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Title of Thesis

Iftikhar Qayum
Institute/University/Department Details
Department of Biological Sciences/ Quaid-i-Azam University Islamabad
Biological Sciences
Number of Pages
Keywords (Extracted from title, table of contents and abstract of thesis)
dna methyl transferease 1, human lymphomas, oncogenic transformation, dna methylation, cellular processes, cpg islands, oncogenes, malignant tissues

In recent years, DNA methylation, both normal and abnormal, has become a hot topic for research into the genetics of normal cellular biological processes as well as malignant diseases. DNA methylation patterns are established essentially through methylation of the base cytosine at specific sites called CpG (Cytosine and Guanine pairs) islands and act as a regulator of gene expression for both normal and abnormal cellular processes. In essence, methylated CpG islands located in the promoter regions of genes cause these genes to become ā€˜silencedā€™ or ā€˜switched off by preventing ligand attachment to the methylated cytosine (5MeC); reversal of methylation allows these sites to bind ligand and be ā€˜switched onā€™. DNA methylation thus acts as an ā€˜epigeneticā€™ system for gene regulation. Methylation of cytosine bases is accomplished by a group of enzymes called DNA Methyltransferases or DNA-Mtases for short. Several types have been described, though DNA methyl transferase 1 (DNMT1) is the major type associated with routine or ā€˜maintenanceā€™ methylation.

Altered methylation patterns have been described in a variety of human malignancies. Most tumors appear to have global hypomethylation along with regional hypermethylation. This observation led to the hypothesis that tumor promoter genes were hypomethylated while tumor suppressor genes were hypermethylated, thus allowing for an unhindered oncogene drive for malignant transformation. The unifying link was the finding of increased DNMTl activity in these tumor types, which accounted for the hypermethylated tumor suppressor genes. Further insights into DNA methylation revealed that 5MeC could become a ā€˜hot spotā€™ for mutation, particularly C to T (Thymine) by deamination of cytosine, which later on gave rise to a T-A (Adenine) base substitution in DNA.

The present comparative study was conducted on human normal/reactive lymph nodes and lymphoma lymph nodes to determine the status of the DNMTI gene in human lymphomas and to assess its role in the transformation process by studying its gene expression through FISH. Two additional genes were studied, viz. p53, a prototype of the tumor suppressor system and PCNA (Proliferating Cell Nuclear Antigen), a prototype of the tumor promoter (proliferation) system. These two genes were included to allow for a correlation of the gene expression of the p53 gene to the gene expression of tumor suppressor or tumor promoter genes.

The study was undertaken at the Department of Biological Sciences (Genetics) of the Quaid-i-Azam University Islamabad and the Department of Pathology of the Ayub Medical College Abbottabad from May 2001 to April 2004. The study was conducted on routinely processed and preserved paraffin embedded archival human lymph node specimens taken from the Department of Pathology of the Ayub Medical College Abbottabad and included 50 cases of normal or reactive lymph nodes (controls) and 50 cases of lymphomas of various types. Sample selection was done by a computer generated random sample from a database of all lymph nodes processed during January 2000 to December 2002. Final samples were selected after excluding lymph node specimens that did not meet the technical requirements for a FISH study.

Variables of main interest were: mean percentage area of cells stained per slide, mean cytoplasmic ā€˜dotsā€™ stained per cell per slide and visual assessment of signal intensities of each slide. In addition, images were captured by CCD camera or other capturing systems and a computer database of images was made. Image analysis was done in the computer software Adobe Photoshop version 7.0, so that histograms of signal intensity were generated providing the Means Ā± S.D. of signal intensity in a quantitative manner.

Data were entered into SPSS version 8.0 for analysis. In addition to frequencies and descriptive analysis, correlation analysis was also performed between the three genes of interest for the control and lymphoma groups. Comparisons between groups were tested for significance by means of the Chi Square Test or the Student's T Test, as applicable; a pā‰¤ 0.05 was considered significant.

Results indicated an overall significant increase in the amount of mRNA present in tumor cells as compared to normal cells as judged by Polyd T staining characteristics (mean percent area 66.30Ā±6.98 for lymphoma cells and 62.10Ā±7.01 for normal cells, p=0.003; mean ā€˜dotsā€™ per cell 11.34Ā±3.80 for lymphoma cells and 8.84 Ā±2.35 for normal cells, p<0.001; mean signal intensity 104.40Ā±3 1.73 for lymphoma cells and 92.93 Ā±24.26 for normal cells, p=0.045).

All three genes of interest were similarly significantly increased in lymphoma cells as compared to normal cells. The Antisense DNMT1 probe results showed mean percent area 36.10 Ā±15.53 for lymphoma cells and 14.20Ā±4.88 for normal cells, p<0.001; mean ā€˜dotsā€™ per cell 11.30Ā±3.15 for lymphoma cells and 8.76Ā±2.51 for normal cells, p<0.001 mean signal intensity 101.85Ā±28.17 for lymphoma cells and 89.75 Ā±28.47 for normal cells, p=0.035. The Antisense p53 probe results showed mean percent area 33.70Ā±12.11 for lymphoma cells and 7.74Ā±2.39 for normal cells, p<0.001; mean ā€˜dotsā€™ per cell 11.46Ā±2.77 for lymphoma cells and 8.90 Ā±2.61 for normal cells, p<0.001; mean signal intensity 105.10Ā±26.65 for lymphoma cells and 89.17 Ā±24.97 for normal cells, p=0.003. The Antisense PCNA probe showed mean percent area 45.30Ā±8.77 for lymphoma cells and 22.40Ā±6.56 for normal cells, p<0.001; mean ā€˜dotsā€™ per cell 11.32Ā±2.75 for lymphoma cells and 8.98Ā±2.34 for normal cells, p<0.001; mean signal intensity 104.64Ā±30.32 for lymphoma cells and 92.46Ā±20.32 for normal cells, p=0.02. All these values were highly significant when compared to their corresponding Sense (negative control) probe values (p<0.001).

The frequency distributions of the mean percent areas of cells stained for control and lymphoma lymph nodes also showed significant differences when grouped into categories of <20%. 21-40%. 41-60%. 61-80% and >80%, (for Antisense PolydT p=0.02S, for Antisense DNMTI probe p<0.001. for Antisense p53 probe p<0.001, for Antisense PCNA probe p<0.001). The frequency distributions of the mean ā€˜dotsā€™ per cell showed significant differences between control and lymphoma lymph nodes when grouped into categories of <8, 9-16 and 17-24 mean ā€˜dotsā€™ per cell (for Antisense PolydT p=0.042, for Antisense DNMTI probe p=0.029, for Antisense p53 probe p=0.016, for Antisense PCNA probe p=0.042). The frequency distributions of the mean signal intensity for control and lymphoma lymph nodes when grouped into categories of low, moderate and high, showed significant differences for the Antisense DNMTI probe (p<0.001) and the Antisense p53 probe (p=0.005), whereas the differences for the Antisense PolydT probe and the Antisense PCNA probe were not significant (p>0.05).

Correlation analysis showed highly significant correlations (all p<0.001)between the Antisense DNMT1 probe. the Antisense p53 probe and the Antisense PCNA probe for the lymphoma group. whereas no correlations were obtained between these three probes for the control group. In the lymphoma group, the greatest correlation was found between the Antisense DNMT1 probe and the Antisense p53 probe (r= 0.832) as compared to the Antisense DNMT1 probe and the Antisense PCNA probe (r = 0.732) or the Antisense p53 probe and the Antisense PCNA probe (r = 0.738).

The results indicate that there were significant quantitative differences in gene expression for the three genes studied. Lymphoma cells show high levels of mRNA for the DNMT1 gene, the (mutated) p53 gene and the PCNA gene. This has implications for the process of malignant transformation in human lymphomas, as high levels of the enzyme DNMT1 have been observed in a number of malignancies and its role in transformation has been linked to increased methylation activity of the CpG islands in the promoter areas of tumor suppressor genes. Increased expression or the mutated p53 along with high levels or DNMT1 gene expression in this study would tend to support such a mechanism of transformation, as evidenced by the greater correlation between the Antisense mRNA probes of these two genes in lymphomas. The correlation with increased PCNA gene expression reflects an increased proliferation rate in lymphoma cells, in relation to both increased DNMT1 activity and lack of the tumor suppressor protein on wild type p53 gene in lymphomas.

In conclusion it can be said that the postulated role of the DNMT1 enzyme in malignant transformation by hypermethylating tumor suppressor genes is indeed plausible and that quantitative FISH studies are helpful in elucidating gene expression in normal and malignant tissues.

Download Full Thesis
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S. No. Chapter Title of the Chapters Page Size (KB)
1 0 Contents
398.8 KB
2 1 Introduction 5
314.02 KB
  1.1 Oncogenes And Anti-Oncogenes 6
  1.2 Dna Methylation 8
  1.3 Methylation Related Gene Functions 10
  1.4 Methylation Patterns In Leukaemias And Lymphomas 11
3 2 Review Of Literature 15
325.45 KB
  2.1 DNA Methylation 15
  2.2 CPG Islands 16
  2.3 DNA Methylation And Cancer 18
  2.4 Oncogenes 19
  2.5 Fluorescent In Situ Hybridization (Fish) 21
4 3 Materials And Methods 25
328.07 KB
  3.1 Study Design, Setting And Duration 25
  3.2 Sample Collection 25
  3.3 Specimen Processing 25
  3.4 Fluorescence Microscopy 31
  3.5 Image Acquisition 31
  3.6 Data Analysis 33
  3.8 Equipments And Reagents Used 35
  3.9 Selection Of Probes 38
5 4 Results And Discussion 73
651.06 KB
  4.1 Basic Demographic Data 40
  4.2 In Situ Hybridization Data 40
  4.3 Correlation Analysis Data 53
  4.4 Staining Characteristics 65
6 5 Discussion 73
293.83 KB
  5.1 Descriptive Data 73
  5.2 Correlation Data 78
7 6 Literature Cited 83
367.28 KB
8 7 Appendix 97
958.72 KB