Current Methods of High-Throughput Expression Profiling in Normal and Disease States - Essay Example

The studies of the variations between normal and diseased cells gene expression and regulation have provided information that was challenging to find, making it easy to detect diseases very early and applying the necessary intervention and treatment procedures on time reducing rates of morbidity and mortality.   

The first step n the quest to understand the cell function would be understanding gene expression of the various cells of the body. In that case, it would be easier to determine when cells are not expressed as expected. Scientists and researchers point out that gene expression anomalies mostly involve the Messenger RNA (mRNA). DNA Microarrays are used to measure the expression of cells within a predefined mRNA. Different cells are expected to be expressed in a certain way in the mRNA. Changes in expression include over-expression or under-expression. For example, scientists have confirmed that breast cancer cells express more mRNA for the membrane receptor (Suter, Babiss, and Wheeldon, 2004).  

DNA methylation which is important in the normal DNA function and gene expression can be used to detect the changes in the DNA leading to abnormal expression and disease. Hyper-methylation and hypo-methylation have been associated with significant changes in some cells. Cells of breast cancer are usually hyper-methylated leading to neuroblastoma risks and response to the tamoxifen (Widschwendter et al., 2004;  Martens et al.,  2005). Hyper methylation has also been associated with Leukemia, Ovarian cancer, and colorectal cancer (Baylin, 2005).

The varying magnitudes of methylation in the cells are associated with different stages of cancer development, and DNA methylation techniques can be used to determine the exact stage (Costello et al, 2000). The use of DNA and genes is made very easy by the availability of data of all genomes in the human body. Researchers can access this information anytime from the human genome project databases. The use of gene expression is a three-step process that involves class comparison, class prediction, and analyzing the various gene set profiles. All this information is presented on pre-processed images which are normalized to make sense (Tarca et al, 2006).

DNA microarrays are limiting in that they can only be used for know cells. This limitation necessitated the introduction of RNA sequencing in which unknown genes expression can be studied (Cloonan et al, 2008). Single-cell sequencing in which the different types of healthy and cancerous cells can be sequenced individually has improved the effectiveness of DNA microarray studies. All the cells that are studied are amplified using the polymerase chain reaction (PCR) to achieve better and accurate results (Wang and Bodovitz, 2010). Microarrays can be used to analyze thousands of cells from different patients at once making it time-efficient unlike the previous methods of analysis.  The technique provides information on DNA, RNA, and proteins simultaneously.

Throughput profiling can also be done at the product level of gene expression; proteins in this case are studied for any anomalies. Mass Spectrometry is used to determine the differences between normal cells and diseased cells for example cancer cells (Aebersold and Mann, 2003). This procedure has proved very important in detecting prostate cancer in early stages, which has been a major challenge. In this case, the fluids, peptides, and serum from the prostate are examined using the SELDI mass spectrometer which uses affinity capture. Some cells are captured by the weak cation exchange while the others are washed away (Wulfkuhle et al, 2003). Thousands of protein peaks are generated and computer algorithms are used to discriminately select the varying cells in which the normal cells are differentiated from the diseased cells. According to Petricoin and colleagues (2002), this strategy was able to distinguish cancer cells from the normal cells in an ovarian cancer study using SELDI mass spectrometer. Studies on prostate cancer have also been successful using this strategy and researchers are certain that it will be possible to detect prostate cancer very early (Diamandis, 2004).
High throughput profiling has become very important in detecting diseased cells in the body. The various technologies use gene expression and regulatory patterns. These methods have made it possible to detect cancers at a very early stage for example prostate cancer which was a challenge to detect in the early stages. The high profiling techniques save a lot of time and provide data results from various levels making them very effective and efficient. The use of these effective techniques can address the current limitations in disease studies thereby reducing morbidity and mortality from cancers and other diseases that have not been well studied.