Effect of Bcl-2 on Lung Cancer - Essay Example

Effect of Bcl-2 on Lung Cancer The context of this study is the effect of Bcl-2 single nucleotide polymorphisms on lung cancer. Bcl-2 has been proven to confer resistance to treatment for cancer cells through the activation of anti-apoptotic defenses in the cell (Xu et al., 2013). The study is grounded in the supposed suppression of lung cancer by apoptosis that is activated through the intrinsic Bcl-2 pathway, as well as the extrinsic death receptor pathway. The objective of this study was to find out whether there are genetic variants of Bcl-2 that are associated with susceptibility to lung cancer and its prognosis in Chinese men. To be able to obtain an accurate and strongly reliable research finding and study conclusion, the research method should always be aligned with the research hypothesis at all times. Back then, it was hypothesized in the study of Xu et al. (2013) that there can be a strong connection between Bcl-2 with a person’s susceptibility to lung cancer and its prognosis among the Chinese men. Specifically the research hypothesis of Xu et al. (2013) is very much in-line with its chosen research method. It means that the authors’ decision to make use of its research method is good enough to determine whether or not the research hypothesis presented in the said study should be accepted or not. For example, in the process of selecting and genotyping a total of 3 Bcl-2’s tagSNP (i.e. rs1564483, rs 1801018, and rs 2279115) in 1017 couple of Chinese male with lung cancer using the TaqMan assay, the authors were able to find out that the genotypes of rs1564483GA, AA, as well as GA+AA were strongly related to the decrease in Chinese men’s susceptibility to lung cancer whereas the allele of rs1564483A increases Chinese men’s susceptibility of developing lung cancer particularly those who had family history of cancer and previous smoking habit. In this study, the clinical term “prognosis” is all about being able to foretell the possible long-term effects after a person has been diagnosed with lung cancer. Using the same research method, Xu et al. (2013) found out that research participants with Bcl-2 rs1564483 GA+AA genotypes are the ones who can experience longer survival rate and reduced risks of untimely deaths as compared to those Chinese men with rs1564483GG genotype. The primary exposure of interest in this study was genetic factors, in particular the polymorphism of the Bcl-2 gene in the Chinese men. This was measured by genotyping using the TaqMan method that used a sequence detection system (Xu et al, 2013). This method uses hydrolysis probes to increase specificity during quantitative PCR and relies on Taq polymerase activity of 5’-3’ exonuclease. TaqMan PCR assay is accurate enough in the genotyping of single nucleotide polymorphisms like the one being measured in this case. The primary outcome of interest in the study was susceptibility and prognosis to cancer of the lungs. This was measured using the Kaplan-Meir method, as well as the log-rank method (Xu et al, 2013). When used together, the two methods are very accurate in determining the fraction of study subjects alive for a particular period following intervention. Specifically the research study of Xu et al. (2013) was a case-control study where the researchers studied the characteristics of a specific group with a particular health outcome and compared them to another similar group without the specified outcome. The study population was recruited from Wuhan Zhongnan Hospital, Wuhan Steel Group Staff-worker Hospital, and the Union Hospital Cancer Center (Xu et al, 2013). The subjects were selected at random after examining their health. Of the subjects examined, 1017 of them were selected for the study. The ratio of proposition to comparison subjects was a 1:1 frequency match between the case and the control groups (Xu et al, 2013). While there was the probability of bias in selection of subjects, this was lowered by the fact that self-selection bias was low, the control group was representative of the population producing the cases, and only subjects that required to be hospitalized were picked for the case group. With regards to bias in collection of information, the probability was again low. This was because the researchers blinded the participants to the hypothesis of the study to prevent recall bias and there was minimal loss to follow up as the patients were included in survival analysis (Xu et al, 2013). Before data analysis, the research study attempted to minimize the influence of confounding variables by ensuring the age of the subjects was within ten years of each other, classification of their cancer stage by medical oncologists, and collection of information on cancer history in the family, smoking habits, and drinking habits using questionnaires. The information collected on the questionnaire, however, may have been insufficient to control for confounding variables since some patients may have lied to feel good about themselves. During data analysis, the research study controlled for the influence of confounding variables. To start with, these variables include age, histology, cancer treatment, stage of cancer, and smoking status. The study used the multiple logistic regression method to control for the influence of confounding variables (Xu et al, 2013). This method was sufficient because it can be used to control the influence of more than one confounding variable at the same time. The method can also be used in assessing effect and confounding modification. The multiple logistics regression method also can be used in the examination of more than one risk factor on dichotomous outcomes, rather than simply focusing on one risk factor (Jewell, 2011). The researchers reported on the odds ratio as a measure of association. This is the ratio of the odds, which an event will occur in a specific group to odds of the same event happening in a related group (Jewell, 2011). In this particular case study, the odds ratio was used in comparing the Bcl-2 single nucleotide polymorphism and risk of lung cancer. For example, in comparison with Bcl-2 3’UTR rs1564483GG genotype, Xu et al. (2013) found out that the odds ratio of rs1564483GA, AA, as well as GA+AA genotypes when it comes to decreasing the Chinese men’s susceptibility to lung cancer was 0.78, 0.73, and 0.76 respectively. In general, the act of computing for the odds ratio is best when trying to estimate the probability wherein a person could develop certain disease such as lung cancer after being exposed to certain environmental or non-environmental factor(s) (Jewell, 2011). In line with this, Jewel (2011) clearly explained that the actual computation of the odds ratio can be done by measuring the probability of being exposure to identified factors and the presence of the said disease. The measure of statistical stability used in the study is reliability, which is a measure of the degree to which observations of phenomena that are identical yield similar or identical results. In this case, the researchers used the Kolmogrov-Smirnov test (Xu et al, 2013), which compares a sample using a reference probability distribution or two samples. The test is particularly useful since it attempts to determine the difference between two sets of data, in addition to, whether the difference is significant, whereas not making any assumptions about the data. The research also uses the chi-square test to test for reliability. This test is best used when one is testing goodness of fit and, in this case, it is appropriate in demonstrating the reliability of the test design as used in the study (Jewell, 2011). This study came up with a few major results. With regards to the relationship between Bcl-2 single nucleotide polymorphisms and risk of lung cancer, subjects with Bcl-2 rs15464483 AA (Odd Ratio = 0.73, P = 0.038), GA (Odd Ratio = 0.78, P = 0.016), or GA+AA (Odd Ratio = 0.76, P = 0.007) had decreased lung cancer risks compared to the GG genotype (Xu et al, 2013). Furthermore, this study also reported that the relationship between Bcl-2 rs1564483 AA, GA, and GA+AA genotype and lung cancer susceptibility was more prevalent in older men (P trend = 0.017), people with history of smoking (P trend = 0.043), and those with no history of cancer in their families (P trend = 0.005) (Xu et al, 2013). In addition, this study also found that a dose-response relationship existed between increased Bcl-2 rs1564483 A allele and lower lung cancer risks (P trend = 0.010). However, they did not find any significant relationship between Bcl-2 rs2279115 C>A (i.e. CA with Odds Ratio = 1.02, P = 0.862; and AA with Odds Ratio = 1.11, P = 0.474) and rs1801018 A>G (i.e. AG with Odds Ratio = 0.92, P = 0.513; GG with Odds Ratio = 0.95, P = 0.916; and GG+AG with Odds Ratio = 0.92, P = 0.513), and lung cancer risk. Xu et al. (2013) also constructed Bcl-2 haplotypes to study their association with risk of lung cancer. In line with this, the authors found that, while CAA haplotype (Odds Ratio = 0.81, P = 0.028) had a decreased lung cancer risk compared to the CAG haplotype, there was no significant relationship between lung cancer risks and the AAA (Odds Ratio = 0.98, P = 0.879) and AAG haplotypes (Odds Ratio = 1.02, P = 0.847). Interpretation of these results was affected by confounding variables, information bias, and selection bias. If the researchers failed to control for confounding variables, there will be bias when estimating the exposure impact under study. Its effects may include observation of differences between the two populations under study where there are no real differences under study, as well as lack of observable differences between the two populations being studied when there are true associations between them (Jewell, 2011). In addition, confounding variables may lead to either overestimation or underestimation of effects. Selection bias may also affect the interpretation of the above results. Depending on the category, case or control, which is under sampled or oversampled, selection bias, may lead to overestimation or underestimation of the expected and true association. Finally, with regards to information bias, if it occurs with more frequency in one group than the other, there is a risk of underestimating or overestimating the relationship between Bcl-2 single nucleotide polymorphism and lung cancer risk (Jewell, 2011). In case there was non-differential misclassification in the study, it can also affect the interpretation of the results. Based on the case study of Xu et al. (2013), the non-differential misclassification with polychotomous variables of exposure will cause odds ratio estimates of lung cancer risk to be biased from the null hypothesis (Jewell, 2011). In addition, non-differential misclassification may lead to the dose-response slope trend in the association between Bcl-2 haplotypes and lung cancer risk for true distribution creating an inverse trend that is false by changing its direction. While the researchers do give the limitations of their study, this particular section in printed in the journal is too brief. For example, one of the limitations that the researchers have provided is that because the study’s subjects were all born in China, as well as the fact their Bcl-2 rs1564483 G>A polymorphism is not yet clear, it was not possible to validate the close association between Bcl-2 single nucleotide polymorphisms and lung cancer risk in other races (Xu et al, 2013). In addition, the study has failed to uncover the Bcl-2 rs1564483 G>A polymorphism’s biological function particularly with regards to the need to regulate the Bcl-2 expression (Xu et al, 2013). The researchers also failed to mention the effects of these limitations in their research findings and overall study conclusion. It is clear that the researchers did not bother to measure the validity of their research study. Therefore, Xu et al. (2013) should have stated this under the limitations of the study. Specifically the overall research study conclusions were very much justified by the findings presented by the authors. In line with this, Xu et al. (2013) was able to justify based on research findings that the Bcl-2 gene’s rs1564483 A allele found on the 3’-UTR could mean that there is a lower risks for the Chinese men to develop lung cancer. With this in mind, one can easily conclude that the presence of genetic variation of rs1564483AA, GA, and AA+GA can be used as a favorable prognosis for Chinese men with an advanced stage of lung cancer. References Jewell, N. P. (2011). Statistics for epidemiology: Boca Raton: Chapman & Hall/CRC. Xu, P.; Liu, L.; Wang, J.; Zhang, K.; Hong, X.; Deng, Q.; Xiang, J.; Zhang, X.; He, M.; Wu, T. & Guo, H. (2013, August 16). Genetic Variation in BCL2 3′-UTR Was Associated with Lung Cancer Risk and Prognosis in Male Chinese Population. Plos One. 8(8):e72197. doi: 10.1371/journal.pone.0072197. eCollection 2013. Read More