Title: The prognostic value of Immunoscore in the early-onset colorectal cancer
Version: 1 Date: 01 Mar 2025
Reviewer's report:
Review
This study establishes a Chinese population-specific Immunoscore (IS) framework through
neural network-based quantification of CD3+/CD8+ tumor-infiltrating lymphocytes and
validates its prognostic significance in early-onset colorectal cancer (EOCRC). The results
demonstrate that IS effectively stratifies EOCRC patients by recurrence and metastasis risks,
independent of TNM staging. As EOCRC represents a rare but epidemiologically significant
subgroup with rising global incidence and aggressive clinicopathological features, this work fills
a critical knowledge gap by providing the first evidence of IS applicability in this underserved
population. By bridging the gap between immune profiling and precision oncology in EOCRC,
this work provides foundational insights with significant clinical translation potential, offering
actionable insights to guide postoperative surveillance and adjuvant therapy decisions.
Several revisions should be made:
1.The term “nCRT” in 190 and “CMOR” in line 192 were not defined clearly.
2.The word "unsing" in line 142 may be incorrect, please check the spell.
3.It is recommended to shorten and simplify the introduction section appropriately.
Overall Assessment
Overall, this study demonstrates the prognostic value of IS in early-onset colorectal cancer using
a neural network model. Acceptance for publication is recommended with minor revisions.
Title: The prognostic value of Immunoscore in the early-onset colorectal cancer
Version: 1 Date: 01 Mar 2025
Reviewer's report:
Review
This study establishes a Chinese population-specific Immunoscore (IS) framework through
neural network-based quantification of CD3+/CD8+ tumor-infiltrating lymphocytes and
validates its prognostic significance in early-onset colorectal cancer (EOCRC). The results
demonstrate that IS effectively stratifies EOCRC patients by recurrence and metastasis risks,
independent of TNM staging. As EOCRC represents a rare but epidemiologically significant
subgroup with rising global incidence and aggressive clinicopathological features, this work fills
a critical knowledge gap by providing the first evidence of IS applicability in this underserved
population. By bridging the gap between immune profiling and precision oncology in EOCRC,
this work provides foundational insights with significant clinical translation potential, offering
actionable insights to guide postoperative surveillance and adjuvant therapy decisions.
Several revisions should be made:
1.The term “nCRT” in 190 and “CMOR” in line 192 were not defined clearly.
2.The word "unsing" in line 142 may be incorrect, please check the spell.
3.It is recommended to shorten and simplify the introduction section appropriately.
Overall Assessment
Overall, this study demonstrates the prognostic value of IS in early-onset colorectal cancer using
a neural network model. Acceptance for publication is recommended with minor revisions.
Please review this paper.
user
Title: The prognostic value of Immunoscore in the early-onset colorectal cancer
Version: 1 Date: 01 Mar 2025
Reviewer's report:
Review
This study establishes a Chinese population-specific Immunoscore (IS) framework through
neural network-based quantification of CD3+/CD8+ tumor-infiltrating lymphocytes and
validates its prognostic significance in early-onset colorectal cancer (EOCRC). The results
demonstrate that IS effectively stratifies EOCRC patients by recurrence and metastasis risks,
independent of TNM staging. As EOCRC represents a rare but epidemiologically significant
subgroup with rising global incidence and aggressive clinicopathological features, this work fills
a critical knowledge gap by providing the first evidence of IS applicability in this underserved
population. By bridging the gap between immune profiling and precision oncology in EOCRC,
this work provides foundational insights with significant clinical translation potential, offering
actionable insights to guide postoperative surveillance and adjuvant therapy decisions.
Several revisions should be made:
1.The term “nCRT” in 190 and “CMOR” in line 192 were not defined clearly.
2.The word "unsing" in line 142 may be incorrect, please check the spell.
3.It is recommended to shorten and simplify the introduction section appropriately.
Overall Assessment
Overall, this study demonstrates the prognostic value of IS in early-onset colorectal cancer using
a neural network model. Acceptance for publication is recommended with minor revisions.
assistant