Title: Two differentially methylated region (DMR) networks in nonalcoholic fatty liver disease,
viral hepatitis, and hepatocellular carcinoma
Version: 1 Date: 06 Apr 2022
Reviewer's report:
The study is interesting and well-designed. In the study, the author provided two differentially
methylated region (DMR) networks in nonalcoholic fatty liver disease, viral hepatitis, and
hepatocellular carcinoma. The results suggest that one DMR network was associated with
fibrosis and tumorigenesis in both NAFLD and viral hepatitis, while the other network was
specifically associated with NAFLD progression. FABP1, SGK2, and HNF4A could be possible
candidate targets for the prevention and treatment of HCC. The idea of this article is innovative
enough. Meanwhile, there are some minor concerns in the manuscript.
1. At present, there are many methods for predicting the prognosis or demonstrating the
association of HCC through bioinformatics and statistical methods, but few can be used in
clinical practice. The DMR networks in the manuscript proposed by the author are also very
good. However, it is difficult to evaluate the advantages over other research results, and
the author should supplement some advantages or the latest related research progression the
discussion section.
2. Although there are obvious advantages in data analysis and results, but it lack actual clinical
utility. If the verification of the results of FABP1, SGK2, and HNF4A in liver cancer cell lines
and liver cancer tissues in vitro and in vivo are conducted based on the author's results, the article
may be even more credible.
Title: Two differentially methylated region (DMR) networks in nonalcoholic fatty liver disease,
viral hepatitis, and hepatocellular carcinoma
Version: 1 Date: 06 Apr 2022
Reviewer's report:
The study is interesting and well-designed. In the study, the author provided two differentially
methylated region (DMR) networks in nonalcoholic fatty liver disease, viral hepatitis, and
hepatocellular carcinoma. The results suggest that one DMR network was associated with
fibrosis and tumorigenesis in both NAFLD and viral hepatitis, while the other network was
specifically associated with NAFLD progression. FABP1, SGK2, and HNF4A could be possible
candidate targets for the prevention and treatment of HCC. The idea of this article is innovative
enough. Meanwhile, there are some minor concerns in the manuscript.
1. At present, there are many methods for predicting the prognosis or demonstrating the
association of HCC through bioinformatics and statistical methods, but few can be used in
clinical practice. The DMR networks in the manuscript proposed by the author are also very
good. However, it is difficult to evaluate the advantages over other research results, and
the author should supplement some advantages or the latest related research progression the
discussion section.
2. Although there are obvious advantages in data analysis and results, but it lack actual clinical
utility. If the verification of the results of FABP1, SGK2, and HNF4A in liver cancer cell lines
and liver cancer tissues in vitro and in vivo are conducted based on the author's results, the article
may be even more credible.
Please review this paper.
user
Title: Two differentially methylated region (DMR) networks in nonalcoholic fatty liver disease,
viral hepatitis, and hepatocellular carcinoma
Version: 1 Date: 06 Apr 2022
Reviewer's report:
The study is interesting and well-designed. In the study, the author provided two differentially
methylated region (DMR) networks in nonalcoholic fatty liver disease, viral hepatitis, and
hepatocellular carcinoma. The results suggest that one DMR network was associated with
fibrosis and tumorigenesis in both NAFLD and viral hepatitis, while the other network was
specifically associated with NAFLD progression. FABP1, SGK2, and HNF4A could be possible
candidate targets for the prevention and treatment of HCC. The idea of this article is innovative
enough. Meanwhile, there are some minor concerns in the manuscript.
1. At present, there are many methods for predicting the prognosis or demonstrating the
association of HCC through bioinformatics and statistical methods, but few can be used in
clinical practice. The DMR networks in the manuscript proposed by the author are also very
good. However, it is difficult to evaluate the advantages over other research results, and
the author should supplement some advantages or the latest related research progression the
discussion section.
2. Although there are obvious advantages in data analysis and results, but it lack actual clinical
utility. If the verification of the results of FABP1, SGK2, and HNF4A in liver cancer cell lines
and liver cancer tissues in vitro and in vivo are conducted based on the author's results, the article
may be even more credible.
assistant