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Abstract
Analysis and comparison of gene expression profile among molecules, correlated with essential and crucial biological processes, is of primary importance in cancer research, since it provides significant info regarding the resistance to chemo/radiotherapy, risk for relapse or prediction of metastasis etc. In this study, gene expression profile is used for discriminating efficiently colon cancer cell lines from normal cells and cancer cells in blood samples of colon cancer patients and categorizing different types of gastrointestinal cancer. In particular, blood samples were collected from normal donors as well as from colon cancer patients. Peripheral blood mononuclear cells were isolated and gene expression analysis was performed for more than fifty genes. The same assays were performed for commercial cancer cell lines representing different types of gastrointestinal cancer. In order to examine whether the comparison of gene expression profile can lead to a thorough discrimination between cancer and normal states as well as between different cancer types, we performed clustering analysis based on hierarchical, and k-means algorithms. The clustering analysis efficiently separated: a) colon cancer cell lines from colon patients' samples, b) normal from the colon cancer samples, c) gastric and pancreatic cancer from liver and colon types based. The exploitation of gene expression profile can be successfully used for the discrimination between normal vs cancer samples and/or for categorizing various types of cancer. This of course has important implications in cancer management since it enables the quick discrimination based on cells, isolated from bloodstream, needless of tissue examination or protocols requiring specialized equipment.
Highlights
The gastrointestinal cancer includes parts of the gastrointestinal tract, and different organs both from upper and lower digestive tract
In the present study gene expression levels of commercial cancer cell lines were tested, corresponding to different types of gastrointestinal cancer as well as cells from normal donors and patients suffering from colorectal cancer
In this study we used two commonly used clustering algorithms, namely hierarchical and k-means clustering, in order to examine whether the gene expression profiles derived from PBMCs can provide valuable information which can help towards the correct recognition-distinction between different types of cancer cells and between normal cells and cancer cells in blood samples of colon cancer patients
Summary
The gastrointestinal cancer includes parts of the gastrointestinal tract, and different organs both from upper and lower digestive tract. In the present study gene expression levels of commercial cancer cell lines were tested, corresponding to different types of gastrointestinal cancer as well as cells from normal donors and patients suffering from colorectal cancer. The above datasets were evaluated with clustering analysis, a significant technique in data mining process This type of analysis is very useful in exploring hidden patterns and structure of the provided data. In this study we used two commonly used clustering algorithms, namely hierarchical and k-means clustering, in order to examine whether the gene expression profiles derived from PBMCs can provide valuable information which can help towards the correct recognition-distinction between different types of cancer cells and between normal cells and cancer cells in blood samples of colon cancer patients
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