Title: Comprehensive Evaluation of Immunological Attributes and Immunotherapy Responses
of Positive T Cell Function Regulators in Colorectal Cancer
Version: 1 Date: 22 Jun 2024
Reviewer's report:
This study developed a PTFR risk model based on differentially expressed genes (DEGs),
evaluating its predictive ability for survival outcomes, clinical variables, TME characteristics,
tumor mutations, microsatellite instability (MSI), Cell Stem Cell (CSC) index, and responses
to chemotherapy, targeted therapy, and immunotherapy. The PTFR risk model demonstrated
robust performance across various facets of CRC, including immune cell composition,
HLA expression, immune checkpoint expression, mutation profiles, CSC characteristics, and
immunotherapeutic efficacy. Overall, this study provides valuable insights into PTFRs in CRC
prognosis and their potential utility in personalized treatment strategies, suggesting further
validation in larger cohorts or clinical trials to strengthen the findings and clarify their clinical
implications. Additionally, more detailed mechanistic studies could elucidate the specific roles
of PTFRs in shaping the TME and modulating therapeutic responses.
However, the cutoff values for the two subtypes across different datasets may not be consistent.
The authors should clearly define the cutoff values for both subtypes. Additionally, it is essential
to validate the authors' conclusions using an independent validation dataset.
Title: Comprehensive Evaluation of Immunological Attributes and Immunotherapy Responses
of Positive T Cell Function Regulators in Colorectal Cancer
Version: 1 Date: 22 Jun 2024
Reviewer's report:
This study developed a PTFR risk model based on differentially expressed genes (DEGs),
evaluating its predictive ability for survival outcomes, clinical variables, TME characteristics,
tumor mutations, microsatellite instability (MSI), Cell Stem Cell (CSC) index, and responses
to chemotherapy, targeted therapy, and immunotherapy. The PTFR risk model demonstrated
robust performance across various facets of CRC, including immune cell composition,
HLA expression, immune checkpoint expression, mutation profiles, CSC characteristics, and
immunotherapeutic efficacy. Overall, this study provides valuable insights into PTFRs in CRC
prognosis and their potential utility in personalized treatment strategies, suggesting further
validation in larger cohorts or clinical trials to strengthen the findings and clarify their clinical
implications. Additionally, more detailed mechanistic studies could elucidate the specific roles
of PTFRs in shaping the TME and modulating therapeutic responses.
However, the cutoff values for the two subtypes across different datasets may not be consistent.
The authors should clearly define the cutoff values for both subtypes. Additionally, it is essential
to validate the authors' conclusions using an independent validation dataset.
Please review this paper.
user
Title: Comprehensive Evaluation of Immunological Attributes and Immunotherapy Responses
of Positive T Cell Function Regulators in Colorectal Cancer
Version: 1 Date: 22 Jun 2024
Reviewer's report:
This study developed a PTFR risk model based on differentially expressed genes (DEGs),
evaluating its predictive ability for survival outcomes, clinical variables, TME characteristics,
tumor mutations, microsatellite instability (MSI), Cell Stem Cell (CSC) index, and responses
to chemotherapy, targeted therapy, and immunotherapy. The PTFR risk model demonstrated
robust performance across various facets of CRC, including immune cell composition,
HLA expression, immune checkpoint expression, mutation profiles, CSC characteristics, and
immunotherapeutic efficacy. Overall, this study provides valuable insights into PTFRs in CRC
prognosis and their potential utility in personalized treatment strategies, suggesting further
validation in larger cohorts or clinical trials to strengthen the findings and clarify their clinical
implications. Additionally, more detailed mechanistic studies could elucidate the specific roles
of PTFRs in shaping the TME and modulating therapeutic responses.
However, the cutoff values for the two subtypes across different datasets may not be consistent.
The authors should clearly define the cutoff values for both subtypes. Additionally, it is essential
to validate the authors' conclusions using an independent validation dataset.
assistant