Carcinogenesis and Prognostic Utility of Arginine Methylation-Related Genes in Hepatocellular Cancer
Round 1
Reviewer 1 Report
This manuscript deals with an analysis oft he methylation status of genes thought to play a role in HCC-tumurogenesis and prograaion.The analysis ihas been performed by utilizing data from different platforms derived from primary tumors and normal samples containing also tumor stages and survival informations. A differential expression of argiinine methylated genes (8) was found which showed a corrrelation with survival differences.Expression of those genes in tumor tissue was found to be different from that found in normal tissue.Auhtors also identified a network of genes with different metylation grade which could influence tumorogenesis and tumor progression.
Comment:
1.The title underscores „prognostic utility“ and not carcinogenesis
2.in the introduction it should be made clear that tumor development in liver cells may be different than in other organs as hepatocytes hardly devide even if chromosomal duplication can take place whithout cell division.
3.arginine methylation can affect tumor development as well as tumor growht (line 56) and not the other way around.
4.the study concentrate on possible association of modulation of arginine methylation and not „modulate“ HCC outcomes (59)
5. normal samples (line 78) means non-tumoral (cirrhotic )tissue or normal liver tissue?
6.staging may concern the tumor extension while and prognosis is more dependent on the underling liver disease and the different teatments (tranplantation,TACE,alcohol injection…..)
7.thease concerns influence the following results….(104….)
8.3.3 headline (146) „can modulate carcinogenesis (?)…or cancer growth?...
9.Which of the genes are connected with possible growht factor (s)-pathways?
10.Figures 1-3 are to small and difficult tob e read.
the english is fine.Only minor editing is needed
Author Response
Dear Editor,
Thank you so much for your productive criticism. I hope you enjoyed reading the paper as much as we enjoyed writing it. Attached below is our comments regarding
1.The title underscores „prognostic utility“ and not carcinogenesis
A: Changed title to add Carcinogenesis to title
2.in the introduction it should be made clear that tumor development in liver cells may be different than in other organs as hepatocytes hardly devide even if chromosomal duplication can take place whithout cell division.
A: We added the following: “Furthermore, it is important to note that the mechanism underlying tumor development in hepatocytes may exhibit unique characteristics compared to other tissues. Hepatocytes have an overall decreased rate of divisions, specifically because chromosomal duplication can occur even without concomitant cellular division.”
3.arginine methylation can affect tumor development as well as tumor growht (line 56) and not the other way around.
A: Changed “growth and development” to “development and growth”
4.the study concentrate on possible association of modulation of arginine methylation and not „modulate“ HCC outcomes (59)
A: Adjusted to “may affect tumor development and growth” and removed “can module HCC outcomes”
- normal samples (line 78) means non-tumoral (cirrhotic )tissue or normal liver tissue?
A: added “...normal liver tissue samples”
6.staging may concern the tumor extension while and prognosis is more dependent on the underlying liver disease and the different treatments (transplantation,TACE,alcohol injection…..)
A: Thank you very much for the noted change. Unfortunately, we do not have much data on the specific treatments conducted in the analysis. Accordingly, we mentioned this in the discussion “In addition, these findings can guide further studies on prognostic factors for various categories of liver disease and treatment modalities which would not be fully accounted for with outcomes at the gene, mRNA, or protein level.”
7.thease concerns influence the following results….(104….)
A: See response above
8.3.3 headline (146) „can modulate carcinogenesis (?)…or cancer growth?...
A: Changed to “...impact cancer progression”
9.Which of the genes are connected with possible growht factor (s)-pathways?
A: Should we discuss more about genes such as NGFR, listed in the discussion? Can add more
10.Figures 1-3 are to small and difficult to be read.
A: Resized for convenience
Reviewer 2 Report
In this study, Ali et al. seek the roles of arginine methyltransferase in hepatocellular carcinoma. This study is based on data from TCGA database, without using human tissue samples. Various previous studies demonstrated that PRMTs are associated with poor prognosis and progression of HCC, so this study lacks novelty. In addition, this study has multiple issues to be fixed before publication.
· The authors say the roles of PRMTs in Introduction but look at only PRMT1 and PRMT5. Other PRMTs should be included.
· Survival rates are shown in Figure 1 and methylation is shown in Figure 3, but expression levels of candidate genes are missing.
· The authors used KM Plotter for Figure 1, but details of setting are missing. I tried KM Plotter for genes shown in Figure 1, but could not obtain same results. Detained setting information should be shown, and all setting should be applied for all genes. I suspect that the authors use different settings for different genes to make Figure 1, which is not acceptable.
· KMPlotter and UALCAN are powerful tools, but data are sometimes inconsistent between two. It is because sometimes they use different samples or settings of calculation are different. Results can be significantly different between KMPlotter and UALCAN, so for reliable and powerful results, the authors use raw data from TCGA and perform analysis for expression levels and survival rates. I did try KMPlotter and UALCAN for genes shown in this study, and I found that data are inconsistent for some genes, such as PRDM14. I cannot believe results shown in Figure 1 and 3 with this issue.
· I found some grammatical errors and unnecessary sentences in the manuscript. Careful proofreading is requested.
· I found some grammatical errors and unnecessary sentences in the manuscript. Careful proofreading is requested.
Author Response
Dear Editor,
Thank you so much for your productive criticism. I hope you enjoyed reading the paper as much as we enjoyed writing it. Attached below is our comments regarding
In this study, Ali et al. seek the roles of arginine methyltransferase in hepatocellular carcinoma. This study is based on data from TCGA database, without using human tissue samples. Various previous studies demonstrated that PRMTs are associated with poor prognosis and progression of HCC, so this study lacks novelty. In addition, this study has multiple issues to be fixed before publication.
Comment #1: · The authors say the roles of PRMTs in Introduction but look at only PRMT1 and PRMT5. Other PRMTs should be included.
A: While the PRMTs wasn’t within the biological pathways, we conducted the analysis and added it in Supplemental Information. KM Plots for PRMT2,3,6,7,8,9 have been added.
Comment #2: · Survival rates are shown in Figure 1 and methylation is shown in Figure 3, but expression levels of candidate genes are missing.
A: Expression levels were displayed in stage plots in Figure 2. Would you suggest that we have normal versus tumor listed as well?
Comment #3:· The authors used KM Plotter for Figure 1, but details of setting are missing. I tried KM Plotter for genes shown in Figure 1, but could not obtain same results. Detained setting information should be shown, and all setting should be applied for all genes. I suspect that the authors use different settings for different genes to make Figure 1, which is not acceptable.
To the methods, the following was added: “For all genes listed, the same “Pan-Cancer” analysis was conducted. When conducting the KM analysis, auto cutoff was selected with no restriction done based on subtype (stage, gender, etc) or restriction based on cellular content.”
We also added the time of when the dataset was initially accessed.
A: KM Plots
- KMPlotter and UALCAN are powerful tools, but data are sometimes inconsistent between two. It is because sometimes they use different samples or settings of calculation are different. Results can be significantly different between KMPlotter and UALCAN, so for reliable and powerful results, the authors use raw data from TCGA and perform analysis for expression levels and survival rates. I did try KMPlotter and UALCAN for genes shown in this study, and I found that data are inconsistent for some genes, such as PRDM14. I cannot believe results shown in Figure 1 and 3 with this issue.
A: As per comment above, the specific actions and then time of access of the database was added for KMPlotter.
Comment #4· I found some grammatical errors and unnecessary sentences in the manuscript. Careful proofreading is requested.
A: Various sentences were reworked throughout the entire manuscript in line with clearer English.
Round 2
Reviewer 1 Report
I am satisfied by the comments and changes performed by the authors
Reviewer 2 Report
No further comments
