Title: Identification and validation of a CD4 + T cell-related prognostic model to predict immune
responses in stage III-IV colorectal cancer
Version: 1 Date: 23 Nov 2024
Reviewer:  Wenlong Chen
Reviewer's report:
1. When performing single-cell data processing, authors should detail how cell subpopulations
are annotated and need to show marker expression for individual cell subpopulations.
2. In Identification of CD4+ T cell-related subtypes of stage III-IV CRC, more evidence is
needed for the accuracy of the choice of k values than just writing when k = 2, the cohort could
be well divided into two subtypes.
3. In line 280, 470... activated CD4 T cell, activated CD8 T cell..., please check the spelling of
the cell name, it should be consistent with the context.
4. In Evaluation of tumor immune microenvironment, imputation of the tumor immune
microenvironment by deconvolutional methods on transcriptomic data is feasible, but other
computational methods should be added to increase the credibility of the results, including but
not limited to MCPcounter, xCell, TIMER, and so on.
5.In Figure6A, 6 key genes are characterized genes obtained by analyzing CD4+ T cells, but
how to explain that some genes such as ANXA2 have no correlation with CD4+ T cells?
6. Results of differences in response to immunotherapy are based on data from colorectal cancer,
so why was a bladder cancer cohort used for validation?  GEO database has enough treatment
response data to support your conclusions (GSE136114, GSE60331...). Similarly, differences
in sensitivity to drugs should be validated with more clinical data.
7. Why not further validate TME differences with single-cell data? even if it's a simple cell ratio.
Title: Identification and validation of a CD4 + T cell-related prognostic model to predict immune
responses in stage III-IV colorectal cancer
Version: 1 Date: 23 Nov 2024
Reviewer:  Wenlong Chen
Reviewer's report:
1. When performing single-cell data processing, authors should detail how cell subpopulations
are annotated and need to show marker expression for individual cell subpopulations.
2. In Identification of CD4+ T cell-related subtypes of stage III-IV CRC, more evidence is
needed for the accuracy of the choice of k values than just writing when k = 2, the cohort could
be well divided into two subtypes.
3. In line 280, 470... activated CD4 T cell, activated CD8 T cell..., please check the spelling of
the cell name, it should be consistent with the context.
4. In Evaluation of tumor immune microenvironment, imputation of the tumor immune
microenvironment by deconvolutional methods on transcriptomic data is feasible, but other
computational methods should be added to increase the credibility of the results, including but
not limited to MCPcounter, xCell, TIMER, and so on.
5.In Figure6A, 6 key genes are characterized genes obtained by analyzing CD4+ T cells, but
how to explain that some genes such as ANXA2 have no correlation with CD4+ T cells?
6. Results of differences in response to immunotherapy are based on data from colorectal cancer,
so why was a bladder cancer cohort used for validation?  GEO database has enough treatment
response data to support your conclusions (GSE136114, GSE60331...). Similarly, differences
in sensitivity to drugs should be validated with more clinical data.
7. Why not further validate TME differences with single-cell data? even if it's a simple cell ratio.
Please review this paper.
user
Title: Identification and validation of a CD4 + T cell-related prognostic model to predict immune
responses in stage III-IV colorectal cancer
Version: 1 Date: 23 Nov 2024
Reviewer:  Wenlong Chen
Reviewer's report:
1. When performing single-cell data processing, authors should detail how cell subpopulations
are annotated and need to show marker expression for individual cell subpopulations.
2. In Identification of CD4+ T cell-related subtypes of stage III-IV CRC, more evidence is
needed for the accuracy of the choice of k values than just writing when k = 2, the cohort could
be well divided into two subtypes.
3. In line 280, 470... activated CD4 T cell, activated CD8 T cell..., please check the spelling of
the cell name, it should be consistent with the context.
4. In Evaluation of tumor immune microenvironment, imputation of the tumor immune
microenvironment by deconvolutional methods on transcriptomic data is feasible, but other
computational methods should be added to increase the credibility of the results, including but
not limited to MCPcounter, xCell, TIMER, and so on.
5.In Figure6A, 6 key genes are characterized genes obtained by analyzing CD4+ T cells, but
how to explain that some genes such as ANXA2 have no correlation with CD4+ T cells?
6. Results of differences in response to immunotherapy are based on data from colorectal cancer,
so why was a bladder cancer cohort used for validation?  GEO database has enough treatment
response data to support your conclusions (GSE136114, GSE60331...). Similarly, differences
in sensitivity to drugs should be validated with more clinical data.
7. Why not further validate TME differences with single-cell data? even if it's a simple cell ratio.
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