Title: Discovery and Validation of Novel Protein Markers in Mucosa of Portal Hypertensive
Gastropathy
Version: 1 Date: 03 Mar 2021
Reviewer:  Oleksandr Petrenko
Reviewer's report:
This pilot study performed by Ying Zhu, Wen Xu, and colleagues illustrates the potential
of label-free proteomics to reveal perspective biomarkers in portal hypertensive gastropathy
with further validation by targeted high-resolution mass spectrometry. The application of an
unbiased proteomics approach produces high-throughput datasets with the potential to shed
light on undiscovered aspects of disease pathogenesis and to distinguish molecular targets with
translational potential.
The authors did impressive work on obtaining human samples, performing mass-spectrometry
experiments, and analyzing the produced data. The following points would be beneficial for the
manuscript and should be considered before publishing.
* Careful proofreading and correction of typos would improve the manuscript;
* After performing the gene set enrichment analysis, the differentially expressed proteins of two
sets (focal adhesion and vascular smooth muscle contraction) are reported. However, findings
associated with other top-ranked sets (for example, "protein digestion and absorption" and
"ECM-receptor interaction") are not discussed.
* The KEGG pathway analysis is discussed selectively, and many of the top-ranked pathways
which may be relevant for the disease are not addressed in the text.
* There are 18(17?) proteins selected for the targeted validation. However, nine of them were
not reported in the previous results (by the coding gene names): CSRP2, CPT1A, SORBS1,
ACSL3, TGFB1I1, MCAM, PDLIM7, TNS1, EFEMP1. This selection is either literature-based
selection or based on differentially expressed gene sets not discussed before. It is essential either
to validate all the top-ranked differentially expressed proteins and include them in the report (to
follow the unbiased approach of the workflow) or to separate the PRM validation and restructure
the manuscript accordingly to the literature-based target selection.
* While there is a clear picture of differentially expressed proteins between both gastropathy
groups and disease-free participants, the number of such proteins between two gastropathy
groups is not that huge. In this regard, either additional justification/explanation is required for
analyzing these cohorts separately or a more specific conclusion regarding the appropriateness
of such separation in further studies based on the proteomics findings.
* There are several inconsistencies throughout the test that should be concerned:
* In the section "2.1 Clinical sample information", it is stated that 15 gastric mucosa samples
were collected for this study. It is indicated in Figure 1, and indirectly in Table 1, that
29 participants underwent biopsies, and section "5.1 Clinical Samples" describes additional
individuals recruited for the PRM analysis. Hence, the first number requires correction.
* In the section "2.6 PRM analysis for protein quantification", it is stated that 18 proteins were
chosen for further study. Still, only 17 of them were quantified — without indicating the reason
for the "missing" protein. Furthermore, it is stated in the Discussion that only 17 proteins were
chosen. The first number should be explained better or corrected.
Several minor points would help to improve the perception of the manuscript:
* Table 1: it is recommended to add a row with the total number of patients per group.
* Figure 1: harmonize the groups' names in the upper and lower parts, for example, by writing
the full groups' names everywhere and specifying the difference between the gastropathy groups
in the description.
* Figure 2: while such visualization is appreciated, it is not directly connected to the manuscripts'
novelty, and therefore can be combined with another figure or attached as a supplementary
figure.
* Figure 3b: the words on the labels should be written separately.
* Figure 3c: it is more informative to label the top up-/downregulated proteins on the volcano
plots.
* Figure 4: Instead of labeling with accessions, it is better to provide protein (entry) names or
coding gene names so that they will be more human-readable. It can be done either instead of
accessions or as an additional column. Alternatively: to leave the labels only near the clusters
of the utmost interest.
* In the Methods section, I recommend mentioning the model of the mass spectrometer in
addition to the described settings;
* More detailed sample preparation for the parallel reaction monitoring is required, for example,
buffer composition since this method is crucial in the study's workflow.
* Mentioning the complete list of the R packages used for data analysis, including references
when applicable, is crucial for reproducibility. The approaches used for data normalization
should be discussed in the relevant section.
* Considering the novelty of the produced datasets and potential benefits to the field from re-
analyzing them or using them for further studies, authors are encouraged to consider publishing
them on a public repository, together with the code used to analyze them.
Title: Discovery and Validation of Novel Protein Markers in Mucosa of Portal Hypertensive
Gastropathy
Version: 1 Date: 03 Mar 2021
Reviewer:  Oleksandr Petrenko
Reviewer's report:
This pilot study performed by Ying Zhu, Wen Xu, and colleagues illustrates the potential
of label-free proteomics to reveal perspective biomarkers in portal hypertensive gastropathy
with further validation by targeted high-resolution mass spectrometry. The application of an
unbiased proteomics approach produces high-throughput datasets with the potential to shed
light on undiscovered aspects of disease pathogenesis and to distinguish molecular targets with
translational potential.
The authors did impressive work on obtaining human samples, performing mass-spectrometry
experiments, and analyzing the produced data. The following points would be beneficial for the
manuscript and should be considered before publishing.
* Careful proofreading and correction of typos would improve the manuscript;
* After performing the gene set enrichment analysis, the differentially expressed proteins of two
sets (focal adhesion and vascular smooth muscle contraction) are reported. However, findings
associated with other top-ranked sets (for example, "protein digestion and absorption" and
"ECM-receptor interaction") are not discussed.
* The KEGG pathway analysis is discussed selectively, and many of the top-ranked pathways
which may be relevant for the disease are not addressed in the text.
* There are 18(17?) proteins selected for the targeted validation. However, nine of them were
not reported in the previous results (by the coding gene names): CSRP2, CPT1A, SORBS1,
ACSL3, TGFB1I1, MCAM, PDLIM7, TNS1, EFEMP1. This selection is either literature-based
selection or based on differentially expressed gene sets not discussed before. It is essential either
to validate all the top-ranked differentially expressed proteins and include them in the report (to
follow the unbiased approach of the workflow) or to separate the PRM validation and restructure
the manuscript accordingly to the literature-based target selection.
* While there is a clear picture of differentially expressed proteins between both gastropathy
groups and disease-free participants, the number of such proteins between two gastropathy
groups is not that huge. In this regard, either additional justification/explanation is required for
analyzing these cohorts separately or a more specific conclusion regarding the appropriateness
of such separation in further studies based on the proteomics findings.
* There are several inconsistencies throughout the test that should be concerned:
* In the section "2.1 Clinical sample information", it is stated that 15 gastric mucosa samples
were collected for this study. It is indicated in Figure 1, and indirectly in Table 1, that
29 participants underwent biopsies, and section "5.1 Clinical Samples" describes additional
individuals recruited for the PRM analysis. Hence, the first number requires correction.
* In the section "2.6 PRM analysis for protein quantification", it is stated that 18 proteins were
chosen for further study. Still, only 17 of them were quantified — without indicating the reason
for the "missing" protein. Furthermore, it is stated in the Discussion that only 17 proteins were
chosen. The first number should be explained better or corrected.
Several minor points would help to improve the perception of the manuscript:
* Table 1: it is recommended to add a row with the total number of patients per group.
* Figure 1: harmonize the groups' names in the upper and lower parts, for example, by writing
the full groups' names everywhere and specifying the difference between the gastropathy groups
in the description.
* Figure 2: while such visualization is appreciated, it is not directly connected to the manuscripts'
novelty, and therefore can be combined with another figure or attached as a supplementary
figure.
* Figure 3b: the words on the labels should be written separately.
* Figure 3c: it is more informative to label the top up-/downregulated proteins on the volcano
plots.
* Figure 4: Instead of labeling with accessions, it is better to provide protein (entry) names or
coding gene names so that they will be more human-readable. It can be done either instead of
accessions or as an additional column. Alternatively: to leave the labels only near the clusters
of the utmost interest.
* In the Methods section, I recommend mentioning the model of the mass spectrometer in
addition to the described settings;
* More detailed sample preparation for the parallel reaction monitoring is required, for example,
buffer composition since this method is crucial in the study's workflow.
* Mentioning the complete list of the R packages used for data analysis, including references
when applicable, is crucial for reproducibility. The approaches used for data normalization
should be discussed in the relevant section.
* Considering the novelty of the produced datasets and potential benefits to the field from re-
analyzing them or using them for further studies, authors are encouraged to consider publishing
them on a public repository, together with the code used to analyze them.
Please review this paper.
user
Title: Discovery and Validation of Novel Protein Markers in Mucosa of Portal Hypertensive
Gastropathy
Version: 1 Date: 03 Mar 2021
Reviewer:  Oleksandr Petrenko
Reviewer's report:
This pilot study performed by Ying Zhu, Wen Xu, and colleagues illustrates the potential
of label-free proteomics to reveal perspective biomarkers in portal hypertensive gastropathy
with further validation by targeted high-resolution mass spectrometry. The application of an
unbiased proteomics approach produces high-throughput datasets with the potential to shed
light on undiscovered aspects of disease pathogenesis and to distinguish molecular targets with
translational potential.
The authors did impressive work on obtaining human samples, performing mass-spectrometry
experiments, and analyzing the produced data. The following points would be beneficial for the
manuscript and should be considered before publishing.
* Careful proofreading and correction of typos would improve the manuscript;
* After performing the gene set enrichment analysis, the differentially expressed proteins of two
sets (focal adhesion and vascular smooth muscle contraction) are reported. However, findings
associated with other top-ranked sets (for example, "protein digestion and absorption" and
"ECM-receptor interaction") are not discussed.
* The KEGG pathway analysis is discussed selectively, and many of the top-ranked pathways
which may be relevant for the disease are not addressed in the text.
* There are 18(17?) proteins selected for the targeted validation. However, nine of them were
not reported in the previous results (by the coding gene names): CSRP2, CPT1A, SORBS1,
ACSL3, TGFB1I1, MCAM, PDLIM7, TNS1, EFEMP1. This selection is either literature-based
selection or based on differentially expressed gene sets not discussed before. It is essential either
to validate all the top-ranked differentially expressed proteins and include them in the report (to
follow the unbiased approach of the workflow) or to separate the PRM validation and restructure
the manuscript accordingly to the literature-based target selection.
* While there is a clear picture of differentially expressed proteins between both gastropathy
groups and disease-free participants, the number of such proteins between two gastropathy
groups is not that huge. In this regard, either additional justification/explanation is required for
analyzing these cohorts separately or a more specific conclusion regarding the appropriateness
of such separation in further studies based on the proteomics findings.
* There are several inconsistencies throughout the test that should be concerned:
* In the section "2.1 Clinical sample information", it is stated that 15 gastric mucosa samples
were collected for this study. It is indicated in Figure 1, and indirectly in Table 1, that
29 participants underwent biopsies, and section "5.1 Clinical Samples" describes additional
individuals recruited for the PRM analysis. Hence, the first number requires correction.
* In the section "2.6 PRM analysis for protein quantification", it is stated that 18 proteins were
chosen for further study. Still, only 17 of them were quantified — without indicating the reason
for the "missing" protein. Furthermore, it is stated in the Discussion that only 17 proteins were
chosen. The first number should be explained better or corrected.
Several minor points would help to improve the perception of the manuscript:
* Table 1: it is recommended to add a row with the total number of patients per group.
* Figure 1: harmonize the groups' names in the upper and lower parts, for example, by writing
the full groups' names everywhere and specifying the difference between the gastropathy groups
in the description.
* Figure 2: while such visualization is appreciated, it is not directly connected to the manuscripts'
novelty, and therefore can be combined with another figure or attached as a supplementary
figure.
* Figure 3b: the words on the labels should be written separately.
* Figure 3c: it is more informative to label the top up-/downregulated proteins on the volcano
plots.
* Figure 4: Instead of labeling with accessions, it is better to provide protein (entry) names or
coding gene names so that they will be more human-readable. It can be done either instead of
accessions or as an additional column. Alternatively: to leave the labels only near the clusters
of the utmost interest.
* In the Methods section, I recommend mentioning the model of the mass spectrometer in
addition to the described settings;
* More detailed sample preparation for the parallel reaction monitoring is required, for example,
buffer composition since this method is crucial in the study's workflow.
* Mentioning the complete list of the R packages used for data analysis, including references
when applicable, is crucial for reproducibility. The approaches used for data normalization
should be discussed in the relevant section.
* Considering the novelty of the produced datasets and potential benefits to the field from re-
analyzing them or using them for further studies, authors are encouraged to consider publishing
them on a public repository, together with the code used to analyze them.
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