Title: Bioinformatics identification of key microRNA-correlated genes associated with
hepatocellular carcinoma heterogeneity and prognosis
Version: 0 Date: 28 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The study uses data from the TCGA-LIGC dataset, which, while robust, may not be sufficiently
diverse or representative of the broader HCC patient population. Additional validation using
independent cohorts or multi-center data would strengthen the generalizability of the findings.
-Although the study identifies potential miRNA-mRNA interactions and predicts prognosis
based on bioinformatics, functional validation (e.g., experimental validation of miRNA
expression and target gene effects) is lacking. This is a critical step for confirming the biological
relevance of the identified biomarkers.
-While the study mentions the involvement of MIRcor genes in biological processes like
“neutrophil degranulation” and “carbohydrate metabolic process,” a deeper mechanistic
exploration of how these processes influence HCC progression is needed. Detailed mechanistic
studies, including pathway analysis and experimental evidence, would provide more clarity.
-While the study identifies a potential prognostic model, little is discussed about how this model
could be implemented in clinical practice. The transition from bioinformatics to practical use in
patient management, including potential therapeutic implications, is not fully explored.
-The interaction of MIRcor genes with the immune microenvironment is mentioned, but the
study does not delve deeply into this aspect. A more detailed exploration of how miRNA-mRNA
interactions modulate immune cells and immune-related pathways in HCC would make the
analysis more comprehensive.
-While the study thoroughly discusses the role of each gene in cancer biology, a deeper
mechanistic investigation into how these genes contribute to HCC pathogenesis is needed. For
example, the discussion could have explored how these genes interact with other oncogenic
pathways, tumor suppressor genes, or the tumor microenvironment at a molecular level.
-While the study points out the correlation between immune cells and the five prognostic genes,
a more detailed analysis of how immune cell infiltration contributes to HCC progression and
how the identified genes modulate this process would add depth to the discussion. Exploring
the specific immune cell types involved in the tumor immune response (e.g., T cells, dendritic
cells) could lead to more targeted therapeutic strategies.
-The discussion on fatty acid metabolism is insightful, but it remains somewhat underexplored
in terms of its direct connection to HCC prognosis and treatment. Given the growing interest
in metabolic reprogramming in cancer, further exploration into how fatty acid metabolism
specifically impacts HCC progression could be a valuable addition.
-While the study demonstrates the potential of the prognostic model, there is limited discussion
on how this model could be practically applied in clinical settings. More details on how this
model might be integrated into routine clinical practice, including how to use it alongside
existing clinical tools like AFP (alpha-fetoprotein), would provide a clearer path to translating
these findings into patient care.
-The study discusses the expression levels of the prognostic genes in HCC, but the underlying
mechanisms behind their regulation are not fully addressed. For example, are these genes
regulated by mutations, epigenetic changes, or post-translational modifications in HCC? These
aspects are essential for fully understanding their role in cancer progression.
Title: Bioinformatics identification of key microRNA-correlated genes associated with
hepatocellular carcinoma heterogeneity and prognosis
Version: 0 Date: 28 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The study uses data from the TCGA-LIGC dataset, which, while robust, may not be sufficiently
diverse or representative of the broader HCC patient population. Additional validation using
independent cohorts or multi-center data would strengthen the generalizability of the findings.
-Although the study identifies potential miRNA-mRNA interactions and predicts prognosis
based on bioinformatics, functional validation (e.g., experimental validation of miRNA
expression and target gene effects) is lacking. This is a critical step for confirming the biological
relevance of the identified biomarkers.
-While the study mentions the involvement of MIRcor genes in biological processes like
“neutrophil degranulation” and “carbohydrate metabolic process,” a deeper mechanistic
exploration of how these processes influence HCC progression is needed. Detailed mechanistic
studies, including pathway analysis and experimental evidence, would provide more clarity.
-While the study identifies a potential prognostic model, little is discussed about how this model
could be implemented in clinical practice. The transition from bioinformatics to practical use in
patient management, including potential therapeutic implications, is not fully explored.
-The interaction of MIRcor genes with the immune microenvironment is mentioned, but the
study does not delve deeply into this aspect. A more detailed exploration of how miRNA-mRNA
interactions modulate immune cells and immune-related pathways in HCC would make the
analysis more comprehensive.
-While the study thoroughly discusses the role of each gene in cancer biology, a deeper
mechanistic investigation into how these genes contribute to HCC pathogenesis is needed. For
example, the discussion could have explored how these genes interact with other oncogenic
pathways, tumor suppressor genes, or the tumor microenvironment at a molecular level.
-While the study points out the correlation between immune cells and the five prognostic genes,
a more detailed analysis of how immune cell infiltration contributes to HCC progression and
how the identified genes modulate this process would add depth to the discussion. Exploring
the specific immune cell types involved in the tumor immune response (e.g., T cells, dendritic
cells) could lead to more targeted therapeutic strategies.
-The discussion on fatty acid metabolism is insightful, but it remains somewhat underexplored
in terms of its direct connection to HCC prognosis and treatment. Given the growing interest
in metabolic reprogramming in cancer, further exploration into how fatty acid metabolism
specifically impacts HCC progression could be a valuable addition.
-While the study demonstrates the potential of the prognostic model, there is limited discussion
on how this model could be practically applied in clinical settings. More details on how this
model might be integrated into routine clinical practice, including how to use it alongside
existing clinical tools like AFP (alpha-fetoprotein), would provide a clearer path to translating
these findings into patient care.
-The study discusses the expression levels of the prognostic genes in HCC, but the underlying
mechanisms behind their regulation are not fully addressed. For example, are these genes
regulated by mutations, epigenetic changes, or post-translational modifications in HCC? These
aspects are essential for fully understanding their role in cancer progression.
Please review this paper.
user
Title: Bioinformatics identification of key microRNA-correlated genes associated with
hepatocellular carcinoma heterogeneity and prognosis
Version: 0 Date: 28 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The study uses data from the TCGA-LIGC dataset, which, while robust, may not be sufficiently
diverse or representative of the broader HCC patient population. Additional validation using
independent cohorts or multi-center data would strengthen the generalizability of the findings.
-Although the study identifies potential miRNA-mRNA interactions and predicts prognosis
based on bioinformatics, functional validation (e.g., experimental validation of miRNA
expression and target gene effects) is lacking. This is a critical step for confirming the biological
relevance of the identified biomarkers.
-While the study mentions the involvement of MIRcor genes in biological processes like
“neutrophil degranulation” and “carbohydrate metabolic process,” a deeper mechanistic
exploration of how these processes influence HCC progression is needed. Detailed mechanistic
studies, including pathway analysis and experimental evidence, would provide more clarity.
-While the study identifies a potential prognostic model, little is discussed about how this model
could be implemented in clinical practice. The transition from bioinformatics to practical use in
patient management, including potential therapeutic implications, is not fully explored.
-The interaction of MIRcor genes with the immune microenvironment is mentioned, but the
study does not delve deeply into this aspect. A more detailed exploration of how miRNA-mRNA
interactions modulate immune cells and immune-related pathways in HCC would make the
analysis more comprehensive.
-While the study thoroughly discusses the role of each gene in cancer biology, a deeper
mechanistic investigation into how these genes contribute to HCC pathogenesis is needed. For
example, the discussion could have explored how these genes interact with other oncogenic
pathways, tumor suppressor genes, or the tumor microenvironment at a molecular level.
-While the study points out the correlation between immune cells and the five prognostic genes,
a more detailed analysis of how immune cell infiltration contributes to HCC progression and
how the identified genes modulate this process would add depth to the discussion. Exploring
the specific immune cell types involved in the tumor immune response (e.g., T cells, dendritic
cells) could lead to more targeted therapeutic strategies.
-The discussion on fatty acid metabolism is insightful, but it remains somewhat underexplored
in terms of its direct connection to HCC prognosis and treatment. Given the growing interest
in metabolic reprogramming in cancer, further exploration into how fatty acid metabolism
specifically impacts HCC progression could be a valuable addition.
-While the study demonstrates the potential of the prognostic model, there is limited discussion
on how this model could be practically applied in clinical settings. More details on how this
model might be integrated into routine clinical practice, including how to use it alongside
existing clinical tools like AFP (alpha-fetoprotein), would provide a clearer path to translating
these findings into patient care.
-The study discusses the expression levels of the prognostic genes in HCC, but the underlying
mechanisms behind their regulation are not fully addressed. For example, are these genes
regulated by mutations, epigenetic changes, or post-translational modifications in HCC? These
aspects are essential for fully understanding their role in cancer progression.
assistant