The incidences of cancer remain high despite advances in our understanding of cancer. Cancer is a class of diseases characterized by out of control cell growth. Normal cells are constantly subject to signals that control whether the cell should divide, differentiate into another cell or die. Cancer cells develop a degree of independence from these signals, which results in uncontrolled growth and proliferation. If this proliferation is allowed to continue and spread, it can be fatal (1). Almost 90% of cancer-related deaths are due to metastasis the complex process of tumor spread through the lymphatic system or bloodstream. The emergence of genomic technologies holds therapeutic potential for personalized cancer management. Personalized cancer management combines standard chemotherapy and radiation treatments with genomic profiling and in vitro cell proliferation studies. Individualized genomic profiling allows the researcher to identify specific genes that contribute to unregulated cellular mechanisms that normally control cellular growth.
By determining the molecular profile of a specific cancer, suitable treatment can be considered that target those gene products (2). Cultured cancer cells have the capacity to dramatically exceed normal doubling times to almost indefinite levels, unlike normal cells. HeLa cells are a great example of this. One of the most widely used continuous cell lines in research is the HeLa cell line, which was derived in 1951 from Henrietta Lacks, a cervical caner patient in 1951. These cells continue to grow and proliferate in hundreds of laboratories across the world to this day. These cancer cells have been called Immortal as they have bypassed the senescence regulators within the cell and acquired the capacity for unlimited division. Measurement of cell viability and proliferation forms the basis for numerous in vitro assays of a cell populations response to external factors. The reduction of tetrazolium salts is now widely accepted as a reliable way to examine cell proliferation.
MTT viability assays is based on the ability of a mitochondrial dehydrogenase enzyme from viable cells to cleave the tetrazolium rings of the pale yellow MTT and form a dark blue formazan crystals, which is largely impermeable to cell membranes, thus resulting in its accumulation within healthy cells. The resulting intracellular purple formazan can be solubilized and quantified by a spectrometer and is then subject to examination to evaluate cell viability. These measurements can be used to evaluate the effectiveness of certain treatments to cells. These anti-cancer drugs in vitro allows drugs to be tested against live cells which helps determine drug effectiveness and side effects.
Cell proliferation, also known as cell growth, cell division, or cell replication is the basic process through which cells form new cell. Cell proliferation is the increase in cell number as a result of cell division and growth. The quantification of cellular growth, including proliferation and viability, has become an essential tool in any laboratory working on cell-based studies. These techniques enable the optimization of cell culture conditions, and the determination of growth factor and cytokine activity.
Even more importantly, the efficiency of therapeutic agents in drug screening, the cytostatic potential of anticancer compounds in toxicology testing, and cell-mediated toxicity can be assessed when quantifying cell growth (3). This practical is designed to evaluate the sensitivity and response of putative anti-cancer drugs using a modified anti-proliferative drug assay. Using a modified MTT drug assay, the sensitivity and response of anti-cancer drugs can be determined. In this blind trial, three unlabeled drugs are tested to discover their properties. The trial of these drugs was carried as a blind trial to insure that the results obtained with unbiased.
In this practical, we were given three drugs. One of the drugs had no known anti-cancer properties; one was a known chemotherapeutic agent and the third was a mystery drug with putative anti-cancer properties. The HeLa cells were also treated with a no-drug, medium-only control. The objective of the study was to identify the nature of the unlabeled drugs. The identities of these three drugs were unknown in order to make the experiment a blind trial. Doing the study as a blind trial allowed any bias data to be avoided in data interpretation (2).
From the raw data obtained column 0 acts as the control, this column contains the HeLa cells but no drug, and is used to see if the unknown drugs A,B and C have an effect on the viability of HeLa cells. The last row on the 96 well plates contained no HeLa cells and acted as a reference to observe whether column 0 contained living cells. When the absorbance value for column 0 was similar to the no cell value, that data set would be ignored, as this would indicate no cells were present in column 0 which would have been invalid as column 0 contained medium only. This method was applied when choosing appropriate data sets for data interpretation.
In this study we were given three drugs. One of the drugs had no known anti-cancer properties, one had a known chemotherapeutic agent and the third was a mystery drug with putative anti-cancer properties. The objective of this blind trial study was to identify the nature of these unlabeled drugs. By observing the overall averages from the results (Table 1 & Figure 1) we can conclude that drug A had the highest percentage cell viability out of the three drugs. The percentage value of A is similar to the percentage value of the control (0). The control consisted of a medium-only solution and not meant to effect the cell viability of HeLa cells at all, this implies that Drug A has no anti-cancer properties and has little effect on the HeLa cells viability. From this data we can conclude that Drug A was the drug with no known anti-cancer properties (negative control). By observing the percentage cell viability of drug B, we can conclude that drug B had the smallest cell viability value that was close to 0%.
Small percentage viability indicates that there is a reduction in cell proliferation occurring in the HeLa cell line, however 0% cell viability would indicate that there are no viable cells in the well, meaning there was a complete reduction in cell proliferation. Lack of cell proliferation means an absence of mitochondrial succinic dehydrogenase activity to metabolize MTT into its results purple formazan, producing a lower absorbance value (4). From this we can conclude that drug B has anti-cancer properties as it had a large negative effect on HeLa cell viability. By observing drug C, we can determine that drug C also has a relatively low percentage cell viability value. This would indicate that drug C, like drug B, has a negative effect on cell viability, meaning it causes a reduction in cell proliferation in HeLa cells.
From this we can conclude that Drug C also had anti-cancer properties as it had a negative effect on HeLa cell viability. At this point, two drugs have yet to be identified, Drug B and Drug C. Both Drug B and Drug C have anti-cancer properties, shown by their low cell viabilities values. A positive control will be a drug that will give a large cell viability percentage. From this, we would conclude that Drug B was the positive control with a chemotherapeutic agent leaving Drug C to be the mystery drug. However we cannot accept this without actually knowing what the mystery drugs anti-cancer properties are. The mystery drug could have stronger anti-cancer properties than the positive control. In this scenario, Drug B would be the mystery drug as it observed the lowest cell viability, making it the most effective against cancer cells. For this reason, we cannot accurately identify drugs B and C without more information about the mystery drug.
However if we accept that the mystery drug has a smaller effect on cancer cells than the positive control, we would then conclude that Drug B is the positive control and Drug C is the mystery drug. If we observe the overall data used to calculate the average cell viability percentages for each drug, we can see there are values higher than 100% and values lower than 0% (negative values). Values higher than 100% would indicate that there are more viable cells present in drug A compared to our control. Since we know drug A has no effect on the cancer cells, we would expect the cell viability of drug A to be similar to the control. These anomalies could be due to cell proliferation in the drug A column, meaning the HeLa cells grew and divided to create new cells, meaning the number of cells in column A increased, resulting in a higher absorbance value, due to the increase in MTT reduction. A higher absorbance value in the no cell row compared to the drug B column results in a negative value.
Absorbance values that are lower than the control cells indicate a reduction in the rate of cell proliferation. Conversely a higher absorbance rate indicates an increase in cell proliferation. Values lower than 0% would indicate that there are fewer cells present in the drug B wells compared to the no cell wells. This could be due to human error where cells where accidently transferred due to poor lab technique, or been caused by a high absorbency of the buffer used in the no cell row. In this study, the reduction of the MMT is used to estimate cell viability and proliferation. However recent studies have shown that superoxide can also reduce tetrazolium salts, such as MTT. Therefore studies investigating the cytological effect of HeLa cells may encounter misleading results when using MTT to measure viability proliferation. This is because MTT assays may yield inaccurate results due to the increase in superoxide formation in cultured HeLa cells (7).
This kind of limitation may have played apart in this study and could have caused our abnormal values discussed in the paragraph above. To overcome this limitation, we could use different techniques to measure cell viability. One way of assessing cytotoxicity is by cell integrity. Compounds that have cytotoxic effects, such as the drugs we are investigating, often compromise cell membrane integrity. An example of this method is a Tryphan Blue exclusion test (10). This exclusion test can be used to determine the number of viable cells present in a cell suspension. It is based on the principle that viable cells have intact cell membranes that are impermeable to dyes, such a trypan blue, whereas dead cells do not. In this test, a cell suspension is mixed with the tryphan blue dye and then visually examined to determine whether cells take up or exclude the dye (11). A viable cell will have a clear cytoplasm whereas a dead cell will have a blue cytoplasm.
Tryphan blue is not affected by superoxide formation so will yield more accurate results than the MTT assay. The problems that arise from dye exclusion tests is that they are operator depend and are subject to human error. Another way of assessing cell viability via membrane integrity is by using fluorescent DNA binding dyes such as SYBR Green I (10). SYBR Green I is a fluorescent dye used as a nucleic acid dye. SYBR Green I binds to DNA and the resulting DNA-dye-complex absorbs blue light and emits green light (9). This is based on the principle that an increase in cell proliferation will cause an increase of DNA in the cell suspension. More SYBR Green 1 will bind to the DNA and more green light will be observed under blue light.