The paper "Determination of PSA Serum Levels Using Enzyme-Linked Immunoabsorbent Assay" is a delightful example of a lab report on medical science. Pro specific antigen (PSA) is a biomarker for prostate and its physiological function is to liquefy post-ejaculation semen (Herschman, Smith, Catalona, 1997). PSA is present in semen as well as in blood (serum). Apart from its physiological function, PSA has a diagnostic value where elevated circulating levels are indicative of prostate abnormalities (Balk, Ko, and Bubley, 2003). For instance, prostate cancer, prostatitis, and benign prostatic hyperplasia cause a marked increase in serum PSA levels (Velonas, Woo, Remedios, and Assinder, 2013).
Quantitative analysis of PSA levels in serum is routinely done using Enzyme-Linked Immunoabsorbent assay (ELISA), an antibody-antigen technique (Lequin, 2005). In Elisa, specific antigens or antibodies or both are detected in a test sample using commercially prepared corresponding antigens and antibodies. In this experiment, PSA serum levels of three patients were determined in both diluted and undiluted state and the results compared. Methodology A standard commercial Elisa kit was used for this assay; the plates were pre-coated with monoclonal antibodies against PSA (Acevedo, et al, 2002).
Blood samples were obtained from the three patients using standard phlebotomy procedure and their respective serum labeled as patient A, patient B and patient C. For the second assay of diluted samples, an aliquot of the three serum samples were diluted fivefold using physiological saline. The samples were loaded on their respective plates (diluted and undiluted), incubated and washed as per the manufacturer’ s instructions. A secondary antibody conjugated to horseradish peroxidase (HRP) was added and incubated for 1 hour (Van Weemen, and Schuurs, 1971).
Unbound antibodies were washed and the HRP substrate added for color development. The enzymatic reaction was stopped by adding a stop solution. The absorbance (OD) of the standard and the samples was read in a standard Elisa plate reader at 450 nm and recorded (Acevedo, et al, 2002). Results To improve the validity of each sample and the standard solution was tested in triplicates and the average calculated and used in the analysis. Table 1 and 2 below show the respective absorbance (OD) of the standard and patient samples.
The background absorbance was corrected by subtracting the absorbance OD from the average OD of the individual test run. The average OD values of the standard solution were used to plot a calibration curve that was used to calculate the individual PSA concentrations in each patient sample tested. The calibration curve is shown in figure 1 below. Figure 1 Standard Curve used to determine the final PSA concentration (0-1000ug/ml). Values represent absorbance reading at 450nm It is important to note that the unexpected peak at point 50ug/ml may have been caused by a technical error during the assay run.
However, it is insignificant in that it does not affect the interpretation of patient sample tests. From the calibration curve shown in figure 1 above the actual PSA concentration for each patient, the sample was calculated and tabulated as shown in table 3 below. The results show the discrepancy between diluted and undiluted samples of the same patient. There are a number of reasons that can explain this observation and are discussed in the following section of the report.
Discussion The experiment was successful in using the ELISA sandwich technique in estimating the PSA serum concentrations of patient samples. However, interpreting these results is not recommended due to questionable validity. Validity and reliability are important in any diagnostic and even scientific test as it boosts the confidence of the results obtained (Acevedo, et al, 2002). There is a couple of techniques used to improve the reliability of laboratory tests results such as the user controls, SOPs, and testing in duplicates or triplicates(Acevedo, et al, 2002). Technical errors such as pipetting and mixing errors are common culprits in many cases of unexpected results.
The peak at the standard concentration of 50ug/ml is a good example. A reliable test should give consistent results even when the sample is diluted and the correct adjustment made. The variation seen in the results of this experiment may be explained by the introduction of an error during the test procedure. The error that caused the unexpected variation in the calibration curve may also have contributed to the difference seen between diluted and undiluted samples.
Other possible sources of error include faults in assay machines and use of wrong samples. The use of SOPS and quality assurance programs are fundamental in reducing and minimizing chances of error (Acevedo, et al, 2002).