Title: Deciphering the Role of KLRB1: A Novel Prognostic Indicator in Hepatocellular
Carcinoma
Version: 0 Date: 13 May 2024
Reviewer's report:
In this manuscript the authors investigate in silico the role of KLRB1-CD161 in published HCC
datasets (TCGA and scRNASeq datasets). They then perform an analysis of CD161 expression
via FACS on HCC patients undergoing resection and during follow up.
They observe a correlation of KLRB1 expression activating immune cell signatures in the TCGA
dataset fitting to  single-cell datawith KLRB1 expression in NK and T cells within HCC TME.
Their clinical analysis  showed reduced KLRB1 expression on NK and T cells in HCC patients
compared to health individuals, with lower expression levels linked to higher recurrence rates
and  reduced survival.
Overall the study is largely descriptive and finds associations of relapse or survival with CD161.
However, conclusions remain limited and the cellular correlates of CD161 expression remain
unexplored.
Major criticism
There is no further phenotypic and functional analysis in the study with respect to the two
major T cell populations expressing CD161,  Tc17 cells and MAIT cells.  It remains unclear if
confounders that could explain the difference in CD161 expression are connected to risk factors
of HCC per se. In the FACS data which was newly generated in this work, differences in CD161
expression between groups appear small but significant. An optimized cutoff effect of CD161
expression is calculated for CD8 and NK cells using X-tile 3.6.1 software.  This categorizes
the expression of KLRB1 on CD8+ T cells and NK cells into high and low expression groups.
Subsequently, KLRB1 expression levels below 17.2% on CD8+ T cells and 32.4% on NK cells
were classified as low expression, while levels above these thresholds were designated as high
expression. This is essentially generating optimized cutoffs for stratification but there is no
biologic interpretation why these cutoffs would be used and why different cutoffs for CD8 T
cells and NK cells would be used. At the very least, this needs to be reproduced in a validation
cohort.
Title: Deciphering the Role of KLRB1: A Novel Prognostic Indicator in Hepatocellular
Carcinoma
Version: 0 Date: 13 May 2024
Reviewer's report:
In this manuscript the authors investigate in silico the role of KLRB1-CD161 in published HCC
datasets (TCGA and scRNASeq datasets). They then perform an analysis of CD161 expression
via FACS on HCC patients undergoing resection and during follow up.
They observe a correlation of KLRB1 expression activating immune cell signatures in the TCGA
dataset fitting to  single-cell datawith KLRB1 expression in NK and T cells within HCC TME.
Their clinical analysis  showed reduced KLRB1 expression on NK and T cells in HCC patients
compared to health individuals, with lower expression levels linked to higher recurrence rates
and  reduced survival.
Overall the study is largely descriptive and finds associations of relapse or survival with CD161.
However, conclusions remain limited and the cellular correlates of CD161 expression remain
unexplored.
Major criticism
There is no further phenotypic and functional analysis in the study with respect to the two
major T cell populations expressing CD161,  Tc17 cells and MAIT cells.  It remains unclear if
confounders that could explain the difference in CD161 expression are connected to risk factors
of HCC per se. In the FACS data which was newly generated in this work, differences in CD161
expression between groups appear small but significant. An optimized cutoff effect of CD161
expression is calculated for CD8 and NK cells using X-tile 3.6.1 software.  This categorizes
the expression of KLRB1 on CD8+ T cells and NK cells into high and low expression groups.
Subsequently, KLRB1 expression levels below 17.2% on CD8+ T cells and 32.4% on NK cells
were classified as low expression, while levels above these thresholds were designated as high
expression. This is essentially generating optimized cutoffs for stratification but there is no
biologic interpretation why these cutoffs would be used and why different cutoffs for CD8 T
cells and NK cells would be used. At the very least, this needs to be reproduced in a validation
cohort.
Please review this paper.
user
Title: Deciphering the Role of KLRB1: A Novel Prognostic Indicator in Hepatocellular
Carcinoma
Version: 0 Date: 13 May 2024
Reviewer's report:
In this manuscript the authors investigate in silico the role of KLRB1-CD161 in published HCC
datasets (TCGA and scRNASeq datasets). They then perform an analysis of CD161 expression
via FACS on HCC patients undergoing resection and during follow up.
They observe a correlation of KLRB1 expression activating immune cell signatures in the TCGA
dataset fitting to  single-cell datawith KLRB1 expression in NK and T cells within HCC TME.
Their clinical analysis  showed reduced KLRB1 expression on NK and T cells in HCC patients
compared to health individuals, with lower expression levels linked to higher recurrence rates
and  reduced survival.
Overall the study is largely descriptive and finds associations of relapse or survival with CD161.
However, conclusions remain limited and the cellular correlates of CD161 expression remain
unexplored.
Major criticism
There is no further phenotypic and functional analysis in the study with respect to the two
major T cell populations expressing CD161,  Tc17 cells and MAIT cells.  It remains unclear if
confounders that could explain the difference in CD161 expression are connected to risk factors
of HCC per se. In the FACS data which was newly generated in this work, differences in CD161
expression between groups appear small but significant. An optimized cutoff effect of CD161
expression is calculated for CD8 and NK cells using X-tile 3.6.1 software.  This categorizes
the expression of KLRB1 on CD8+ T cells and NK cells into high and low expression groups.
Subsequently, KLRB1 expression levels below 17.2% on CD8+ T cells and 32.4% on NK cells
were classified as low expression, while levels above these thresholds were designated as high
expression. This is essentially generating optimized cutoffs for stratification but there is no
biologic interpretation why these cutoffs would be used and why different cutoffs for CD8 T
cells and NK cells would be used. At the very least, this needs to be reproduced in a validation
cohort.
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