Cancer Therapy Vol 3, 249-252, 2005

An analysis on the gene expression profiling of lymphotoxin tumor necrosis factor-b in lymphoma

Research Article

Viroj Wiwanitkit

Department of Laboratory Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok Thailand 10330

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*Correspondence: Viroj Wiwanitkit, M.D., Department of Laboratory Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand 10330; Tel: 662 256 4136; Fax: 662 218 3640; e-mail: Viroj.W@Chula.ac.th

Key words: Lymphotoxin tumor necrosis factor-b, gene expression, profiling

Abbreviations: adult T cell leukemia, (ATL); focal adhesion kinase, (FAK); Gene Expression Pattern Analysis Suite, (GEPAS); human T cell leukemia virus type I, (HTLV-I); osteoclast activating factor, (OAF); Phosphatidylinositol 3-kinase, (PI3K); Self-Organising Tree Algorithm,, (SOTA); tumor necrosis factor-b, (TNF-b)

Received: 12 April 2006; Revised: 10 June 2006

Accepted: 8 August 2006; electronically published: August 2006

Summary

Lymphotoxin tumor necrosis factor-b (TNF-b) is believed to relate to hypercalcemia in patients with lymphoma. It is also found that the extent of TNF-b gene expression was correlated with the histopathological features of neovascularization and there was also a relationship between the extent of TNF-b gene expression and the presence of B-symptoms in those lymphoma patients, which could imply for the prognostic factor prediction. Here, the author performed a bioinformatics analysis on the gene expression pattern of lymphotoxin TNF-b. Based on transciptomic technology, a clustering gene expression of lymphotoxin TNF-b gene and other closed relate lymphoma genes was generated and presented. The DNA array data from the published report concerning lymphoma was extracted and further analyzed by Sotarray analysis. The result of the algorithm is a hierarchical cluster, genes with similar expression profiles are clustered together. According to this study, the node for lymphotoxin TNF-b gene and other closed relate lymphoma genes was derived at cluster “node 690”. The genes corresponding to focal adhesion kinase (FAK) and Phosphatidylinositol 3-kinase p110 catalytic gamma are the two known genes detected as closed related genes to lymphotoxin TNF-b gene. According to the closed related in gene expression profiling of the three genes, the concerns on the prognostic factor prediction as well as cancer treatment based on lymphotoxin TNF-b might be applied for the other two genes, FAK and PI3K.

I. Introduction

Hypercalcemia in hematological malignancy is frequently encountered in lymphoid malignancies such as adult T cell leukemia (ATL) and multiple myeloma and is difficult to manage (Ishibashi et al, 1992). Lymphotoxin tumor necrosis factor-b (TNF-b) is believed to relate to hypercalcemia in patients with lymphoma (Ishibashi et al, 1992). Ishibashi et al noted that the TNF-b secreted from ATL cells might be one of the factors contributing to the hypercalcemia in patients with ATL functioning as an osteoclast activating factor (OAF) (Ishibashi et al, 1992). In 1994, Kato et al investigated the levels of TNF-b mRNA in the tumorous tissues of a series of Japanese patients with lymphoma, to assess the contribution of the expression of this gene to the features of the disease and found the level of TNF-b mRNA was semiquantified against that in MT-2 cells, a line of human T cells infected with human T cell leukemia virus type I (HTLV-I) (Kato et al, 1994). They also found that the extent of TNF-b gene expression was correlated with the histopathological features of neovascularization and there was also a relationship between the extent of TNF-b gene expression and the presence of B-symptoms in those lymphoma patients, which could imply the prognostic factor prediction (Kato et al, 1994).

The antitumor effect of lymphotoxin and the underlying cellular mechanism have been mentioned (Qin and Blankenstein, 1995). The cancer treatment outcome might have some clinical correlated to the lymphotoxin TNF-b. However, the knowledge on the gene expression of lymphotoxin TNF-b gene is limited. Here, the author performed a bioinformatics analysis on the gene expression pattern of lymphotoxin TNF-b. Based on transciptomic technology, a clustering gene expression of

Figure 1. Clustering gene expression of lymphotoxin TNF-b gene and other closed relate lymphoma genes

lymphotoxin TNF-b gene b other closed relate lymphoma genes was generated and presented.

II. Materials and Methods

A. DNA array data

The DNA array data was extracted from the report of Alizadeh et al (2000). In that study, Alizadeh et al used DNA microarrays to conduct a systematic characterization of gene expression in lymphoma (Alizadeh et al, 2000). The data in GenePix GPR file format was used for further analysis.

B. Data processing

In data processing, the author used the Gene Expression Pattern Analysis Suite (GEPAS) program (Herrero et al, 2003) for all in silico simulation. The author performed Sotarray analysis on the published data to get the cluster of the lymphotoxin TNF-b gene and other closed relate lymphoma genes (Herrero et al, 2003). Normalization of the data was performed using Diagnosis and Normalization for Microarray Data (DNMAD) tool (Vaquerizas et al, 2004). Concerning the Sotarray analysis, it is a new approach to the analysis of gene expression data coming from DNA array experiments, using an unsupervised neural network, the Self-Organising Tree Algorithm, (SOTA), that grows adopting the topology of a binary tree (Dopazo and Carazo, 1997). In this study, the algorithm parameters were “error threshold = 0.0001, actualization factors = 0.01, 0.005, 0.001 and maximum number of epoch in a cycle = 1000” and the distance between genes was set as “correlation coefficiency (linear)”. The result of the algorithm is a hierarchical cluster obtained with the accuracy and robustness of a neural network (Herrero et al, 2001). Then the derived cluster was viewed by TreeView (Herrero et al, 2003).

III. Results

The results from the Sotarray analysis showed 625 clusters. Of those 625 clusters, the node for lymphotoxin TNF-b gene and other closed relate lymphoma genes was derived at cluster “node 690”. This cluster was selected and viewed with TreeView and the result was shown in Figure 1.

IV. Discussion

According to this study, the author can generate the clustering gene expression of lymphotoxin TNF-b gene and other closed relate lymphoma genes. The genes corresponding to FAK and Phosphatidylinositol 3-kinase p110 catalytic gamma are the two known genes detected as closed related genes to lymphotoxin TNF-b gene. Since genes with similar expression profiles are clustered together in this study, these two genes should have closed related expressions. Concerning FAK, it is is activated by TNF a, UV light and increases in intracellular calcium levels (Chauhan et al, 1999). The correlation to calcium metabolism can have some linkage to the expression of lymphotoxin TNF-b. In addition, transient overexpression of FAK induces apoptosis (Chauhan et al, 1999), which might also correlate to the tumor necrosing of TNF-b.

Concerning Phosphatidylinositol 3-kinase (PI3K), Ward performed an analysis of neutrophil migration from mice deficient in the gamma-isoform of the p110 catalytic subunit (Ward, 2004). Ward found that PI3K activation can be a dispensable signal for directed cell migration in T lymphocytes. This expression is similar to lymphotoxin TNF-b (Ward, 2004). Ward noted that the non-universal role of PI3K in directional cell migration and the existence of cell-specific signalling pathways for chemotactic responses had important implications for the validation of effective new targets for inflammation, where one aim was to block migration of leukocytes to the site of inflammatory lesion (Ward, 2004).

According to the closed related in gene expression profiling of the three genes, the concerns on the prognostic factor prediction as well as cancer treatment based on lymphotoxin TNF-b might be applied for the other two genes, FAK and PI3K. Some limitations of the study should be mentioned. Co-expression is a suggestion of similar functionality, not a proof. To demonstrate co-expression and form a practical point of view, suggest other molecules as markers, more datsets should be used. However, there is no more available public accessible dataset on B-cell lymphoma at present, future use of more datasets when available is planned for clearly proof.

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