5-Methylcytosine (m5C) Modification Patterns and Tumor Immune Infiltration Characteristics in Clear Cell Renal Cell Carcinoma
Round 1
Reviewer 1 Report
The presented manuscript introduces bioinformatics analysis of expression and mutational information on 5-methylcytosine (m5C) in kidney renal clear cell carcinoma (KIRC).
I would suggest using full name of 5-methylcytosine instead of abbreviation in the article title.
The Abstract lacks methodology section, which should be present; a short sentence about the databases and bioinformatics analysis should be added.
Line 84; 95-97: How many samples from each database were taken for analysis? What clinical information was extracted from database? How many samples were excluded? What were the exclusion criteria?
Line 102: Which databases? What was the key of their selection?
Line 147: What are the 14 regulators selected for the study? What criteria were used to select these regulators?
Line 157 and further: genes names should be italicized, authors must check carefully where they refer to a gene and where to a protein.
The Figures are of poor quality and are hard to read.
Figure 1 and 2 are the same, from the text it may seem that Figure 1 is misplaced, as it does not correspond to the provided caption.
Line 205 – what were the clustering criteria?
Line 206 – missing ‘in pattern C’
In Figure 2C, 3ABC and further is data presented as medians/means/errors/SD or some else? Please provide a legend.
The negative correlation at Figure 6A is questionable, as the R value is shown as 0.12.
The Kaplan Meier curve in Figure 6D is also questionable, since there is large disproportion in patients’ numbers, I suggest to draw conclusions carefully.
I recommend a revision of the text by a native English language speaker since there are some parts that present moderate language problems.
Overall, it is a well-described work and worthy of publication, however, a few corrections should be considered before acceptance.
Author Response
Dear Editors and Reviewers:
Thank you for your kind email and recognition of our answers. We are extremely grateful for the reviewers’ professional work and responsibility. Those comments are all valuable and very helpful for improving our paper, as well as the important guiding significance to our researches. In this response, we have made efforts to address these concerns, and the manuscript has been changed according to the reviewers’ suggestions. We hope that the revision is acceptable, and we look forward to hearing from you soon. About the questions, we have answered all questions according to the reviewers’ comment one by one (please see the below in blue color).
Review1
Comments and Suggestions for Authors
The presented manuscript introduces bioinformatics analysis of expression and mutational information on 5-methylcytosine (m5C) in kidney renal clear cell carcinoma (KIRC).
1.I would suggest using full name of 5-methylcytosine instead of abbreviation in the article title.
RE: We have changed the abbreviation of m5C in the title to its full name.
2.The Abstract lacks methodology section, which should be present; a short sentence about the databases and bioinformatics analysis should be added.
RE: We have supplemented the methodology section in the abstract.
3.Line 84; 95-97: How many samples from each database were taken for analysis? What clinical information was extracted from database? How many samples were excluded? What were the exclusion criteria?
RE: We obtained 91 KIRC raw data from the ICGC database. As the ICGC database was used to analyse the expression levels of m5C regulators, all 91 KIRC samples were taken for expression analysis. The raw TCGA-KIRC cohort contained 535 tumour samples. After matching these 535 samples to the survival information downloaded from the TCGA database, we found that there were "multiple sample ids for one patient". In this case, only one sample was retained. The final study included 530 TCGA-KIRC samples.
4.Line 102: Which databases? What was the key of their selection?
RE: The two databases referred to the TCGA and ICGC databases. We previously considered using some of the GEO chips, but through screening we found that some of the GEO chips could not contain all 14 m5C regulators in this study, and some of the GEO chips had too small a sample size. Therefore, we mainly used the TCGA and ICGC databases for this study.
5.Line 147: What are the 14 regulators selected for the study? What criteria were used to select these regulators?
RE: We were referred to two reviews[1, 2] published in 2021 to determine the 14 m5C regulators included in this study.
References:
- Han X, Wang M, Zhao YL, Yang Y, Yang YG: RNA methylations in human cancers. Semin Cancer Biol 2021, 75:97-115.
- Zhang Q, Liu F, Chen W, Miao H, Liang H, Liao Z, Zhang Z, Zhang B: The role of RNA m(5)C modification in cancer metastasis. Int J Biol Sci 2021, 17(13):3369-3380.
6.Line 157 and further: genes names should be italicized, authors must check carefully where they refer to a gene and where to a protein.
RE: We have italicised the gene names throughout the text and highlighted them in red.
7.The Figures are of poor quality and are hard to read.
RE: We are very sorry for small font in the figures which are unfriendly to you and readers. We have re-inserted the image in the word document and kept its original resolution (600dpi).
8.Figure 1 and 2 are the same, from the text it may seem that Figure 1 is misplaced, as it does not correspond to the provided caption.
RE: We double-checked the first version of the uploaded manuscript and did not put in the wrong images. To prevent accidents, we re-uploaded all the images again.
9.Line 205 – what were the clustering criteria?
RE: Unsupervised cluster analysis was conducted using ConsensuClusterPlus package to identify m5C modification patterns according to the expression of 14 m5C regulators. The number of possible clusters (k) was defined in the range of 2 to 9. When k=3, the clustering result was the best. So, we found three new disease subtypes to do further analysize. The parameters were set as “clusterAlg="km", distance="euclidean", reps=50, pItem=0.8, pFeature=1, maxK=9” while conducting the “ConsensuClusterPlus” package.
10.Line 206 – missing ‘in pattern C’
RE: We have added the missing 'in pattern C'.
11.In Figure 2C, 3ABC and further is data presented as medians/means/errors/SD or some else? Please provide a legend.
RE: Most of the data in the graph is in the form of means. The box plot contains mainly medians, upper and lower quartiles and outliers (scatter). Each point in the scatter plot represents a specific value for each sample. We have rewritten the legends and we hope they are detailed enough to understand the data now.
12.The negative correlation at Figure 6A is questionable, as the R value is shown as 0.12.
RE: We are very sorry for this clerical error in the manuscript and the inconvenience they caused in your reading. The manuscript has been thoroughly revised and edited, so we hope it can meet the journal's standard.
13.The Kaplan Meier curve in Figure 6D is also questionable, since there is large disproportion in patients’ numbers, I suggest to draw conclusions carefully.
RE: We were aware of this problem - the apparent imbalance in the size of the two groups - during the initial application of the m5C scoring groupings and noted the implications of this in the original text. We have modified the conclusions drawn based on this grouping throughout the text and no longer use absolute conclusions.
14.I recommend a revision of the text by a native English language speaker since there are some parts that present moderate language problems.
RE: We have submitted the document to the MDPI website for linguistic corrections. The English editor for the changes is Kelly O'Keefe and the changes are also marked in red.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The manuscript analyzed m5C modification and immune infiltration using TCGA data and developed a m5C score that predicts patient outcome. Several comments for authors to consider
1. Figure 1 and 2 are identical. Please include the correct Figure 1.
2. Line 46, it should be "pembrolizumab"
3. Line 241 and 242 - should be in the same sentence
4. Figure 4B - texts are too small to read
Author Response
Dear Editors and Reviewers:
Thank you for your kind email and recognition of our answers. We are extremely grateful for the reviewers’ professional work and responsibility. Those comments are all valuable and very helpful for improving our paper, as well as the important guiding significance to our researches. In this response, we have made efforts to address these concerns, and the manuscript has been changed according to the reviewers’ suggestions. We hope that the revision is acceptable, and we look forward to hearing from you soon. About the questions, we have answered all questions according to the reviewers’ comment one by one (please see the below in blue color).
Review2
- Figure 1 and 2 are identical. Please include the correct Figure 1.
RE: We double-checked the first version of the uploaded manuscript and did not put in the wrong images. To prevent accidents, we re-uploaded all the images again.
- Line 46, it should be "pembrolizumab"
RE: We are very sorry for some spelling mistakes in the manuscript and the inconvenience they caused in your reading. The manuscript has been thoroughly revised and edited, so we hope it can meet the journal's standard.
- Line 241 and 242 - should be in the same sentence
RE: Thank you very much for pointing this out. We have merged the two paragraphs.
- Figure 4B - texts are too small to read
RE: We have rewritten the Figure 4 legend and we hope they are detailed enough to understand now.
Review3:
1.Please consider changes in the body title “kidney renal clear cell carcinoma” with “clear cell renal cell carcinoma” and KIRC with ccRCC in the text.
RE: In the cancer abbreviations on the TCGA website, the abbreviation for renal clear cell carcinoma is KIRC. In view of the rigour of the article, we have changed KIRC to ccRCC in the manuscript.
2.In line 46, did you mean pablizumab or pembrolizumab?
RE: This should be pembrolizumab. We are very sorry for some spelling mistakes in the manuscript and the inconvenience they caused in your reading. The manuscript has been thoroughly revised and edited, so we hope it can meet the journal's standard.
3.All author's statistics were based on the use of database information in a retrograde fashion, and the clinical transposition of their findings needs to be supplementarily highlighted in the discussion section. The most important fact regarding m5Cscore is the correlation with the therapeutic response not only to estimate the prognostic of the patients. Please consider an extension in the discussion section.
RE: We have added relevant studies on m5C and tumour and drug therapy to the discussion section of the article.
Author Response File: Author Response.docx
Reviewer 3 Report
I read with interest the manuscript entitled " m5C modification patterns and tumour immune infiltration characteristics in kidney renal clear cell carcinoma".
Kidney cancer is still a big problem with high costs in almost all healthcare systems, with little progress in fundamental research despite being very accessible for comprehensive analysis. In recent years efforts have been made to understand the molecular differences between types of renal carcinoma and discover new ways to anticipate the progression, directly impacting therapeutic strategy. With increasing valid evidence, physicians can decide on a better combination and administration time and sequence, enhancing efficacy and reducing the toxicities.
In this study, the authors try to identify the role of m5C methylation in ccRCC immune infiltration and immunotherapeutic response. The m5Cscore was calculated by the principal component analysis algorithm and was designed to measure individual patients’ m5C modification patterns.
Statistical analysis is consistent and complex and responds to the authors' needs.
Recommendation:
Please consider changes in the body title “ kidney renal clear cell carcinoma” with “clear cell renal cell carcinoma” and KIRC with ccRCC in the text.
In line 46, did you mean pablizumab or pembrolizumab?
All author's statistics were based on the use of database information in a retrograde fashion, and the clinical transposition of their findings needs to be supplementarily highlighted in the discussion section. The most important fact regarding m5Cscore is the correlation with the therapeutic response not only to estimate the prognostic of the patients. Please consider an extension in the discussion section.
The article is well-written and needs minor revision to increase its impact and relevance.
Author Response
Dear Editors and Reviewers:
Thank you for your kind email and recognition of our answers. We are extremely grateful for the reviewers’ professional work and responsibility. Those comments are all valuable and very helpful for improving our paper, as well as the important guiding significance to our researches. In this response, we have made efforts to address these concerns, and the manuscript has been changed according to the reviewers’ suggestions. We hope that the revision is acceptable, and we look forward to hearing from you soon. About the questions, we have answered all questions according to the reviewers’ comment one by one (please see the below in blue color).
Review3:
1.Please consider changes in the body title “kidney renal clear cell carcinoma” with “clear cell renal cell carcinoma” and KIRC with ccRCC in the text.
RE: In the cancer abbreviations on the TCGA website, the abbreviation for renal clear cell carcinoma is KIRC. In view of the rigour of the article, we have changed KIRC to ccRCC in the manuscript.
2.In line 46, did you mean pablizumab or pembrolizumab?
RE: This should be pembrolizumab. We are very sorry for some spelling mistakes in the manuscript and the inconvenience they caused in your reading. The manuscript has been thoroughly revised and edited, so we hope it can meet the journal's standard.
3.All author's statistics were based on the use of database information in a retrograde fashion, and the clinical transposition of their findings needs to be supplementarily highlighted in the discussion section. The most important fact regarding m5Cscore is the correlation with the therapeutic response not only to estimate the prognostic of the patients. Please consider an extension in the discussion section.
RE: We have added relevant studies on m5C and tumour and drug therapy to the discussion section of the article.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
I find the changes and responses sufficient and recommend your manuscript for publication.
Reviewer 2 Report
Thank you addressing my comments. No additional comments.
Reviewer 3 Report
I agree with the revised version.
