Clonality analysis of pulmonary tumors by genome-wide copy number profiling

Multiple tumors in patients are frequently diagnosed, either synchronous or metachronous. The distinction between a second primary and a metastasis is important for treatment. Chromosomal DNA copy number aberrations (CNA) patterns are highly unique to specific tumors. The aim of this study was to assess genome-wide CNA-patterns as method to identify clonally related tumors in a prospective cohort of patients with synchronous or metachronous tumors, with at least one intrapulmonary tumor. In total, 139 tumor pairs from 90 patients were examined: 35 synchronous and 104 metachronous pairs. Results of CNA were compared to histological type, clinicopathological methods (Martini-Melamed-classification (MM) and ACCP-2013-criteria), and, if available, EGFR- and KRAS-mutation analysis. CNA-results were clonal in 74 pairs (53%), non-clonal in 33 pairs (24%), and inconclusive in 32 pairs (23%). Histological similarity was found in 130 pairs (94%). Concordance between histology and conclusive CNA-results was 69% (74 of 107 pairs: 72 clonal and two non-clonal). In 31 of 103 pairs with similar histology, genetics revealed non-clonality. In two out of four pairs with non-matching histology, genetics revealed clonality. The subgroups of synchronous and metachronous pairs showed similar outcome for the comparison of histological versus CNA-results. MM-classification and ACCP-2013-criteria, applicable on 34 pairs, and CNA-results were concordant in 50% and 62% respectively. Concordance between mutation matching and conclusive CNA-results was 89% (8 of 9 pairs: six clonal and two non-clonal). Interestingly, in one patient both tumors had the same KRAS mutation, but the CNA result was non-clonal. In conclusion, although some concordance between histological comparison and CNA profiling is present, arguments exist to prefer extensive molecular testing to determine whether a second tumor is a metastasis or a second primary.

Applications of array-CGH for lung cancer

This chapter summarizes the current knowledge on gene copy number changes found in lung tumors, and their application in the diagnosis, prognostication, and prediction of response to chemotherapy. Examples of the identification of specific "driver" oncogenes within amplified DNA segments are described. A model of how array-CGH could be integrated clinically into the routine workup of lung cancers in clinical laboratory is proposed.

A meta-analysis of array-CGH studies implicates antiviral immunity pathways in the development of hepatocellular carcinoma

Background

The development and progression of hepatocellular carcinoma (HCC) is significantly correlated to the accumulation of genomic alterations. Array-based comparative genomic hybridization (array CGH) has been applied to a wide range of tumors including HCCs for the genome-wide high resolution screening of DNA copy number changes. However, the relevant chromosomal variations that play a central role in the development of HCC still are not fully elucidated.

Methods

In present study, in order to further characterize the copy number alterations (CNAs) important to HCC development, we conducted a meta-analysis of four published independent array-CGH datasets including total 159 samples.

Results

Eighty five significant gains (frequency ≥25%) were mostly mapped to five broad chromosomal regions including 1q, 6p, 8q, 17q and 20p, as well as two narrow regions 5p15.33 and 9q34.2-34.3. Eighty eight significant losses (frequency ≥25%) were most frequently present in 4q, 6q, 8p, 9p, 13q, 14q, 16q, and 17p. Significant correlations existed between chromosomal aberrations either located on the same chromosome or the different chromosomes. HCCs with different etiologies largely exhibited surprisingly similar profiles of chromosomal aberrations with only a few exceptions. Furthermore, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the genes affected by these chromosomal aberrations were significantly enriched in 31 canonical pathways with the highest enrichment observed for antiviral immunity pathways.

Conclusions

Taken together, our findings provide novel and important clues for the implications of antiviral immunity-related gene pathways in the pathogenesis and progression of HCC.

A double-layered mixture model for the joint analysis of DNA copy number and gene expression data

Copy number aberration is a common form of genomic instability in cancer. Gene expression is closely tied to cytogenetic events by the central dogma of molecular biology, and serves as a mediator of copy number changes in disease phenotypes. Accordingly, it is of interest to develop proper statistical methods for jointly analyzing copy number and gene expression data. This work describes a novel Bayesian inferential approach for a double-layered mixture model (DLMM) which directly models the stochastic nature of copy number data and identifies abnormally expressed genes due to aberrant copy number. Simulation studies were conducted to illustrate the robustness of DLMM under various settings of copy number aberration frequency, confounding effects, and signal-to-noise ratio in gene expression data. Analysis of a real breast cancer data shows that DLMM is able to identify expression changes specifically attributable to copy number aberration in tumors and that a sample-specific index built based on the selected genes is correlated with relevant clinical information.

Multiple aberrations of chromosome 3p detected in oral premalignant lesions

The study of oral premalignant lesions (OPL) is crucial to the identification of initiating genetic events in oral cancer. However, these lesions are minute in size, making it a challenge to recover sufficient DNA from microdissected cells for comprehensive genomic analysis. As a step toward identifying genetic aberrations associated with oral cancer progression, we used tiling-path array comparative genomic hybridization to compare alterations on chromosome 3p for 71 OPLs against 23 oral squamous cell carcinomas. 3p was chosen because although it is frequently altered in oral cancers and has been associated with progression risk, its alteration status has only been evaluated at a small number of loci in OPLs. We identified six recurrent losses in this region that were shared between high-grade dysplasias and oral squamous cell carcinomas, including a 2.89-Mbp deletion spanning the FHIT gene (previously implicated in oral cancer progression). When the alteration status for these six regions was examined in 24 low-grade dysplasias with known progression outcome, we observed that they occurred at a significantly higher frequency in low-grade dysplasias that later progressed to later-stage disease (P < 0.003). Moreover, parallel analysis of all profiled tissues showed that the extent of overall genomic alteration at 3p increased with histologic stage. This first high-resolution analysis of chromosome arm 3p in OPLs represents a significant step toward predicting progression risk in early preinvasive disease and provides a keen example of how genomic instability escalates with progression to invasive cancer.

Genome-wide analysis of pancreatic cancer using microarray-based techniques

BACKGROUND/AIMS

Microarray-based comparative genomic hybridisation (CGH) has allowed high-resolution analysis of DNA copy number alterations across the entire cancer genome. Recent advances in bioinformatics tools enable us to perform a robust and highly sensitive analysis of array CGH data and facilitate the discovery of novel cancer-related genes.

METHODS

We analysed a total of 29 pancreatic ductal adenocarcinoma (PDAC) samples (6 cell lines and 23 microdissected tissue specimens) using 1-Mb-spaced CGH arrays. The transcript levels of all genes within the identified regions of genetic alterations were then screened using our Pancreatic Expression Database.

RESULTS

In addition to 238 high-level amplifications and 35 homozygous deletions, we identified 315 minimal common regions of 'non-random' genetic alterations (115 gains and 200 losses) which were consistently observed across our tumour samples. The small size of these aberrations (median size of 880 kb) contributed to the reduced number of candidate genes included (on average 12 Ensembl-annotated genes). The database has further specified the genes whose expression levels are consistent with their copy number status. Such genes were UQCRB, SQLE, DDEF1, SLA, ERICH1 and DLC1, indicating that these may be potential target candidates within regions of aberrations.

CONCLUSION

This study has revealed multiple novel regions that may indicate the locations of oncogenes or tumour suppressor genes in PDAC. Using the database, we provide a list of novel target genes whose altered DNA copy numbers could lead to significant changes in transcript levels in PDAC.

A process for analysis of microarray comparative genomics hybridisation studies for bacterial genomes

Background

Microarray based comparative genomic hybridisation (CGH) experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity.

Results

The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data.

Conclusion

After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.

ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data

BACKGROUND

Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies.

METHODOLOGY/PRINCIPAL FINDINGS

ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers.

CONCLUSIONS/SIGNIFICANCE

ADACGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45x); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects.