Comprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance

Round 1

Reviewer 1 Report

In this manuscript, Soledvilla and coll, investigated the metabolomic profile of NET patients as compared to the one of non-cancer patients, through bioinformatic tools.

Overall, the work presented here, is very interesting and I have to congratulate the authors for these consequent,  new and elegant datas. It also paves the way for further studies deciphering new signaling pathways of interest in the field of NETs

Author Response

In this manuscript, Soledvilla and coll, investigated the metabolomic profile of NET patients as compared to the one of non-cancer patients, through bioinformatic tools.

Overall, the work presented here, is very interesting and I have to congratulate the authors for these consequent, new and elegant datas. It also paves the way for further studies deciphering new signaling pathways of interest in the field of NETs

We are incredibly grateful to the Reviewer1 for his/her positive and encouraging comments on our work. No further changes to the manuscript were requested by this reviewer.   

Reviewer 2 Report

The manuscript is very well written presenting valuable concepts and clinically relevant data. However, the below proposed revision may further increase visibility and overall quality of the publication.

1. Keywords might be extended to increase visibility of this important publication to multi-professional groups. Following items could be added: molecular pathways, machine learning, disease modelling
2. The title would provide more attractive message, if reconsidered as  "Comprehensive plasma metabolomic profile of patients..."
3. In the "Discussion" sub-titles could be used for the "Study limitations", "Study advantages", "Outlook".
4. Specifically for the "Outlook", the statement might be extended regarding added value of "multi-omics", if metabolomic profile would be combined with complementary analytical approaches in plasma such as cell-free nucleic acids profiling that might be particularly useful for early diagnostics and patient stratification followed by targeted treatment. Below noted reference might be helpful to present corresponding concept for the outlook:                                                                                                     - Torres Crigna A et al. Cell-Free Nucleic Acid Patterns in Disease Prediction and Monitoring – Hype or Hope? 2020. doi: 10.1007/s13167-020-00226-x. 

Author Response

REVIEWER  2

The manuscript is very well written presenting valuable concepts and clinically relevant data. However, the below proposed revision may further increase visibility and overall quality of the publication.

1. Keywords might be extended to increase visibility of this important publication to multi-professional groups. Following items could be added: molecular pathways, machine learning, disease modelling

Following the reviewer’s suggestion, we have included the recommended additional terms in the Keywords section to increase the visibility of our work.

2. The title would provide more attractive message, if reconsidered as "Comprehensive plasma metabolomic profile of patients..."

We have renamed the title following the reviewer’s suggestion to provide a more attractive message to the readers.

3. In the "Discussion" sub-titles could be used for the "Study limitations", "Study advantages", "Outlook".

Following the journal instructions for original work, no subtitles have been added to the Discussion section

4. Specifically for the "Outlook", the statement might be extended regarding added value of "multi-omics", if metabolomic profile would be combined with complementary analytical approaches in plasma such as cell-free nucleic acids profiling that might be particularly useful for early diagnostics and patient stratification followed by targeted treatment. Below noted reference might be helpful to present corresponding concept for the outlook:                                                                                                     - Torres Crigna A et al. Cell-Free Nucleic Acid Patterns in Disease Prediction and Monitoring – Hype or Hope? 2020. doi: 10.1007/s13167-020-00226-x. 

Following the reviewer’s suggestion, we have highlighted the need to complete our metabolomic profile data with other -omic approaches to obtain a comprehensive view of NET disease, remarking the relevance of the combination of metabolomic profile detected in NETs with other analysis in plasma samples such as the profiling of cell-free nucleic acids. For this purpose, the last paragraph of the discussion section has been modified and now reads as follows:

“Moreover, complementary omic approaches, such us exome, transcriptome or methylome of these patients are needed to further understand the underlying mechanisms in NET development and progression. In particular, the metabolomic profile could be combined with complementary analytical approaches in plasma such as cell-free nucleic acids profiling that might be particularly useful for early diagnostics and patient stratification for personalized clinical management. Plasma omic profiling has the additional advantage of providing a dynamic characterization of disease biology, which could be eventually utilized, beyond accompanying diagnostics, for targeted prevention or screening, individualized treatment strategies, therapeutic monitoring and prediction of patient’s outcome.”