Universidad Nacional Autónoma de México Facultad de Medicina
Hospital General de México Whole genome mapping of copy number alterations and loss of heterozygosity in four cervical cancer cell lines using the Affymetrix 100K SNP mapping array 1
Facultad de Medicina. Universidad Nacional Autónoma de México. Unidad de Medicina Genómica. Hospital General de México. Laboratorio de Oncología Genómica, 4 Unidad de Investigación Médica en Enfermedades Oncológicas, Hospital de Oncología, CMN Siglo XXI-IMSS. Departamento de Atención a la Salud, División de Ciencias Biológicas y de la Salud. Universidad Autónoma Metropolitana, Campus Xochimilco.
Number of CNde altered regions Número regiones
E6 and E7 oncogenes. The expression of E6 and E7 in proliferating cells has been shown to disturb the mechanisms of chromosome duplication and segregation during mitosis and induces severe chromosomal instability. We believe that such instability could have an impact in the expression profile of cells due to alterations in the copy number (CN), such as amplifications and deletions of chromosome regions and loss
Número degenes genes Number of
Cervical cancer (CC) has been recognized as a multi-step process resulting from deregulated transcription of
2000 1500 1000
of heterozygosity (LOH). Although cancers are indeed extremely diverse and heterogeneous, some data
suggest that underlying this variability lies a small number of events whose convergence is required for the
Cellcelular line Línea C
CaLo, CaSki, HeLa and SiHa was performed using the high-resolution Affymetrix Mapping 100K singlenucleotide polymorphism (SNPs) array. We propose that commonly altered regions in the four CCL are
Number of regions Número deLOH regiones
process. In the present work, whole genome CN and LOH analysis of four cervical cancer cell lines (CCL)
identification of novel genes (tumor suppressor genes and oncogenes) involved in cell transformation
candidate to contain genes relevant to the tumoral process.
3000 2500 2000 1500
LOH6000 LOH+ 4000
Cellcelular line Línea
Materials and Methods
Cellcelular line Línea
FIG 3. Genome-wide CN and LOH alterations in four cervical cancer cell lines. A) Number of regions found with altered CN at each CCL. B) Number of genes found in the regions with altered (NCBI build 36.2) CN at each CCL. C) Number of regions found with LOH at each CCL. D) Number of genes found in the regions with altered LOH at each CCL. *When we separated the regions under the criteria of having or not having genes, we didn’t find significantly differences between both groups.
Cell lines: Derived from cervical cancer (CaLo, CaSki, HeLa, SiHa) Experimental Design (fig 1): A. Whole Genome Sampling Analysis Assay (WGSA) with the Affymetrix Mapping 100K single-nucleotide polymorphism array (116204 SNPs) Average distance between adjacent SNPs: 24 Kb Genome-wide scan of all autosomic chromosomes and the X
CN 832 Altered regions 937 Altered genes
Commonly altered regions
LOH 304 Altered regions 420 Altered genes
Number of altered regions per cell line
Obtaining signal intensities from GCOS software
FIG 4. Identification process of genes with abnormal CN and LOH. Genes mapped within an altered region were identified and then grouped as shown in table 2.
B. Alleles were typed by GTYPE analysis software ver. 4.1 C. Copy number estimates were generated by CNAT 4 analysis tool
D. Filtering via thresholds using Ideogram Browser software tool Número Numberde ofgenes genes
% (Number of genes)
80 60 40
20 0 X 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 18 19 20 21 22 23 Chromosome Cromosoma
FIG 5 . Frequency of genes commonly altered in four cervical cancer cell lines by chromosome. The figure shows the number of genes found inside regions altered commonly at all CCL. Chromosomes that contain the majority of affected genes were the X, 13, 5, 18 and 11.
Status (no. of genes) GO Term, Biological Process
D. Ideogram Browser
Cellcelular line Línea
Number ofde genes Número genes
development of CC. Therefore, common events of alteration of CN and LOH could provide clues for the
The signal intensities of each SNP were obtained from GCOS software
C. CNAT software was used to classify each SNP into 5 different CN and 2 LOH
2/1 (255) FIG. 1. A) Genomic DNA was extracted by standard phenol chloroform technique and treated as described. Intensity signals of each SNP were obtained by GCOS software. B) Signal intensities were then processed with GTYPE software to call alleles of each SNP. C) Next step was to classify each SNP into five different states of CN (0=double deletion, 1=single deletion, 2=normal copy number, 3=amplification, 4=gain) and two states of LOH (0=LOH negative, 1=LOH positive). All estimations were made by comparing to a control set of normal individuals . D) Altered regions were defined as those were at least were 3 SNPs with the same state and positioned consecutively, regions were identified by Ideogram-Browser software. Once we had altered regions by cell line, we compared the sets of altered regions in order to identify those that were common to all.
5 5.99 (64) 0.094 TABLE 1. Most affected chromosomes by number of commonly altered genes. Table indicates the number of genes and percentage of total genes in that chromosome. P-value indicates the degree of gene enrichment compared to the total genes localizated in the same chromosome. (Genome Biol. 2003; 4(9): R60).
metabolism primary metabolism regulation of cellular process cellular macromolecule metabolism protein metabolism regulation of cellular metabolism
139 133 70 64 64 54
34.58 33.08 17.41 15.92 15.92 13.43
regulation of nucleic acid transcription
cell communication signal transduction transport cell proliferation
22 21 16 6
16.18 15.44 11.76 4.41
cell communication transport signal transduction intracellular signaling cascade cell-cell signaling cell adhesion
48 43 41 21 13 11
20.87 18.70 17.83 9.13 5.65 4.78
transport ion transport neurophysiological process cation transport
31 18 15 13
13.54 7.86 6.55 5.68
TABLE 2. Genes found altered mixing CN and LOH status with the most frequent Biological-Process-GeneOntology terms found at each group. Combining CN and LOH status we found 1192 genes commonly altered that were grouped into six different categories, in the table are shown only four of the categories. Each group could represent different mechanisms of alteration. The interpretation of status codes is explained in figure 1. GO= Gene Ontology, NF= Not found. p-Value indicates the degree of gene enrichment of that GO term in the total number of genes on that group of genes (Genome Biol. 2003; 4: R60).*Number of genes classified in the corresponding GO term. ** Percentage of the total genes in that group.
Conclusions 1. About 3/4 of the SNPs analyzed were found altered in SiHa/HeLa whereas only 50% in CaSki/CaLo CCL. 2. The main SNP alterations in the four CCL was amplifications, followed by deletions without LOH. It’s noteworthy the high proportion of SNPs with LOH and normal CN in the four CCL. 3. Although the number of altered regions were higher in CaLo/CaSki than in HeLa/SiHa, the number of altered
genes wer higher in the las two CCL. 4. A total of 1192 genes were commonly altered in al four CCL. 607 were deleted, 248 were amplified, 82 were CN/LOH
gained and 255 had LOH with normal CN. 5. The most affected chromosomes classified by number of affected genes were the X, 13, 11, suggesting that they could have special importance in the common genetic instability of this CCL.
6. Classification by GO shown that biological process terms enrich the groups differently in mechanisms such as metabolism, cell communication and transport. This work represents the first step into an effort to map with the highest resolution all the alterations that happen in FIG 2. Status of 116,204 SNPs in four CCL. Each SNP was classified taking into account its CN status and LOH status. In this manner we end up with nine different groups of SNPs depending of the CN/LOH status. We have five different states of CN (0=double deletion, 1=single deletion, 2=normal copy number, 3=amplification, 4=gain) and two LOH states (0=LOH negative, 1=LOH positive).
CCL and tumors from CC. Although most alterations found are very likely originated by the well known process of genomic instability, we were able to find alterations common to all. Many of them could be target of further analysis to elucidate the role of genomic instability in the process of cellular transformation of these CCL.
Published on Aug 24, 2011
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