor heterogeneity has become of paramount importance with the advent of targeted therapies. Analysis for detection should be comprehensive, timely and based on routinely available tumor samples.

Aim

To evaluate the diagnostic potential of targeted multigene next-generation sequencing (TM-NGS) in characterizing gastrointestinal cancer molecular heterogeneity.

Methods

35 gastrointestinal tract tumors, five of each intestinal type gastric carcinomas, pancreatic ductal adenocarcinomas, pancreatic intraductal papillary mucinous neoplasms, ampulla of Vater carcinomas, hepatocellular carcinomas, cholangiocarcinomas, pancreatic solid pseudopapillary tumors were assessed for mutations in 46 cancer-associated genes, using Ion Torrent semiconductor-based TM-NGS. One ampulla of Vater carcinoma cell line and one hepatic carcinosarcoma served to assess assay sensitivity. TP53, PIK3CA, KRAS, and BRAF mutations were validated by conventional Sanger sequencing.

Results

TM-NGS yielded overlapping results on matched fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissues, with a mutation detection limit of 1% for fresh-frozen high molecular weight DNA and 2% for FFPE partially degraded DNA. At least one somatic mutation was observed in all tumors tested; multiple alterations were detected in 20/35 (57%) tumors. Seven cancers displayed significant differences in allelic frequencies for distinct mutations, indicating the presence of intratumor molecular heterogeneity; this was confirmed on selected samples by immunohistochemistry of p53 and Smad4, showing concordance with mutational analysis.

Conclusions

TM-NGS is able to detect and quantitate multiple gene alterations from limited amounts of DNA, moving one step closer to a next-generation histopathologic diagnosis that integrates morphologic, immunophenotypic, and multigene mutational analysis on routinely processed tissues, essential for personalized cancer therapy.     

Progressive genomic instability in the FVB/Kras(LA2) mouse model of lung cancer

Alterations in DNA copy number contribute to the development and progression of cancers and are common in epithelial tumors. We have used array Comparative Genomic Hybridization (aCGH) to visualize DNA copy number alterations across the genomes of lung tumors in the Kras(LA2) model of lung cancer. Copy number gain involving the Kras locus, as focal amplification or whole chromosome gain, is the most common alteration in these tumors and with a prevalence that increased significantly with increasing tumor size. Furthermore, Kras amplification was the only major genomic event among the smallest lung tumors, suggesting that this alteration occurs early during the development of mutant Kras-driven lung cancers. Recurring gains and deletions of other chromosomes occur progressively more frequently among larger tumors. These results are in contrast to a previous aCGH analysis of lung tumors from Kras(LA2) mice on a mixed genetic background, in which relatively few DNA copy number alterations were observed regardless of tumor size. Our model features the Kras(LA2) allele on the inbred FVB/N mouse strain, and in this genetic background, there is a highly statistically significant increase in level of genomic instability with increasing tumor size. These data suggest that recurring DNA copy alterations are important for tumor progression in the Kras(LA2) model of lung cancer and that the requirement for these alterations may be dependent on the genetic background of the mouse strain.     

Improved reproducibility in genome-wide DNA methylation analysis for PAXgene-fixed samples compared with restored formalin-fixed and paraffin-embedded DNA

Formalin fixation has been the standard method for conservation of clinical specimens for decades. However, a major drawback is the high degradation of nucleic acids, which complicates its use in genome-wide analyses. Unbiased identification of biomarkers, however, requires genome-wide studies, precluding the use of the valuable archives of specimens with long-term follow-up data. Therefore, restoration protocols for DNA from formalin-fixed and paraffin-embedded (FFPE) samples have been developed, although they are cost-intensive and time-consuming. An alternative to FFPE and snap-freezing is the PAXgene Tissue System, developed for simultaneous preservation of morphology, proteins, and nucleic acids. In the current study, we compared the performance of DNA from either PAXgene or formalin-fixed tissues to snap-frozen material for genome-wide DNA methylation analysis using the Illumina 450K BeadChip. Quantitative DNA methylation analysis demonstrated that the methylation profile in PAXgene-fixed tissues showed, in comparison with restored FFPE samples, a higher concordance with the profile detected in frozen samples. We demonstrate, for the first time, that DNA from PAXgene conserved tissue performs better compared with restored FFPE DNA in genome-wide DNA methylation analysis. In addition, DNA from PAXgene tissue can be directly used on the array without prior restoration, rendering the analytical process significantly more time- and cost-effective.     

Analytical Validation of AmpliChip p53 Research Test for Archival Human Ovarian FFPE Sections

The p53 tumor suppressor gene (TP53) is reported to be mutated in nearly half of all tumors and plays a central role in genome integrity. Detection of mutations in p53 can be accomplished by many assays, including the AmpliChip p53 Research Test. The AmpliChip p53 Research Test has been successfully used to determine p53 status in hematologic malignancies and fresh frozen solid tissues but there are few reports of using the assay with formalin fixed, paraffin-embedded (FFPE) tissue. The objective of this study was to describe analytical performance characterization of the AmpliChip p53 Research Test to detect p53 mutations in genomic DNA isolated from archival FFPE human ovarian tumor tissues. Method correlation with sequencing showed 96% mutation-wise agreement and 99% chip-wise agreement. We furthermore observed 100% agreement (113/113) of the most prevalent TP53 mutations. Workflow reproducibility was 96.8% across 8 samples, with 2 operators, 2 reagent lots and 2 instruments. Section-to-section reproducibility was 100% for each sample across a 60 μm region of the FFPE block from ovarian tumors. These data indicate that the AmpliChip p53 Research Test is an accurate and reproducible method for detecting mutations in TP53 from archival FFPE human ovarian specimens.