Microarray comparative genomic hybridization detection of chromosomal imbalances in uterine cervix carcinoma

BACKGROUND: Chromosomal Comparative Genomic Hybridization (CGH) has been applied to all stages of cervical carcinoma progression, defining a specific pattern of chromosomal imbalances in this tumor. However, given its limited spatial resolution, chromosomal CGH has offered only general information regarding the possible genetic targets of DNA copy number changes. METHODS: In order to further define specific DNA copy number changes in cervical cancer, we analyzed 20 cervical samples (3 pre-malignant lesions, 10 invasive tumors, and 7 cell lines), using the GenoSensor microarray CGH system to define particular genetic targets that suffer copy number changes. RESULTS: The most common DNA gains detected by array CGH in the invasive samples were located at the RBP1-RBP2 (3q21-q22) genes, the sub-telomeric clone C84C11/T3 (5ptel), D5S23 (5p15.2) and the DAB2 gene (5p13) in 58.8% of the samples. The most common losses were found at the FHIT gene (3p14.2) in 47% of the samples, followed by deletions at D8S504 (8p23.3), CTDP1-SHGC- 145820 (18qtel), KIT (4q11-q12), D1S427-FAF1 (1p32.3), D9S325 (9qtel), EIF4E (eukaryotic translation initiation factor 4E, 4q24), RB1 (13q14), and DXS7132 (Xq12) present in 5/17 (29.4%) of the samples. CONCLUSION: Our results confirm the presence of a specific pattern of chromosomal imbalances in cervical carcinoma and define specific targets that are suffering DNA copy number changes in this neoplasm

Single-cell chromosomal imbalances detection by array CGH

Genomic imbalances are a major cause of constitutional and acquired disorders. Therefore, aneuploidy screening has become the cornerstone of preimplantation, prenatal and postnatal genetic diagnosis, as well as a routine aspect of the diagnostic workup of many acquired disorders. Recently, array comparative genomic hybridization (array CGH) has been introduced as a rapid and high-resolution method for the detection of both benign and disease-causing genomic copy-number variations. Until now, array CGH has been performed using a significant quantity of DNA derived from a pool of cells. Here, we present an array CGH method that accurately detects chromosomal imbalances from a single lymphoblast, fibroblast and blastomere within a single day. Trisomy 13, 18, 21 and monosomy X, as well as normal ploidy levels of all other chromosomes, were accurately determined from single fibroblasts. Moreover, we showed that a segmental deletion as small as 34 Mb could be detected. Finally, we demonstrated the possibility to detect aneuploidies in single blastomeres derived from preimplantation embryos. This technique offers new possibilities for genetic analysis of single cells in general and opens the route towards aneuploidy screening and detection of unbalanced translocations in preimplantation embryos in particular

waviCGH: a web application for the analysis and visualization of genomic copy number alterations

waviCGH is a versatile web server for the analysis and comparison of genomic copy number alterations in multiple samples from any species. waviCGH processes data generated by high density SNP-arrays, array-CGH or copy-number calls generated by any technique. waviCGH includes methods for pre-processing of the data, segmentation, calling of gains and losses, and minimal common regions determination over a set of experiments. The server is a user-friendly interface to the analytical methods, with emphasis on results visualization in a genomic context. Analysis tools are introduced to the user as the different steps to follow in an experimental protocol. All the analysis steps generate high quality images and tables ready to be imported into spreadsheet programs. Additionally, for human, mouse and rat, altered regions are represented in a biological context by mapping them into chromosomes in an integrated cytogenetic browser. waviCGH is available at http://wavi.bioinfo.cnio.es

An all-statistics, high-speed algorithm for the analysis of copy number variation in genomes

Detection of copy number variation (CNV) in DNA has recently become an important method for understanding the pathogenesis of cancer. While existing algorithms for extracting CNV from microarray data have worked reasonably well, the trend towards ever larger sample sizes and higher resolution microarrays has vastly increased the challenges they face. Here, we present Segmentation analysis of DNA (SAD), a clustering algorithm constructed with a strategy in which all operational decisions are based on simple and rigorous applications of statistical principles, measurement theory and precise mathematical relations. Compared with existing packages, SAD is simpler in formulation, more user friendly, much faster and less thirsty for memory, offers higher accuracy and supplies quantitative statistics for its predictions. Unique among such algorithms, SAD's running time scales linearly with array size; on a typical modern notebook, it completes high-quality CNV analyses for a 250 thousand-probe array in ∼1 s and a 1.8 million-probe array in ∼8 s

CNV-seq, a new method to detect copy number variation using high-throughput sequencing

<p>Abstract</p> <p>Background</p> <p>DNA copy number variation (CNV) has been recognized as an important source of genetic variation. Array comparative genomic hybridization (aCGH) is commonly used for CNV detection, but the microarray platform has a number of inherent limitations.</p> <p>Results</p> <p>Here, we describe a method to detect copy number variation using shotgun sequencing, CNV-seq. The method is based on a robust statistical model that describes the complete analysis procedure and allows the computation of essential confidence values for detection of CNV. Our results show that the number of reads, not the length of the reads is the key factor determining the resolution of detection. This favors the next-generation sequencing methods that rapidly produce large amount of short reads.</p> <p>Conclusion</p> <p>Simulation of various sequencing methods with coverage between 0.1× to 8× show overall specificity between 91.7 – 99.9%, and sensitivity between 72.2 – 96.5%. We also show the results for assessment of CNV between two individual human genomes.</p

The reg4 Gene, Amplified in the Early Stages of Pancreatic Cancer Development, Is a Promising Therapeutic Target

BACKGROUND: The aim of our work was to identify the genes specifically altered in pancreatic adenocarcinoma and especially those that are altered early in cancer development. METHODOLOGY/PRINCIPAL FINDINGS: Gene copy number was systematically assessed with an ultra-high resolution CGH oligonucleotide microarray in DNA from samples of pancreatic cancer. Several new cancer-associated variations were observed. In this work we focused on one of them, involving the reg4 gene. Gene copy number gain of the reg4 gene was confirmed by qPCR in 14 cancer samples. It was also found with increased copy number in most PanIN3 samples. The relationship betweena gain in reg4 gene copy number and cancer development was investigated on the human pancreatic cancer cell line Mia-PaCa2 xenografted under the skin of nude mice. When cells were transfected with a vector allowing reg4 expression, they generated tumors almost twice larger in size. In addition, these tumors were more resistant to gemcitabine treatment than control tumors. Interestingly, weekly intraperitoneal administration of a monoclonal antibody to reg4 halved the size of tumors generated by Mia-PaCa2 cells, suggesting that the antibody interfered with a paracrine/autocrine mechanism involving reg4 and stimulating cancer progression. The addition of gemcitabine resulted in further reduction, tumors becoming 5 times smaller than control. Exposure to reg4 antibody resulted in a significant decrease in intra-tumor levels of pAkt, Bcl-xL, Bcl-2, survivin and cyclin D1. CONCLUSIONS/SIGNIFICANCE: It was concluded that adjuvant therapies targeting reg4 could improve the standard treatment of pancreatic cancer with gemcitabine

pRb Inactivation in Mammary Cells Reveals Common Mechanisms for Tumor Initiation and Progression in Divergent Epithelia

Retinoblastoma 1 (pRb) and the related pocket proteins, retinoblastoma-like 1 (p107) and retinoblastoma-like 2 (p130) (pRb(f), collectively), play a pivotal role in regulating eukaryotic cell cycle progression, apoptosis, and terminal differentiation. While aberrations in the pRb-signaling pathway are common in human cancers, the consequence of pRb(f) loss in the mammary gland has not been directly assayed in vivo. We reported previously that inactivating these critical cell cycle regulators in divergent cell types, either brain epithelium or astrocytes, abrogates the cell cycle restriction point, leading to increased cell proliferation and apoptosis, and predisposing to cancer. Here we report that mouse mammary epithelium is similar in its requirements for pRb(f) function; Rb(f) inactivation by T(121), a fragment of SV40 T antigen that binds to and inactivates pRb(f) proteins, increases proliferation and apoptosis. Mammary adenocarcinomas form within 16 mo. Most apoptosis is regulated by p53, which has no impact on proliferation, and heterozygosity for a p53 null allele significantly shortens tumor latency. Most tumors in p53 heterozygous mice undergo loss of the wild-type p53 allele. We show that the mechanism of p53 loss of heterozygosity is not simply the consequence of Chromosome 11 aneuploidy and further that chromosomal instability subsequent to p53 loss is minimal. The mechanisms for pRb and p53 tumor suppression in the epithelia of two distinct tissues, mammary gland and brain, are indistinguishable. Further, this study has produced a highly penetrant breast cancer model based on aberrations commonly observed in the human disease

CDCOCA: a statistical method to define complexity dependent co-occurring chromosomal aberrations

<p>Abstract</p> <p>Background</p> <p>Copy number alterations (CNA) play a key role in cancer development and progression. Since more than one CNA can be detected in most tumors, frequently co-occurring genetic CNA may point to cooperating cancer related genes. Existing methods for co-occurrence evaluation so far have not considered the overall heterogeneity of CNA per tumor, resulting in a preferential detection of frequent changes with limited specificity for each association due to the high genetic instability of many samples.</p> <p>Method</p> <p>We hypothesize that in cancer some linkage-independent CNA may display a non-random co-occurrence, and that these CNA could be of pathogenetic relevance for the respective cancer. We also hypothesize that the statistical relevance of co-occurring CNA may depend on the sample specific CNA complexity. We verify our hypotheses with a simulation based algorithm CDCOCA (complexity dependence of co-occurring chromosomal aberrations).</p> <p>Results</p> <p>Application of CDCOCA to example data sets identified co-occurring CNA from low complex background which otherwise went unnoticed. Identification of cancer associated genes in these co-occurring changes can provide insights of cooperative genes involved in oncogenesis.</p> <p>Conclusions</p> <p>We have developed a method to detect associations of regional copy number abnormalities in cancer data. Along with finding statistically relevant CNA co-occurrences, our algorithm points towards a generally low specificity for co-occurrence of regional imbalances in CNA rich samples, which may have negative impact on pathway modeling approaches relying on frequent CNA events.</p