Title: Construction of immune-related lncRNA signature to predict aggressiveness, immune
landscape, and drug resistance of colon cancer
Version: 2 Date: 05 Nov 2021
Reviewer's report:
The overall design idea of the article is clear and the model design is reasonable. It is suggested
to answer several questions and make necessary modifications.
Major issues:
1. As mentioned in the manuscript, the authors established a pairs-risk model and an exp-risk
model respectively and then combined them to predict the prognosis. What are the advantages
of these three models, that is, under what circumstances to choose a model?
2. The author uses the data in the TCGA database to establish the model. To ensure the stability
and credibility of the model, should other datasets be used for verification? (such as datasets
in GEO).
Minor issues:
1. In the discussion, the authors should emphasize their model's strengths over other prognostics
scoring systems.
2. The authors found two immune-correlative genes, TGFB2 and LAG3. However, there is no
relevant discussion on these two genes.
3. It is suggested that it may be better to rearrange the picture. For example, in Figure 6B-X,
the positive and negative immune cells correlation with the risk value of the model, are listed
together to facilitate readers' understanding. In addition, the same is true in Figure 7. It would
be better to list 2 genes and 5 chemotherapeutic drugs respectively.
4. Needs some language corrections before being published. For example, spelling mistakes in
the name of the corresponding author on the title page, “Baoqing Jia” for “Boqing Jia”. Other
small grammatical errors need to be corrected.
Title: Construction of immune-related lncRNA signature to predict aggressiveness, immune
landscape, and drug resistance of colon cancer
Version: 2 Date: 05 Nov 2021
Reviewer's report:
The overall design idea of the article is clear and the model design is reasonable. It is suggested
to answer several questions and make necessary modifications.
Major issues:
1. As mentioned in the manuscript, the authors established a pairs-risk model and an exp-risk
model respectively and then combined them to predict the prognosis. What are the advantages
of these three models, that is, under what circumstances to choose a model?
2. The author uses the data in the TCGA database to establish the model. To ensure the stability
and credibility of the model, should other datasets be used for verification? (such as datasets
in GEO).
Minor issues:
1. In the discussion, the authors should emphasize their model's strengths over other prognostics
scoring systems.
2. The authors found two immune-correlative genes, TGFB2 and LAG3. However, there is no
relevant discussion on these two genes.
3. It is suggested that it may be better to rearrange the picture. For example, in Figure 6B-X,
the positive and negative immune cells correlation with the risk value of the model, are listed
together to facilitate readers' understanding. In addition, the same is true in Figure 7. It would
be better to list 2 genes and 5 chemotherapeutic drugs respectively.
4. Needs some language corrections before being published. For example, spelling mistakes in
the name of the corresponding author on the title page, “Baoqing Jia” for “Boqing Jia”. Other
small grammatical errors need to be corrected.
Please review this paper.
user
Title: Construction of immune-related lncRNA signature to predict aggressiveness, immune
landscape, and drug resistance of colon cancer
Version: 2 Date: 05 Nov 2021
Reviewer's report:
The overall design idea of the article is clear and the model design is reasonable. It is suggested
to answer several questions and make necessary modifications.
Major issues:
1. As mentioned in the manuscript, the authors established a pairs-risk model and an exp-risk
model respectively and then combined them to predict the prognosis. What are the advantages
of these three models, that is, under what circumstances to choose a model?
2. The author uses the data in the TCGA database to establish the model. To ensure the stability
and credibility of the model, should other datasets be used for verification? (such as datasets
in GEO).
Minor issues:
1. In the discussion, the authors should emphasize their model's strengths over other prognostics
scoring systems.
2. The authors found two immune-correlative genes, TGFB2 and LAG3. However, there is no
relevant discussion on these two genes.
3. It is suggested that it may be better to rearrange the picture. For example, in Figure 6B-X,
the positive and negative immune cells correlation with the risk value of the model, are listed
together to facilitate readers' understanding. In addition, the same is true in Figure 7. It would
be better to list 2 genes and 5 chemotherapeutic drugs respectively.
4. Needs some language corrections before being published. For example, spelling mistakes in
the name of the corresponding author on the title page, “Baoqing Jia” for “Boqing Jia”. Other
small grammatical errors need to be corrected.
assistant