X or Y Cancer: An Extensive Analysis of Sex Differences in Lung Adenocarcinoma

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Although the authors have attempted to answer to all the point of the review, there are still some points that need further clarification.

1) The authors should provide a supplementaty table with the list of the name of 161 DEG together with fold change and p-value obtained by EdgeR analysis.

2) The authors stated in their rebuttal report and in the new version of the manuscript that GSEA was perfomed using HumanMsigDB. However, gene sets name reported in Table 1 does not to resemble the ones present in the MsigDB (https://www.gsea-msigdb.org/gsea/msigdb/human/genesets.jsp). Did the author grouped enriched gene sets in larger categories (e.g. cell cycle)? If yes, the authors must clarify this point otherwise they should report the exact names of enriched gene sets. Moreover, the authors should provide a supplementary table reporting the name of enriched gene set together with the FDR q-value and the NES.

Author Response

We appreciate the time and effort that you have dedicated to providing your valuable feedback on our manuscript.

We are grateful for the insightful comments and have been able to incorporate changes to reflect your suggestions.  We have highlighted the changes within the manuscript and uploaded a new version for the supplementary file with the required information.

1)The authors should provide a supplementaty table with the list of the name of 161 DEG together with fold change and p-value obtained by EdgeR analysis.

We added the information in supplementary table 3 and have also mentioned it in the text of the manuscript.

2) The authors stated in their rebuttal report and in the new version of the manuscript that GSEA was perfomed using HumanMsigDB. However, gene sets name reported in Table 1 does not to resemble the ones present in the MsigDB (https://www.gsea-msigdb.org/gsea/msigdb/human/genesets.jsp). Did the author grouped enriched gene sets in larger categories (e.g. cell cycle)? If yes, the authors must clarify this point otherwise they should report the exact names of enriched gene sets. Moreover, the authors should provide a supplementary table reporting the name of enriched gene set together with the FDR q-value and the NES.

We added supplementary table 4 and supplementary table 5 and changed the description in the manuscript (highlighted lines 281-284) to best reflect our approach.  

As already described in our methods section our approach to identifying the biological interpretation of our DEGs included GSEA, ShinyGO and literature i.e. our previously grouped sets (lines 169-173). 

Initially, we resorted to GSEA with all our 20,501 genes for preliminary analysis; it was the source for the analysis to follow - to try and analyse differences between males and females. It did provide a general picture showing different expression between females and males. Therefore, we then collected all the genes from all the enriched genesets (FDR q-value <0.25 as reported significant by GSEA) and found around 11,120 enriched genes for males and females. 

Then we identified the mutual genes with those differentially expressed from EdgeR. This lead us to confirming differences in metabolism and immune responses. We then proceeded to use our already grouped enriched gene sets regarding Warburg effect and proliferation (as you inferred) which we use for our other papers including 10.3389/fcell.2020.592616.  

Finally, the combined analysis from GSEA and EdgeR identified genes  to link these DEGs with molecular pathways and functional categories to understand the difference they contribute to carcinogenesis in LUAD between males and females and provide a bigger picture (figure 8). We used ShinyGo and have uploaded table 4 in the supplementary with the Enrichment FDR, Fold Enrichment, ShinyGo downloads various pathway data obtained from MSigDB-we included Humans only. 

Regarding ARH signalling pathway, it is associated with xenobiotic metabolism so we did think they will be linked and of importance therefore we used all gene ontology sets(including cc, mf, bp, wp) from Human gensets from MSigdb to identify them such as Human Gene Set: WP_2586_ARYL_HYDROCARBON_RECEPTOR_PATHWAY. 

 

 

Reviewer 2 Report (Previous Reviewer 2)

I don't have additional comments

Author Response

Thank you very much, we appreciate the time and effort that you  have dedicated to our manuscript.

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

In the submitted article entitled “X Or Y Cancer: An Extensive Analysis of Sex Differences in Lung Adenocarcinoma”, the authors carried out an in silico analysis using TGCA-LUAD dataset and identified several sex-related molecular differences in lung adenocarcinoma. However,  the data presented seems preliminary and lacks the support of proper statistical tests in key point of the work.

 Major Concerns:

1) In the first part of the paper (Figure 1 and 2) the authors reported 161 differentially expressed genes (DEG), some of which were encoded on sex chromosomes. However, no statistical test was performed to define the genes that are DEG. This is problematic since all the article findings were mainly based on this analysis.

2) Table 1 reports a selection of pathways significant enriched in LUAD cohort. This analysis should be supported by statistical significance. The authors could for example perform GSEA analysis to identify those gene signatures that are enriched between male and female.

Minor Concerns:

1)   It seems there is a lack of references. For instance, in line 57-79 the references should be properly included.

2)   The discussion section is more suitable for a review article rather than a research article. This part should be strongly reduced.

3)   Figures presented in the paper lack proper legends.

4)    A new version of Figure 7 that summarizes all sex-related molecular differences in LUAD would be more useful for the readers rather than focusing only at T cell receptor signaling.

 

Author Response

We are grateful for the insightful comments on our paper and have been able to rewrite the manuscript to incorporate changes to reflect the suggestions provided. We have highlighted the changes within the manuscript. Below is a point-by-point response to the comments.

 

1) In the first part of the paper (Figure 1 and 2) the authors reported 161 differentially expressed genes (DEG), some of which were encoded on sex chromosomes. However, no statistical test was performed to define the genes that are DEG. This is problematic since all the article findings were mainly based on this analysis.

Statistical tests have been performed using EdgeR as previously described in detail  in the material and method section. We further added it to the “statistical analysis section” line 188. Additionally, to further clarify this, we have added a workflow (figure 1) with this information and we also added an MD plot in the supplementary and more information in the Results section lines 202-217.

 

2) Table 1 reports a selection of pathways significant enriched in LUAD cohort. This analysis should be supported by statistical significance. The authors could for example perform GSEA analysis to identify those gene signatures that are enriched between male and female.

 

You are right we missed on mentioning that GSEA was also used in initial analysis performed to select gene sets (cutting edge) showing statistically significant expression differentitation, we added in the lines 159-161. GSEA was used to determine whether the identified DEGs showed significant functions between the patient subgroups using all Human MSigDB ( Molecular Signatures Database ) gene set collection.

However, as addressed in point 1 all genes have been statistically validated using EdgeR: Benjamini-Hochberg (BH) method on the p-values <0.05 was used to control the false discovery rate (FDR), and generalized linear model glmFit to minimise error function were used to determine differential expression.

 

Minor Concerns:

1) It seems there is a lack of references. For instance, in line 57-79 the references should be properly included.

You are right we had to change the formatting of the references from () to [] and might’ve accidentally deleted it but we added it again.

 

2)   The discussion section is more suitable for a review article rather than a research article. This part should be strongly reduced.

We have reduced it by over a 1000 words.

 

3)   Figures presented in the paper lack proper legends.

We agree and we have fixed it.

 

4)   A new version of Figure 7 that summarizes all sex-related molecular differences in LUAD would be more useful for the readers rather than focusing only at T cell receptor signaling.

There was a “graphical abstract” that we have merged as part of the discussion (figure8) line 599.

Reviewer 2 Report

Lung cancer remains a significant clinical challenge and a cancer with a poor prognosis. In recent years, a large number of new molecularly targeted drugs have been developed and knowledge of the biology of this cancer has increased significantly.

Therefore, the topic addressed by the authors of this manuscript is very important.

The data presented are interesting. However, I have one general comment - do the authors see a practical use of the results obtained and the possibility of reducing the risk of cancer by modifying environmental factors? Including diet, use of hormonal therapies? Other factors?

I also suggest moving the "Methods" section to the beginning of the manuscript (before the "Results" section)

 

 

Author Response

We are grateful for the insightful comments on our paper.

Thank you so much for your kind words.

In our opinion, we know that diet and hormonal status affects cancers like colorectal cancer or hormonal dependent tissue cancer (BRCA and PRAD). But as we can also see from our results it also seems to affect LUAD progression. We do hope in the future we would be able to test the obtained data, taking into account all environmental factors which will hopefully emphasise and show the need for personalised medicine to optimise anticancer therapies.

 

Regarding risk factors, there are already a number of papers published about environmental factors affecting cancer susceptibility, however, regarding differences between males and females no strong evidence is known yet about lung cancer. In lung cancer data is limited probably because the extensively studied risk factors include smoking and pollution and factors like diet or physiological factors maybe additional contributors which we preliminary tried identifying in our presented study. However, we don’t see any strong evidence as risk factors but rather a direct association with cancer progression and prognosis.

We have also moved the methods section to follow the results section as recommended.