Title: Single-cell transcriptomic analysis reveals prognosis-related stromal signatures that
potentiate stratification of patients with extrahepatic cholangiocarcinoma
Version: 0 Date: 13 Jan 2025
Reviewer's report:
Thank you for submitting your manuscript titled "Single-cell transcriptomic analysis reveals
prognosis-related stromal signatures that potentiate stratification of patients with extrahepatic
cholangiocarcinoma". This study is both well-written and insightful, particularly in highlighting
the potential role of stromal signatures in patient stratification and prognosis. Below, I provide
suggestions to help enhance the quality and clarity of your manuscript.
Major Concerns
1. Prognostic Analysis and Confounding Factors
When evaluating the correlation between gene expression and prognosis, disease progression
in individual patients is a significant confounding factor. A multivariate analysis that includes
TNM staging and the status of curative resection should be performed to better assess the
independent correlation of these novel genetic classification with prognosis. This would
strengthen the validity of your conclusions.
2. Sample Size for Survival Analysis
The sample size for survival analysis using bulk RNA sequencing appears to be insufficient. To
ensure statistical reliability, I recommend validating your findings using public databases with
larger cohorts. Incorporating external validation would make your study more comprehensive
and generalizable.
3. Molecular Reprogramming in Stromal Cells
The statement, "Compared to those from adjacent normal tissues, the transcriptional activity
of HPLCs, fibroblasts and T cells in tumors tended to be altered, indicating molecular
reprogramming in these stromal cells," would benefit from additional evidence. Specifically,
analyzing paired tumor and stromal cells from the same patients to directly compare their
transcriptional profiles would strengthen this claim.
4. Clinical Applicability
To enhance the impact of your study, discussing its clinical applications would be beneficial. For
example, could the identified stromal signatures contribute to selecting candidates for adjuvant
chemotherapy post-surgery? A brief discussion of potential clinical implications would help
contextualize your findings for translational purposes.
Minor Concerns
1. Clarification on B-cell Subsets
The identification of six B-cell subsets is mentioned. Could you clarify whether this was derived
from single-cell RNA sequencing or bulk RNA analysis? This section is currently unclear due
to the preceding discussion of bulk RNA sequencing. Providing a clearer distinction between
the methodologies would improve the manuscript's readability.
2. Markers for Hematopoietic Progenitor-like Cells
In Results (lines 333-334), MKI67 and TOP2A are cited as representative markers for
hematopoietic progenitor-like cells. However, these genes are primarily associated with cell
proliferation. It would be more appropriate to show the expression levels of established markers
such as CD34, KIT, THY1, PROM1, RUNX1, GATA2, and SPI1, as depicted in Figure 1c. This
adjustment would improve the specificity and accuracy of your interpretation.
I hope these comment will be helpful.
Title: Single-cell transcriptomic analysis reveals prognosis-related stromal signatures that
potentiate stratification of patients with extrahepatic cholangiocarcinoma
Version: 0 Date: 13 Jan 2025
Reviewer's report:
Thank you for submitting your manuscript titled "Single-cell transcriptomic analysis reveals
prognosis-related stromal signatures that potentiate stratification of patients with extrahepatic
cholangiocarcinoma". This study is both well-written and insightful, particularly in highlighting
the potential role of stromal signatures in patient stratification and prognosis. Below, I provide
suggestions to help enhance the quality and clarity of your manuscript.
Major Concerns
1. Prognostic Analysis and Confounding Factors
When evaluating the correlation between gene expression and prognosis, disease progression
in individual patients is a significant confounding factor. A multivariate analysis that includes
TNM staging and the status of curative resection should be performed to better assess the
independent correlation of these novel genetic classification with prognosis. This would
strengthen the validity of your conclusions.
2. Sample Size for Survival Analysis
The sample size for survival analysis using bulk RNA sequencing appears to be insufficient. To
ensure statistical reliability, I recommend validating your findings using public databases with
larger cohorts. Incorporating external validation would make your study more comprehensive
and generalizable.
3. Molecular Reprogramming in Stromal Cells
The statement, "Compared to those from adjacent normal tissues, the transcriptional activity
of HPLCs, fibroblasts and T cells in tumors tended to be altered, indicating molecular
reprogramming in these stromal cells," would benefit from additional evidence. Specifically,
analyzing paired tumor and stromal cells from the same patients to directly compare their
transcriptional profiles would strengthen this claim.
4. Clinical Applicability
To enhance the impact of your study, discussing its clinical applications would be beneficial. For
example, could the identified stromal signatures contribute to selecting candidates for adjuvant
chemotherapy post-surgery? A brief discussion of potential clinical implications would help
contextualize your findings for translational purposes.
Minor Concerns
1. Clarification on B-cell Subsets
The identification of six B-cell subsets is mentioned. Could you clarify whether this was derived
from single-cell RNA sequencing or bulk RNA analysis? This section is currently unclear due
to the preceding discussion of bulk RNA sequencing. Providing a clearer distinction between
the methodologies would improve the manuscript's readability.
2. Markers for Hematopoietic Progenitor-like Cells
In Results (lines 333-334), MKI67 and TOP2A are cited as representative markers for
hematopoietic progenitor-like cells. However, these genes are primarily associated with cell
proliferation. It would be more appropriate to show the expression levels of established markers
such as CD34, KIT, THY1, PROM1, RUNX1, GATA2, and SPI1, as depicted in Figure 1c. This
adjustment would improve the specificity and accuracy of your interpretation.
I hope these comment will be helpful.
Please review this paper.
user
Title: Single-cell transcriptomic analysis reveals prognosis-related stromal signatures that
potentiate stratification of patients with extrahepatic cholangiocarcinoma
Version: 0 Date: 13 Jan 2025
Reviewer's report:
Thank you for submitting your manuscript titled "Single-cell transcriptomic analysis reveals
prognosis-related stromal signatures that potentiate stratification of patients with extrahepatic
cholangiocarcinoma". This study is both well-written and insightful, particularly in highlighting
the potential role of stromal signatures in patient stratification and prognosis. Below, I provide
suggestions to help enhance the quality and clarity of your manuscript.
Major Concerns
1. Prognostic Analysis and Confounding Factors
When evaluating the correlation between gene expression and prognosis, disease progression
in individual patients is a significant confounding factor. A multivariate analysis that includes
TNM staging and the status of curative resection should be performed to better assess the
independent correlation of these novel genetic classification with prognosis. This would
strengthen the validity of your conclusions.
2. Sample Size for Survival Analysis
The sample size for survival analysis using bulk RNA sequencing appears to be insufficient. To
ensure statistical reliability, I recommend validating your findings using public databases with
larger cohorts. Incorporating external validation would make your study more comprehensive
and generalizable.
3. Molecular Reprogramming in Stromal Cells
The statement, "Compared to those from adjacent normal tissues, the transcriptional activity
of HPLCs, fibroblasts and T cells in tumors tended to be altered, indicating molecular
reprogramming in these stromal cells," would benefit from additional evidence. Specifically,
analyzing paired tumor and stromal cells from the same patients to directly compare their
transcriptional profiles would strengthen this claim.
4. Clinical Applicability
To enhance the impact of your study, discussing its clinical applications would be beneficial. For
example, could the identified stromal signatures contribute to selecting candidates for adjuvant
chemotherapy post-surgery? A brief discussion of potential clinical implications would help
contextualize your findings for translational purposes.
Minor Concerns
1. Clarification on B-cell Subsets
The identification of six B-cell subsets is mentioned. Could you clarify whether this was derived
from single-cell RNA sequencing or bulk RNA analysis? This section is currently unclear due
to the preceding discussion of bulk RNA sequencing. Providing a clearer distinction between
the methodologies would improve the manuscript's readability.
2. Markers for Hematopoietic Progenitor-like Cells
In Results (lines 333-334), MKI67 and TOP2A are cited as representative markers for
hematopoietic progenitor-like cells. However, these genes are primarily associated with cell
proliferation. It would be more appropriate to show the expression levels of established markers
such as CD34, KIT, THY1, PROM1, RUNX1, GATA2, and SPI1, as depicted in Figure 1c. This
adjustment would improve the specificity and accuracy of your interpretation.
I hope these comment will be helpful.
assistant