1.1 Background
Nowadays cancer has become one of the deadly diseases affecting people’s life worldwide.
Based on the statistical reports published by World Health Organization (WHO), cancers in lung, colorectal and stomach are the three major cancer types that affected lives in both sexes for many years globally. Lung and stomach cancers are the life-threatening factors in male populations as to that of breast and cervical cancers in female populations. WHO has estimated that approximately over ten million people will be diagnosed with cancer on an annual base. By year 2020, however, approximately fifteen million of new cancer patients will be reported annually (Yang et al., 2002).
According to the published data for top ten leading causes of death by Taiwanese Department of Health for year 2004, cancer is once again ranked the top leading cause of death for a consecutive of twenty-two years. Among various cancer types, cancers in lung (19.67%), liver (19.42%), colorectal (19.73%), breast (3.68%, which is only calculated based on female population) and stomach (6.88%) have ranked the top five deadly diseases in Taiwan. In addition to the humiliate statistics, on average approximately every fifteen minute would a Taiwanese lose his/her life due to cancer (DOH Website, 2004).
As cancer has drawn great attention and focus in the medical field due to its life-threatening nature, many researchers around the world have dedicated their time to look for a better
developed yet. Effective treatments on cancer patients basically rely on a better understanding of the tumour genes in relation to the specific cancer type. Scientists have used high-throughput methods to define the relationship between cancer and genes. Gel electrophoresis, microarray technology and serial analysis of gene expression (SAGE) are the most popular ones known today. Among them all, microarray technology is most well-known for its ability to determine the cancer gene expressions in related to the cancer types (Liotta et al., 2000; Nelson et al., 2000; SEER’s Training Website, 2005).
1.2 Motivation
The current cancer research trend favours the idea that genetic mutation has driven the initial formation of malignant tumours. It is generally believed that cancer begins at the cellular level, in which the disease actually initiates in a single cell that will eventually pass its acquired abnormality onto its progeny (Lu et al., 2003). Based on Aranda-Anzaldo’s view, those initiated cells must contain a few “caner-causing genes” in their DNA. It is very possible that those caner-causing genes may have remained in latent stages for a long time, and are waiting to be triggered by any cancer-promoting agents. Even if caner-causing genes are not activated at all, or do not transform into lethal cancerous cells, they still possess certain degrees of dangerous factors that might affect people’s life (Aranda-Anzaldo et al., 2001).
Within the OMIM database, many literatures have been reviewed and categorized into different groups based on their research topics and contents by scientists at John Hopkins University. Articles that include information on genes that have caused cancers can easily be sorted out by having limited the search result to “cancer”, “carcinoma” and “tumor”.
Moreover, a list of cancer-related genes can be resulted from reading through these articles (OMIM, 2000). On the other hand, microarray technologies have become a biological research trend over the last few years for monitoring gene expression in human cell lines and tissues. Previous understanding of gene expression levels in different cancer types by microarray hybridization have provided an idea that this is indeed a useful and eventually will be an essential method to identify possible biomarkers as well as drug targets.
categorize different cancer types. Moreover, literatures found in OMIM database do reveal that different cancer types have possessed different microarray gene expressions. Based on those two understandings, we would like to find out whether there will be one or more genes that are related to various types of cancers at once by using OMIM literatures as our evident cancer-gene finders and combining with microarray gene expressions to confirm our thoughts.
1.3 Objective
Our goal is to focus on the cancer-related genes mentioned in the literatures. We would like to identify the gene-tissue relationship as well as how those genes are expressed in normal and cancer tissues. Based on the cancer-related gene list obtained from OMIM database, we would match those genes with the gene expressions from the microarray datasets. At the same time, we would also determine cancer-related gene lists for microarray expression datasets. Following the collection of all the relevant data, including cancer-related genes from both OMIM database and publicly accessible microarray databases, and microarray expression datasets, we would further analyze and look for any relationships of those cancer-related gene lists with the biological pathways via KEGG database. When the determination of the relationship between cancer-related genes and pathways completed, we would like to see if there is one or more genes that are located in the upper stream of the pathway. By this means, medical researchers can develop both prevention and more effective cancer treatments that are specifically targeted on those genes.