Title: Identification of a Novel m6A-related lncRNA Pair Signature for Predicting the Prognosis
of Gastric Cancer Patients
Version: 4 Date: 19 Dec 2021
Reviewer's report:
This is a nice work which integrated omics data with survival data to identify the prognostic
m6A-associated lncRNA signature for stratification of gastric cancer patient. I have a few
suggestions and comments to improve the manuscript.
Introduction:
• Could the author provide the GC disease statistics in 2021 rather than in 2018?
• I suggest author to shorten the introduction section.
• In the introduction section the author discusses about the mortality rate of advanced gastric
cancer is about 50%, and therefore early prognosis biomarkers are required for the cancer
diagnosis. However, the current design of the study does not focus on detection of early gastric
cancer. Could author comment on that?
Result:
• In the text is not clear what proportion of patients were stratified as testing set and training set.
• How many lncRNAs were extracted from the TCGA RNAseq dataset?
• It is not clear how the author narrowed down to 10 m6A regulators? If the author had already
decided to focus on those 10 m6A regulators, then why did they perform the co-expression
analysis between 21 m6A regulators and lncRNAs? It is still not clear how many lncRNAs were
used for the pairwise co-expression analysis?
• The author first performed the pairwise co-expression analysis between lncRNAs and m6A
regulators and found 625 interactions, and 491 lncRNA and then 444 lncRNAs associated with
10 m6A regulators, and then again, to narrow down they performed differential expression
analysis. Is it they started the differential expression analysis from 491 lncRNAs? If this is the
case, then it might be they will miss other potential lncRNAs that can significantly differentiate
gastric cancer and associated with patient survival. In my point of view, they should first perform
the differential expression analysis of whole genome lncRNAs and then can perform differential
analysis between m6A regulators and differentially expressed lncRNAs?
• Can author provide the significance of studying lncRNAs pairs? And then why one should
study pairs, why not 3 or 4 lncRNAs combination? The methods of deriving the lncRNA pairs
is poorly described.
• Is the splitting of the cohort was performed only one time and whether the risk score was
developed from training cohort? And validated in the testing cohort and whole cohort? To check
the robustness of the biomarker, I would suggest splitting the whole cohort into training and
testing set let’s say 100 times, and at each split derive the signature from the training set and
validate them in the testing set. Then record the AUC at each split in the testing set and check
the mean AUC obtained from the 100 iterations.
• Is there any specific reason to choose the median threshold to stratify patient into two risk
groups? Can you try other cut-off for example lower quartile and upper-quartile and show us
which cut-off performs better to stratify patients into two risk groups?
• The author has shown the lncRNA signature is an independent predictor in the TCGA dataset.
Can you please show its reproducibility in the validation datasets? Similarly, can you please
show the accuracy of lncRNA score in predicting survival in the validation datasets?
• Could author compare the accuracy for predicting prognosis of the lncRNA signature with
other established molecular signatures developed for gastric cancer?
• Does the lncRNA signature is beneficial to stratify early cancer stages patients into risk groups?
General comments:
This paper requires significant English editing.
Title: Identification of a Novel m6A-related lncRNA Pair Signature for Predicting the Prognosis
of Gastric Cancer Patients
Version: 4 Date: 19 Dec 2021
Reviewer's report:
This is a nice work which integrated omics data with survival data to identify the prognostic
m6A-associated lncRNA signature for stratification of gastric cancer patient. I have a few
suggestions and comments to improve the manuscript.
Introduction:
• Could the author provide the GC disease statistics in 2021 rather than in 2018?
• I suggest author to shorten the introduction section.
• In the introduction section the author discusses about the mortality rate of advanced gastric
cancer is about 50%, and therefore early prognosis biomarkers are required for the cancer
diagnosis. However, the current design of the study does not focus on detection of early gastric
cancer. Could author comment on that?
Result:
• In the text is not clear what proportion of patients were stratified as testing set and training set.
• How many lncRNAs were extracted from the TCGA RNAseq dataset?
• It is not clear how the author narrowed down to 10 m6A regulators? If the author had already
decided to focus on those 10 m6A regulators, then why did they perform the co-expression
analysis between 21 m6A regulators and lncRNAs? It is still not clear how many lncRNAs were
used for the pairwise co-expression analysis?
• The author first performed the pairwise co-expression analysis between lncRNAs and m6A
regulators and found 625 interactions, and 491 lncRNA and then 444 lncRNAs associated with
10 m6A regulators, and then again, to narrow down they performed differential expression
analysis. Is it they started the differential expression analysis from 491 lncRNAs? If this is the
case, then it might be they will miss other potential lncRNAs that can significantly differentiate
gastric cancer and associated with patient survival. In my point of view, they should first perform
the differential expression analysis of whole genome lncRNAs and then can perform differential
analysis between m6A regulators and differentially expressed lncRNAs?
• Can author provide the significance of studying lncRNAs pairs? And then why one should
study pairs, why not 3 or 4 lncRNAs combination? The methods of deriving the lncRNA pairs
is poorly described.
• Is the splitting of the cohort was performed only one time and whether the risk score was
developed from training cohort? And validated in the testing cohort and whole cohort? To check
the robustness of the biomarker, I would suggest splitting the whole cohort into training and
testing set let’s say 100 times, and at each split derive the signature from the training set and
validate them in the testing set. Then record the AUC at each split in the testing set and check
the mean AUC obtained from the 100 iterations.
• Is there any specific reason to choose the median threshold to stratify patient into two risk
groups? Can you try other cut-off for example lower quartile and upper-quartile and show us
which cut-off performs better to stratify patients into two risk groups?
• The author has shown the lncRNA signature is an independent predictor in the TCGA dataset.
Can you please show its reproducibility in the validation datasets? Similarly, can you please
show the accuracy of lncRNA score in predicting survival in the validation datasets?
• Could author compare the accuracy for predicting prognosis of the lncRNA signature with
other established molecular signatures developed for gastric cancer?
• Does the lncRNA signature is beneficial to stratify early cancer stages patients into risk groups?
General comments:
This paper requires significant English editing.
Please review this paper.
user
Title: Identification of a Novel m6A-related lncRNA Pair Signature for Predicting the Prognosis
of Gastric Cancer Patients
Version: 4 Date: 19 Dec 2021
Reviewer's report:
This is a nice work which integrated omics data with survival data to identify the prognostic
m6A-associated lncRNA signature for stratification of gastric cancer patient. I have a few
suggestions and comments to improve the manuscript.
Introduction:
• Could the author provide the GC disease statistics in 2021 rather than in 2018?
• I suggest author to shorten the introduction section.
• In the introduction section the author discusses about the mortality rate of advanced gastric
cancer is about 50%, and therefore early prognosis biomarkers are required for the cancer
diagnosis. However, the current design of the study does not focus on detection of early gastric
cancer. Could author comment on that?
Result:
• In the text is not clear what proportion of patients were stratified as testing set and training set.
• How many lncRNAs were extracted from the TCGA RNAseq dataset?
• It is not clear how the author narrowed down to 10 m6A regulators? If the author had already
decided to focus on those 10 m6A regulators, then why did they perform the co-expression
analysis between 21 m6A regulators and lncRNAs? It is still not clear how many lncRNAs were
used for the pairwise co-expression analysis?
• The author first performed the pairwise co-expression analysis between lncRNAs and m6A
regulators and found 625 interactions, and 491 lncRNA and then 444 lncRNAs associated with
10 m6A regulators, and then again, to narrow down they performed differential expression
analysis. Is it they started the differential expression analysis from 491 lncRNAs? If this is the
case, then it might be they will miss other potential lncRNAs that can significantly differentiate
gastric cancer and associated with patient survival. In my point of view, they should first perform
the differential expression analysis of whole genome lncRNAs and then can perform differential
analysis between m6A regulators and differentially expressed lncRNAs?
• Can author provide the significance of studying lncRNAs pairs? And then why one should
study pairs, why not 3 or 4 lncRNAs combination? The methods of deriving the lncRNA pairs
is poorly described.
• Is the splitting of the cohort was performed only one time and whether the risk score was
developed from training cohort? And validated in the testing cohort and whole cohort? To check
the robustness of the biomarker, I would suggest splitting the whole cohort into training and
testing set let’s say 100 times, and at each split derive the signature from the training set and
validate them in the testing set. Then record the AUC at each split in the testing set and check
the mean AUC obtained from the 100 iterations.
• Is there any specific reason to choose the median threshold to stratify patient into two risk
groups? Can you try other cut-off for example lower quartile and upper-quartile and show us
which cut-off performs better to stratify patients into two risk groups?
• The author has shown the lncRNA signature is an independent predictor in the TCGA dataset.
Can you please show its reproducibility in the validation datasets? Similarly, can you please
show the accuracy of lncRNA score in predicting survival in the validation datasets?
• Could author compare the accuracy for predicting prognosis of the lncRNA signature with
other established molecular signatures developed for gastric cancer?
• Does the lncRNA signature is beneficial to stratify early cancer stages patients into risk groups?
General comments:
This paper requires significant English editing.
assistant