Immune Biomarkers in Blood from Sarcoma Patients: A Pilot Study

Round 1

Reviewer 1 Report

The authors included substantial changes within the manuscript, covering my previous remarks and recommendation. Hence I recommend publication.

Author Response

Thank you for your comments. The suggested amendments have been made as suggested.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Munisamy et al. describe relative quantification of CD4+ T cells and regulatory T cells in newly diagnosed sarcoma patients (n=26). In a fraction (?) cytokine release (IL-17A, IFN-g, TNF, TGFB1) after stimulation of peripheral blood mononuclear (PBMCs) as well as plasma cytokine levels were studied. An additional qRT-PCR-based T cell marker gene panel was utilized to further characterize possible Th1/Th2/Th17 differentiation in another 5 PBMC samples from additional 5 soft tissue sarcoma patients.

A major limitation of the study is the heterogenicity of sarcoma entities. Also the authors decided to include pediatric sarcoma samples, which should be decribed in more detail... why? for which analysis exactly? And a subgroup analysis could be performed, separating pediatric and adult sarcoma results.

It is unclear, which tumor entities were used for which analyses. This must be added. I recommend a supplemental file/table summarizing all analyzed patients, including relative numbers of FlowCy experiements (CD4+/Treg), levels of cytokines in plasma and after PBMC stimulation, with further indication where T cell marker gene expression analysis was performed.

Another mandatory addition is the disease status of patients (localized/metastasized/systemic disease? bone marrow disease?). Especially a metastatic status to the bone marrow might influence CD4+ T cell levels as well as Treg levels, amongst many others. Furthermore, the range of age should be indicated in Table 1, as pediatric tumor entities are included.

Furthermore, it is unclear which blood cells were analyzed exactly. The authors talk about  peripheral blood leukocytes and PBMCs (used as synonym, as far as I understood the authots) but i did not find any description of the use of ficoll/bicoll density gradient separation by centrifugation. Please specify, as e.g. polymorphic granulocytes (and also PMN-MDSCs) might have been present in culture assays potentially suppressing T cell cytokine production.

I deeply agree with the authors that peripheral blood phenotypes of sarcoma patients are understudied. This analysis found that CD4+ T cell levels from analyzed sarcoma patients are lower than in controls. Also, there seems to be a decreased capacity of respective PBLs/PBMCs to secrete Th1-cytokines (TNF and IFN-g).

The qRT-PCR analyses are of minor importance in my opinion. They would be more meaningful, if CD4+ T cells were purified (e.g. via magnetic beads) before RNA was isolated, as other immune cell subsets might influence gene expression analysis.

Additional experiments should be performed to further characterize CD4+ T cell phenotypes (at least in a fraction of representative patients and controls)... this could be achieved by either intracellular staining of transcription factors (T-bet, GATA3, RORc) or preferentially cytokines (such as IFNg and IL-4) in CD4 T cells or culture experiments after stimulation with an extension of Th2 cytokines (e.g. IL-4, -5, -13).

Are data availabe also on relative CD8+ T cell  levels? A CD4/CD8 ratios also would be interesting.

The discussion should be more concise.

Please add/change within the text:

line 34/35: pediatric sarcomas are rapidly growing and highly metastatic tumors!!! also include reference

line 50/51: usually Bob Schreiber should be cited here... who first decribed immunoediting

line 114: mouse anti-human... the dash is missing

Paragraph 3.3 heading: --> rename e.g. Cytokine Production and plasma cytokine levels

line 233: other plasma cytokines, namely XXXX

Figure 3 y-axis: --> pg/mL??

line 280: in patients with metastatic disease compared to...

line 281: change few into a selection of

line 285: erase the first 'in' after the comma

section 283-313 write more concise

line 311-313: rephrase, the sentence does'nt make sense

line 379: erase the first 'have'

Clearly state the limitations in the study... cytokine production/gene expression analysis from all peripheral blood leukocytes? (also neutrophils, monocytes etc?).

Results from requested experiments should be discussed in section 314-361

Author Response

Thanks for your comments, please find point-by-point response in the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Munisamy et al described cytokine production and Treg occurrence in sarcoma patients’ peripheral blood samples compared to control samples. Overall the study lacks fundamental data and methodological knowledge and cannot be published in the current format. See Major and Minor Comments below.

Major:

Why do only focus on CD4+ T cells in your study and do not include CD8+ T cells? Would have been “easy” and valuable for your paper.

Table 1: Why have you used only male patients for qPCR? Gender!

FACS analysis: Enlarge your FACS panel on intracellular cytokine staining, there you can nicely gate on CD4 vs CD8 and further Th subsets. Also include more transcription factors (e.g. Tbet, RORgt) to define Th subsets in your Foxp3 panel. Which kit have you used to fix your cells for Foxp3 staning?

Figure 2: I wondered why you have so many orange lymphocytes in (d) if you gated them away in (b) on CD4+ T cells….
(f) % of T-reg cells  - total or parent CD4+CD25+?
Gating strategy. Do you obtain the same results if you gate first on CD4+ T cells and then CD25 (y axis) vs. Foxp3 (x axis) and gate on the double positive cells?

Cytokine Production: You just isolated PBLs and not sorted for CD4+ T cells – so with your stimulation you stimulate all lymphocytes from the blood and cannot distinguish which cell produced the cytokines in your 3-day culture. Might be CD8, or others
To define cytokines from CD4+ T cells you need to first isolate T cells and activate them in culture. After your FACS analysis you know you would expect between 20-30% CD4+ Tcells – the majority are other cell types!!

qRT-PCR: In general I have a problem how you proceeded with RNA samples. You isolated RNA from whole peripheral blood leukocytes and performed qPCR analysis, but you have all the other cell types still in your samples. For RNA isolation I think you should have used isolated CD4+ T cells to get a pure data set just for your cell type of interest without any noisy other cell types

Figure 4: How do you explain that RPL13A is a known housekeeping gene used in qRT-PCR and you have observed a two-fold downregulation?
You have no differences in FACS of Foxp3+ Tregs but in the qPCR Foxp3 is one of the genes downregulated more than two-fold – please explain!

Minor:

Line 18: (TNFa), interferon …

Line 57: delete in once

Line 58: reference to all Th subsets, Th21, Tfh … mention that there are more

Line 188: % calculation for 33 patients unreproducible (if 41 patients are 100% - 80,49% = 33 patients)

Table 1: normal ctrls – check font!

Table 2: maybe change order – start with most representative and end with lowest %

Line 229: There was no significant …

Line 231: normal controls (Figure 3).

Line 231: Plasma levels …tend to be lower … controls, but did not reach statistical significance.

Line 232: significant (p=0.275) (Figure 3).

Line 235: delete last sentence “The level of cytokines …. Shown in Figure 3”.

Figure 3 – Legend: describe also plasma samples – maybe separate bar chart

English needs to be edited!!

Author Response

Thanks for your comments, please find point-by-point response in the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

The manuscript by Sarmini Munisamy et al. presents an interesting study of the CD4+ T-cell population as well as some other biomarkers in a cohort of sarcoma patients. For the improvement of the study, some suggestions are added below:

Line 14. Host immune system is charged with. It should be ‘in charge of’.

Line 14. and eliminating cancers. ‘cancer cells’ should be more appropriate.

Line 18. Small erratum: … factor-alpha 17 (TNF-α) (comma) interferon-gamma (IFN-γ)

Line 16-19. Description of the study is a bit long, I suggest dividing it into two sentences (immune biomarkers and differentially regulated genes).

For the whole text. Leukocytes is more common than leucocytes.

Line 55. Starts explaining CD4+ T-cells subsets, then go to CTL and then comes back to Th (CD4+). I suggest reorder it, starting with CTL and following with all CD4+ T-cell subsets for better following.

Line 60. CD8+ T-cells (CTL): CTL has been already described.

Line 65. However, more advanced cancers – in? more advanced cancers…

Line 74. ‘This study aims to investigate the level of CD4+ T-cells (Th)’. I understand that it is referred to T-helper CD4+ T cells (or global CD4+ T cells named ‘Th’ now?). Should be clearly stated to about misunderstanding of the studied population.

Line 80. Tables 1 and 2 should be addressed here. I missed this information until I read it later.

Line 81 and Table 1. While groups present similar median age, study of children and adult patients might be of interest. Have the authors considered to study this biomarkers only in the children/adults?

Figure 2e and f. Numbers and letter are too small, font size should be increased.

Figure 2e and f. Plotting of individual patients inside each group is recommended.

In this regard, do the authors find different ‘clusters’ inside the groups control or sarcoma? The visualization of the data as group instead of individual dots impedes these observations.

Is there a correlation between levels of CD4+ and overall survival (or any other clinical feature) of the sarcoma patients? Deeper study of the sarcoma patients group would be of interest.

Line 219. Results show a significantly lower percentage of the CD4+ T-cells’. It should be lower percentage of the CD4+ subets inside T-cells, or similar. The authors are not measuring the % of CD4+ T cells in blood or a total numbers, they are studying the CD4+ subset inside T cells.

Results showing levels of general T cells in blood should be of interest.

Representation of Treg cells / T-lymphocytes (not only T-reg cells / CD4+ T-cells ) should be of interest.

Line 231. ‘Plasma levels of TGF-β1 in sarcoma patients was lower than the normal controls’. As stated in the text, this was not statistically significant, I suggest to write it as a trend.

Some figure legends refer to groups as Sarcoma and Control, while others refers to groups as CTRL and SARCOMA. It should be unified in the text.

In a similar way, figure 2 show bars from Control group with stripes while other Figure 3 show bars from Sarcoma group with stripes. Similar representation of the groups through the whole manuscript should be addressed for better follow up.

Statistics should be shown similarly in the two figures.

Figure 3. If data comes from each patient, visualization of individual dot plots in each group should be of interest.

Line 253. Reference to at least one of the STRING papers should be cited, as stated by the contributors: https://string-db.org/cgi/about?footer_active_subpage=references

Figure 4. Graph is too small to be read.

Line 261. ‘upregulated genes more than two folds’ sounds grammatically incorrect.

Figure 5. Cluster analysis in STRING might be not accurate and gives no substantial information. In STRING, when you apply the ‘kmeans clustering’, the network is clustered to a specified number of clusters: 3 in this case. But this is not calculated, it is chosen by the analyst. MCL clustering, in which the network is clustered to a specified "MCL inflation parameter", might be more useful. In any case, this division in clusters gives no relevant information.

Line 280. Patients with metastasis (or metastasic disease)

Line 283-286. Three sentences together, not easy to read, some grammar mistakes. I suggest dividing the ideas in shorter sentences to make the points more clear.

Some abbreviations like MDSCs, TAMs or ROS are defined but no used again.

Author Response

Thanks for your comments, please find point-by-point response in the attachment.

Author Response File: Author Response.pdf