Tomentosin a Sesquiterpene Lactone Induces Antiproliferative and Proapoptotic Effects in Human Burkitt Lymphoma by Deregulation of Anti- and Pro-Apoptotic Genes

Round 1

Reviewer 1 Report

In this manuscript, Virdis et al studied the anticancer features and potential mechanisms of tomentosin on Burkitt’s lymphoma (BL) Raji cell line. The authors found that tomentosin induced cell cycle arrest and cell apoptosis on Raji cells and a microarray gene expression analysis identified 75 deregulated genes in tomentosin-treated Raji cells. Tomentosin-treatment in BL cells induces downregulation of genes enriched in immune-system pathways, PI3K/AKT and JAK/STAT pathways and anti-apoptosis. Overall, the manuscript was written nicely. But the experimental design was too simple. The results/conclusion from microarray gene expression analysis need to be confirmed further.

Major comments:

1.     Were the in vivo anti-tumor effects of tomentosin on BL studies tested using mouse models? Such as improving the survival of BL xenografted mice?

2. For cytotoxicity, cell cycle, apoptotic assays, the authors need to test the effect of tomentosin on other BL cell lines and primary BL cells if possible to make a strong conclusion.
3. Did the authors confirm some of the up-regulated and down-regulated genes (especially the ones mentioned in the discussion) and the changes of NF-kappa B, PI3K/AKT, and JAK/STAT signaling pathway from the gene expression profiling using other methods such as real-time PCR and western blots?
4. Did the author confirm the up-regulated and down-regulated genes and the changed pathways in Raji by tomentosin treatment in another BL cell line?

 

Minor comments

1. In page 4 line 145, the sentence ‘p values <0.05, using….” was not finished.

 

Author Response

We are grateful for your consideration of this manuscript, and we thank the reviewer who have permitted us to improve the quality of our work with their suggestions. All the comments we received on this study have been considered and we have addressed all of them in our point-by-point reply below.

 

-Were the in vivo anti-tumor effects of tomentosin on BL studies tested using mouse models? Such as improving the survival of BL xenografted mice?

We are grateful for the comment, although our current experiments were concentrated in in vitro, our prospective investigations will include in vivo experiments to analyze the molecular mechanisms by which tomentosin induce pharmacologic effects in Burkitt lymphoma, supported by the gene expression profile obtained by Raji cell lines Tomentosin-treatment. In fact, no data are presented in the literature on Tomentosin pharmacologic effects in in vivo experiments on cancer.

-For cytotoxicity, cell cycle, apoptotic assays, the authors need to test the effect of tomentosin on other BL cell lines and primary BL cells if possible to make a strong conclusion.

-Did the author confirm the up-regulated and down-regulated genes and the changed pathways in Raji by tomentosin treatment in another BL cell line.

-Did the authors confirm some of the up-regulated and down-regulated genes (especially the ones mentioned in the discussion) and the changes of NF-kappa B, PI3K/AKT, and JAK/STAT signaling pathway from the gene expression profiling using other methods such as real-time PCR and western blots?

-Did the author confirm the up-regulated and down-regulated genes and the changed pathways in Raji by tomentosin treatment in another BL cell line.

We are grateful for the comments, however based on the extreme heterogeneity of cell lines and on our prospective investigations in in vivo experiments, our priority is to directly analyze the molecular mechanisms of tomentosin and confirm the up-regulated and down-regulated genes and the changed pathways with in vivo experiments. Considering the limitation of the in vitro experiments we added a phrase at the endo of the discussion (see pag. 10).

-In page 4 line 145, the sentence ‘p values <0.05, using….” was not finished.

Thanks for the reviewer’s comment. The phrase had to end at p value <0.05. We corrected it.

 

Reviewer 2 Report

The MS entitled "Tomentosin a sesquiterpene lactone induces antiproliferative and proapoptotic effects in human Burkitt lymphoma by deregulation of anti- and pro-apoptotic genes” is well written and presents a substantial amount of very interesting data. However, there is some points that need to be clarified or improved.

1. It is better to reduce the number of key words and check based on mesh term.
2. Provide abbreviation list.
3. Write Running title

Author Response

We are grateful for your consideration of this manuscript, and we thank the reviewer who have permitted us to improve the quality of our work with their suggestions. All the comments we received on this study have been considered and we have addressed all of them in our point-by-point reply below.

-It is better to reduce the number of key words and check based on mesh term.

Thanks for the reviewer’s comment. We reduced the number of key words: Tomentosin; Burkitt lymphoma; BCL2A1; CDKN1A; PMAIP1.

 -Provide abbreviation list.

Thanks for the reviewer’s comment. We added an abbreviation list at the end of manuscript.

 -Write Running title

Thanks for the reviewer’s comment. We added the following running title in the manuscript: Tomentosin deregulates anti- and pro-apoptotic genes in Burkitt Lymphoma.

Reviewer 3 Report

The proposed results are not particularly new (the authors have already published on the subject in Tumor biology in 2020 and the antiproliferative and proapoptotic effects of tomentosine have been shown by others in other cell types) but the manuscript is written in professional language and the design research is appropriate. There is an error in the introduction L.38 "which are all marked by the chromosomal translocation t(8;14)". In fact, this is the main translocation but there are two others t(8;22) and t(2;8). My main concern is that the statistical analysis should be improved.If the authors do not follow the sample size guidelines for parametric tests (e.g., n>20), they should use a nonparametric test.  When you have a very small sample size, you may not even be able to test the distribution of your data because tests of distribution will not have sufficient power to provide meaningful results. Thus, ANOVA should be replaced by Kruskal and Wally.    In addition, it is sometimes difficult to understand what is being compared to what and what is significant, as in Figures 1, 2 and 3. So, here my comments on this paper.

Author Response

We are grateful for your consideration of this manuscript, and we thank the reviewer who have permitted us to improve the quality of our work with their suggestions. All the comments we received on this study have been considered and we have addressed all of them in our point-by-point reply below.

-There is an error in the introduction L.38 "which are all marked by the chromosomal translocation t(8;14)". In fact, this is the main translocation but there are two others t(8;22) and t(2;8).

We are grateful for the comment, and we agree with the reviewer’s suggestion. We added the translocation variants in the introduction section (pag. 1, lane 41).

-My main concern is that the statistical analysis should be improved. If the authors do not follow the sample size guidelines for parametric tests (e.g., n>20), they should use a nonparametric test.  When you have a very small sample size, you may not even be able to test the distribution of your data because tests of distribution will not have sufficient power to provide meaningful results. Thus, ANOVA should be replaced by Kruskal and Wally.   

Thanks for the reviewer’s comment. We modified the test accordingly (pag.4 lanes 147-150).

-In addition, it is sometimes difficult to understand what is being compared to what and what is significant, as in Figures 1, 2 and 3.

Thanks for the reviewer’s comment. We modified the figure legends accordingly.

Round 2

Reviewer 1 Report

The authors answered all questions raised by the reviewers properly.

Author Response

The authors answered all questions raised by the reviewers properly.

The reviewer has not added any comments to reply to.

Reviewer 3 Report

I would like to thank the authors for taking my comments into consideration. I just have one more request, I still find it difficult to understand what is being compared in the figures in terms of statistics. For example, figure 1 is only the 50 dose sinificant compared to the control? In figure 2, are all doses significant compared to the control?
You can take a look at figure 3 of this paper published in elife recently to see what I mean: https://elifesciences.org/articles/65068

Translated with www.DeepL.com/Translator (free version)

Author Response

-I would like to thank the authors for taking my comments into consideration. I just have one more request, I still find it difficult to understand what is being compared in the figures in terms of statistics. For example, figure 1 is only the 50-dose significant compared to the control? In figure 2, are all doses significant compared to the control? You can take a look at figure 3 of this paper published in elife recently to see what I mean: https://elifesciences.org/articles/65068

Thanks for the reviewer’s comment. For what concerns the questions regarding the statistics in Figure 1 and 2, here is the point. Figure 1: we applied the Kruskal-Wallis H Test (or Kruskal-Wallis ANOVA test) on all the RLU values from all samples at all the concentrations. Specifically: RLU values were grouped based on the compound concentration. So, there are 7 groups (untreated, 50 µM, 25 µM, 12.5 µM, 6.25 µM, 3.12 µM, 1.56 µM or 0.8 µM), 3 samples in each group. Then, we applied Kruskal-Wallis to all the groups. Our purpose was to determine if there are statistically significant differences between all the groups. If yes, it means that at least one concentration had an effect. If no, it means that the compound had no effects at all. We didn’t want to test if each concentration of the compound has an effect versus the untreated samples since we thought this was not the proper way to identify minimum concentration at which the compound has an effect (we had also to apply for multivariate analysis). However, we tested numerous concentrations to calculate IC50 with confidence interval, which is the best way to determine concentration at which the compound has an effect. So, the stars next to 50 µM dose, blue line, refers to the p-value of the entire test, which refers to all the RLU samples. We did the same on all the GFI values. So, the stars next to 50 µM dose, red line, refers to the p-value of the Kruskal-Wallis, testing all the concentrations together. The same for Figure 2. Each star in each graph refers to all the samples of that graph, to see if caspase is activated at least in one of the doses.