Title: Development of an immune-related gene prognostic risk model and identification of an
Immune infiltration signature in the tumor microenvironment of colon cancer
Version: 1 Date: 23 Dec 2022
Reviewer's report:
In this manuscript, the authors performed bioinformatic analysis in search of potential prognostic
biomarkers in tumor microenvironment of colon cancer. Specifically, the authors utilized
publicly available datasets and built a statistical model with immune-related gene signatures for
patient stratifications. The study, in general, represents a novel application of genomic data in
immuno-oncology research and might be of interest to a broad scope of audience. However, I
do have following comments:
Major:
1. I was confused about the data integration. In this study, the authors mentioned five data
sources: transcriptomics and clinical data from TCGA, immunogenic data from ImmPort, and
immune infiltration data from TIMER, TF from Cistrome, and immune cell content data from
timer.cistrome.org. Are these data from same patients/cohort? If no, they cannot be correlated
and analyzed in the same context. If yes, the author should mention it in the manuscript.
2. From my understanding, the authors defined ‘validation’ as using one bioinformatic model to
validate the results from others bioinformatic method outputs, which is cross-reference. There
is neither internal validation using cross-validation nor external validation using independent
cohort, adding significant limitations to the universality of this work. I suggest authors validate
their model on external dataset from other publicly available sources.
Minor:
1. Explain jargon at their first appearance (provide their full spelling). For example, FDR, logFC,
(line 100), HR (Hazard ratio?) at line 112.
2. Provide the environment for the packages utilized in the study, e.g., R or Python.
3. Provide proper reference to the software used in the study, e.g, cytoscape at line 108:
Shannon, Paul, et al. "Cytoscape: a software environment for integrated models of biomolecular
interaction networks." Genome research 13.11 (2003): 2498-2504.
Title: Development of an immune-related gene prognostic risk model and identification of an
Immune infiltration signature in the tumor microenvironment of colon cancer
Version: 1 Date: 23 Dec 2022
Reviewer's report:
In this manuscript, the authors performed bioinformatic analysis in search of potential prognostic
biomarkers in tumor microenvironment of colon cancer. Specifically, the authors utilized
publicly available datasets and built a statistical model with immune-related gene signatures for
patient stratifications. The study, in general, represents a novel application of genomic data in
immuno-oncology research and might be of interest to a broad scope of audience. However, I
do have following comments:
Major:
1. I was confused about the data integration. In this study, the authors mentioned five data
sources: transcriptomics and clinical data from TCGA, immunogenic data from ImmPort, and
immune infiltration data from TIMER, TF from Cistrome, and immune cell content data from
timer.cistrome.org. Are these data from same patients/cohort? If no, they cannot be correlated
and analyzed in the same context. If yes, the author should mention it in the manuscript.
2. From my understanding, the authors defined ‘validation’ as using one bioinformatic model to
validate the results from others bioinformatic method outputs, which is cross-reference. There
is neither internal validation using cross-validation nor external validation using independent
cohort, adding significant limitations to the universality of this work. I suggest authors validate
their model on external dataset from other publicly available sources.
Minor:
1. Explain jargon at their first appearance (provide their full spelling). For example, FDR, logFC,
(line 100), HR (Hazard ratio?) at line 112.
2. Provide the environment for the packages utilized in the study, e.g., R or Python.
3. Provide proper reference to the software used in the study, e.g, cytoscape at line 108:
Shannon, Paul, et al. "Cytoscape: a software environment for integrated models of biomolecular
interaction networks." Genome research 13.11 (2003): 2498-2504.
Please review this paper.
user
Title: Development of an immune-related gene prognostic risk model and identification of an
Immune infiltration signature in the tumor microenvironment of colon cancer
Version: 1 Date: 23 Dec 2022
Reviewer's report:
In this manuscript, the authors performed bioinformatic analysis in search of potential prognostic
biomarkers in tumor microenvironment of colon cancer. Specifically, the authors utilized
publicly available datasets and built a statistical model with immune-related gene signatures for
patient stratifications. The study, in general, represents a novel application of genomic data in
immuno-oncology research and might be of interest to a broad scope of audience. However, I
do have following comments:
Major:
1. I was confused about the data integration. In this study, the authors mentioned five data
sources: transcriptomics and clinical data from TCGA, immunogenic data from ImmPort, and
immune infiltration data from TIMER, TF from Cistrome, and immune cell content data from
timer.cistrome.org. Are these data from same patients/cohort? If no, they cannot be correlated
and analyzed in the same context. If yes, the author should mention it in the manuscript.
2. From my understanding, the authors defined ‘validation’ as using one bioinformatic model to
validate the results from others bioinformatic method outputs, which is cross-reference. There
is neither internal validation using cross-validation nor external validation using independent
cohort, adding significant limitations to the universality of this work. I suggest authors validate
their model on external dataset from other publicly available sources.
Minor:
1. Explain jargon at their first appearance (provide their full spelling). For example, FDR, logFC,
(line 100), HR (Hazard ratio?) at line 112.
2. Provide the environment for the packages utilized in the study, e.g., R or Python.
3. Provide proper reference to the software used in the study, e.g, cytoscape at line 108:
Shannon, Paul, et al. "Cytoscape: a software environment for integrated models of biomolecular
interaction networks." Genome research 13.11 (2003): 2498-2504.
assistant