Title: Comprehensive analysis of CXCL14 uncovers its role during liver metastasis in colon
cancer
Version: 1 Date: 24 Jun 2023
Reviewer's report:
Zhou and their colleagues systematically explored the molecules involved in the liver metastasis
process of colon cancer. The biological role of these molecules was identified through the GO
and KEGG analysis. Moreover, they identified that the molecules SERPINA3, SERPINA1,
MMP3, ALDH1A3, PBK and CXCL14 were the independent factors for patients survival. The
CXCL14 was selected for further analysis for its most significant P value. Single-cell analysis
showed that the CXCL14 was mainly expressed in the fibroblasts. Meanwhile, the biological role
of fibroblasts in the colon cancer microenvironment was investigated. Further, the clinical role of
CXCL14 in colon cancer was also explored. The result showed that the CXCL14 is a protective
factor against colon cancer independent of other clinical parameters like age, gender, clinical
stage, and TNM classifications. Then, biological enrichment analysis indicated that the CXCL14
is predominantly involved in the activating of the WNT/#/catenin pathway, pancreas beta cells,
peroxisome and bile acid metabolism. Immune infiltration analysis showed that for the patients
with high CXCL14 levels, the plasma B cells, CD8 + T cells, neutrophil and NK cells might
infiltrate more, in contrast to B cells, monocyte and macrophages. Furthermore, they found that
the patients with low CXCL14 expression might be more sensitive to etoposide, rapamycin and
sunitinib. I think that this is an interesting study with clinical translational significance. However,
some problems should be solved.
1. A detailed flowchart will greatly improve the reading experience of readers like me and help
me better understand the article.
2. Baseline data for patients is required.
3. The author conducted data preprocessing, but will this affect the stability of the results? What
are the specific aspects reflected in?
4. Some typos are there; rectify those.
5. Can the author improve the details of the GDSC database?
6. Can the author provide specific parameters for the clusterprofiler package?
7. Figure legend section is still not detailed enough.
Title: Comprehensive analysis of CXCL14 uncovers its role during liver metastasis in colon
cancer
Version: 1 Date: 24 Jun 2023
Reviewer's report:
Zhou and their colleagues systematically explored the molecules involved in the liver metastasis
process of colon cancer. The biological role of these molecules was identified through the GO
and KEGG analysis. Moreover, they identified that the molecules SERPINA3, SERPINA1,
MMP3, ALDH1A3, PBK and CXCL14 were the independent factors for patients survival. The
CXCL14 was selected for further analysis for its most significant P value. Single-cell analysis
showed that the CXCL14 was mainly expressed in the fibroblasts. Meanwhile, the biological role
of fibroblasts in the colon cancer microenvironment was investigated. Further, the clinical role of
CXCL14 in colon cancer was also explored. The result showed that the CXCL14 is a protective
factor against colon cancer independent of other clinical parameters like age, gender, clinical
stage, and TNM classifications. Then, biological enrichment analysis indicated that the CXCL14
is predominantly involved in the activating of the WNT/#/catenin pathway, pancreas beta cells,
peroxisome and bile acid metabolism. Immune infiltration analysis showed that for the patients
with high CXCL14 levels, the plasma B cells, CD8 + T cells, neutrophil and NK cells might
infiltrate more, in contrast to B cells, monocyte and macrophages. Furthermore, they found that
the patients with low CXCL14 expression might be more sensitive to etoposide, rapamycin and
sunitinib. I think that this is an interesting study with clinical translational significance. However,
some problems should be solved.
1. A detailed flowchart will greatly improve the reading experience of readers like me and help
me better understand the article.
2. Baseline data for patients is required.
3. The author conducted data preprocessing, but will this affect the stability of the results? What
are the specific aspects reflected in?
4. Some typos are there; rectify those.
5. Can the author improve the details of the GDSC database?
6. Can the author provide specific parameters for the clusterprofiler package?
7. Figure legend section is still not detailed enough.
Please review this paper.
user
Title: Comprehensive analysis of CXCL14 uncovers its role during liver metastasis in colon
cancer
Version: 1 Date: 24 Jun 2023
Reviewer's report:
Zhou and their colleagues systematically explored the molecules involved in the liver metastasis
process of colon cancer. The biological role of these molecules was identified through the GO
and KEGG analysis. Moreover, they identified that the molecules SERPINA3, SERPINA1,
MMP3, ALDH1A3, PBK and CXCL14 were the independent factors for patients survival. The
CXCL14 was selected for further analysis for its most significant P value. Single-cell analysis
showed that the CXCL14 was mainly expressed in the fibroblasts. Meanwhile, the biological role
of fibroblasts in the colon cancer microenvironment was investigated. Further, the clinical role of
CXCL14 in colon cancer was also explored. The result showed that the CXCL14 is a protective
factor against colon cancer independent of other clinical parameters like age, gender, clinical
stage, and TNM classifications. Then, biological enrichment analysis indicated that the CXCL14
is predominantly involved in the activating of the WNT/#/catenin pathway, pancreas beta cells,
peroxisome and bile acid metabolism. Immune infiltration analysis showed that for the patients
with high CXCL14 levels, the plasma B cells, CD8 + T cells, neutrophil and NK cells might
infiltrate more, in contrast to B cells, monocyte and macrophages. Furthermore, they found that
the patients with low CXCL14 expression might be more sensitive to etoposide, rapamycin and
sunitinib. I think that this is an interesting study with clinical translational significance. However,
some problems should be solved.
1. A detailed flowchart will greatly improve the reading experience of readers like me and help
me better understand the article.
2. Baseline data for patients is required.
3. The author conducted data preprocessing, but will this affect the stability of the results? What
are the specific aspects reflected in?
4. Some typos are there; rectify those.
5. Can the author improve the details of the GDSC database?
6. Can the author provide specific parameters for the clusterprofiler package?
7. Figure legend section is still not detailed enough.
assistant