Introduction
Cancer and its aspects have always been at the center of many research works. In this paper, the experiment by Peng et al. described in the article “Prognostic implication and functional exploration for microRNA-20a as a molecular biomarker of gastrointestinal cancer” is analyzed in detail. The study is based on the widespread opinion that microRNA-20a (miR-20a) plays a significant role in detecting gastrointestinal cancer (GIC). Therefore, the experiment included analyzing the biological functions of miR-20a as an independent variable and its association with the GIC prognosis as a dependent variable. The study aims to prove that there is a direct connection between miR-20a and the clinical outcomes of GIC. Since cancer is a widespread problem in modern medicine, the experiment can be considered relevant, and its results may contribute to the development of disease detection.
Main body
The study is based on several variables used to identify the prognostic implication of miR-20a. The predictive role of miR-20a, or the association between this RNA and GIC diagnosis, is a dependent variable of the research (Peng et al. 1). The changeable indicators include protein-protein interaction (PPI) data, hub nodes, and module nodes, which were studied to identify miR20-a prognostic function (Peng et al. 3). As for the constant variables, the ethnicity of participants and the type of cancer were considered. The subdivision of the sample proves that these variables were controlled; however, the researchers confirm that they did not have clinical significance.
The study can be called bias-free since the tests were mostly based on calculations and facts. The design of the research is rather complicated: the authors used both literature review and bioinformatics (Peng et al. 3). Even though the study is accurate and thorough, fewer research methods would have made the experiment more understandable and precise. The sample can be considered random since the participants of different origins and ages were selected. The researchers confirm that a larger sample size would have led to more accurate results (Peng et al. 12). However, the research includes multiple tests, such as the CytoNCA and the MCODE plug-ins and GO and KEGG analysis, replicating the experimental conditions and making the results more reliable.
The authors provide specific and detailed conclusions about the role of each critical hub protein and pathway. However, they accept that additional demographic and clinical factors would help develop the experiment (Peng et al. 12). Some of the results are visualized in the form of tables and graphs. Most of them contributed to a better understanding of the experiment; however, due to the complexity of the topic, some figures could have been explained in more detail. It is worth mentioning that the analysis fully corresponds to the hypothesis. The study can be considered ethical since the authors respected participants’ confidentiality and willingness to contribute to the research. The resources cited by the authors vary from earlier studies to recent works, which provide a comprehensive theoretical basis. The experiment itself can be called credible due to its comprehensive scientific approaches and profoundness.
Conclusion
In conclusion, it is possible to say that the discussed experiment is a profound and significant work in the sphere of medicine. The use of bioinformatic methods and the detailed results make the authors’ findings reliable and precise. However, some parts of the experiment were rather difficult to understand, and the limited sample size proves that additional research should be conducted to confirm the results. At the same time, the study proved the hypothesis about the direct connection between miR-20a and the poor prognosis of GIC patients. This scientific contribution can help improve early disease detection and develop treatment methods, which is essential in the field of medicine.
Work Cited
Peng, Qiliang, et al. “Prognostic Implication and Functional Exploration for MicroRNA-20a as a Molecular Biomarker of Gastrointestinal Cancer.” BMC Cancer, vol. 20, no. 1, 2020, pp. 1-14.